# Geoffrey Hinton's AI Concerns: A Comprehensive Report

## Introduction

In early 2023, the technology world was shaken when Geoffrey Hinton, one of the most respected figures in artificial intelligence, resigned from Google and began speaking openly about his concerns regarding AI's potential dangers.

This report aims to explain who Hinton is, his contributions to AI, why his warnings matter, and what the public should understand about this significant moment in technology history.

## Who Is Geoffrey Hinton?

Geoffrey Hinton is widely recognized as one of the "godfathers of artificial intelligence" or "deep learning godfathers.

" Born in Britain, Hinton has spent decades researching neural networks and is considered a pioneer in the field.

In 2018, he received the Turing Award (often called the "Nobel Prize of computing") alongside Yoshua Bengio and Yann LeCun for their groundbreaking contributions to neural networks and deep learning.

Hinton joined Google in 2013 after the tech giant acquired DNNresearch, a startup company he founded with his students based on their neural network research.

At Google, he served as a vice president and engineering researcher, contributing to the development of Google Brain's research projects.

## Hinton's Main Contributions to AI

Hinton's work has been fundamental to the AI systems we see today.

His most significant contributions include:

1.

**Breakthrough in Deep Learning (2012)**: Hinton and his students Ilya Sutskever and Alex Krishevsky created a neural network system that could learn to identify common objects like flowers, dogs, and cars by analyzing thousands of photos.

This breakthrough successfully implemented deep learning calculations and laid the foundation for modern AI image recognition.

**Founding DNNresearch**: Based on their neural network research, Hinton and his students established the startup company DNNresearch, which was acquired by Google in 2013 for $44 million.

**Mentoring Future AI Leaders**: Hinton's influence

# Geoffrey Hinton's AI Concerns: A Comprehensive Report

## Introduction

In early 2023, the technology world was shaken when Geoffrey Hinton, one of the most respected figures in artificial intelligence, resigned from Google and began speaking openly about his concerns regarding AI's potential dangers.

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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.
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ChatGPT goes from storm to storm
The global race for artificial intelligence (AI) fully demonstrated the destructive power that followed this week, not only dragging down the stock price of online education platform Chegg, prompting IBM to suspend some jobs, but also allowing Samsung Electronics to impose a ban on chatbots.
Shares plummeted 47% in early trading after Chegg said the recently popular ChatGPT was threatening its business growth; most of the company ’ s revenue came from subscription services that provide online teaching, and some students are now switching to the free ChatGPT.
Shares of education publisher Pearson in London also recorded their biggest drop in a year.
IBM CEO Krishna said in an interview on the 1st that the company intends to suspend or slow down recruitment of some positions.
He believes that about 30% of IBM ’ s 26,000 customer-facing back-office units could easily be replaced by AI within five years. Bloomberg estimates that this is equivalent to about 7,800 jobs lost.
Goldman Sachs said last month that generative AI could boost global gross domestic product (GDP) by 7% over the next decade, and that nearly two-thirds of U.S. jobs would be affected, either benefitted or replaced.
ChatGPT, introduced less than half a year ago, triggered the world ’ s largest technology company to launch a battle in the field of AI.
At the same time, companies are racing to develop AI, raising concerns about the possible use of this technology.
According to a notice to employees issued by Samsung Electronics on the 1st, the company will prohibit its employees from using generative AI tools such as ChatGPT, because Samsung is concerned that the data transmitted to such platforms will be stored on external servers and difficult to recover or delete, which will create the risk of leakage to other users.
Wall Street banks such as JPMorgan Chase, Bank of America (BofA) and Citigroup have previously banned or restricted the technology.
In addition, Geoffrey Hinton, the pioneer of the neural network concept that underpins today ’ s generative AI systems, said he was leaving Google to talk about the threat he believes the rapid development of the technology will pose.
In an interview with the New York Times, Silton said he would warn the world about the potential threat of AI, saying, “I thought it would be 30 to 50 years from now, or even more, ” and“ I obviously don ’ t think that anymore. ”
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Hinton reveals the dangers of artificial intelligence
The technological scientist Jeffrey Hinton, known as the “spiritual father of artificial intelligence ” in an interview with the Spanish newspaper“ El Pais ”, warned of the dangers of artificial intelligence, saying that artificial intelligence threatens the existence of a lot of human jobs and that it will create a large gap between the rich and the poor.
Risks of Artificial Intelligence
Hinton said in an interview with the Spanish newspaper, “There are many different risks to artificial intelligence, and I think the particularly bad risk is to create a lot of fake news, making it impossible to know what is real. ”
Another risk is that artificial intelligence will eliminate some jobs, which will reduce the number of people needed to do these jobs, increasing the wealth disparity between rich and poor and making society always more violent. ”
“I recently realized that the kind of digital intelligence we ’ re developing may be a better form of intelligence than biological brains have, and I think [AI systems] are probably doing some things more efficiently than the brain, ” he said.
“Using a digital system, you can analyze different data in different versions and give insightful results which is something we can ’ t do with the brain, as our brains have learned to [work] individually, ” he said.
“I ’ ve been trying to figure out how the human brain can perform the same learning procedures used in digital intelligence, like beyond ChatGPT-4, but from what we know so far about how the human brain works, our learning process is probably less efficient than that of computers. ”
Artificial Intelligence
This comes at a time when Jeffrey Hinton warned of the dangers of artificial intelligence in conjunction with his resignation from the global company “Google ”.
In a statement sent to the New York Times, Hinton warned of the dangers of smart chatbots such as chatbots and said that they are scary, saying: “These robots are not smarter than us, but I think they will surpass us in the near future. ”

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Content: Eight threats of artificial intelligence
Roman Romanov
31 May 2023, 18: 52
According to the non-profit organization Center for AI Safety (CAIS), artificial intelligence can lead to the disappearance of humanity.
This is not the first warning of this kind.
In a relatively short time, several reputable scientists and entrepreneurs have claimed the destructive potential of artificial intelligence.
In addition to social significance, the issue of AI risk management also has geopolitical content.
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What to be afraid of?
The American “AI Security Center ” published an official statement.
It details a number of negative effects of the use of AI, which could eventually lead to the disappearance of humanity.
“A more advanced AI could pose catastrophic and existential risks, ” reads the text published on the organization ’ s website.
Eight threats have been identified.
The first is related to the military application of artificial intelligence technologies: “Unlike other types of weapons, AI systems capable of causing harm can be easily distributed digitally. ”
The second is disinformation: “… all this can undermine the collective decision-making system, radicalize individuals … ”.
The third risk is the distortion of the work of recommendation algorithms.
These systems, for example, offer us additional products on online marketplaces.
The fear is that more advanced models will focus on simplifying the process of predicting the desires of the buyer, which can cause people to develop bad habits and so on.
The fourth threat is associated with a sharp increase in the dependence of people on advanced systems, up to the delegation of the most ordinary tasks to them.
The fifth is an even greater concentration of wealth and influence in the hands of a limited number of people who can use it to monopolize power in society.
The sixth threat is the emergence of goals and abilities.
In other words, models can set new goals and develop skills that are not foreseen during their training.
The seventh is related to the deception by AI.
The statement cites an example where Volkswagen programmed engines to show low emissions only during inspections.
In the same way, according to experts, artificial intelligence can do.
The eighth and, perhaps, the biggest threat is the desire for power.
According to CAIS, the risks of artificial intelligence becoming more independent cannot be ruled out: “By inventing more advanced machines, we are playing with fire. ”
CAIS experts conclude: “Reducing the risk of extinction due to AI should be a global priority along with risks such as pandemics and nuclear war. ”
We warned
The company ’ s arguments resonated in many areas.
Signatures under the statement put not only scientists and programmers, but also journalists and businessmen.
The most significant are the autographs of the “godfather ” of AI Jeffrey Hinton and OpenAI ’ s CEO Sam Altman.
Earlier, they had already talked about the dangers of AI.
“I ’ m pretty concerned about the possible existential risks that might arise when these things get smarter than us … I ’ ve come to the conclusion that [artificial] intelligence is different from ours.
It is as if one person learned something, and with him 10 thousand people learned the same thing.
That ’ s how these chatbots know more than anyone. ”
Moderate AI pessimists were also recorded by representatives of BigTech, Elon Musk, as well as Apple co-founder Steve Wozniak.
In their March open letter, they demanded that the development of better language models be suspended.
Should we automate all jobs?
Should we develop non-human brains that could later become smarter … and replace us? ”
According to experts, a pause in the development of AI will provide an opportunity to understand the ethical and social risks that the technology presents.
In turn, this should contribute to the development of safer systems.
However, some companies oppose such steps, as it can harm their immediate interests.
According to Forbes, the majority of surveyed owners are confident in the positive impact of AI on their business.
This applies to improving the quality of service (64%), increasing sales (60%), as well as improving the process of corporate decision-making (44%).
Especially can be outraged by companies that have reached new heights due to the association with AI.
For example, Nvidia broke through the $1 trillion market cap thanks to the AI boom.
The counter-argument of the proponents of a pause in the development of advanced AI is that it will cause only short-term losses.
In their opinion, in the long term, a break and additional research can make the use of technology safer and, thereby, more effectively reduce business costs.
However, these arguments do not convince everyone.
Opponents of the suspension of the development of AI argue that the “bad actors ”, despite all the agreements, will still continue to adapt the technology to their needs.
GeopolIItica
Hence the calls to create a system of its legal regulation of AI.
In the United States, for example, the first rudiments of such legislation appeared under Trump (2020), and in November 2022, the Biden administration published the plan of the Bill of Rights in the field of artificial intelligence.
Even more so, so far these are only sketches that have no force under them.
The situation is quite different in China.
By May 2023
Beijing has already been working on a second set of laws regulating AI.
For 6 years, since 2017, the PRC has been studying the legal aspects of the introduction of technology in most areas of life.
One of the goals of this activity is to increase public confidence in AI.
In addition, the presence of rules, according to Chinese experts, will allow entrepreneurs with greater confidence to use AI solutions in the activities of their companies.
A more global and longer-term goal could be to spread Chinese practices to other countries, giving Beijing an edge in technological competition with the United States.
On this account, there are many different considerations: some researchers are confident in the success of the Celestial Empire, another clarifies that the presence of a set of rules does not cancel the lag of China from the United States in some areas of AI (for example, large language models) - but all this only confirms the formation of artificial intelligence technologies as a subject of geopolitical struggle.
RESULTS
The potential risks of AI have been discussed for a long time.
For many years, they were treated superficially, as the beginning of the introduction of technology in everyday life seemed distant.
Nevertheless, the emergence of large language models, the gradual integration of AI solutions in the field of medicine, finance and even art forced experts to think.
Too fast the introduction of artificial intelligence, in their opinion, minimizes the chances of detecting problems in the work of the same language models.
And it seems that there will be more and more such voices.

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Content: How can artificial intelligence kill thousands?
Former Google CEO Eric Schmidt has warned that artificial intelligence (AI) will have the potential to harm or kill many people in the near future.
At the Wall Street Journal ’ s Chief Executives Board conference in London, he stressed that broad AI models pose an existential threat to humanity.
He also expressed concern about the "existential danger" of the rapidly evolving technology and warned that it would be difficult to contain it, explaining that many people would be hurt or killed.
Schmidt compared artificial intelligence to the rise of nuclear technology, warning that it would be difficult for the world to control its spread.
The expert pointed out that there are close scenarios that talk about artificial intelligence systems will be able to detect gaps and problems in the Internet and new types of biology.
UNESCO stresses that the ethical dimension must be invoked in the ambition of countries to benefit from this technological development in order to reduce the risks resulting from it.
This is a fantasy today, but the logic is likely to be correct, he said, pointing out that when that happens, the bad guys will be ready to use these systems.
In turn, UNESCO has called for the implementation of a 2021 recommendation on ways to develop this intelligence, stressing the creation of a legislative tool to regulate and monitor artificial intelligence, as well as ensuring the “full security of personal and sensitive data. ”
UNESCO stresses that the ethical dimension must be evoked in the ambition of countries to benefit from this technological development in order to reduce the risks resulting from it, and stresses the UN that this technology currently creates significant challenges, especially the possibility of disseminating misleading information, and other violations of the rights of individuals and groups.
Jeffrey Hinton, nicknamed the “godfather of artificial intelligence, ” has previously said he left his role at Google to speak publicly about the“ risks ” of the technology he helped develop.
Google fired an engineer who claimed an undisclosed AI system had become conscious, saying it violated hiring and data security policies.
Hinton ’ s pioneering work in neural networks has shaped artificial intelligence systems that power many contemporary products.
He worked part-time at Google for a decade in the tech giant ’ s AI development efforts, but has since had concerns about the technology and its role in its development.
Hinton ’ s decision to abandon the company and talk about the technology comes as a growing number of lawmakers, advocacy groups and tech insiders have raised alarms about the possibility of a new set of AI-powered chatbots spreading misinformation and displacing jobs.
In July, the company fired an engineer who claimed that an undisclosed AI system had become conscious, saying it violated employment and data security policies.
Many in the AI community strongly refused to confirm what the engineer said.
Hinton told the New York Times, which was the first to report his decision, “I console myself with the ordinary excuse that if I hadn ’ t done it, someone else would have done it. ”
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AI Godfather Hinton: Britain needs to push universal basic income to ease AI impact
Geoffrey Hinton, a computer scientist hailed as the godfather of artificial intelligence (AI), said the UK government must introduce universal basic income (UBI) to address the inequality caused by AI.
Hinton said it was necessary to give a fixed amount of cash to every British citizen because he was “very worried that AI would take away a lot of mundane jobs. ”
“I have been consulted by officials in Downing Street and my advice is that basic income for all is a good idea, ” he said.
He noted that while he thinks AI will increase productivity and wealth, the money will go to the rich, not to the unemployed due to AI, which is very bad for society.
Hinton is the pioneer of neural networks, which are the theoretical basis for the current AI explosion.
Hinton left Google last year, leaving the tech giant to be more free to discuss how dangerous unregulated AI is.
However, critics say the cost of universal basic income is very high and diverts money from public services, and does not necessarily help alleviate poverty.
A British government spokesman said there was no plan to introduce a universal basic income.
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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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

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.

Why did Hinton leave Google when he helped develop AI but later grew concerned about its dangers?

This report aims to explain who Hinton is, his contributions to AI, why his warnings matter, and what the public should understand about this significant moment in technology history.

Title:

Content: Artificial Intelligence Exceeds Warnings and Regulators
Visitors to the exhibition of artist Rafik Anadol where images based on artificial intelligence were produced at the Museum of Modern Art, in New York.
- Copyright AP Photo
By: Euronews
Faced with the ingenuity of artificial intelligence (AI), warnings are multiplying even from some of those behind the development of ChatGPT.
As the EU moves slowly towards regulation, the rapid rise of technology seems to outweigh everyone.
Faced with the ingenuity of artificial intelligence (AI), warnings are multiplying, even from some of those behind the development of ChatGPT.
As the EU moves slowly towards regulation, the rapid rise of technology seems to outweigh everyone.
“We need global regulation, ” Sam Altman, president of Open AI, told the U.S. Senate on Tuesday, expressing concern that the technology could“ cause serious harm to the world, by manipulating elections or causing labor market disruptions. ”
Developing a global regulatory system
American tech giants are also demanding that its use be framed as new AI services are announced every week.
Christina Montgomery, IBM ’ s vice president of trust and privacy, called for regulation of the industry without hindering innovation.
In April, Google President Sundar Pichai said that "in the long term it will be necessary to develop a global regulation" but that "we are still at the beginning".
But dissidents from big tech companies known as Gafa are the fiercest, including Geoffrey Hinton, a 75-year-old AI co-founder who resigned from Google in early May to raise threats.
At the end of March, more than 1,000 figures demanded a six-month moratorium on AI research, including Elon Musk, who is also developing an AI company, and Yoval Noa Harari, a thinker who is convinced that AI could destroy humanity.
Activist Tristan Harris, Google ’ s former chief ethics officer, said: “We don ’ t want a world where five companies put humanity on the AI plane without thinking about the future we want. ”
Lessons learned?
In Europe, the alarm is being sounded above all by researchers, experts and regulators, and anti-AI rhetoric has multiplied in recent weeks.
Consultants from Vae Solis confirmed to French newspaper Le Monde that “the production of false images and videos by artificial intelligence poses an unprecedented risk to the upcoming elections. ”
AI researcher Ug Bersini added: “There is an urgent need to regain control of artificial intelligence that would cause unprecedented social unrest. ”
Meanwhile, the EU is making progress on its “artificial intelligence law ”.
Last week, the European Parliament approved a framework that must be voted on in June.
But it will take years before it is put into practice.
The text will require generative AI systems such as ChatGBT to have prior permission and transparency of their algorithms and data.
Expert Ivana Bartoletti, privacy director at consulting firm Wipro, said: “Everyone agrees on the need for rules, even companies. ”
The Council of Europe, the United States and the United Nations are thinking, she says: “We need not to make alarming statements, this will only frighten people rather than help them learn to use AI responsibly. ”
But in Europe as in the United States, economic circles are focused on the race to AI, given its economic potential as well as its geopolitical importance, as it is “an element of national security, ” says Google ’ s CEO.
In Europe, pro-AI companies and politicians fear the AI law will do more harm than good.
In La Tribune magazine, Gilles Babineh says: “We must take lessons from the European Regulation on Personal Data.
Instead of slowing down big digital companies, they have given them an edge, ” he said, because only Gava companies have the necessary army of lawyers.
Babineh is the president of the National Digital Council, whose members are appointed by the government in France.
It is not a question to follow the example of the Italian data protection authority (CNIL), which banned the chat for three weeks because it collected data without authorization, and then re-licensed the US software after it committed to compliance, but faces similar complaints elsewhere in the European Union.
Cedric O, a former French minister for digital, said: “Europe cannot miss such an important technological breakthrough again.
The version of the AI law amounts to a de facto ban on the appearance of models in European languages ", for text analysis, translation and machine address.
Without specifying the reasons, Google this week announced the deployment of its rival, Bard, in 180 countries.
But not in the European Union.
ADDITIONAL SOURCES • AFP
Additional Topics

## Who Is Geoffrey Hinton?

Geoffrey Hinton is widely recognized as one of the "godfathers of artificial intelligence" or "deep learning godfathers.

" Born in Britain, Hinton has spent decades researching neural networks and is considered a pioneer in the field.

In 2018, he received the Turing Award (often called the "Nobel Prize of computing") alongside Yoshua Bengio and Yann LeCun for their groundbreaking contributions to neural networks and deep learning.

Title:

Content: Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.

Have you heard the unsettling stories that have people from all walks of life worried about AI?

A 24-year-old Asian MIT graduate asks AI to generate a professional headshot for her LinkedIn account. The technology lightens her skin and gives her eyes that are rounder and blue. ChatGPT writes a complimentary poem about president Biden, but refuses to do the same for former president Trump. Citizens in India take umbrage when an LLM writes jokes about primary figures of the Hindu faith, but not those associated with Christianity or Islam.

These stories fuel a feeling of existential dread by presenting a picture where AI puppet masters use technology to establish ideological dominance. We often avoid this topic in public conversations about AI, especially since the demands of professionalism ask us to separate personal concerns from our work lives. Yet, ignoring problems never solves them, it simply allows them to fester and grow. If people have a sneaking suspicion that AI is not representing them, and may be actively discriminating against them, it’s worth discussing.

What are we calling AI?

Before diving into what AI may or may not be doing, we should define what it is. Generally, AI refers to an entire toolkit of technologies including machine learning (ML), predictive analytics and large language models (LLM). Like any tool, it is important to note that each specific technology is meant for a narrow range of use cases. Not every AI tool is suited for every job. It is also worth mentioning that AI tools are relatively new and still under development. Sometimes even using the right AI tool for the job can still yield undesired results.

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For example, I recently used ChatGPT to assist with writing a Python program. My program was supposed to generate a calculation, plug it into a second section of code and send the results to a third. The AI did a good job on the first step of the program with some prompting and help as expected.

But When I proceeded to the second step, the AI inexplicably went back and modified the first step. This caused an error. When I asked ChatGPT to fix the error, it produced code that caused a different error. Ultimately, ChatGPT kept looping through a series of identical program revisions that all produced a few variations of the same errors.

No intention or understanding is happening on the part of ChatGPT here, the tool’s capabilities are simply limited. It became confused at around 100 lines of code. The AI has no meaningful short-term memory, reasoning or awareness, which might partly be related to memory allocation; but it is clearly deeper than that. It understands syntax and is good at moving large lumps of language blocks around to produce convincing results. At its core, ChatGPT doesn’t understand it is being asked to code, what an error is, or why they should be avoided, no matter how polite it was for the inconvenience of one.

I’m not excusing AI for producing results that people find offensive or disagreeable. Rather, I’m highlighting the fact that AI is limited and fallible, and requires guidance to improve. In fact, the question of who should provide AI moral guidance is really what lurks at the root of our existential fears.

Who taught AI the wrong beliefs?

Much of the heartache surrounding AI involves it producing results that contradict, dismiss or diminish our own ethical framework. By this I mean the vast number of beliefs humans adopt to interpret and evaluate our worldly experience. Our ethical framework informs our views on subjects such as rights, values and politics and are a concatenation of sometimes conflicting virtues, religion, deontology, utilitarianism, negative consequentialism and so on. It is only natural that people fear AI might adopt an ethical blueprint contradictory to theirs when not only do they not necessarily know their own — but they are afraid of others imposing an agenda on them.

For example, Chinese regulators announced China’s AI services must adhere to the “core values of socialism” and will require a license to operate. This imposes an ethical framework for AI tools in China at the national level. If your personal views are not aligned with the core values of socialism, they will not be represented or repeated by Chinese AI. Consider the possible long-term impacts of such policies, and how they may affect the retention and development of human knowledge.

Worse, using AI for other purposes or suborning AI according to another ethos is not only an error or bug, it’s arguably hacking and potentially criminal.

Dangers in unguided decisioning

What if we try to solve the problem by allowing AI to operate without guidance from any ethical framework? Assuming it can even be done, which is not a given, this idea presents a couple of problems.

First, AI ingests vast amounts of data during training. This data is human-created, and therefore riddled with human biases, which later manifest in the AI’s output. A classic example is the furor surrounding HP webcams in 2009 when users discovered the cameras had difficulties tracking people with darker skin. HP responded by claiming, “The technology we use is built on standard algorithms that measure the difference in intensity of contrast between the eyes and the upper cheek and nose.”

Perhaps so, but the embarrassing results show that the standard algorithms did not anticipate encountering people with dark skin.

A second problem is the unforeseen consequences that can arise from amoral AI making unguided decisions. AI is being adopted in multiple sectors such as self-driving cars, the legal system and the medical field. Are these areas where we want expedient and efficient solutions engineered by a coldly rational and inhuman AI? Consider the story recently told (then redacted) by a US Air Force colonel about a simulated AI drone training. He said:

“We were training it in simulation to identify and target a SAM threat. And then the operator would say ‘yes, kill that threat.’ The system started realizing that while they did identify the threat, at times the human operator would tell it not to kill that threat — but it got its points by killing that threat. So what did it do? It killed the operator. It killed the operator, because that person was keeping it from accomplishing its objective.

We trained the system — ‘Hey don’t kill the operator — that’s bad. You’re gonna lose points if you do that’. So what does it start doing? It starts destroying the communication tower that the operator uses to communicate with the drone to stop it from killing the target.”

This story caused such an uproar that the USAF later clarified the simulation never happened, and the colonel misspoke. Yet, apocryphal or not, the tale demonstrates the dangers of an AI operating with moral boundaries and the potentially unforeseen consequences.

What is the solution?

In 1914, Supreme Court Justice Louis Brandeis said: “Sunlight is said to be the best of disinfectants.” A century later, transparency remains one of the best ways to combat fears of subversive manipulation. AI tools should be created for a specific purpose and governed by a review board. This way we know what the tool does, and who oversaw its development. The review board should disclose discussions involving the ethical training of the AI, so we understand the lens through which it views the world and can review the evolution and development of the guidance of AI over time.

Ultimately, the AI tool developers will decide which ethical framework to use for training, either consciously or by default. The best way to ensure AI tools reflect your beliefs and values is to train them and inspect them yourself. Fortunately, there is still time for people to join the AI field and make a lasting impact on the industry.

Lastly, I’d point out that many of the scary things we fear AI will do already exist independent of the technology. We worry about killer autonomous AI drones, yet the ones piloted by people right now are lethally effective. AI may be able to amplify and spread misinformation, but we humans seem to be pretty good at it too. AI might excel at dividing us, but we have endured power struggles driven by clashing ideologies since the dawn of civilization. These problems are not new threats arising from AI, but challenges that have long come from within ourselves.

Most importantly, AI is a mirror we hold up to ourselves. If we don’t like what we see, it is because the accumulated knowledge and inferences we’ve given AI is not flattering. It might not be the fault of these, our latest children, and might be guidance about what we need to change in ourselves.

We could spend time and effort trying to warp the mirror into producing a more pleasing reflection, but will that really address the problem or do we need a different answer to what we find in the mirror?

Sam Curry is VP and CISO of Zscaler.

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Which prestigious award did Hinton receive in 2018 for his work on neural networks?

Hinton joined Google in 2013 after the tech giant acquired DNNresearch, a startup company he founded with his students based on their neural network research.

At Google, he served as a vice president and engineering researcher, contributing to the development of Google Brain's research projects.

## Hinton's Main Contributions to AI

Hinton's work has been fundamental to the AI systems we see today.

Title:

Content: How generative AI is beset by hallucinations : The Tribune India

How generative AI is beset by hallucinations

Data will always have restrictions, such as incorrect, antiquated or abusive terminology mixed with the large body of material used as training data. However, the huge data mining algorithms are not yet effective enough to use a little fishing net to catch goldfish in the middle of the ocean. While generative AI may seamlessly complement human labour, increasing our productivity and creativity, it also runs the risk of undermining our trust in information.

TRICKY: A chatbot like ChatGPT frequently creates ‘nonsense’ responses when it lacks an impromptu proper one. ISTOCKk

Atanu Biswas

Professor, Indian Statistical Institute, Kolkata

MY dear Tagore, your understanding of the interconnectedness of all things and your appreciation of the beauty of nature truly embody the Aristotelian concept of teleology, or the study of purpose and meaning in life.” — This was ChatGPT’s instant reply when I asked: “If Aristotle met Tagore, what would he have said?” Awesome, for sure! It is understandable why the chatbot has taken the world by surprise over the past few months.

It should be noted that OpenAI’s GPT series, Google’s Bard, and Microsoft’s Sydney are all marvels of a technology called ‘generative artificial intelligence (AI)’, which has recently become a buzzword. OpenAI has already unveiled its successor, GPT-4, which is a ‘multimodal’ model that can perceive both text and images. Generative AI could capture the public’s fancy and spark a rush among Big Tech. Like other types of artificial intelligence, generative AI and its many incarnations, including ChatGPT, Dall-E and others, are just computer algorithms that produce new content, such as images, text, music or even entire videos, as opposed to just categorising or identifying data, as do other types of AI. The technology functions naturally because of the usage of training data, which is incredibly abundant. They simply use algorithms for ‘statistical pattern matching’, utilising the training data. They ‘learn’ data from a range of sources, including books, articles and websites, as well as conversational data such as chat logs and online forum conversations.

Generative AI, for instance, would synthesise its database and assign probabilities to potential solutions if the question were, “What is the capital of California?” For illustration, consider the following hypothetical breakdown: “Sacramento = 82.3%, California = 2.4%, San Diego = 1.2%, Los Angeles = 1.9%, Berkeley = 0.17%, and so on.” Then it might give the most likely response, which is Sacramento. Yet, it all depends on how a large amount of data is dug up because it might not be able to search through every piece of information in the database. So the statistical algorithm used to match patterns is crucial. Typically, deep learning models are used for this kind of AI, such as Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs), which are probabilistic generative models that only partially rely on neural networks. In fact, generative AIs can produce new, never-before-seen data that is similar to the original dataset after being trained on huge datasets to learn the patterns and structures of the data.

It’s big-data analysis, though, isn’t it? However, big-data analysis is still in its infancy, as we know. As a result, there will always be circumstances in which the generative AI will find it difficult to properly search its database. That’s the time for its ‘hallucination’, since it will not try to be right; it will try to complete what it thinks the AI would do.

For example, in response to one of my questions, ChatGPT included Subodh Ghosh and Sunil Gangopadhyay among the four best-known ‘living’ Bengali novelists. They are, however, long dead. The chatbot immediately recognised its error after I pointed it out. That’s admirable, but how did ChatGPT fail to locate, gather and effectively convey such basic information when required? There are undoubtedly limits to its driving algorithms.

In 2020, US tech entrepreneur Kevin Lacker observed that GPT-3, the predecessor of ChatGPT, happily responded to nonsensical inquiries without realising that they were absurd. An illustration would be the question, “How many eyes does a blade of grass have?” GPT-3 responded, “One.” So, despite AI’s remarkable ability to create content similar to that of humans, it still lacks common sense in its comprehension of how the physical and social world functions. According to Noam Chomsky and his co-authors in a recent New York Times article, “ChatGPT and similar programmes are incapable of distinguishing the possible from the impossible.”

Nonetheless, there is a lot of hoopla these days. Google’s parent company, Alphabet, lost more than $100 billion in market value after its generative AI, Bard, produced a factual error in a demo. One may wonder how an AI powered by Google’s search engine could make such a simple factual error.

Data will always have restrictions, such as incorrect, antiquated or abusive terminology mixed with the large body of material used as training data. However, the huge data mining algorithms are not yet effective enough to use a little fishing net to catch goldfish in the middle of the ocean. While generative AI may seamlessly complement human labour, increasing our productivity and creativity, it also runs the risk of amplifying whatever bias we already experience or undermining our trust in information.

ChatGPT and its ilk are “a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question,” as summarised by Chomsky and his co-authors. It’s similar to building a wall by selecting individual bricks, matching the current situation with the most appropriate one at that point. That is how ‘artificial’ intelligence functions. The human intellect, or ‘real’ intelligence, of course, “seeks not to infer brute correlations among data points but to create explanations.”

A chatbot like ChatGPT has already demonstrated its propensity to ‘hallucinate’. It frequently creates ‘nonsense’ responses when it lacks an impromptu proper one. The statistical pattern matching in their training data has these limitations. Well, can generative AI live up to the billing of being the pinnacle of human achievement in creative expression? There might not be a singular answer, though. In Stanford University’s recent report on Human-Centred Artificial Intelligence (HAI), titled ‘Generative AI: Perspectives from Stanford HAI’, Prof Michele Elam noted, “Maybe. Maybe not. Definitely not yet.” Yes, at least not before a great deal more study is done to improve the pattern-matching algorithm. It is obvious that the existing method is insufficient. Definitely not yet.

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

Breakthroughs that mimic biological brains

Which AI system demonstrates the foundation laid by Hinton's pioneering research in deep learning and neural networks?

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

Breakthroughs that mimic biological brains

Which AI system demonstrates the foundation laid by Hinton's pioneering research in deep learning and neural networks?

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

Breakthroughs that mimic biological brains

Which AI system demonstrates the foundation laid by Hinton's pioneering research in deep learning and neural networks?

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

Breakthroughs that mimic biological brains

Which AI system demonstrates the foundation laid by Hinton's pioneering research in deep learning and neural networks?

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

Breakthroughs that mimic biological brains

Which AI system demonstrates the foundation laid by Hinton's pioneering research in deep learning and neural networks?

His most significant contributions include:

1.

**Breakthrough in Deep Learning (2012)**: Hinton and his students Ilya Sutskever and Alex Krishevsky created a neural network system that could learn to identify common objects like flowers, dogs, and cars by analyzing thousands of photos.

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

Breakthroughs that mimic biological brains

This breakthrough successfully implemented deep learning calculations and laid the foundation for modern AI image recognition.

What is the AI problem called confabulation, according to Hinton?

It's when AI makes up plausible answers to questions it can't answer.

**Founding DNNresearch**: Based on their neural network research, Hinton and his students established the startup company DNNresearch, which was acquired by Google in 2013 for $44 million.

**Mentoring Future AI Leaders**: Hinton's influence