When Might AI Outsmart Us? It Depends Who You Ask – TIME
In 1960, Herbert Simon, who went on to win both the Nobel Prize for economics and the Turing Award for computer science, wrote in his book The New Science of Management Decision that machines will be capable, within 20 years, of doing any work that a man can do.
History is filled with exuberant technological predictions that have failed to materialize. Within the field of artificial intelligence, the brashest predictions have concerned the arrival of systems that can perform any task a human can, often referred to as artificial general intelligence, or AGI.
So when Shane Legg, Google DeepMinds co-founder and chief AGI scientist, estimates that theres a 50% chance that AGI will be developed by 2028, it might be tempting to write him off as another AI pioneer who hasnt learnt the lessons of history.
Still, AI is certainly progressing rapidly. GPT-3.5, the language model that powers OpenAIs ChatGPT was developed in 2022, and scored 213 out of 400 on the Uniform Bar Exam, the standardized test that prospective lawyers must pass, putting it in the bottom 10% of human test-takers. GPT-4, developed just months later, scored 298, putting it in the top 10%. Many experts expect this progress to continue.
Read More: 4 Charts That Show Why AI Progress Is Unlikely to Slow Down
Leggs views are common among the leadership of the companies currently building the most powerful AI systems. In August, Dario Amodei, co-founder and CEO of Anthropic, said he expects a human-level AI could be developed in two to three years. Sam Altman, CEO of OpenAI, believes AGI could be reached sometime in the next four or five years.
But in a recent survey the majority of 1,712 AI experts who responded to the question of when they thought AI would be able to accomplish every task better and more cheaply than human workers were less bullish. A separate survey of elite forecasters with exceptional track records shows they are less bullish still.
The stakes for divining who is correct are high. Legg, like many other AI pioneers, has warned that powerful future AI systems could cause human extinction. And even for those less concerned by Terminator scenarios, some warn that an AI system that could replace humans at any task might replace human labor entirely.
Many of those working at the companies building the biggest and most powerful AI models believe that the arrival of AGI is imminent. They subscribe to a theory known as the scaling hypothesis: the idea that even if a few incremental technical advances are required along the way, continuing to train AI models using ever greater amounts of computational power and data will inevitably lead to AGI.
There is some evidence to back this theory up. Researchers have observed very neat and predictable relationships between how much computational power, also known as compute, is used to train an AI model and how well it performs a given task. In the case of large language models (LLM)the AI systems that power chatbots like ChatGPTscaling laws predict how well a model can predict a missing word in a sentence. OpenAI CEO Sam Altman recently told TIME that he realized in 2019 that AGI might be coming much sooner than most people think, after OpenAI researchers discovered the scaling laws.
Read More: 2023 CEO of the Year: Sam Altman
Even before the scaling laws were observed, researchers have long understood that training an AI system using more compute makes it more capable. The amount of compute being used to train AI models has increased relatively predictably for the last 70 years as costs have fallen.
Early predictions based on the expected growth in compute were used by experts to anticipate when AI might match (and then possibly surpass) humans. In 1997, computer scientist Hans Moravec argued that cheaply available hardware will match the human brain in terms of computing power in the 2020s. An Nvidia A100 semiconductor chip, widely used for AI training, costs around $10,000 and can perform roughly 20 trillion FLOPS, and chips developed later this decade will have higher performance still. However, estimates for the amount of compute used by the human brain vary widely from around one trillion floating point operations per second (FLOPS) to more than one quintillion FLOPS, making it hard to evaluate Moravecs prediction. Additionally, training modern AI systems requires a great deal more compute than running them, a fact that Moravecs prediction did not account for.
More recently, researchers at nonprofit Epoch have made a more sophisticated compute-based model. Instead of estimating when AI models will be trained with amounts of compute similar to the human brain, the Epoch approach makes direct use of scaling laws and makes a simplifying assumption: If an AI model trained with a given amount of compute can faithfully reproduce a given portion of textbased on whether the scaling laws predict such a model can repeatedly predict the next word almost flawlesslythen it can do the work of producing that text. For example, an AI system that can perfectly reproduce a book can substitute for authors, and an AI system that can reproduce scientific papers without fault can substitute for scientists.
Some would argue that just because AI systems can produce human-like outputs, that doesnt necessarily mean they will think like a human. After all, Russell Crowe plays Nobel Prize-winning mathematician John Nash in the 2001 film, A Beautiful Mind, but nobody would claim that the better his acting performance, the more impressive his mathematical skills must be. Researchers at Epoch argue that this analogy rests on a flawed understanding of how language models work. As they scale up, LLMs acquire the ability to reason like humans, rather than just superficially emulating human behavior. However, some researchers argue it's unclear whether current AI models are in fact reasoning.
Epochs approach is one way to quantitatively model the scaling hypothesis, says Tamay Besiroglu, Epochs associate director, who notes that researchers at Epoch tend to think AI will progress less rapidly than the model suggests. The model estimates a 10% chance of transformative AIdefined as AI that if deployed widely, would precipitate a change comparable to the industrial revolutionbeing developed by 2025, and a 50% chance of it being developed by 2033. The difference between the models forecast and those of people like Legg is probably largely down to transformative AI being harder to achieve than AGI, says Besiroglu.
Although many in leadership positions at the most prominent AI companies believe that the current path of AI progress will soon produce AGI, theyre outliers. In an effort to more systematically assess what the experts believe about the future of artificial intelligence, AI Impacts, an AI safety project at the nonprofit Machine Intelligence Research Institute, surveyed 2,778 experts in fall 2023, all of whom had published peer-reviewed research in prestigious AI journals and conferences in the last year.
Among other things, the experts were asked when they thought high-level machine intelligence, defined as machines that could accomplish every task better and more cheaply than human workers without help, would be feasible. Although the individual predictions varied greatly, the average of the predictions suggests a 50% chance that this would happen by 2047, and a 10% chance by 2027.
Like many people, the experts seemed to have been surprised by the rapid AI progress of the last year and have updated their forecasts accordinglywhen AI Impacts ran the same survey in 2022, researchers estimated a 50% chance of high-level machine intelligence arriving by 2060, and a 10% chance by 2029.
The researchers were also asked when they thought various individual tasks could be carried out by machines. They estimated a 50% chance that AI could compose a Top 40 hit by 2028 and write a book that would make the New York Times bestseller list by 2029.
Nonetheless, there is plenty of evidence to suggest that experts dont make good forecasters. Between 1984 and 2003, social scientist Philip Tetlock collected 82,361 forecasts from 284 experts, asking them questions such as: Will Soviet leader Mikhail Gorbachev be ousted in a coup? Will Canada survive as a political union? Tetlock found that the experts predictions were often no better than chance, and that the more famous an expert was, the less accurate their predictions tended to be.
Next, Tetlock and his collaborators set out to determine whether anyone could make accurate predictions. In a forecasting competition launched by the U.S. Intelligence Advanced Research Projects Activity in 2010, Tetlocks team, the Good Judgement Project (GJP), dominated the others, producing forecasts that were reportedly 30% more accurate than intelligence analysts who had access to classified information. As part of the competition, the GJP identified superforecastersindividuals who consistently made above-average accuracy forecasts. However, although superforecasters have been shown to be reasonably accurate for predictions with a time horizon of two years or less, it's unclear whether theyre also similarly accurate for longer-term questions such as when AGI might be developed, says Ezra Karger, an economist at the Federal Reserve Bank of Chicago and research director at Tetlocks Forecasting Research Institute.
When do the superforecasters think AGI will arrive? As part of a forecasting tournament run between June and October 2022 by the Forecasting Research Institute, 31 superforecasters were asked when they thought Nick Bostromthe controversial philosopher and author of the seminal AI existential risk treatise Superintelligencewould affirm the existence of AGI. The median superforecaster thought there was a 1% chance that this would happen by 2030, a 21% chance by 2050, and a 75% chance by 2100.
All three approaches to predicting when AGI might be developedEpochs model of the scaling hypothesis, and the expert and superforecaster surveyshave one thing in common: theres a lot of uncertainty. In particular, the experts are spread widely, with 10% thinking it's as likely as not that AGI is developed by 2030, and 18% thinking AGI wont be reached until after 2100.
Still, on average, the different approaches give different answers. Epochs model estimates a 50% chance that transformative AI arrives by 2033, the median expert estimates a 50% probability of AGI before 2048, and the superforecasters are much further out at 2070.
There are many points of disagreement that feed into debates over when AGI might be developed, says Katja Grace, who organized the expert survey as lead researcher at AI Impacts. First, will the current methods for building AI systems, bolstered by more compute and fed more data, with a few algorithmic tweaks, be sufficient? The answer to this question in part depends on how impressive you think recently developed AI systems are. Is GPT-4, in the words of researchers at Microsoft, the sparks of AGI? Or is this, in the words of philosopher Hubert Dreyfus, like claiming that the first monkey that climbed a tree was making progress towards landing on the moon?
Second, even if current methods are enough to achieve the goal of developing AGI, it's unclear how far away the finish line is, says Grace. Its also possible that something could obstruct progress on the way, for example a shortfall of training data.
Finally, looming in the background of these more technical debates are peoples more fundamental beliefs about how much and how quickly the world is likely to change, Grace says. Those working in AI are often steeped in technology and open to the idea that their creations could alter the world dramatically, whereas most people dismiss this as unrealistic.
The stakes of resolving this disagreement are high. In addition to asking experts how quickly they thought AI would reach certain milestones, AI Impacts asked them about the technologys societal implications. Of the 1,345 respondents who answered questions about AIs impact on society, 89% said they are substantially or extremely concerned about AI-generated deepfakes and 73% were similarly concerned that AI could empower dangerous groups, for example by enabling them to engineer viruses. The median respondent thought it was 5% likely that AGI leads to extremely bad, outcomes, such as human extinction.
Given these concerns, and the fact that 10% of the experts surveyed believe that AI might be able to do any task a human can by 2030, Grace argues that policymakers and companies should prepare now.
Preparations could include investment in safety research, mandatory safety testing, and coordination between companies and countries developing powerful AI systems, says Grace. Many of these measures were also recommended in a paper published by AI experts last year.
If governments act now, with determination, there is a chance that we will learn how to make AI systems safe before we learn how to make them so powerful that they become uncontrollable, Stuart Russell, professor of computer science at the University of California, Berkeley, and one of the papers authors, told TIME in October.
Link:
When Might AI Outsmart Us? It Depends Who You Ask - TIME
- Here Are My Top Artificial Intelligence (AI) Stocks to Buy Right Now - The Motley Fool - April 26th, 2024 [April 26th, 2024]
- Types of Artificial Intelligence That You Should Know in 2024 - Simplilearn - March 11th, 2024 [March 11th, 2024]
- This Red-Hot Artificial Intelligence (AI) Company Just Joined Nvidia and AMD in the S&P 500: Is It Time to Buy? - Yahoo Finance - March 11th, 2024 [March 11th, 2024]
- Nasdaq All-Time High: 3 Artificial Intelligence (AI) Stocks That Led the Index to Its Highest Level Ever (and Can Help ... - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- This Artificial Intelligence (AI) Stock Has Jumped 158% in a Year, and It Could Soar Another 60% - MSN - March 11th, 2024 [March 11th, 2024]
- Justice Department beefs up focus on artificial intelligence enforcement, warns of harsher sentences - ABC News - March 11th, 2024 [March 11th, 2024]
- Ready to Invest in Artificial Intelligence (AI)? 2 Nvidia Alternatives - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- The Scariest Part About Artificial Intelligence - The New Republic - March 11th, 2024 [March 11th, 2024]
- Artificial intelligence vs machine learning: what's the difference? - ReadWrite - March 11th, 2024 [March 11th, 2024]
- AI singularity may come in 2027 with artificial 'super intelligence' sooner than we think, says top scientist - Livescience.com - March 11th, 2024 [March 11th, 2024]
- 2 Artificial Intelligence (AI) Stocks You May Regret Not Buying Right Now Before They Soar 31% to 88% - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- This Artificial Intelligence (AI) Stock Could Double, and It Is Way Cheaper Than Nvidia - Yahoo Finance - March 11th, 2024 [March 11th, 2024]
- Billionaire David Tepper Slashed His Position in Nvidia. Here Are the Artificial Intelligence (AI) Stocks He Bought Instead. - Yahoo Finance - March 11th, 2024 [March 11th, 2024]
- Artificial Intelligence, Real Consequences: The use of Artificial Intelligence platforms in higher-education - The Justice - March 11th, 2024 [March 11th, 2024]
- Meet T-Stitch: A Simple Yet Efficient Artificial Intelligence Technique to Improve the Sampling Efficiency with Little or No Generation Degradation -... - March 11th, 2024 [March 11th, 2024]
- A.I. Is Learning What It Means to Be Alive - The New York Times - March 11th, 2024 [March 11th, 2024]
- The Adams administration quietly hired its first AI czar. Who is he? - City & State New York - March 11th, 2024 [March 11th, 2024]
- Think Palantir Technologies Stock Is Expensive? Here's a Cheaper Artificial Intelligence (AI) Stock to Buy Before It ... - Yahoo Finance - March 11th, 2024 [March 11th, 2024]
- 1 Artificial Intelligence (AI) Stock That Has Created Millionaires and Will Continue to Make More - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- Report: Artificial Intelligence A Threat to Climate Change, Energy Usage and Disinformation - Friends of the Earth - March 11th, 2024 [March 11th, 2024]
- Artificial-intelligence tool shows high accuracy for diagnosing ear infections - University of Minnesota Twin Cities - March 11th, 2024 [March 11th, 2024]
- Artificial Intelligence Takes the Spotlight at TiEcon Delhi 2024 - CXOToday.com - March 11th, 2024 [March 11th, 2024]
- This Week in AI: Ethics, Chips and Small Business Investments - PYMNTS.com - March 11th, 2024 [March 11th, 2024]
- Artificial Intelligence (AI) Stock Nvidia May Be the Bubble of the Century, and History Suggests It Won't End Well - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- The Terrifying A.I. Scam That Uses Your Loved One's Voice - The New Yorker - March 11th, 2024 [March 11th, 2024]
- Driving Innovation: Exploring the Automotive Artificial Intelligence Market In The Latest Research - WhaTech - March 11th, 2024 [March 11th, 2024]
- Chinas lawmakers walk fine line between AI development and tighter regulation - South China Morning Post - March 11th, 2024 [March 11th, 2024]
- The benefits and risks of Artificial Intelligence - IT Brief Australia - March 11th, 2024 [March 11th, 2024]
- The Bull Market Is Official: 1 Superb Artificial Intelligence (AI) Growth Stock to Buy Before the Nasdaq Soars Higher in ... - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- Learn the ways of machine learning with Python through one of these 5 courses and specializations - Fortune - March 11th, 2024 [March 11th, 2024]
- Forget Nvidia: These 2 Artificial Intelligence (AI) Stocks Are Considerably Cheaper and Not in a Bubble - The Motley Fool - March 11th, 2024 [March 11th, 2024]
- A Technologist Spent Years Building an AI Chatbot Tutor. He Decided It Cant Be Done. - EdSurge - January 22nd, 2024 [January 22nd, 2024]
- MotoGP, China close to Ducati: Lenovo uses artificial intelligence in the 'Remote Garage' - GPOne.com - January 22nd, 2024 [January 22nd, 2024]
- Here's the Only Artificial Intelligence (AI) Stock That Warren Buffett and Cathie Wood Both Own As 2024 Begins - Yahoo Finance - January 22nd, 2024 [January 22nd, 2024]
- 3 Artificial Intelligence (AI) Stocks to Buy Today, Still Below Their 2021 Highs - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Demystifying AI: The Probability Theory Behind LLMs Like OpenAI's ChatGPT - PYMNTS.com - January 22nd, 2024 [January 22nd, 2024]
- The Urgent but Difficult Task of Regulating Artificial Intelligence - Amnesty International - January 22nd, 2024 [January 22nd, 2024]
- 1 Spectacular Artificial Intelligence (AI) Growth Stock Down 35% to Buy Hand Over Fist in 2024 - Yahoo Finance - January 22nd, 2024 [January 22nd, 2024]
- The Diabetic Cyborg Life 01/22: Artificial Intelligence Makes for Lies in New Hampshire - Medium - January 22nd, 2024 [January 22nd, 2024]
- Comparing Student Reactions To Lectures In Artificial Intelligence And Physics - Science 2.0 - January 22nd, 2024 [January 22nd, 2024]
- Critics Say Sweeping Artificial Intelligence Regulations Could Target Parody, Satire Such as South Park, Family Guy - R Street - January 22nd, 2024 [January 22nd, 2024]
- Could Snowflake Be the Best Artificial Intelligence (AI) Stock to Own in 2024? - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Forget Nvidia: 2 Artificial Intelligence Stocks That Could Help Make You Rich in 2024 - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Stanford Researchers Introduce PEPSI: A New Artificial Intelligence Method to Identify Tumor-Immune Cell Interactions from Tissue Imaging -... - January 22nd, 2024 [January 22nd, 2024]
- Does Microsoft's Latest Artificial Intelligence (AI) Product Make It a Screaming Buy? - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Artificial Intelligence: inevitable integration enterprises | Top Stories | theweeklyjournal.com - The Weekly Journal - January 22nd, 2024 [January 22nd, 2024]
- Seven technologies to watch in 2024 - Nature.com - January 22nd, 2024 [January 22nd, 2024]
- Artificial intelligence helped scientists create a new type of battery - Science News Magazine - January 22nd, 2024 [January 22nd, 2024]
- Beware The Coming Artificial Intelligence Tax - Forbes - January 22nd, 2024 [January 22nd, 2024]
- AI News: Artificial Intelligence Trends And Top AI Stocks To Watch - Investor's Business Daily - January 22nd, 2024 [January 22nd, 2024]
- WHO releases AI ethics and governance guidance for large multi-modal models - World Health Organization - January 22nd, 2024 [January 22nd, 2024]
- 1 Spectacular Artificial Intelligence (AI) Growth Stock Down 35% to Buy Hand Over Fist in 2024 - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Youngkin signs a new executive order on artificial intelligence - WRIC ABC 8News - January 22nd, 2024 [January 22nd, 2024]
- UAE establishes Artificial Intelligence and Advanced Technology Council - Al Arabiya English - January 22nd, 2024 [January 22nd, 2024]
- Artificial intelligence cant replace the majority of jobs right now in cost-effective ways: study - National Post - January 22nd, 2024 [January 22nd, 2024]
- 2 Stock-Split Artificial Intelligence (AI) Stocks to Buy Before They Soar 50% and 80%, According to Certain Wall Street ... - Yahoo Finance - January 22nd, 2024 [January 22nd, 2024]
- 3 Artificial Intelligence (AI) Stocks That Could Make You a Millionaire - Yahoo Finance - January 22nd, 2024 [January 22nd, 2024]
- Artificial Intelligence and Nuclear Stability - War On The Rocks - January 22nd, 2024 [January 22nd, 2024]
- Test Yourself: Which Faces Were Made by A.I.? - The New York Times - January 22nd, 2024 [January 22nd, 2024]
- History Suggests the Nasdaq Will Surge in 2024: My Top 7 Artificial Intelligence (AI) Growth Stocks to Buy Before It Does - The Motley Fool - January 22nd, 2024 [January 22nd, 2024]
- Cathie Wood's Ark Invest Is Selling Nvidia Stock and Buying These 2 Artificial Intelligence (AI) Growth Stocks Ahead of ... - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- 2 Unstoppable Artificial Intelligence (AI) Stocks Up 159% and 217% in 2023 to Buy in 2024 - Yahoo Finance - December 31st, 2023 [December 31st, 2023]
- Nvidia Stock Has This Under-the-Radar Artificial Intelligence (AI) Growth Strategy for 2024 - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- This Is Warren Buffett's Favorite Artificial Intelligence (AI) Stock. Here's Why. - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- If I Could Buy Only 1 Artificial Intelligence (AI) Stock, This Would Be It - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- Quantitative gait analysis and prediction using artificial intelligence for patients with gait disorders | Scientific Reports - Nature.com - December 31st, 2023 [December 31st, 2023]
- AI Revolution: Unleashing the Power of Artificial Intelligence in Our Lives - Medium - December 31st, 2023 [December 31st, 2023]
- Arguing the Pros and Cons of Artificial Intelligence in Healthcare - HealthITAnalytics.com - December 31st, 2023 [December 31st, 2023]
- This "Magnificent Seven" Stock Could Win Big From Artificial Intelligence (AI) in 2024, and Beyond - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- Is artificial intelligence about to free us from the curse of Babel? - New Scientist - December 31st, 2023 [December 31st, 2023]
- 1 Artificial Intelligence (AI) Stock Down 58% to Buy Hand Over Fist in 2024 - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- This Artificial Intelligence Stock Could Be Like Buying Amazon in 1997 - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- 3 Artificial Intelligence (AI) Stocks With 48% to 123% Upside in 2024, According to Select Wall Street Analysts - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- Michael Cohen Used Artificial Intelligence to Feed Lawyer Bogus Cases - Yahoo! Voices - December 31st, 2023 [December 31st, 2023]
- AI Assimilation: 7 Stocks Leading in Artificial Intelligence Adoption - InvestorPlace - December 31st, 2023 [December 31st, 2023]
- 1 Dow Jones Artificial Intelligence (AI) Stock to Buy Hand Over Fist in 2024. Hint: It's Not in the "Magnificent Seven." - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- Worried About Nvidia's Valuation? 1 Artificial Intelligence (AI) Stock to Buy Right Now Before It Soars Higher - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- Why Are the "Magnificent Seven" So Magnificent? Hint: Artificial Intelligence - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- History Says the Nasdaq Will Soar in 2024: 1 Artificial Intelligence (AI) Growth Stock to Buy Before It Does - The Motley Fool - December 31st, 2023 [December 31st, 2023]
- The top 10 people in artificial-intelligence hardware - Business Insider - December 31st, 2023 [December 31st, 2023]
Tags: