Geoffrey Hinton is a pioneer in the field of artificial intelligence, known for his work on neural networks and deep learning, and has made significant contributions to the development of AI systems.

He is considered one of the most influential researchers in the field of artificial intelligence, and his work has had a major impact on the development of AI technologies.

Hinton's recent warnings about the potential dangers of AI have made headlines, with him stating that AI could outsmart humans if not carefully managed, and that it may pose an existential threat to humanity.

He has emphasized the need for careful management and regulation of AI development, and has called for a global effort to mitigate the risks associated with AI.

Hinton's concerns about AI have been echoed by other experts, including Elon Musk and Sam Altman, who have also warned about the potential risks of advanced AI systems.

The development of AI has the potential to bring significant benefits to various industries, including healthcare, finance, and education, but it also poses significant risks, such as job displacement, social surveillance, and socioeconomic inequality.

Experts have emphasized the need for responsible AI development, and have called for the establishment of regulatory frameworks to mitigate the risks associated with AI.

The European Union has proposed the Artificial Intelligence Act, which aims to establish a harmonized framework for AI regulation across EU member states, and to impose strict prohibitions on certain AI applications deemed unacceptable.

The US has no federal regulations restricting AI, but some states have measures, and Canada is pushing the Artificial Intelligence and Data Act to monitor AI development.

The G7 has agreed to introduce a regulatory bill on AI based on risks, and governments and firms should allocate at least one third of AI funding to safety.

Overall, the development of AI requires careful consideration and regulation to ensure that it is developed and used responsibly, and that its potential risks are mitigated.

The public should understand that AI has the potential to bring significant benefits, but it also requires careful management and regulation to avoid its potential risks.

AI can transform industries like education and healthcare, but it also raises ethical concerns and requires international cooperation for responsible use.

The development of AI should be guided by human values such as communication, empathy, and fairness, and should prioritize the well-being and safety of humanity.

Experts believe that future AI systems may outmatch humans in cognitive skills, emphasizing the importance of prioritizing safety and transparency in AI development.

The US Biden administration announced self-regulation of AI development by major tech companies in July 2023, aiming to promote responsible AI innovation.

The EU proposed a classification scoring system for AI tools with 7 key requirements, including transparency and accountability, to ensure AI safety and security.

Canada introduced a mandatory risk assessment tool, Algorithmic Impact Assessment, in 2020, demonstrating a proactive approach to AI governance.

The NIST AI Risk Management Framework acknowledges shortcomings of metrics used to measure AI risk, highlighting the need for ongoing research and improvement.

CoSAI, an open-source initiative, was formed to address AI security fragmentation and develop best practices for AI safety, with sponsorship from major companies like Google and IBM.

The US is developing AI standards with companies like Apple and Google, while California proposes AI regulation with safety standards, aiming to codify US standards into law.

The Biden administration created the AI Safety Institute Consortium to develop guidelines for safety testing and promote AI safety research.

Independent auditing can reduce AI risks and surface previously overlooked harms, emphasizing the importance of rigorous testing and evaluation.

Meaningful human oversight of critical AI decisions is required to ensure accountability and prevent AI-related accidents.

Public funding for non-industry AI research is necessary for safety and transparency, as it allows for unbiased and objective investigation of AI risks and benefits.

The global community is taking proactive measures to address AI safety risks, with 18 countries signing an agreement on AI security standards and prioritizing customer and public protection.

Companies pledged safe AI development, committing to prioritize security and transparency, and allowing third-party researchers to find vulnerabilities in their AI systems.

The US Cybersecurity and Infrastructure Security Agency collaborated on AI guidelines, emphasizing the importance of cybersecurity in AI safety and security.

Cybersecurity is foundational to AI safety, and AI systems should be designed with security in mind to prevent data poisoning attacks and other vulnerabilities.

Governments prioritize data privacy, control, and trust in AI systems, recognizing the need for robust safeguards to protect sensitive information.

AI systems should be privacy-preserving and secure, with built-in measures to prevent data breaches and unauthorized access.

The NCSC published guidelines on AI cyber security, aiming to promote a secure-by-design culture in AI development and emphasizing radical transparency and security ownership.

The guidelines were developed with US CISA and G7 nations, demonstrating international cooperation and a shared commitment to AI safety and security.

The EU is a notable absentee from the list of signatories to the NCSC guidelines, highlighting the need for broader international participation and agreement on AI standards.

The Biden-Harris Administration completed key AI actions in 180 days, including the establishment of a framework for nucleic acid synthesis screening and the release of draft documents on managing generative AI risks.

NIST released draft documents on managing generative AI risks, acknowledging the need for ongoing research and development of AI safety standards.

Agencies established a framework for AI safety and security guidelines for critical infrastructure, recognizing the importance of protecting essential systems and services.

The AI Safety and Security Board was launched to advise on AI development, providing a platform for experts to share knowledge and best practices.

Biden issued an executive order for AI safety standards, requiring companies to share AI system safety test details and prioritize safety and security in AI development.

The National Institute of Standards sets safety test standards for AI systems, ensuring a consistent and rigorous approach to AI evaluation and certification.

The Department of Homeland Security enforces AI standards, providing a critical layer of oversight and accountability in the development and deployment of AI systems.

Geoffrey Hinton is a pioneer in the field of artificial intelligence, known for his work on neural networks and deep learning, and has made significant contributions to the development of AI systems.

Title:

Content: • |
• Fast Quote
• |
• Member
• Product Services / Streaming
• Settings
12 / 05 / 2023
The White House ordered AI to be evaluated, and the European Union proposed legislation to regulate AI, teach AI to be human or the best solution!
• Add Favorite Column
• Collection of articles
• Fang Zhanqi
Fang Zhanze
When I was a teenager, I studied Geographic Information System, but unfortunately I didn ’ t learn anything and I graduated with luck.
After adulthood, the accidental hit into the media circle, first and then in the print, electronic, online media to roll, slightly small.
After middle age, he completed a master ’ s degree in information technology and gradually expanded his horizons. He was determined to join a start-up company and explore different fields of technology.
In recent years, he has been actively engaged in data analysis and digital strategies, and has also been involved in the development of Location Intelligence projects. Sometimes, he can also take time to teach, not only to share what he has learned with others, but also to motivate himself to keep learning for life.
Tales of Wisdom City
Generative AI is definitely the hottest topic in the technology world today. After the popularity of ChatGPT, many companies rushed to launch similar products and gradually applied them to various industries.
But more and more people are worried that when AI is fully popularized, it will aggravate the problem of fake information flow, online fraud and other problems; even Sheffield Hinton, who is known as the "godfather of AI", is worried that AI will become too smart, afraid that it will evolve into a killer robot, which may eventually lead to the death of mankind!
How big can the negative impact of AI technology be?
How do governments around the world respond to the potential threat of AI?
Neural network is the foundation technology of ChatGPT
Fifty-one years ago, Geoffrey Hinton, who had not yet been called the “godfather of AI, ” entered the University of Edinburgh in Scotland as a graduate student and began research on artificial neural networks.
The so-called “artificial neural network ” is a mathematical model that mimics the structure and function of biological neural networks, especially the brain, and is able to learn skills by analyzing data.
This is the foundational technology behind OpenAI ChatGPT and Google Bard.
After Hinton resigned from Google, he did not have to worry about the harm his words would bring to Google, so he was interviewed by different media and said his heart: "AI may lead to the death of mankind." (Photo: University of Toronto official website)
In 2012, Hinton and his students, Ilya Sutskever and Alex Krishevsky, created a neural network system that analyzes thousands of photos and learns to recognize common things like flowers, dogs, cars, etc.
Subsequently, Hinton and two students founded DNNresearch, a startup based on this research project.
In 2013, Google acquired DNNresearch for US $44 million (approximately HK $343 million), and Hinton joined Google as Vice President and Engineering Researcher, responsible for some of the research work on Google Brain.
His protégé, Suzkville, left Google to co-found OpenAI with like-minded people, and became chief scientist, leading the research team to successfully develop the GPT model and ChatGPT.
Hinton ’ s top student, Suzkville, gave up his lucrative job at Google in 2015 to co-found OpenAI with Altman and others, and led the development of GPT and DALL-E models. (Image: University of Toronto website)
I regret working my whole life because I am worried about the dangers of AI.
In 2018, Hinton, along with University of Montreal professor Yoshua Bengio and Meta chief AI scientist Yann LeCun, won the A.M. Turing Award in recognition of their great contributions to neural networks and deep learning.
As a result, the three later became known as the “godfathers of AI ” or“ godfathers of deep learning. ”
Around the same time, Google and OpenAI began to build large-scale deep learning systems based on neural networks, which became the basis for future development of Bard and ChatGPT.
From this, it seems that Sinton plays an important role in creating the current glory of generative AI.
However, in the current era of AI, Sinton suddenly left Google in April 2023, shocking the entire AI industry.
Hinton explained that he left Google to talk freely about the potential risks of AI without harming Google.
Speaking about 50 years of research into neural networks, he said, “I ’ m very sorry about my life ’ s work. ”
The Internet will be filled with more and more fake AI-generated text, photos, and even videos, but the average person will not be able to tell the truth, Hinton said.
Moreover, sooner or later, AI technology will completely disrupt the job market, causing more and more jobs to disappear.
What is even more worrying is that at present, users can not only instruct ChatGPT to generate code, but also ask the AI to execute the code; in this way, the AI killer robots that often appear in science fiction movies will one day become a reality.
Is it not impossible for AI to destroy humanity?
Of course, this pessimistic future scenario is only a hypothetical one, but Hinton stressed that what could lead to it is already happening: a global race for AI technology has begun between Microsoft and Google, and even between China and the United States.
Most people think that the future of AI dominating everything is still far away, but he believes that AI may not take 30 to 50 years to control humans, and even find a way to kill humans, which may eventually lead to human extinction.
In the 1980s, Hinton was a professor of computer science at Carnegie Mellon University in the United States, but because he was not satisfied that the university's AI research was sponsored by the United States Department of Defense, he decided to leave the United States to teach at the University of Toronto's School of Computer Science.
He pointed out that without some kind of global regulatory agreement or regulatory mechanism, the AI arms race will intensify.
For this reason, Hinton believes that the threat posed by AI to humans may be more urgent than climate change, because the solution to climate change is obvious, as long as carbon emissions are reduced or carbon neutrality is achieved, but the current AI crisis does not know how to start. Although AI may pose an existential threat to humans, he does not agree to suspend AI research, because it can never erase the benefits and application value of AI.
Hinton believes it would be better to step up regulation of AI and make everyone aware of its potential harms.
OpenAI co-founder and CEO Sam Altman also acknowledged that ChatGPT has developed some reasoning capabilities that they can ’ t explain, and that it ’ s not entirely impossible for AI to destroy humans.
However, he said that he has installed a kill switch for ChatGPT, and if the development of ChatGPT exceeds human expectations, he will immediately press the switch to stop working.
OpenAI CEO Altman, known as the “father of ChatGPT, ” recently said he was“ a little scared ” about the potential of his children, and even admitted that there is a real possibility that AI will destroy humanity. (Image: Wikipedia)
Altman admits that ChatGPT ’ s influence in elections and the spread of disinformation is a concern, so the 2024 U.S. presidential election will be a focus for OpenAI.
(Image source: Pexels Gallery website)
The Curtain of Ignorance Makes AI Right Values
However, before we press the switch, we can try to instill the right values in AI, such as helping those most in need, not destroying humans. Google ’ s DeepMind paper published in April 2023 in the Proceedings of the National Academy of Sciences suggests that AI can be taught from the perspective of political philosopher John Rawls.
Rawls has proposed a concept called “The Veil of Ignorance ”, which aims to achieve the most equitable distribution of benefits when group decisions are made.
According to his book, The Debate, if a group of people stand behind a curtain, all of them will instantly lose their memory, become ignorant, and forget their identity and status in the real world.
The political philosopher Ross assumes that people are behind the “curtain of ignorance ” (left) and have no idea of their skills, identities, and status.
In this scenario, people tend to choose the most equitable distribution of rights for all. (Image: Wikipedia)
At this time, these people are asked to vote for a working principle for the society.
Because they do not know where they are in this society, they cannot make decisions in an egoistic way, and they can only judge according to the principle of fairness to all people.
The situation is like, at the birthday party, you are responsible for cutting the cake, because you do not know which piece you will get, so you will try to cut each piece to the same size.
Under the curtain of ignorance, fairness and justice that has nothing to do with personal interests will emerge.
For this reason, DeepMind believes that applying the “curtain of ignorance ” to AI training may help promote fairness in the process of“ aligning ” AI with human values.
By “alignment ”, it means aligning AI ’ s wishes with those of humanity.
If AI shares fair values with humans, AI will not have the intention to destroy humanity.
White House convenes tech giants to discuss AI threats
However, even if AI does not intend to destroy humans, it may still have many negative effects on human society.
The Center for Artificial Intelligence and Digital Policy (CAIDP), a U.S. technology ethics organization, has complained to the Federal Trade Commission (FTC) that OpenAI ’ s latest large language model, GPT-4, is biased and deceptive and poses a risk to privacy and public safety.
The CAIDP lists potential threats that may arise from GPT-4, including: helping hackers churn out malicious code to exacerbate cyberattacks; and biased AI training data that may reinforce social stereotypes and make people of all races and genders vulnerable to unfair treatment. The FTC is investigating OpenAI, said FTC Chairman Lina Khan. "They cannot be separated from existing legislation and the Federal Trade Commission will actively enforce them," he said.
In an effort to make GPT-4 more secure, OpenAI hired 50 experts and academics to test GPT-4 against lies, language manipulation, and dangerous scientific common sense.
The OpenAI headquarters is pictured here. (Image: Wikipedia)
In early May 2023, the White House invited Google CEO Sundar Pichai, Microsoft CEO Satya Nadella, OpenAI founder Altman, and artificial intelligence startup Anthropic founder Dario Amodei to attend a conference to discuss the impact of AI on society.
Government officials at the meeting included Vice President Kamala Harris, Biden Chief of Staff Jeff Zients, National Security Adviser Jake Sullivan, National Economic Council Chairman Lael Brainard, and Commerce Secretary Gina Raimondo.
U.S. President Joe Biden also attended the meeting.
EU to pass world ’ s first AI regulatory law
Generative AI, while helping to improve lives, can also pose security, privacy and fraud issues, says Ms Ho.
She noted that AI companies have an ethical and legal responsibility to ensure the safety of their AI products, while at the same time working with governments to protect civil rights and privacy.
She stressed that the White House will work to advance potential new legislation and support new legislation to mitigate the potential harms of AI technology.
In contrast, Europe has taken a step ahead in AI legislation.
On 11 May 2023, the European Parliament ’ s Committee on Civil Liberties and Consumer Protection overwhelmingly approved a position paper calling for restrictions on the use of AI in Europe, a crucial first step towards the adoption of the world ’ s first AI regulation bill.
The draft bill will be submitted to the full European Parliament for a vote in June of the same year, after which representatives of the European Parliament, the Council of the European Union and the European Commission will work out the final terms of the bill in tripartite talks.
The European Parliament has adopted a position paper that strengthens restrictions on biometrics, facial recognition, and the use of AI by police in routine duties.
The parliament believes the move could lead to the world ’ s first AI regulation bill. (Image: Wikipedia)
On the other hand, the White House announced that Google, Microsoft, OpenAI, NVIDIA, Stability AI, Anthropic, and Hugging Face have all committed to participating in DEF CON 31, a computer security conference to be held in August 2023, so that their AI models will be tested and evaluated by hackers and AI experts.
Experts will try to identify errors, failures, and vulnerabilities in AI tools so that AI companies can solve existing problems in their models early on.
However, these AI companies simply agree to a one-time test, rather than a commitment to a continuous evaluation when launching or improving their products, and may therefore not be sufficient to meet the regulatory requirements.
Despite this, DEF CON 31 is still seen as the first step for an AI model to be publicly evaluated.
We hope that after each important first step in legislative regulation and public evaluation, we can put generative AI trains on the right track, so that everyone can safely benefit from technological innovation.
DEF CON is one of the largest computer security conferences in the world. In addition to cybersecurity experts and hackers, participants included staff from the FBI, the Department of Defense, and the Postal Inspection Service.
The conference covered areas such as software security, computer architecture, hardware modifications, and other vulnerable areas of information. (Image: DEF CON official website)
The content of the signed and / or unsigned articles published by Economic Times is the author's personal opinion and does not represent the position of Economic Times, and the role of Economic Times is to provide a free speech platform.
etnet won the HKEX Awards 2022 “Best Performing Securities Data Provider ” and“ Best Performing Derivative Data Provider ” ► Learn More
I want to respond
You may be interested
Enlarge display
I know. I know.
Featured Articles
• Life
• DIVA
• Healthy and good life

What breakthroughs has Hinton achieved through his 40+ years of work on artificial neural networks?

Breakthroughs that mimic biological brains

He is considered one of the most influential researchers in the field of artificial intelligence, and his work has had a major impact on the development of AI technologies.

Title:

Content: Mark Woods: Is orange the color of progress on Jacksonville riverfront? Let's hope so.
GUEST

Retired engineering dean: Urgent steps needed to mitigate catastrophic potential of AI

Dr. Suresh Chandra
Guest columnist

In historical terms, not many topics have attracted as much attention as artificial intelligence has in the past year. Catastrophic predictions by experts in this revolutionary field have propelled them to urge governments and technology corporations to urgently put in place regulations and guidelines to ensure that pernicious effects of AI are avoided.

Geoffrey Hinton, “the godfather of AI,” recently made headlines as he left Google after a long association so he could sound the alarm about AI’s ability to outsmart humans and spawn devastating problems for mankind’s existence. Sam Altman, CEO of ChatGPT maker OpenAI, appeared before the U. S. Congress in May and articulated the same concern. He has recently embarked on a whirlwind tour of Asian and European countries to share his anxiety regarding AI and recommend urgent action in his meetings with political and technical leaders there.

Altman is one of the dozens of top experts and industry leaders to warn about the existential threat to humanity presented by AI in the next five to 10 years. They strongly feel that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

JU law dean:The classic conundrum presented by ChatGPT, especially in academia

More:AI firm to map Jacksonville inch-by-inch. How might its findings affect homeowners' bills?

Letters:Why won’t Gov. DeSantis talk about his Navy service at Guantanamo prison?

This also reflects the view of a large number of participants in the Yale CEO Summit in June.

In May top U.S. and European officials met in Sweden to discuss oversight of AI and pledged to help establish voluntary codes of conduct. The European Union plans to place new requirements on high-risk AI in socioeconomic processes, the government use of AI and the regulated consumer products with AI systems.

Unfortunately the U. S. Congress, despite dire warnings, has been reluctant to come up with needed legislation for fear of alienating key corporations. Not surprisingly, some prominent U.S. corporations have expressed reservations about the drastic steps that the European Union has decided to implement.

The rise of AI has led many economists to issue stern warnings regarding our labor market. As many as 300 million jobs around the world could eventually be automated, according to Goldman Sachs. Some 14 million positions could disappear in the next five years alone. Even the jobs that survive will quite possibly not look much like the jobs of today.

Other potentially harmful outcomes include social surveillance (gathering data on citizens’ activities, relationships and political views), widening socioeconomic inequality, autonomous weapons powered by AI, financial crises brought about by AI algorithms and ransom/extortion threats through manipulation of voice and photos.

The beneficial impact of AI technology in the past decade is manifest in smartphone photos; facial recognition software; numerous medical applications, such as analyzing MRI scans, spotting lung cancer or managing mental health issues; understanding by farmers of crop yields; popular apps like Google Maps; use of speech recognition to translate words from one language to another; advances in social networks (Facebook, Instagram, Twitter, Amazon’s Alexa, Apple’s Siri and Google Assistant); and creating musical compositions or paintings.

Inevitably, AI technology is expected to bring more opportunities in jobs and industries that weren’t previously possible. Thus, one of the most promising aspects of AI is expected to be our entry into a golden age of human possibility, technological development and economic growth.

The above-stated amazing AI-related progress notwithstanding, the potential for destruction of the societal structure is a grave threat and must be avoided. It is imperative that the world develop national and international regulations for AI without delay. The creation of organizational standards for applying AI, making it part of company culture and discussions — as well as infusing humanities perspectives in technology development — are part of this all-important process.

Suresh Chandra, Ph.D., is professor emeritus and former dean of the College of Engineering at North Carolina A&T State University. He lives in Ponte Vedra.

This guest column is the opinion of the author and does not necessarily represent the views of the Times-Union. We welcome a diversity of opinions.

Hinton's recent warnings about the potential dangers of AI have made headlines, with him stating that AI could outsmart humans if not carefully managed, and that it may pose an existential threat to humanity.

What did Hinton, the renowned British-Canadian expert reveal about AI that caused widespread concern?

Exposed serious AI risks, shocking the tech world and affecting major company stocks.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

What future risk did Hinton warn about AI?

What risks did the global summit report highlight about AI?

Creating malicious software for cyberattacks, potentially posing an existential threat if humans lose control.

He has emphasized the need for careful management and regulation of AI development, and has called for a global effort to mitigate the risks associated with AI.

What did Hinton, the renowned British-Canadian expert reveal about AI that caused widespread concern?

Exposed serious AI risks, shocking the tech world and affecting major company stocks.

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

What risks did the global summit report highlight about AI?

Creating malicious software for cyberattacks, potentially posing an existential threat if humans lose control.

Hinton's concerns about AI have been echoed by other experts, including Elon Musk and Sam Altman, who have also warned about the potential risks of advanced AI systems.

Title:

Content: The ‘Godfather of AI’ warns about potential dangers of the technology as he quits Google

British-Canadian computer scientist Geoffrey Hinton admits he has fears for the future of AI

In a Frankenstein-esque tale of maker and master, Geoffrey Hinton, 75, dubbed ‘the godfather of AI’, has left Google with a parting warning over the dangers of artificial intelligence.

In 2012, the British-Canadian computer scientist invented technology with two students at University of Toronto that would become the intellectual foundation for AI systems. Google purchased the rights to this neural network tech to the tune of $44 million, which also propelled Dr Hinton to receive the Turing Award in 2018, considered the Nobel Prize of computing.

Read More
The ultimate part-AI girl? One Tatler correspondent entrusts ChatGPT with her next assignment

ChatGPT’s the new It Girl in Town and now she’s got all the gossip, writes Dora Davies-Evitt in the April issue

Yet now, Dr Hinton has packed in the day job at Google to join a chorus of anxious experts demanding a rollback of AI research until more robust safety measures are designed and deployed. Dr Hinton told the BBC: ‘Right now, they’re not more intelligent than us, as far as I can tell. But I think they soon may be.’

While many look upon AI as a natural technological development akin to the internet that could lead to exciting breakthroughs for humanity, there are growing fears that AI is a Pandora’s box. Reflecting on the effects of his work, Dr Hinton said: ‘I console myself with the normal excuse: If I hadn’t done it, somebody would have,’ as he admitted, ‘it is hard to see how you can prevent the bad actors from using it for bad things.’

Read More
Cyber Society: Meet the NFT duo dominating the metaverse

Old Etonian digital artists Dominic Smith and Joe Carnell have caught the attention of Brooklyn Beckham, Steve Aoki and Jaden Smith

The scientist went on to warn that AI could be taught to ‘create sub-goals like “I need to get more power”’, and be harnessed by nefarious actors to wreak havoc. With innovation driven forward by the unstoppable competition between behemoths like Google and Microsoft, Dr Hinton warned innovation will only increase exponentially in the coming years.

There are those who are trying to apply the brakes to this runaway train. In March, an open letter was signed by over 1,000 tech leaders and researchers, including Elon Musk and fellow Turing Award winner Yoshu Bengio, calling for a six-month moratorium on AI development. A few days later, 19 leaders of the Association for the Advancement of Artificial Intelligence released their own letter on the risks of AI. The signatures included that of Eric Horvitz, chief scientific officer at Microsoft.

The main outcry over AI lies in its ability to create and disseminate false news and images, which the public may find increasingly hard to identify. AI also poses a threat to academia and careers (see: Tatler’s foray into the world of ChatGPT). Dr Hinton believes that AI will fundamentally disrupt the workplace and take over the ‘drudge work’.

Read More
Lady Meta: my stratospheric rise through the metaverse

The Crypto Fashion Week debutante on becoming VR’s favourite It Girl

However Google’s chief scientist, Jeff Dean, offered words of comfort, adding: 'We remain committed to a responsible approach to AI. We’re continually learning to understand emerging risks while also innovating boldly.’

What did Hinton, the renowned British-Canadian expert reveal about AI that caused widespread concern?

Exposed serious AI risks, shocking the tech world and affecting major company stocks.

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

The development of AI has the potential to bring significant benefits to various industries, including healthcare, finance, and education, but it also poses significant risks, such as job displacement, social surveillance, and socioeconomic inequality.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

What risks did Hinton associate with AI's rapid advancement?

Experts have emphasized the need for responsible AI development, and have called for the establishment of regulatory frameworks to mitigate the risks associated with AI.

Title:

Content: Artificial intelligence (AI) is a rapidly growing technological advancement with the potential to transform various industries. The development of AI has brought about significant changes in education, music, transportation, and healthcare. It holds the promise of self-driving cars, revolutionary medical breakthroughs, and increased productivity. However, concerns arise regarding the potential dangers associated with the development of General Artificial Intelligence (AGI).

AGI is a theoretical form of AI that possesses human-level intelligence and self-awareness. While Narrow AI, designed for specific tasks, has made impressive progress, achieving AGI remains uncertain. One of the main challenges is developing algorithms that can reason abstractly and think creatively, skills that current AI systems lack. Replicating human-like abstract and creative thinking in machines is a complex task.

In the medical field, AI shows great potential in diagnosing diseases and developing more effective treatments. It can analyze big data to prevent the spread of infectious diseases by creating early-warning systems. In other areas, such as climate change and transportation, AI can contribute to scientific advancements. Predictive modeling and early-warning systems can help us prepare for climate-related events, while self-driving cars have the potential to revolutionize transportation.

However, ethical concerns arise when it comes to AI’s impact on the arts, particularly in music production. Questions arise regarding the role of human artists and the authenticity of AI-generated music. Additionally, the use of AI in military technology raises ethical questions about decision-making without human intervention. Countries like the United States, China, and Russia have already implemented AI in weapons systems and drones, sparking the need for global regulations to ensure responsible use.

Renowned physicist Stephen Hawking has warned against the development of AGI, expressing concerns that it could surpass human intelligence and redesign itself at an exponential rate, potentially rendering humanity obsolete. This highlights the importance of ethical considerations, regulations, and international cooperation to mitigate any risks associated with AI development.

As AI continues to advance, it is crucial to strike a balance between harnessing its potential benefits and addressing the potential dangers. Measures such as ethical considerations, regulations, and international cooperation are necessary to ensure the responsible use of AI and to mitigate any risks associated with its development.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

The European Union has proposed the Artificial Intelligence Act, which aims to establish a harmonized framework for AI regulation across EU member states, and to impose strict prohibitions on certain AI applications deemed unacceptable.

Title:

Content: EU AI Regulations

AI REGULATION IN THE EU

The EU AI Act (COM/2021/206) is hailed as the first comprehensive regulation on AI. It represents a significant milestone in AI governance via legislation. It aims to establish a harmonised framework for AI regulation across EU member states.

The Act's key provisions include a risk-based approach to AI governance. Specifically, with stringent requirements for high-risk AI systems to undergo conformity assessments. These assessments are conducted by notified bodies accredited by EU member states, instilling accountability and oversight in the development and deployment of high-risk AI applications.

Additionally, the Act imposes strict prohibitions on certain AI applications deemed unacceptable. Social scoring systems and real-time biometric identification in public spaces are a good example of this. By delineating clear boundaries on permissible AI applications, the EU aims to safeguard fundamental rights, including privacy, non-discrimination, and autonomy, while fostering public trust in AI technologies.

To facilitate effective implementation and enforcement of the AI Act, the legislation establishes the European Artificial Intelligence Board (EAIB). Comprising representatives from EU member states, the EAIB is tasked with providing guidance, monitoring compliance, and fostering international cooperation on AI governance. Furthermore, the Act empowers national competent authorities to enforce regulatory requirements and impose sanctions for non-compliance, ensuring robust enforcement mechanisms across the EU.

The EU AI Act (COM/2021/206) is hailed as the first comprehensive regulation on AI. It represents a significant milestone in AI governance via legislation. It aims to establish a harmonised framework for AI regulation across EU member states.

The Act's key provisions include a risk-based approach to AI governance. Specifically, with stringent requirements for high-risk AI systems to undergo conformity assessments. These assessments are conducted by notified bodies accredited by EU member states, instilling accountability and oversight in the development and deployment of high-risk AI applications.

Additionally, the Act imposes strict prohibitions on certain AI applications deemed unacceptable. Social scoring systems and real-time biometric identification in public spaces are a good example of this. By delineating clear boundaries on permissible AI applications, the EU aims to safeguard fundamental rights, including privacy, non-discrimination, and autonomy, while fostering public trust in AI technologies.

To facilitate effective implementation and enforcement of the AI Act, the legislation establishes the European Artificial Intelligence Board (EAIB). Comprising representatives from EU member states, the EAIB is tasked with providing guidance, monitoring compliance, and fostering international cooperation on AI governance. Furthermore, the Act empowers national competent authorities to enforce regulatory requirements and impose sanctions for non-compliance, ensuring robust enforcement mechanisms across the EU.

US AI Regulations

In contrast, the AI regulatory landscape in the US is characterised by a patchwork of laws and guidelines. As usual, reflecting a more decentralised and sector-specific approach. Federal agencies such as the Federal Trade Commission (FTC) and the National Highway Traffic Safety Administration (NHTSA) have issued guidelines and regulations addressing specific aspects of AI, such as consumer protection and autonomous vehicles. However, comprehensive federal legislation on AI remains elusive, with regulatory efforts primarily focused on addressing sector-specific challenges.

The Department of Defence (DoD) is actively engaged in regulating AI technologies. In particular, within the context of national security and defence applications. The DoD has issued guidelines and policies for the ethical development and use of AI in military operations, including principles for AI governance, human-AI collaboration, and risk management. It also collaborates with industry partners and academia to advance AI research while ensuring national security interests are upheld.

Beyond the FTC, NHTSA, and DoD, several other federal agencies are involved in regulating AI technologies within their respective domains. The Food and Drug Administration (FDA) oversees the regulation of AI-driven medical devices and diagnostic tools, ensuring safety, efficacy, and accuracy standards are met. Similarly, the Department of Homeland Security (DHS) addresses AI-related cybersecurity threats, while the Department of Justice (DOJ) focuses on legal and ethical considerations in AI applications, such as predictive policing and criminal justice reform.

Challenges and Disparities

AI REGULATION

The result is a heterogeneous system of laws and regulations. Against this backdrop, businesses, developers, and policymakers face the challenge of navigating a complex and evolving regulatory landscape. While the EU AI Act provides a comprehensive framework for AI governance in the EU, the regulatory environment in the UnS remains fragmented, with varying approaches across states and sectors. This disparity poses challenges for multinational companies operating in both jurisdictions, as they must reconcile conflicting regulatory requirements and ensure compliance with evolving standards.

UK AI Regulations

AI REGULATION in the UK

The AI Sector Deal is the UK government's strategic initiative to grow their AI legislative scope. It represents a concerted effort to position the UK as a global leader in AI innovation, research, and development. It was released in 2018 as part of the Industrial Strategy, aiming to leverage the transformative potential of AI technologies to drive economic growth, improve public services, and address societal challenges.

Key components of the Deal include substantial public and private sector investments, primarily in AI research, initiatives to foster AI talent development, and measures to promote ethical and responsible uses of AI technologies. Furthermore, the deal emphasises collaboration between industry, academia, and government to accelerate AI innovation and adoption across various sectors.

This outlines the UK's commitment to invest in AI research and innovation. In fact, the government pledged to invest £603 million in AI-related initiatives; with an additional £342 million in private sector investment, totalling £945 million. This underscores the government's recognition of AI as a strategic priority for economic growth and improving societal outcomes.

Moreover, the Deal places a strong emphasis on skills development and education. This aims to ramp up the UK workforce, giving them the necessary tools to thrive in an AI-driven economy.

Initiatives such as the AI Skills and Talent Package aim to support a wide-range development of AI skills. In fact various educational levels are included, from primary schools to universities; promoting diversity and inclusivity in the AI workforce.

In addition to fostering innovation and talent development, the AI Sector Deal underscores the importance of ethical and responsible AI development and deployment. It includes provisions for establishing an AI Council to provide guidance on AI policy and ethics, as well as initiatives to develop standards and best practices for AI governance and regulation.

Navigating the AI Frontier: Conclusion

AI REGULATION

While western governments are starting to take AI seriously, diverging legislations in a globalised world pose a daunting challenge. As businesses, developers, and policymakers navigate the complex and evolving regulatory landscape, they must reconcile differing approaches and ensure compliance with evolving standards. Multinational companies operating across jurisdictions face challenges in navigating regulatory disparities. However, initiatives such as the EU AI Act and the UK's AI Sector Deal provide guiding frameworks for responsible AI governance, fostering innovation while safeguarding societal interests.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

The US has no federal regulations restricting AI, but some states have measures, and Canada is pushing the Artificial Intelligence and Data Act to monitor AI development.

Title:

Content: How does China ’ s development of AI demand “socialist core values ” differ from country to country?
Author: United Morning Post
Published: Updated:
China ’ s artificial intelligence (AI) boom continues.
Three first-tier cities, Beijing, Shanghai and Shenzhen, released policy documents to encourage AI development in the last two days of May, once again demonstrating official support for the hottest track in the technology war.
According to the Securities Times, Shanghai issued a document on Tuesday (May 30) to strengthen support for the development of private investment, and proposed to give full play to the guiding role of artificial intelligence innovation and development, and support private enterprises to participate widely in the construction of artificial intelligence infrastructure such as data and computing power.
The two documents released by Beijing on the same day put forward specific goals such as the scale of the core industry of artificial intelligence to reach 300 billion yuan (RMB, the same below) by 2025, the continuous growth of more than 10%, and the scale of the radiation industry to exceed 1 trillion yuan.
At the same time, it also proposed specific measures in five aspects, such as improving the ability to coordinate and supply computing resources, and general AI technology systems such as system construction models, to promote breakthroughs in domestically produced AI chips, and deployed AI technology innovation and application related work around six fields, such as finance, medical care, and autonomous driving.
The global artificial intelligence (AI) boom continues. (Reuters)
The plan to promote the development and application of artificial intelligence released by Shenzhen on Wednesday (May 31) also proposed that the city should build a new generation of national artificial intelligence innovation and development pilot area and national artificial intelligence innovation and application pilot area, and strive to create a global artificial intelligence pioneer city.
The plan is clear, to build a city-level computing power coordination and scheduling platform, promote "thousands of industries + AI", and encourage enterprises in the financial, business, industrial, transportation and other fields to upgrade existing production, service and management methods through artificial intelligence.
It can be seen that the recent exposure of AI fake news and AI fraud has not shaken China's official support for the development of AI.
Internationally, when foreign dignitaries and experts are debating how to manage the threat of artificial intelligence, China ’ s optimism and enthusiasm for AI, and its rapid development in this field, are particularly unique.
China ’ s AI ambitions
China is so keen on AI development that cities are scrambling to launch support initiatives that are closely related to the approaching milestones for the country ’ s ambitious goals set a few years ago.
Baidu held a press conference in Beijing headquarters on the afternoon of March 16, officially launched the big language model "Wenxin One Word":
In 2017, the State Council issued the "New Generation Artificial Intelligence Development Plan", which proposed that China's overall artificial intelligence technology and application should be synchronized with the world's advanced level in 2020; in 2025, it will achieve a major breakthrough in artificial intelligence basic theory, so that AI will become the main driving force for industrial upgrading and economic transformation; in 2030, AI theory, technology and application will reach the world's leading level.
To lead the world in AI for more than a decade is a challenging goal for China.
Perhaps due to multiple factors such as the Sino-US trade and technology war, the epidemic, and the rectification of technology companies, Chinese officials have not announced that they have reached the 2020 goal, but at the same time, there is no sign of abandoning or adjusting the next two goals.
This means that the time left for scientific research institutions and technology enterprises to complete major breakthroughs in basic theory and achieve a leading position in some fields will be two and a half years.
And from the end of last year chatbot ChatGPT phenomenal explosion, Chinese technology companies launched the performance of the target products, at least in the field of generative AI, China has not much advantage.
On the other hand, a 2021 Harvard Business Review article pointed out that although the number of Chinese research papers in the field of AI has jumped from 1,086 in 1997 to 30,343 in 2017, more than the number of US research papers in the same period, academic research does not necessarily translate into innovation in AI and the advantage of global leadership.
Harvard Business Review points out that although China (Deep Blue Line) has surpassed the United States (Yellow Line) in the number of research papers in the field of AI, academic research does not necessarily translate into the advantages of innovation and global leadership in the field of AI. (Internet)
The article also summarizes the advantages of China ’ s rapid development in the field of AI, including the large amount of learning data available in a large market, as well as strong support for AI development and relatively weak privacy protection regulations.
As an example, China ’ s ubiquitous surveillance cameras have created excellent conditions for AI companies specializing in facial recognition – a field that will be much more difficult to develop in countries and regions with stricter regulations on privacy.
Different countries have different regulatory focus.
China does not have laws and regulations on the protection of privacy information, but neither the "Personal Information Protection Law" passed in 2021, nor the draft "Management Measures for Generative Artificial Intelligence Services" proposed in April this year, does not prohibit or restrict the access of relevant enterprises to personal information, but emphasizes that the collection and processing of personal information should have a clear and reasonable purpose, and the data should contain personal information and obtain the consent of the subject of personal information.
On the other hand, the focus of the management method of generative AI services is not on the protection of personal information and privacy, but rather on the content generated should reflect the core values of socialism, and must not contain content that subverts state power, overthrows the socialist system, incites division or undermines national unity, promotes terrorist extremism, ethnic hatred, and may disrupt economic and social order.
Merchants use AI face changing technology to let the anchor pretend to be a star with goods. (Network resource map)
At the same time, it is also clear that China supports independent innovation, application and international cooperation in basic technologies such as artificial intelligence algorithms and frameworks.
Today, when artificial intelligence has become a mainstream development, China is not the only country that has expressed support for development while also giving regulatory opinions on AI.
Tech experts warn AI threat equates to pandemic and nuclear war
According to the official website of the Organization for Economic Cooperation and Development (OECD) AI Policy Observation Platform (Oecd.AI), 69 countries and the European Union have proposed strategic plans for AI development.
Many of these countries have launched or are studying guidance and regulatory measures for AI, but their strength and direction are not small differences.
According to the official website of Oecd.AI, 69 countries and the European Union have put forward strategic plans for the development of AI, and many of them have launched or are studying guidance and regulatory measures for AI.
For example, India, like China, a developing country in Asia, has also strongly encouraged the development of AI, but has yet to introduce regulations or regulations that specifically target AI.
Japan, as a developed country in Asia, although there are no prohibitive regulations for AI, is cautious about AI risks and has issued guiding regulations; South Korea, which is also a developed country, is expected to introduce regulations to classify risk levels and put forward different regulatory requirements for AI applications within the year on the premise of allowing AI development.
In the developed countries of Europe and America, the United States as a leader in the field of AI, although there are no regulations restricting AI at the federal government level, many officials have recently expressed a stronger regulatory will; at the same time, there are different levels of regulatory measures in different states and organizations in the United States.
Canada, a neighbor of the United States, is pushing the Artificial Intelligence and Data Act to clarify the threat of AI to individuals and monitor their development.
The European Union, which has the most stringent attitude towards AI regulation, introduced the Artificial Intelligence Act in 2021, emphasizing the need to control risks through the establishment of a regulatory system to ensure that AI development is safe, ethical and trustworthy.
The bill assesses the risks of using AI in different areas and prohibits the use of AI in areas of “unacceptable risk. ”
However, not all EU countries agree with the risk classification of the bill, such as France ’ s AI video surveillance program, which is contrary to the EU law.
In 2017, Tesla founder Musk and 116 other AI experts from around the world signed a letter asking the United Nations to ban countries from developing killer robots to avoid World War III. (Reuters)
On the other hand, while member states have different attitudes towards AI regulation, the Group of Seven (G7) Digital and Technology Ministers, after concluding their meeting in Japan at the end of April, agreed to introduce a regulatory bill on AI based on risks while maintaining an open and enabling environment.
In addition, according to a joint statement released on the White House website on Wednesday, the United States-EU Trade and Technology Commission meeting held in Sweden at the end of May also discussed the potential regulation of AI and reached cooperation on monitoring and measuring existing and future AI risks.
Overall, calls for AI regulation are higher in developed countries; compared to Asian countries, European and American countries are generally more worried about AI development.
Pray for wealth?
In addition to differences in attitude at the government level, AI threat theory is also the focus of attention of the industry and the general public. With the rapid development of AI technology, many people are worried that AI will replace millions of white-collar jobs and even threaten human survival.
For example, more than 350 AI technology leaders and experts jointly warned on Tuesday (May 30) that the extinction risks posed by AI are on a par with other social-scale risks such as pandemics and nuclear war.
In March, more than a thousand industry figures called for a moratorium on the development of AI systems more powerful than GPT-4 for at least six months, citing potential risks to society and humanity.
On the other hand, an Ipsos survey released in 2022 showed that the American people are the most pessimistic about the future of AI technology, with only 35% of Americans believing that the benefits of AI outweigh the risks, while China is the most optimistic country in the world, with nearly 80% of Chinese believing that the benefits of AI outweigh the risks.
Robots are developing rapidly, and many people in the outside world worry that robots will get out of control and do harm to human beings.
However, it seems that before the episode of "Transgression", the harm caused by robots to people is due to the network security problems of robots and hackers, not the AI itself. (online picture)
From strongly encouraging development to implementing stronger regulation, it seems that every emerging sector has to go through the process, and AI, a large and opportunistic market, is no exception.
According to International Data Corporation (IDC), global AI revenue will exceed the US $500 billion mark in 2023 (the same below, about S $675.5 billion).
IDC also predicts that China ’ s AI market spending will increase to $14.75 billion in 2023, accounting for about one-tenth of the global total.
ChatGPT, a chatbot, believes that the arguments against regulating AI, including over-regulation, could make it downhill when it comes to technology competition with other countries. (Reuters)
If ChatGPT is asked whether it should regulate AI, it gives reasons for opposition, including that regulation will not keep pace, that regulation will limit industry innovation and economic growth, that regulation will place an undue burden on relevant companies, and that over-regulation may discourage competition in technology with other countries.
Perhaps this is the last reason why both China and the United States, which are engaged in a technology war, are reluctant to introduce tougher regulatory measures against AI.
Although experts have analyzed that even China ’ s best big language modeling technology is still 18 months to two years behind the United States, such a gap will not take the United States lightly – especially when China looks like it is ready to overtake the curve with AI.
This article was published under the authority of the United Morning Post.

The G7 has agreed to introduce a regulatory bill on AI based on risks, and governments and firms should allocate at least one third of AI funding to safety.

Title:

Content: Governments, firms should spend more on AI safety, top researchers say

By

'At least one third of their AI research and development funding'.

Artificial intelligence companies and governments should allocate at least one third of their AI research and development funding to ensuring the safety and ethical use of the systems, top AI researchers said in a paper.

The paper, issued a week before the international AI Safety Summit in London, lists measures that governments and companies should take to address AI risks.

"Governments should also mandate that companies are legally liable for harms from their frontier AI systems that can be reasonably foreseen and prevented," according to the paper written by three Turing Award winners, a Nobel laureate, and more than a dozen top AI academics.

Currently there are no broad-based regulations focusing on AI safety, and the first set of legislation by the European Union is yet to become law as lawmakers are yet to agree on several issues.

"Recent state of the art AI models are too powerful, and too significant, to let them develop without democratic oversight," said Yoshua Bengio, one of the three people known as the godfather of AI.

"It (investments in AI safety) needs to happen fast, because AI is progressing much faster than the precautions taken," he said.

Authors include Geoffrey Hinton, Andrew Yao, Daniel Kahneman, Dawn Song and Yuval Noah Harari.

Since the launch of OpenAI's generative AI models, top academics and prominent CEOs such as Elon Musk have warned about the risks on AI, including calling for a six-month pause in developing powerful AI systems.

Some companies have countered this, saying they will face high compliance costs and disproportionate liability risks.

"Companies will complain that it's too hard to satisfy regulations - that 'regulation stifles innovation' - that's ridiculous," said British computer scientist Stuart Russell.

"There are more regulations on sandwich shops than there are on AI companies."

Got a news tip for our journalists? Share it with us anonymously here.
Tags:

Most Read Articles

Services Australia's digital credential sharing with NSW on ice

CBA to test products and messaging on AI-created 'customers'

Australian Federal Police officers using more online face search tools

ANZ targets 3000 engineers to use GitHub Copilot

Log In

  |  Forgot your password?

Overall, the development of AI requires careful consideration and regulation to ensure that it is developed and used responsibly, and that its potential risks are mitigated.

Title:

Content: Free speech, you can make AI can not replace
You can make AI impossible to replace.
Su Wei-cheng
The World Economic Forum (WEF) latest research report, "The Future of Jobs Report 2023", pointed out that due to the impact of economic growth, high inflation, digital transformation, artificial intelligence (AI) and other changes in the labor market, it is estimated that 83 million jobs will be eliminated worldwide in the next five years, and 69 million new jobs will be created in emerging industries; In short, 14 million jobs will disappear, with record clerks, bank tellers, clerical or administrative jobs suffering the most, while jobs such as information security and data analysts, green engineers and scientists, and sustainability specialists are expected to grow by 30%.
With the rise of emerging technologies, automation, globalization and digital transformation, resulting in lower labor demand, coupled with the rise of generative AI, many people are worried about being replaced by AI. (Reuters)
IBM CEO Arvind Krishna said in an interview with Bloomberg that IBM estimates that about 7,800 internal service jobs will be replaced by AI in the next five years, so it will suspend recruitment of AI-capable people.
Even the latest report from Goldman Sachs, a multinational investment group, points out that a new wave of generative AI may affect about 300 million jobs, and even lawyers or administrators may face the risk of being replaced by AI, but it will also drive global GDP growth.
However, Microsoft founder Bill Gates is not so pessimistic, believes that AI is still important in improving productivity, improving the quality of health care, promoting equality in education, and improving the workplace; and, people should think of AI as a personal digital assistant to help improve efficiency, so that AI will not replace manpower, especially teachers' work is difficult to replace, and can bring about disruptive change in paperwork.
With the wave of emerging technologies, automation, globalization and digital transformation, resulting in lower labor demand, coupled with the rise of generative AI, many people are worried about being replaced by AI.
In fact, as long as you know how to make good use of AI technology as an auxiliary tool, you will not only not have to worry about being replaced, but also use your power to create more niche. Data statistics or analysis, financial planning, risk forecasting, operations management, transportation and logistics, information security, medical and nursing, fraud prevention, mapping or drafting can all be used to reduce labor costs, improve efficiency, and optimize resources.
Of course, there are risks in the use of AI, such as technical bias, poor design or limitations, or human improper use of the resulting forged, altered, fake photos, fake videos, fake information, fake text, fraud, privacy, infringement and other legal and ethical disputes.
In addition, AI brings convenience in time and space, but it may also lead to a reduction in the quality and quantity of human interaction, and the relationship between each other is becoming more and more distant.
How can we make it impossible to replace it?
The author believes that the key lies in our “values ” as human beings, such as warm communication between people, love exchange and emotional expression, accumulation and inheritance of experience, innovation and creativity, cross-domain integration and sharing of thinking, decision-making and problem-solving attitude, artistic beauty and cultural background, etc. The diversity represented by life is our most unique and best value as human beings. The" ability "is boundless, and can be gradually strengthened and deepened by learning, experience, growth, life experience, education, etc., which AI can not easily replace.
Further, in an era of social change and rapid technological development, human intelligence, flexibility, empathy, independent thinking and analysis, and people-to-people communication, cooperation, trust and sharing are increasingly important in the workplace, and these are also things that machines cannot do.
We must continue to improve our competitiveness, in addition to professional and technical skills, but also to increase: learning, digital, communication, collaboration, reading, understanding, thinking, creativity, social, innovation, stress, service, leadership, social influence and other key capabilities, actively let themselves continue to add value, improve "irreplaceable" and master. Create more opportunities and strive to make future dreams come true.
※ This article refers to the content of the relevant website supplement:
The Future of Jobs Report 2023
IBM CEO Arvind Krishna interviewed by Bloomberg
IBM to Pause Hiring for Jobs That AI Could Do
The latest report from Goldman Sachs
The Potentially Large Effects of Artificial Intelligence on Economic Growth
Microsoft founder Bill Gates
Bill Gates thinks AI may transform the workforce, healthcare, and education – but says we'll still need teachers
(The writer is a university lecturer and former secretary to the president of the Legislative Yuan.)
Free Speech is an electronic forum that provides public dialogue. Whether it is political, economic, social, cultural and other news issues, you are welcome to express your opinions and express your opinions.
Please do not submit more than one manuscript, the length of the text is 700 words, please attach the real name (must be written).
Please note that you have a pen name, occupation, contact number, e-mail account.
This report has the right to accept and delete the right, no remuneration for the draft; the acceptance or non-acceptance will be without notice.
Submission mailbox: LTNTALK @ gmail.com
No need to smoke, no need to grab, now use the APP to watch the news, guarantee the daily winning point I download the APP
I've added friends, thank you.
Welcome to [Free Commentary]
It's a compliment. Good.
It has been praised, thank you.
Related News
Editor 's Choice

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

What risks did the global summit report highlight about AI?

Creating malicious software for cyberattacks, potentially posing an existential threat if humans lose control.

The public should understand that AI has the potential to bring significant benefits, but it also requires careful management and regulation to avoid its potential risks.

Title:

Content: The Impact of Artificial Intelligence on Society

Moatsim Nasir

Artificial Intelligence (AI) has become an increasingly prevalent technology today, with its impact being felt across various industries. AI has the potential to revolutionize the way we live, work, and interact with each other. From autonomous vehicles to intelligent personal assistants, AI can transform the world around us in ways that were once thought impossible. However, as AI advances, questions about its impact on society are raised. Will it create new opportunities or lead to job displacement? How will it affect privacy and security? The answers to these questions will shape the future of AI and its role in our lives.

The Positive Impact of AI on Society

Improved Healthcare

The integration of AI in healthcare has revolutionized how we approach medical diagnosis, treatment, and patient care. With the ability to process vast amounts of data quickly and accurately, AI algorithms can help clinicians make more informed decisions and provide personalized patient treatment plans. This has improved patient outcomes, reduced medical errors, and increased efficiency in healthcare delivery. AI-powered medical imaging and diagnostics have also helped detect diseases at earlier stages, leading to better chances of recovery and survival. Moreover, AI has enabled healthcare providers to optimize resource allocation, reduce healthcare costs, and improve access to healthcare in underserved communities. Overall, the positive impact of AI in healthcare is undeniable, and its potential to transform the healthcare industry is only beginning to be realized.

Enhanced Education

The integration of AI in education has brought about a significant transformation in the way we learn, teach, and assess students. With the ability to process vast amounts of data and adapt to individual learning needs, AI algorithms can provide personalized learning experiences to students, enhancing their engagement and motivation. Moreover, AI-powered educational tools such as chatbots, virtual tutors, and intelligent learning management systems can provide students with real-time feedback, support, and guidance, leading to better academic performance and higher retention rates. AI-powered analytics can also help educators to track student progress and identify areas where students need more support, enabling them to adjust teaching strategies accordingly. Additionally, AI-powered assessment tools can provide a more accurate and objective evaluation of student performance, reducing the potential for bias and subjectivity. Overall, the positive impact of AI in education is immense, and its potential to revolutionize the way we learn and teach is vast.

Increased Efficiency and Productivity

The integration of AI in various industries has brought about a significant increase in efficiency and productivity. AI-powered automation has enabled businesses to automate repetitive tasks, allowing employees to focus on more strategic and creative tasks. This has increased productivity and reduced errors, resulting in cost savings and increased profits. Moreover, AI-powered decision-making systems can analyze vast amounts of data quickly and accurately, providing insights that humans may miss and enabling businesses to make more informed decisions. Additionally, AI-powered supply chain management systems can optimize inventory levels, reduce wastage, and improve delivery times, increasing customer satisfaction. Furthermore, AI-powered predictive maintenance systems can detect equipment failures before they occur, reducing downtime and maintenance costs. Overall, the positive impact of AI on efficiency and productivity is significant, and its potential to transform how businesses operate is vast.

Improved Safety and Security

The integration of AI in safety and security has significantly improved how we detect and prevent potential threats. AI-powered surveillance systems can analyze real-time data and identify potential security breaches, enabling authorities to respond quickly and effectively. Additionally, AI-powered predictive analytics can help identify potential risks before they occur, enabling authorities to take preventive measures. Moreover, AI-powered biometric identification systems can enhance security by accurately identifying individuals, reducing the potential for fraud and identity theft. Furthermore, AI-powered natural language processing systems can help law enforcement agencies analyze vast amounts of data, enabling them to detect patterns and uncover potential criminal activity. Overall, the positive impact of AI on safety and security is immense, and its potential to enhance public safety and prevent criminal activity is vast.

The Negative Impact of AI on Society

Job Displacement

The widespread adoption of artificial intelligence (AI) technologies is causing significant job displacement across many industries, potentially negatively impacting individuals, families, and society. As machines become more capable of performing tasks previously done by humans, workers may be replaced by automation, leading to unemployment or underemployment. This can have many negative consequences, including reduced income, loss of job-related benefits, and increased social and economic inequality. Moreover, displaced workers may face challenges in retraining for new careers or finding new employment, particularly in areas where AI has disrupted many industries. Addressing the negative impact of job displacement due to AI will be crucial for creating a more equitable and sustainable future for all.

Privacy Concerns

The rise of AI technologies has also led to increased privacy concerns, potentially negatively impacting individuals and society. AI systems are often designed to collect vast amounts of data about individuals, including personal and sensitive information, such as biometric data, browsing history, and social media activity. This data can be used to train AI algorithms and improve their accuracy, but it can also be misused, hacked, or sold to third parties without the consent or knowledge of the individuals concerned. Moreover, AI systems may make decisions that significantly impact people's lives, such as determining eligibility for loans, insurance, or employment, raising questions about fairness, transparency, and accountability. Addressing privacy concerns related to AI will require careful consideration of ethical and legal frameworks that protect individuals' rights while enabling the benefits of AI technologies to be realized.

Bias and Discrimination

Another negative impact of AI in society is the potential for bias and discrimination. AI algorithms are trained on vast amounts of data; if this data is biased, the resulting AI models will be biased too. This can lead to discriminatory hiring, lending, and criminal justice outcomes, perpetuating and even amplifying existing social and economic inequalities. For example, facial recognition systems are less accurate in identifying people of color and women, leading to increased misidentification and false arrests. Additionally, AI systems may be influenced by the biases of their designers or the data they are trained on, leading to unintended discriminatory outcomes. Addressing bias and discrimination in AI will require ongoing efforts to ensure that data used to train AI models is diverse and representative and that the design and deployment of AI systems are subject to rigorous ethical and legal standards.

Increased Dependency

The increasing use of AI in various aspects of society has led to an alarming level of dependency on technology. While AI has undoubtedly revolutionized many industries and made many tasks more efficient, the negative impacts of over-reliance on AI cannot be ignored. As people become more reliant on machines and algorithms to make decisions and perform tasks, they become less capable of doing those things themselves. This can lead to a loss of critical thinking and problem-solving skills and a decreased ability to adapt to new situations. Furthermore, the potential for AI to make mistakes or perpetuate biases can have serious consequences when people blindly trust and follow its decisions. Ultimately, while AI can be a valuable tool, it is essential to recognize and mitigate its negative impacts on society's overall abilities and autonomy.

Ethical Considerations and Regulations

As AI advances and becomes more integrated into society, ethical considerations and regulations must be a top priority. AI has the potential to impact people's lives in significant ways, such as affecting their employment, privacy, and even their physical safety. Therefore, it is essential to ensure that the development and use of AI align with ethical principles, such as fairness, transparency, and accountability. Additionally, regulations must be put in place to prevent the misuse of AI and protect against potential harm. This includes laws around data privacy and security, as well as guidelines for developing and deploying AI systems. The responsibility for ensuring ethical considerations and regulations falls on various stakeholders, from individual developers and organizations to government agencies and policymakers. By addressing these issues, we can ensure that AI is used for the benefit of society while mitigating potential harm.

Upshot

The impact of artificial intelligence on society has been both transformative and complex. AI has brought many benefits, from increased efficiency and productivity to medical breakthroughs and scientific discoveries. However, it has also raised important ethical considerations and regulatory challenges, including the potential loss of jobs, the perpetuation of biases, and threats to privacy and security. As AI continues to evolve, we must approach its development and implementation with careful consideration and accountability. By working together to ensure that AI is developed and used ethically and responsibly, we can harness its potential to improve society and create a better future for all.

Published by

An experienced blogger, writing about digital marketing, Education in this era, and creating attention-grabbing content. My expertise helps creating quality and to-the-point content.

Michigan Center, MI
7 followers

More from Moatsim Nasir

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

AI can transform industries like education and healthcare, but it also raises ethical concerns and requires international cooperation for responsible use.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

The development of AI should be guided by human values such as communication, empathy, and fairness, and should prioritize the well-being and safety of humanity.

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

Experts believe that future AI systems may outmatch humans in cognitive skills, emphasizing the importance of prioritizing safety and transparency in AI development.

Title:

Content: Presented By
Getty Images
Ideas
Jan Brauner is a Ph.D. researcher in Artificial Intelligence at the University of Oxford, focusing on the safety of AI systems and their application in public health.
Alan Chan is a Ph.D. student at Mila, a research institute in Montreal focusing on AI, where he works on technical and socio-technical problems in AI safety. He's particularly interested in evaluation and AI regulation.

In May, more than 100 artificial intelligence (AI) professors, including some of the field's leading experts, scholars from other areas, and AI executives signed a one-sentence statement: "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” Many signing researchers have explained their reason for worry: the risk that we might build powerful AI systems that we cannot control within this decade or the next ones.

Some have suggested the statement is an industry ploy to hype up AI companies’ products or influence regulation, ignoring that most of the signatories—ourselves included—are academics who do not work for industry. But the most common concern we have heard is that, by focusing on the risk of extinction, the statement distracts from present-day AI harms. As volunteers involved in collecting signatures for and constructing the statement, we disagree because both problems share a common core. The false dichotomy between ongoing harms and emergent risks makes it needlessly difficult to address common root causes.

AI poses many ongoing problems. AI systems can sustain human rights abuses, perpetuate systemic discrimination, and entrench power imbalances. Because AI systems are often widely deployed, harms can reach massive scales. For example, tens of thousands of families were pushed into poverty when the Dutch Tax and Customs Administration wrongly accused them of fraud and requested they pay back large sums of money, based on risk profiles created with AI systems.

The root causes of AI harm

There are several root causes that contribute to many instances of the harm caused by AI. One is that we do not know how to design AI systems that reliably behave exactly as we intend them to. For example, a health system was designed to allocate care based on need but discriminated against Black hospital patients. It turned out the algorithm used health care costs as a proxy for need, but institutionalized racism means that less money has been spent on Black patients historically. In many similar cases, companies do not explicitly set out to build harmful AI systems. Instead, creating state-of-the-art AI systems requires vast amounts of data, and the AI systems unintendedly inherit the biases encoded in this data.

Another cause is competitive pressures and limited accountability. There is often a strong economic incentive to deploy AI systems without sufficient safety checks. For example, Microsoft rushed the release of the Bing chatbot, which resulted in the chatbot threatening and insulting users. When the Dutch Tax Administration replaced human judgment with AI systems, this, too, happened in the name of efficiency.

Without decisive action to address these root causes, increasingly powerful and widely deployed AI systems will cause even more pervasive and significant harm. Many experts believe future AI systems may outmatch humans in crucial cognitive skills, such as social persuasion, planning, and development of novel technologies. Just as these cognitive abilities enabled humanity to control the fate of other species, the same skills could enable smarter AI systems to out-perform us. Given competition and limited accountability, there would be pressure on organizations to replace expensive human labor with AI systems. Economic forces encourage the rapid deployment of new AI systems (at the cost of safety testing), making them ever more powerful, building general (and potentially more powerful) systems rather than narrow (and potentially more controllable) systems, and increasing the autonomy of AI systems to take action in the world. AI systems could increasingly control our society's key productive, managerial, and military capacities. By then, we must have figured out how to design systems that always and truly behave as we intend. Otherwise, powerful AI systems that pursue goals at odds with humanity could lead to human marginalization or even extinction.

Read More: An AI Pause is Humanity's Best Bet for Preventing Extinction

Moreover, many researchers expect us to develop such advanced AI systems very soon. Companies are pouring more money and talent into AI development while the cost of computing power is decreasing. Simply using more computing power and data has reliably produced more capable AI systems, while AI algorithms have also improved. After seeing the rapid progress in AI over the past five years, Geoffrey Hinton, a founding father of modern AI, now expects that AI could broadly surpass human cognitive abilities—such as persuasion, planning, and scientific reasoning—within five to 20 years. Such time horizons are shared by many in the AI research community.

Twenty years is short; in discussions about the climate crisis, we regularly consider effects on such timescales. And just as climate change requires us to face air pollution and ongoing natural disasters as well as prevent future, even more, extreme weather events, we must tackle various AI risks and harms simultaneously. Even if we might be a couple of decades away from AI systems that are smarter than humans, that is little time to create the complex global governance structures necessary for this technology.

Work to address ongoing harms sometimes differs from work to manage extinction risk. We do not wish to erase nuance or potential differences between the perspectives. Yet, given common root causes, there is much room for collaboration and cooperation.

Four possible interventions

Many interventions could address the root problems. First, the public currently has little to no say over what models are built and how they are deployed. For example, those most affected by welfare systems have had little say in their automation. Private companies decide which risks are acceptable, as they have free rein over computing power and data, the key levers of AI development. Stronger democratic oversight over the supply of computing power and data would enhance public control over AI development and associated risks. For example, governments can monitor when large amounts of computing power are being used and for what purpose.

Second, a strong auditing regime, where independent third-parties would scrutinize the practices and development processes of AI labs, would help reduce risks overall. Auditing has already surfaced previously overlooked harms, such as bias in facial recognition, and could catch future failure modes like AI systems subverting human control or replicating autonomously. A standards body could ensure  AI systems, both before and after deployment, meet specified safety guidelines. Domestic agencies could enforce compliance, while an international organization would create universal standards.

Third, we should require meaningful human oversight of critical AI decisions, and avoid very-high-risk use cases such as lethal autonomous weapons. Uncertainty about AI systems' current and near-future capabilities means we should proceed cautiously around their deployment in critical domains.

Fourth, we should rebalance the  funding going into AIs and urge companies to spend less on making them smarter while increasing funding into making them safer, more transparent, and studying their social impacts. While it is good that industry labs are funding such research, this funding is liable to change with market conditions. Much more public funding for non-industry groups is required.

The development of increasingly powerful AI systems poses increasingly vast societal-scale risks. The complexity of these risks requires cooperation between people with potentially different motivations but with a shared interest in ensuring that AI development proceeds in a just and beneficial way.

More Must-Reads From TIME

Contact us at letters@time.com.

You May Also Like
EDIT POST

What did Sam Altman admit about ChatGPT and the potential risks of AI?

Advanced AI could pose an existential risk to humanity.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

What future risk did Hinton warn about AI?

The US Biden administration announced self-regulation of AI development by major tech companies in July 2023, aiming to promote responsible AI innovation.

Title:

Content: As Artificial Intelligence's (AI) use in business and government increases by leaps and bounds, the need for transparent, fair, and safe governance standards has moved off the planning list into action.

Introduction

As Artificial Intelligence's (AI) use in business and government increases by leaps and bounds, the need for transparent, fair, and safe governance standards has moved off the planning list into action. In a vacuum of universal guidelines, many corporations and governments have already begun to create their own standards to address the key topics of model transparency, explainability, and fairness. While these guidelines have been an excellent start, there is still a need for organizations to control and guide their AI development while also keeping the current and emerging regulatory environment in mind.

Due to the nascent nature of the field, there are few widely implemented and agreed upon best practices. The 2023 World Privacy Forum (WPF) report on Assessing and Improving AI Governance Tools1 attempts to remedy this gap by highlighting examples across 6 categories:

  1. Practical Guidance consisting of general education information on AI governance,
  2. Self-assessment Questionnaires,
  3. Procedural Framework with step-by-step workflows on AI systems and/or improvements,
  4. Technical Framework,
  5. Technical Code/Software,
  6. Scoring or Classification Output.

WPF are using the following definition of AI governance tools to shape their work: "socio-technical tools for mapping, measuring, or managing AI systems and their risks in a manner that operationalizes or implements trustworthy AI". In other words, when making decisions with AI, it is necessary to account for the system's transparency, explainability, fairness and potential societal impact.

Table 1: AI Governance tool types Lexicon

Category Tools
Practical Guidance Includes general educational information, practical guidance, or other consideration factors
Self-assessment Questions Includes assessment questions or detailed questionnaire
Procedural Framework Includes process steps or suggested workflow for AI system assessments and/or improvements
Technical Framework Includes technical methods or detailed technical process guidance or steps
Technical Code or Software Includes technical methods, including use of specific code or software
Scoring or Classification Output Includes criteria for determining a classification, or a mechanism for producing a quantifiable score or rating reflecting a particular aspect of an AI system

Table 1: AI Governance Tool Types Lexicon
Source: World Privacy Forum2

These tools mentioned are in active use worldwide, making them an excellent starting point to ensure compliance with present and future regulations. Without the appropriate tools in place, it is nearly impossible to ensure a trustworthy AI future. A survey conducted by the AI Risk and Security (AIRS) group evaluated the current status of AI governance across their members (Figure 1). The survey revealed that there is room to improve, with only 30% of enterprises have established roles or responsibilities for AI systems, and just 20% have a centrally managed and budgeted department dedicated to AI governance.

"Global spending on AI is expected to increase from $150 billion in 2023 to $300 billion by 2026. The use of AI is moving at a rapid pace with regulators' eyes keeping a close watch, and we're seeing leaders in the TMT industry create their own governance tools as a commercial and operational imperative." George Haitsch, WTW Technology, Media and Telecom Industry Leader

"

Global spending on AI is expected to increase from $150 billion in 2023 to $300 billion by 2026."

George Haitsch | WTW Technology, Media and Telecom Industry Leader

Implementing several AI governance tools fosters a collective understanding and assessment of possible risks and limitations in AI explainability, transparency, and fairness across different departments. All personnel engaging with AI models should possess awareness regarding its capabilities and shortcomings, emphasizing the importance of maintaining a skeptical perspective toward AI outputs.

Figure 1: The current status of AI governance in enterprises

Notes: Respondents included professionals from technology risk, information security, legal, privacy, architecture, model risk management, and other fields, working in financial and technology organizations, as well as academic institutions.

Emerging AI governance regulations

Regulation is evolving in different pathways around the world. Policy makers across the globe are hurriedly addressing the issues, gaps, and limitations of AI driven decisions.

This has prompted a surge of literature and research into the subject. In July 2023, the U.S. Biden administration announced3 that Amazon, Anthropic, Google, Inflection, Meta, Microsoft and OpenAI will self-regulate their AI development.

  • Congress' blueprint for an AI Bill of Rights4 provides practical guidance through a set of five principles and practices to government agencies and a call to action for technology companies, researchers, and civil society to build these protections5.

The EU produced a similar set of ethical guidelines to the US with 7 key requirements including transparency, accountability, and respect for privacy and data protection6. They also proposed a classification scoring system. In the European Union's A.I. Act, regulations are assigned proportionate to the level of risk posed by an AI tool: unacceptable, high, limited, and minimal risk.

  • Unacceptable risks that would be banned include AI systems that perform social scoring of individuals or real-time facial recognition in public places. Other tools carrying less risk, such as software that generates manipulated videos and "deepfake" images must disclose that people are seeing AI-generated content. Violators could be fined 6% of their global sales. Minimally risky systems include spam filters and AI-generated video games.

Canada produced a mandatory risk assessment tool in 2020 named as the Algorithmic Impact Assessment (AIA).7

  • It consists of 51 risk and 34 mitigation self-assessment questions to determine the impact level of an automated decision-system. The final assessment scores are based on factors such as system's design, algorithm, decision type, impact, and data.

Singapore launched a technical framework and software with AI Verify8 in partnership with companies from different sectors and scale including AWS, DBS Bank, Google, Meta, Microsoft, Singapore Airlines, and Standard Chartered Bank. It became open source in June 2023.

In June 2023, China revealed that it was developing an "Artificial Intelligence Law" that could offer practical guidance, a technical framework, and a classification scoring system. Rather than devising a comprehensive regulatory plan, China has chosen to regulate AI through individual legislation, with specific laws addressing issues such as algorithms, generative AI, and deepfakes.

Global companies will be facing increasing pressure to comply with regulatory standards in AI governance. This often presents a challenge as they must also comply with other regulatory measures, such as ESG. As a result, companies may spend more time disclosing information about their algorithms rather than making tangible progress.

Risks and limitations – Explainability, oversimplification & bias

Several AI governance tools, including fairness AI auditing software, may be limited in their application to specific phases of the AI life cycle. AI fairness tools might solely address fairness concerns during the model training stage of AI development. However, ensuring fairness at one stage does not guarantee its persistence throughout the entire AI life cycle.

AI Life Cycle
Source: NHS England "Creating an international approach to AI for healthcare"9

Addressing bias in AI models through technical code or software is just the beginning for AI governance. Companies must extend their focus beyond the technical developers' Proof Of Value. AI fairness auditing implemented across the entire AI life cycle along with comprehensive documentation is key. The documentation should incorporate various AI governance tools understandable to both technical and non-technical audiences.

Technical developers are focused on achieving explainability by describing the mechanisms of an AI system or algorithm through software/code. One of the major problems for evaluating explainability from the technical developer's point of view is oversimplification.

  • For example, the utilization of both SHAP10 (Shapley Additive exPlanations) and LIME11 (Local Interpretable Model-agnostic Explanations) for model explainability has seen an uptick. This rise in popularity is partly owed to the methods' model-agnostic nature, allowing evaluation of any model, and to their abundance of user-friendly documentation.

In a typical scenario, a data scientist may opt for SHAP or LIME to show how an output was determined for a single instance of a model input, such as a specific decision or prediction, rather than the entire model. In other words, both methods operate by approximating more intricate, non-linear models (often referred to as "black-box" models) with simpler linear models, potentially resulting in misleading outcomes.

Global companies will be facing increasing pressure to comply with regulatory standards in AI governance.

Oversimplification and the potential lack of critical context poses a significant challenge. Some algorithms designed for specific social settings may be inaccurately applied in different contexts, resulting in technical inaccuracies and misguided outcomes. The NIST AI Risk Management Framework12, examined in Part II of the report, acknowledges the shortcomings of metrics used to measure AI risk, citing the risk of oversimplification, gaming, lack of critical nuance, and unexpected reliance.

This deficiency in contextual understanding could lead to unfair resource allocation or access, with implications across various areas such as mortgage lending, employment screening, college admissions, child welfare, and medical diagnoses.

Business recommendations and model framework

An AI governance framework should encompass internal governance structures and measures, define the extent of human involvement in AI decision-making, address operations management, facilitate stakeholder interaction and communication, and illustrate de-risking strategies for AI across the entire business to mitigate large-scale failures.

1. Internal governance structures and measures

Internal governance structures and measures play a crucial role in ensuring robust oversight of an organization's use of AI. They should be addressing risks and integrating ethical considerations through ethics review boards.

Organizations may explore features for their internal governance structures, such as clear roles and responsibilities for ethically deploying AI. A decentralized governance mechanism might be considered when a centralized approach is suboptimal, bringing ethical considerations into day-to-day decision-making.

2. Determining the level of human involvement in AI decision-making

Before deploying AI solutions, organizations are advised to determine how much influence humans have in the process. The levels addressing human oversight with AI are listed below:

Human-in-the-loop: In this model, human oversight is active, with people retaining full control. The AI provides recommendations or input to the humans driving the process.

Human-out-of-the-loop: In this model, there is no human oversight, and the AI system has full control without the option of human override.

Human-over-the-loop (or human-on-the-loop): This model involves human oversight to the extent that the human is in a supervisory role, with the ability to take control in the face of unexpected events. Humans can adjust parameters during the algorithm's operation. Examples include: AI assisted medical diagnoses, product recommendations, or GPS navigation systems.

3. Data management and governance

The individuals involved in model training and selection, whether internal staff or external providers, should work collaboratively. Data accountability practices, including understanding data lineage, ensuring data quality, and minimizing inherent bias, are essential. Organizations must understand the lineage of data and address factors affecting data quality.

Minimizing inherent bias involves being aware of biases in datasets, using heterogeneous datasets, and employing different datasets for training, testing, and validation. Regular review and updating of datasets, even if non-personal, are recommended for accuracy, quality, and reliability. Good data accountability practices apply even when using non-personal data or anonymized personal data in AI model training.

In deploying AI algorithms, organizations must iterate through model development until achieving the most suitable results for their use case. The interaction between data and algorithms/models is vital. Datasets, sourced from various places, both personal and non-personal, are integral to the AI solution's success.

4. Stakeholder interaction and communication

Effective AI governance relies on clear end-to-end communication with various stakeholders such as developers, executives, regulators, external AI tool customers, internal business users, and more. Achieving this involves concise and accessible AI documentation, addressing model gaps and biases, and specifying appropriate use cases.

Transparent communication, simple user interfaces, opt-out mechanisms, and feedback channels are paramount for user understanding and interaction. Organizations should regularly assess their AI governance against evolving ethical standards and share the results with relevant stakeholders. Meta's "Why am I seeing this?"13 feature exemplifies transparency in advertising and machine learning model training. As AI progresses, AI governance evolves. WTW will continue to keep pace with that change and explore collaboration amongst employees, executives, users, and researchers on examining and enhancing AI for optimal governance.

Footnotes

1. World Privacy Forum - Risky Analysis - December 2023. Return to article undo

2. Model Artificial Intelligence Governance Framework - Second Edition. Return to article undo

3. Readout of White House Listening Session on Tech Platform Accountability. Return to article undo

4. A Framework for U.S. AI Governance: Creating a Safe and Thriving AI Sector. Return to article undo

5. Generative AI: Implications for Trust and Governance. Return to article undo

6. What is AI Verify? Return to article undo

7. Artificial intelligence act. Return to article undo

8. Creating an international approach to AI for healthcare. Return to article undo

9. AI Risk Management Framework. Return to article undo

10. An introduction to explainable AI with Shapley values. Return to article undo

11. LIME - Local Interpretable Model-Agnostic Explanations. Return to article undo

12. AI Risk Management Framework. Return to article undo

13. Increasing Our Ads Transparency. Return to article undo

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

The EU proposed a classification scoring system for AI tools with 7 key requirements, including transparency and accountability, to ensure AI safety and security.

Canada introduced a mandatory risk assessment tool, Algorithmic Impact Assessment, in 2020, demonstrating a proactive approach to AI governance.

The NIST AI Risk Management Framework acknowledges shortcomings of metrics used to measure AI risk, highlighting the need for ongoing research and improvement.

CoSAI, an open-source initiative, was formed to address AI security fragmentation and develop best practices for AI safety, with sponsorship from major companies like Google and IBM.

Title:

Content: Science and Technology
Technology: Google, Microsoft, Nvidia and many other tech giants collaborate for AI safety
14 major AI companies including Google, Microsoft, Amazon, Nvidia, and Intel, as well as OpenAI, IBM, PayPal, Cisco, and Anthropic, have come together to form the Secure Artificial Intelligence Alliance (CoSAI).
This development is said to be aimed at addressing the fragmented landscape of AI security.
Hosted by the global standards body OASIS, CoSAI is an open source initiative that aims to provide all AI practitioners and developers with the guidance and tools they need to create and design secure AI systems.
It is expected to build a collaborative ecosystem to share open source methods, standardized frameworks and tools.
CoSAI is an open source community led by a project board (responsible for developing and managing its public agenda), and a technical steering committee (composed of AI experts from academia and industry, which oversees its workflows).
What are the main objectives of the initiative?
• Develop best practices for AI safety
• Facing challenges in artificial intelligence
• Ensuring the security of artificial intelligence applications
CoSAI ’ s scope of work includes building, integrating, deploying, and operating AI systems securely, with a focus on mitigating risks such as model theft, data poisoning, tip injection, domain misuse, and heuristic attacks.
Heather Adkins, vice president of security at Google, said:
Artificial intelligence has been under development for many years, with the continued potential it offers to defenders, while also recognizing the opportunities it offers to enemies.
CoSAI will help organizations large and small integrate AI safely and responsibly, helping them leverage the benefits of AI while mitigating risk.
The initiative is reportedly sponsored by Google, IBM, Intel, Microsoft, Nvidia, PayPal, Amazon, Anthropic, Cisco, Chainguard, Cohere, GenLab, OpenAI, and Wiz.
Source
Advertisements
You may also read.

The US is developing AI standards with companies like Apple and Google, while California proposes AI regulation with safety standards, aiming to codify US standards into law.

Title:

Content: sdecoret - stock.adobe.com

US works to develop AI standards while California legislates

California has proposed AI regulation as the U.S. works to develop AI standards by bringing together companies such as Apple, Amazon, Google and Microsoft.

While the Biden administration is working to develop AI safety standards, California may move faster and make AI safety the law.

Califiornia Sen. Scott Wiener (D-San Francisco) introduced Senate Bill 1047 on Thursday, AI legislation that would establish safety standards for developers of large AI systems. The standards would not apply to startups developing "less potent models," according to a statement. By "less potent AI," Wiener is likely referring to AI systems known as narrow or weak AI, which are designed for specific tasks, such as predictive modeling. The bill also establishes a public cloud offering called CalCompute to enable startups, researchers and others to participate in developing large AI systems.

The proposed legislation follows on the heels of the Biden administration's creation of the U.S. AI Safety Institute Consortium (AISIC), which will help meet the goals Biden set out in his executive order on AI last year. The consortium will help develop guidelines for red-team safety testing, risk management, safety, security and watermarking AI-generated content. It brings together more than 200 leading AI stakeholders to weigh in on the development of AI safety standards, including Amazon, Apple, Google, Adobe, Accenture, Intel, Meta, Microsoft, Nvidia, OpenAI, Salesforce and Workday.

Wiener recognized that developers have pioneered safe development practices for AI systems. However, the release announcing the proposed AI regulation said that California's government "cannot afford to be complacent" about regulating AI.

"With Congress paralyzed and the future of the Biden administration's executive order in doubt, California has an indispensable role to play in ensuring that we develop this extremely powerful technology with basic safety guardrails," according to the statement.

California wants to build off US standards with AI regulation

The proposed AI legislation in California aims to advance AISIC's efforts in AI safety by codifying its best practices into law, according to the statement.

Wiener said that the proposed legislation offers a chance to use insights gained from past failures to regulate other technologies.

"We've seen the consequences of allowing the unchecked growth of new technology without evaluating, understanding or mitigating the risks," he said in the statement. "SB 1047 does just that, by developing responsible, appropriate guardrails around development of the biggest, most high-impact AI systems to ensure they are used to improve Californians' lives, without compromising safety or security."

Some of the AI safety standards set out in SB 1047 include pre-deployment safety testing and implementation of cybersecurity protections for a handful of "extremely large AI developers," according to the release. The bill creates "no new obligations for startups or business customers of AI products."

Congress has yet to advance any AI legislation, and policymakers are unsure about what AI legislation might be adopted in 2024. The Biden administration has taken steps through executive powers to advance AI safety standards, including creating the consortium and relying on public sector partners to help develop those guidelines.

"The U.S. government has a significant role to play in setting the standards and developing the tools we need to mitigate the risks and harness the immense potential of artificial intelligence," Gina Raimondo, U.S. secretary of commerce, said in a statement. "By working with this group of leaders from industry, civil society and academia, together we can confront these challenges to develop the measurements and standards we need to maintain America's competitive edge and develop AI responsibly."

California's advancement of AI regulation could create confusion for businesses if they're eventually forced to navigate multiple sets of AI safety standards, especially if individual states' rules conflict with broader U.S. standards, said Hodan Omaar, senior policy analyst at the Information Technology and Innovation Foundation's Center for Data Innovation.

"Creating California-specific safety standards for large-scale AI systems is problematic because it sets the stage for a patchwork of safety rules, with different states coming up with their own diverse sets of standards that providers of these systems will have to navigate," she said. "A national set of standards that preempts states from creating their own standards is a much better approach."

Makenzie Holland is a news writer covering big tech and federal regulation. Prior to joining TechTarget Editorial, she was a general reporter for Wilmington StarNews and a crime and education reporter at the Wabash Plain Dealer.

Dig Deeper on Risk management and governance

Cloud Computing
Mobile Computing
Data Center
Sustainability and ESG
Close

The Biden administration created the AI Safety Institute Consortium to develop guidelines for safety testing and promote AI safety research.

Independent auditing can reduce AI risks and surface previously overlooked harms, emphasizing the importance of rigorous testing and evaluation.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

Meaningful human oversight of critical AI decisions is required to ensure accountability and prevent AI-related accidents.

What does Hinton warn could happen to AI if companies and regulators fail to implement effective rules and controls?

Public funding for non-industry AI research is necessary for safety and transparency, as it allows for unbiased and objective investigation of AI risks and benefits.

The global community is taking proactive measures to address AI safety risks, with 18 countries signing an agreement on AI security standards and prioritizing customer and public protection.

Title:

Content: AI design should be based on security, 18 countries including the United Kingdom and the United States sign agreements
▲ The 18 signatory countries agreed that companies designing and deploying AI must develop and deploy it from the perspective of protecting customers and the general public from the threat of AI abuse.
(Schematic / CFP)
Central News Agency, Washington, 26.
Eighteen countries, including the United States and Britain, today announced an international agreement that, according to senior U.S. officials, is the first time that the international community has documented how to protect AI from unscrupulous people and promote companies to create “security-based ” AI systems.
In the 20-page document released today, 18 signatories agreed that companies designing and deploying artificial intelligence (AI) must develop and deploy it in a way that protects customers and the general public from the threat of AI abuse.
The agreement is non-binding and consists mainly of general recommendations, such as monitoring AI systems for abuse, protecting data against tampering, and vetting software vendors.
Still, Jen Easterly, director of the Department of Homeland Security ’ s Cybersecurity and Infrastructure Security Agency (CISA), said it ’ s important that so many countries agree that AI systems need to put security first.
“This is the first time we ’ ve seen a statement in black and white that (AI) shouldn ’ t just be about cool features, how quickly it can be launched in the market, or how to compete with each other to reduce costs, ” Eastley told Reuters.
He said that the guidelines represent a consensus that the number one priority in the design phase of AI is safety.
The agreement is the latest in a series of initiatives by governments around the world to shape AI development, even if few of them are truly “powerful. ”
AI ’ s influence is becoming more and more felt in both the industry and society.
In addition to the United States and the United Kingdom, Germany, Italy, the Czech Republic, Estonia, Poland, Australia, Chile, Israel, Nigeria and Singapore have signed the new guidelines.
The framework addresses the issue of how to prevent AI technology from being manipulated by hackers and recommends that companies only publish models that pass security tests.
But the guide doesn ’ t address a few thorny issues, including how to properly use AI or how to access input model data.
The rise of AI has raised a host of concerns, including fears that AI could be used to disrupt the democratic process, facilitate fraud, and cause serious unemployment.
Share with friends:
※ This article is copyrighted and cannot be reproduced without permission. [ETtoday Copyright Notice]
Related News
Key words:
Hot News
The best video
And more.
Hot News
Back to the top.

Companies pledged safe AI development, committing to prioritize security and transparency, and allowing third-party researchers to find vulnerabilities in their AI systems.

Title:

Content: The Daily Ripple-News Music Ideas

Switch to desktop

Articles

Companies have pledged safe AI development, White House says

The Biden administration said it has received voluntary commitments from the world’s largest developers of artificial intelligence systems that the companies would pursue development in a safe and secure manner.

Google, Amazon, Inflection, Meta, Microsoft, Anthropic and OpenAI have committed to developing such technologies in a “safe, secure, and transparent” manner, a White House official told reporters Thursday on the condition of anonymity, while discussing a meeting taking place Friday between the top executives of the companies and administration officials.

The Biden administration is preparing an executive order “that will ensure the federal government is doing everything in its power to advance safe, secure, and trustworthy AI and manage its risks to individuals and society,” the official said.

The White House also is coordinating with efforts in Congress aimed at establishing a “legal and regulatory regime,” the official said.

Senate Majority Leader Charles E. Schumer has arranged a series of briefings for senators on artificial intelligence systems and has said he intends to draw up legislation to regulate AI systems in the next few months. On Friday, Schumer said he welcome the voluntary commitments, but added that harnessing the potential while tackling challenges posed by AI “requires legislation to build and expand on the actions” by the White House.

Sen. Mark Warner, D-Va., chair of the Senate Intelligence Committee also said “some degree of regulation” was needed to ensures that AI companies “prioritize security, combat bias, and responsibly roll out new technologies.” In April Warner wrote to CEOs of major tech companies asking them to prioritize security in design and development of technologies.

The White House official said the companies have committed to making sure their products and technologies are safe before they’re publicly launched, building systems with security as a priority, and ensuring that consumers and users know which content is generated by AI and publicly reporting on inappropriate uses of the technology.

Some companies including OpenAI already have said they use so-called red teams, which pretend to emulate nefarious actors’ actions, to test for weakness in the ChatGPT-4 model. The voluntary commitments are intended to ensure that all companies adopt similar practices, as well as “pushing the envelope” safety, security, and transparency measures, the official said.

One of the measures that would advance the goal of safety and trust is an effort by companies to develop a watermarking system, the official said. Tech companies have committed to developing a system that would label audio and video content developed by artificial intelligence tools to distinguish them from those generated by humans, the official said.

Brad Smith, vice chairman and president of Microsoft, wrote in a blog post on Friday that the company would go beyond those commitments by collaborating with the National Science Foundation to explore the creation of a national AI research resource that would facilitate independent research by academics on AI safety. The company also would back the creation of a national registry of high-risk AI systems, Smith wrote.

Companies also have committed to sharing information with each other and with academic researchers, government agencies, and civil society groups on best practices, and information on managing risks, according to a White House fact sheet

The fact sheet also said the companies have committed to allowing third-party researchers to find and report vulnerabilities in the AI systems.

The post Companies have pledged safe AI development, White House says appeared first on Roll Call.

Read more https://www.rollcall.com/2023/07/21/companies-have-pledged-safe-ai-development-white-house-says/

News aggregator updating headlines throughout the day to top news & Links to international news, social commentary and columnists creating a better world. External links are provided for reference purposes. The Daily Ripple is not responsible for the content of external Internet sites. tlr workshop 2015

Top Desktop version

The US Cybersecurity and Infrastructure Security Agency collaborated on AI guidelines, emphasizing the importance of cybersecurity in AI safety and security.

Title:

Content: BETA
This is a BETA experience. You may opt-out by clicking here

More From Forbes

Edit Story

Why Cybersecurity Is Foundational To AI Safety

Click to save this article.
You'll be asked to sign into your Forbes account.
Got it

Marcus Fowler is SVP of Strategic Engagements and Threats at Darktrace and CEO of Darktrace Federal.

From smartphones and social media to the internet itself, technology has the power to fundamentally change our daily lives. But too often technology’s rapid development and adoption outpaces our ability to discuss their associated risks. While the benefits of these advancements are great, there are often unintended consequences with lasting effects.

With generative AI such as ChatGPT becoming widely available, AI has seen a rapid rise in public adoption across industry verticals. This new generation of AI marks a technological advancement that is potentially on par with the introduction of the internet but with adoption orders of magnitude faster. The potential benefits are vast; however, we’re already seeing early signs of how this technology could be misused and threats that could derail its potential. For example, deepfakes are being used to spread misinformation, and sophisticated novel social engineering attacks are crafted using generative AI.

Global Initiatives: Addressing AI Safety And Security

Fortunately, the global community has demonstrated a strong commitment to moving quickly to address the potential risks. The U.K. hosted the inaugural AI Safety Summit in early November. In the same week, the Biden-Harris Administration released an executive order establishing new standards for AI safety and security. Both countries have announced new AI Safety Institutes to develop robust techniques to evaluate AI. Most recently, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) and the U.K. National Cyber Security Centre (NCSC) collaborated on guidelines for building secure AI systems, which have been adopted by 21 other international agencies.

As AI becomes embedded into the tools and processes we depend on every day, it is vital that they are secure. In fact, the Biden-Harris Administration’s executive order highlights cybersecurity as a significant risk to AI systems. Cybersecurity is foundational to AI safety—it is a prerequisite for trustworthy and safe AI.

To realize the importance of prioritizing cybersecurity, it’s helpful to understand the cyber risks to AI safety: offensive applications of AI in cyberspace, accidental insider threats and cyberattacks targeting AI itself.

At Darktrace, we have been researching offensive applications of AI in cyberspace for years. The rise of generative AI is lowering barriers for attackers and is poised to make them faster. AI-powered cyberattacks can involve using large language models (LLM) to generate sophisticated or highly personalized text in phishing emails, and this process can be completely automated using tools like AutoGPT. LLMs are already showing up on the dark web that claim to write malware code for a few hundred dollars, and attackers can use AI to augment nearly every stage of the attack lifecycle from reconnaissance to command and control.

It’s not just attackers who are using AI to drive more efficiency. AI tools have been rapidly adopted by companies and workers: As of June 2023, we saw that nearly 75% of our customers already had some employees using generative AI tools. However, well-intentioned employees run the risk of inadvertent misuse. For example, an employee inserting sensitive data into a prompt-based LLM tool such as ChatGPT might unintentionally leak proprietary or personal data.

In a high-profile incident, these concerns motivated the U.S. Space Force to temporarily ban Guardians from using government data in generative AI solutions, with a Space Force spokesperson citing the need to "ensure that sensitive DOD data is safeguarded when using such platforms."

It is also important to protect AI systems themselves against cyberattacks. Take, for example, the secure development of AI. This involves defending against threats such as "data poisoning" attacks that corrupt training data to adversely affect the AI’s behavior. Attacks like these may cause the AI to behave in ways that are unexpected or harmful. As AI gets embedded into critical infrastructure and business processes, it’s critical that attackers can’t hijack or trick the guardrails within these tools. Cyberattacks can also be used to steal intellectual property (IP), not only for AI algorithms and data but also for advanced chips that drive AI development.

Priorities: Data Privacy, Control And Trust

It’s positive to see governments taking action to predict the challenges this new generation of general-purpose AI presents. Our history of predicting or properly securing and overseeing technologies, such as the internet and social media adoption, is inadequate, and we can see how much more difficult it is to put the genie back in the bottle. There are three areas of action that governments and companies should prioritize: data privacy, control and trust.

AI systems should be privacy-preserving. Companies building and using general-purpose AI need to protect the data they collect and use to train their models. Organizations should invest in safeguards to detect, identify and test potential risks that can come from within their businesses. That means guarding against personally protected information accidentally being leaked through prompt injections on generative AI platforms.

Humans need control, particularly as general-purpose AI tools become increasingly relied on to take real-world actions. It’s critical to apply cybersecurity best practices to protect models and invest in safeguards to keep AI systems protected at all stages of the AI lifecycle to avoid unintended behaviors or potential hijacking of the algorithms.

Security and transparency are always the foundation of trust: If people cannot have faith in the cybersecurity of their AI systems, they will not be able to trust them to carry out critical functions. Developers can help to ensure that people understand and are aware of how an AI system reaches its decisions and answers.

Though the AI safety risks posed by malicious cyber activity are serious, there is no reason to fall into pessimism. Instead, one should feel optimistic to see the proactive measures taken by the global community. Agencies across the U.S. Federal Government are already working to implement the executive order, and South Korea and France are working on a second and third Global AI Safety Summit.

The good news is that tried-and-true AI tools already exist for cyber defense and have been defending critical infrastructure and other sensitive environments for over a decade. Cybersecurity is foundational to AI safety, and AI itself can play a vital role in mitigating risks.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Follow me on LinkedInCheck out my website

Cybersecurity is foundational to AI safety, and AI systems should be designed with security in mind to prevent data poisoning attacks and other vulnerabilities.

What risks did the global summit report highlight about AI?

Creating malicious software for cyberattacks, potentially posing an existential threat if humans lose control.

Governments prioritize data privacy, control, and trust in AI systems, recognizing the need for robust safeguards to protect sensitive information.

AI systems should be privacy-preserving and secure, with built-in measures to prevent data breaches and unauthorized access.

The NCSC published guidelines on AI cyber security, aiming to promote a secure-by-design culture in AI development and emphasizing radical transparency and security ownership.

Title:

Content: Laurent - stock.adobe.com

NCSC publishes landmark guidelines on AI cyber security

The NCSC and its US counterpart CISA have brought together tech companies and governments to countersign a new set of guidelines aimed at promoting a secure-by-design culture in AI development

The UK’s National Cyber Security Centre has published a set of guidelines designed to help ensure that artificial intelligence (AI) technology is developed safely and securely, written alongside tech sector partners, and developed with crucial assistance from the US’ Cybersecurity and Infrastructure Security Agency (CISA).

The Guidlelines for secure AI system development are said to be the first of their kind in the world, and besides the UK and US, were developed with input from other G7 nations, international agencies, and government bodies from a number of countries, including voices from the Global South.

“We know that AI is developing at a phenomenal pace and there is a need for concerted international action, across governments and industry, to keep up,” said NCSC CEO Lindy Cameron.

“These guidelines mark a significant step in shaping a truly global, common understanding of the cyber risks and mitigation strategies around AI to ensure that security is not a postscript to development but a core requirement throughout.

“I’m proud that the NCSC is leading crucial efforts to raise the AI cyber security bar: a more secure global cyber space will help us all to safely and confidently realise this technology’s wonderful opportunities,” she said.

Cameron’s American counterpart, CISA director Jen Easterly, added: “The release of the Guidelines for secure AI system development marks a key milestone in our collective commitment – by governments across the world – to ensure the development and deployment of artificial intelligence capabilities that are secure by design.

“As nations and organisations embrace the transformative power of AI, this international collaboration, co-developed by the UK NCSC and CISA, underscores the global dedication to fostering transparency, accountability, and secure practices.

“The domestic and international unity in advancing secure-by-design principles and cultivating a resilient foundation for the safe development of AI systems worldwide could not come at a more important time in our shared technology evolution. This joint effort reaffirms our mission to protect critical infrastructure and reinforces the importance of cross-border collaboration in securing our digital future.”

The set of guidelines has been designed to help the developers of any system that incorporates AI make informed decisions about cyber security during the development process – whether it is being built from scratch or as an add-on to an existing tool or service provided by another entity.

The NCSC believes security to be an “essential pre-condition of AI system safety” and integral to the development process from the outset and throughout.

In a similar way to how the secure-by-design principles alluded to by CISA’s Easterly are increasingly being applied to software development, the cognitive leap to applying the same guidance to the world of AI should not be too difficult to make.

The guidelines, which can be accessed in full via the NCSC website, break down into four main tracks – Secure Design, Secure Development, Secure Deployment and Secure Operation and Maintenance, and include suggested behaviours to help improve security. These include taking ownership of security outcomes for customers and users, embracing “radical transparency”, and baking secure-by-design practices into organisational structures and leadership hierarchies.

The document has already been endorsed and co-sealed by a number of key organisations in the field, including tech giants Amazon, Google, Microsoft and OpenAI, and representatives from 17 other countries – besides the Five Eyes intelligence alliance and the G7, these include Chile, Czechia, Estonia, Israel, Nigeria, Norway, Poland, Singapore and South Korea.

For the UK government, the document’s creation builds on discussions held at its AI Safety Summit at the beginning of November, which while not explicitly a cyber security-focused event, nevertheless sought to begin the necessary conversation around how society should manage the risks of AI.

For the Americans, it follows on from a recently published CISA roadmap on AI, which supports an October Executive Order signed by president Joe Biden that aims to build a foundation of standards that might one day underpin state or federal-level legislation in the US – with inevitable global impact.

CISA’s roadmap sets out five “lines of effort” that it means to pursue. These are:

  1. To responsibly use AI to support CISA’s core cyber mission;
  2. To assess and assure secure-by-design AI tech across the private and public sectors;
  3. To protect critical national infrastructure (CNI) from malicious AIs;
  4. To collaborate and communicate on AI efforts in the US and across the rest of the world;
  5. And to expand AI expertise and skills.

Industry reacts

“These early days of AI can be likened to blowing glass: while the glass is fluid it can be made into any shape, but once it has cooled, its shape is fixed. Regulators are scrambling to influence AI regulation as it takes shape,” said WithSecure cyber security advisor Paul Brucciani.

“Guidelines are quick to produce since they do not require legislation, nonetheless, NCSC and CISA have worked with impressive speed to corral this list of signatories. Amazon, Google, Microsoft and OpenAI, the world-leading AI developers, are signatories. A notable absentee from the list is the EU.”

Darktrace global head of threat analysis, Toby Lewis, said: “Security is a pre-requisite for safe and trustworthy AI and today’s guidelines from agencies including the NCSC and CISA provide a welcome blueprint for it. I’m glad to see the guidelines emphasise the need for AI providers to secure their data and models from attackers, and for AI users to apply the right AI for the right task.

“Those building AI should go further and build trust by taking users on the journey of how their AI reaches its answers. With security and trust, we’ll realise the benefits of AI faster and for more people,” added Lewis, who prior to his appointment at Darktrace served as deputy technical director of incident management at the NCSC for four years.

Read more about cyber security and AI

  • Supported by Darktrace, Loughborough University is to recruit five doctoral researchers focusing on cross-disciplinary research in AI and cyber security.
  • As cyber threats increasingly target cloud infrastructure, demand for robust and reliable incident response measures is through the roof. Find out why you might want to consider bringing AI to the table.
  • We know that malicious actors are starting to use artificial intelligence (AI) tools to facilitate attacks, but on the other hand, AI can also be a powerful tool within the hands of cyber security professionals.

Read more on Security policy and user awareness

CIO
Security
Networking
Data Center
Data Management
Close

The guidelines were developed with US CISA and G7 nations, demonstrating international cooperation and a shared commitment to AI safety and security.

The EU is a notable absentee from the list of signatories to the NCSC guidelines, highlighting the need for broader international participation and agreement on AI standards.

The Biden-Harris Administration completed key AI actions in 180 days, including the establishment of a framework for nucleic acid synthesis screening and the release of draft documents on managing generative AI risks.

Title:

Content: Biden-Harris Administration Commends Federal Agencies for Completing Key AI Actions in 180 Daysby@whitehouse
183 reads

Biden-Harris Administration Commends Federal Agencies for Completing Key AI Actions in 180 Days

by The White HouseMay 1st, 2024

Too Long; Didn't Read

The Biden-Harris Administration celebrates the successful completion of key AI actions mandated by President Biden's Executive Order, focusing on AI safety, security, equity, innovation, and talent acquisition. Federal agencies report significant progress in managing AI risks, promoting fairness, harnessing AI for good, and recruiting AI talent into government roles.

Biden-Harris Administration Announces Key AI Actions 180 Days Following President Biden’s Landmark Executive Order

Six months ago, President Biden issued a landmark Executive Order to ensure that America leads the way in seizing the promise and managing the risks of artificial intelligence (AI). Since then, agencies all across government have taken vital steps to manage AI’s safety and security risks, protect Americans’ privacy, advance equity and civil rights, stand up for consumers and workers, promote innovation and competition, advance American leadership around the world, and more.

Today, federal agencies reported that they completed all of the 180-day actions in the E.O. on schedule, following their recent successes in completing each 90-day, 120-day, and 150-day action on time. Agencies also progressed on other work tasked by the E.O. over longer timeframes.

Actions that agencies reported today as complete include the following:

Managing Risks to Safety and Security:

Over 180 days, the Executive Order directed agencies to address a broad range of AI’s safety and security risks, including risks related to dangerous biological materials, critical infrastructure, and software vulnerabilities. To mitigate these and other threats to safety, agencies have:

  • Established a framework for nucleic acid synthesis screening to help prevent the misuse of AI for engineering dangerous biological materials. This work complements in-depth study by the Department of Homeland Security (DHS), Department of Energy (DOE) and Office of Science and Technology Policy on AI’s potential to be misused for this purpose, as well as a DHS report that recommended mitigations for the misuse of AI to exacerbate chemical and biological threats. In parallel, the Department of Commerce has worked to engage the private sector to develop technical guidance to facilitate implementation. Starting 180 days after the framework is announced, agencies will require that grantees obtain synthetic nucleic acids from vendors that screen.

  • Released for public comment draft documents on managing generative AI risks, securely developing generative AI systems and dual-use foundation models, expanding international standards development in AI, and reducing the risks posed by AI-generated content. When finalized, these documents by the National Institute of Standards and Technology (NIST) will provide additional guidance that builds on NIST’s AI Risk Management Framework, which offered individuals, organizations, and society a framework to manage AI risks and has been widely adopted both in the U.S. and globally.

  • Developed the first AI safety and security guidelines for critical infrastructure owners and operators. These guidelines are informed by the completed work of nine agencies to assess AI risks across all sixteen critical infrastructure sectors.

  • Launched the AI Safety and Security Board to advise the Secretary of Homeland Security, the critical infrastructure community, other private sector stakeholders, and the broader public on the safe and secure development and deployment of AI technology in our nation’s critical infrastructure. The Board’s 22 inaugural members include representatives from a range of sectors, including software and hardware company executives, critical infrastructure operators, public officials, the civil rights community, and academia.

  • Piloted new AI tools for identifying vulnerabilities in vital government software systems. The Department of Defense (DoD) made progress on a pilot for AI that can find and address vulnerabilities in software used for national security and military purposes. Complementary to DoD’s efforts, DHS piloted different tools to identify and close vulnerabilities in other critical government software systems that Americans rely on every hour of every day.

Standing up for Workers, Consumers, and Civil Rights

The Executive Order directed bold steps to mitigate other risks from AI—including risks to workers, to consumers, and to Americans’ civil rights—and ensure that AI’s development and deployment benefits all Americans. Today, agencies reported that they have:

  • Developed bedrock principles and practices for employers and developers to build and deploy AI safely and in ways that empower workers. Agencies all across government are now starting work to establish these practices as requirements, where appropriate and authorized by law, for employers that receive federal funding.

  • Released guidance to assist federal contractors and employers comply with worker protection laws as they deploy AI in the workplace. The Department of Labor (DOL) developed a guide for federal contractors and subcontractors to answer questions and share promising practices to clarify federal contractors’ legal obligations, promote equal employment opportunity, and mitigate the potentially harmful impacts of AI in employment decisions. DOL also provided guidance regarding the application of the Fair Labor Standards Act and other federal labor standards as employers increasingly use of AI and other automated technologies in the workplace.

  • Released resources for job seekers, workers, and tech vendors and creators on how AI use could violate employment discrimination laws. The Equal Employment Opportunity Commission’s resources clarify that existing laws apply the use of AI and other new technologies in employment just as they apply to other employment practices.

  • Issued guidance on AI’s nondiscriminatory use in the housing sector. In two guidance documents, the Department of Housing and Urban Development affirmed that existing prohibitions against discrimination apply to AI’s use for tenant screening and advertisement of housing opportunities, and it explained how deployers of AI tools can comply with these obligations.

  • Published guidance and principles that set guardrails for the responsible and equitable use of AI in administering public benefits programs. The Department of Agriculture’s guidance explains how State, local, Tribal, and territorial governments should manage risks for uses of AI and automated systems in benefits programs such as SNAP. The Department of Health and Human Services (HHS) released a plan with guidelines on similar topics for benefits programs it oversees. Both agencies’ documents prescribe actions that align with the Office of Management and Budget’s policies, published last month, for federal agencies to manage risks in their own use of AI and harness AI’s benefits.

  • Announced a final rule clarifying that nondiscrimination requirements in health programs and activities continue to apply to the use of AI, clinical algorithms, predictive analytics, and other tools. Specifically, the rule applies the nondiscrimination principles under Section 1557 of the Affordable Care Act to the use of patient care decision support tools in clinical care, and it requires those covered by the rule to take steps to identify and mitigate discrimination when they use AI and other forms of decision support tools for care.

  • Developed a strategy for ensuring the safety and effectiveness of AI deployed in the health care sector. The strategy outlines rigorous frameworks for AI testing and evaluation, and it outlines future actions for HHS to promote responsible AI development and deployment.

Harnessing AI for Good

President Biden’s Executive Order also directed work to seize AI’s enormous promise, including by advancing AI’s use for scientific research, deepening collaboration with the private sector, and piloting uses of AI. Over the past 180 days, agencies have done the following:

  • Announced DOE funding opportunities to support the application of AI for science, including energy-efficient AI algorithms and hardware.

  • Prepared convenings for the next several months with utilities, clean energy developers, data center owners and operators, and regulators in localities experiencing large load growth. Today, DOE announced new actions to assess the potential energy opportunities and challenges of AI, accelerate deployment of clean energy, and advance AI innovation to manage the growing energy demand of AI.

  • Launched pilots, partnerships, and new AI tools to address energy challenges and advance clean energy. For example, DOE is piloting AI tools to streamline permitting processes and improving siting for clean energy infrastructure, and it has developed other powerful AI tools with applications at the intersection of energy, science, and security. Today, DOE also published a report outlining opportunities AI brings to advance the clean energy economy and modernize the electric grid.

  • Initiated a sustained effort to analyze the potential risks that deployment of AI may pose to the grid. DOE has started the process of convening energy stakeholders and technical experts over the coming months to collaboratively assess potential risks to the grid, as well as ways in which AI could potentially strengthen grid resilience and our ability to respond to threats—building off a new public assessment.

  • Authored a report on AI’s role in advancing scientific research to help tackle major societal challenges, written by the President’s Council of Advisors on Science and Technology

Bringing AI Talent into Government

The AI and Tech Talent Task Force has made substantial progress on hiring through the AI Talent Surge. Since President Biden signed the E.O., federal agencies have hired over 150 AI and AI-enabling professionals and, along with the tech talent programs, are on track to hire hundreds by Summer 2024. Individuals hired thus far are already working on critical AI missions, such as informing efforts to use AI for permitting, advising on AI investments across the federal government, and writing policy for the use of AI in government.

This was originally published, on April 29, 2024, on whitehouse.gov.

NIST released draft documents on managing generative AI risks, acknowledging the need for ongoing research and development of AI safety standards.

Agencies established a framework for AI safety and security guidelines for critical infrastructure, recognizing the importance of protecting essential systems and services.

The AI Safety and Security Board was launched to advise on AI development, providing a platform for experts to share knowledge and best practices.

Biden issued an executive order for AI safety standards, requiring companies to share AI system safety test details and prioritize safety and security in AI development.

Title:

Content: Biden issues an executive order setting safety, security and transparency standards for artificial intelligence systems - Sunrise Portal
Tuesday 31 October 2023 8: 44 AM Cairo Cairo 24 °
Most Read
You might like it, too.
Share your opinion
Do you support calls to boycott some restaurants that have been proven to support the occupation soldiers?
Biden issues executive order setting safety, security and transparency standards for artificial intelligence systems
US President Joe Biden
Published on: Tuesday 31 October 2023 - 8: 08 AM | Last updated on Tuesday 31 October 2023 - 8: 08 AM
US President Joe Biden on Monday issued an executive order setting out safety, security and transparency standards for artificial intelligence systems, requiring companies developing them to share details of systems safety tests with the US government.
Companies that train in artificial intelligence through so-called foundational models, which may pose risks to national security and public health depending on how they are deployed, must disclose safety results to U.S. agencies.
Foundational models refer to AI systems that absorb large amounts of data and can then be deployed in a variety of applications.
Many AI systems that use natural language processing, and those that propose the creation of new chemical compounds, use foundational models.
The National Institute of Standards and Technology will set a standard for the types of safety tests that companies must perform before releasing AI systems.
The Department of Homeland Security will then apply these standards to systems used in critical infrastructure sectors and establish a safety and security board on artificial intelligence.
The Biden order uses the authority the president has under the Defense Production Act, which presidents routinely use to oversee U.S. companies for the purpose of national security.
Former President Donald Trump used the law during the COVID-19 pandemic to control exports of medical goods and boost production of vital supplies.
You might like it, too.
Share your comment

The National Institute of Standards sets safety test standards for AI systems, ensuring a consistent and rigorous approach to AI evaluation and certification.

The Department of Homeland Security enforces AI standards, providing a critical layer of oversight and accountability in the development and deployment of AI systems.