What The Stanford 2022 A.I Index Says about the Future of A.I.?

I want to write and summarize impactful News on artificial intelligence. Every year, the Stanford Institute for Human-Centered Artificial Intelligence (HAI) puts out its AI Index, a massive compendium of data and graphs that tries to sum up the current state of artificial intelligence.

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The data is starting to become more interesting.

The new report highlights an AI investment boom, impressive new technical capabilities, and a fresh focus on ethics (including a new chapter on fairness and bias).

Artificial Intelligence in an Integrated Digital Transformation Economy

“2021 was the year that AI went from an emerging technology to a mature technology—we’re no longer dealing with a speculative part of scientific research, but instead something that has real-world impact, both positive and negative,” says Jack Clark, co-chair of the AI Index. “This year’s AI Index tells us that AI is being integrated into the economy and the effects of it are beginning to go global across research, deployment, and even funding.” 

Read the 2022 AI Index Report

The 2022 AI Index, which came out this week, is as impressive as ever, with 190 pages covering R&D, technical performance, ethics, policy, education, and the economy. There are many graphs worth taking a closer look at and it’s just fascinating for any A.I. enthusiast.

The Golden Spring of A.I. Research

We are indeed at an unpreceded moment in A.I. Adoption, with major risks and incredible funding. We are still living in a golden AI summer with ever-increasing publications, the AI job market is still global, and there’s still a disconcerting gap between corporate recognition of AI risks and attempts to mitigate said risks.

When we call A.I. a disruptive technology, we have to think at the scale of adoption. I think this graph maybe best demonstrates this. It is one of the most important graphs in technology and business today.

What I especially appreciate is how the Standard Index summarizes and visualizes what we intuitively know wis happening in the world of A.I.

The AI Index Report tracks, collates, distills, and visualizes data relating to artificial intelligence. Its mission is to provide unbiased, rigorous, and comprehensive data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI.

When I started the AiSupremacy Newsletter, this is exactly the kind of data I wanted to present and talk about.

The amount of money pouring into AI is mind-boggling

  • The private investment in AI in 2021 totaled around $93.5 billion—more than double the total private investment in 2020, while the number of newly funded AI companies continues to drop, from 1051 companies in 2019 and 762 companies in 2020 to 746 companies in 2021.

The index is an independent program developed by an interdisciplinary team at HAI in partnership with academia, industry, and government. It analyzes and distills trends in the industry, from investment and startups to technical capability, education and public policy.

Read the Top Takeaways

Consolidation and Centralization of A.I.’s Power

The report also notes that all that money is being funneled to fewer companies, since the number of newly funded startups has been dropping since 2018. It’s a great time to join an AI startup, but maybe not to found one yourself.

In fact the Index this year really adds some ethical context to A.I.’s development. 2021 saw the globalization and industrialization of AI intensify, while the ethical and regulatory issues of these technologies multiplied. 

Key Advances of A.I. in 2021

The new report shows several key advances in AI in 2021: 

  • Private investment in AI has more than doubled since 2020, in part due to larger funding rounds. In 2020, there were four funding rounds worth $500 million or more; in 2021, there were 15.
  • AI has become more affordable and higher performing. The cost to train an image classification has decreased by 63.6% and training times have improved by 94.4% since 2018. The median price of robotic arms has also decreased 46.2% in the past five years.
  • The United States and China have dominated cross-country research collaborations on AI as the total number of AI publications continues to grow. The two countries had the greatest number of cross-country collaborations in AI papers in the last decade, producing 2.7 times more joint papers in 2021 than between the United Kingdom and China—the second highest on the list.
  • The number of AI patents filed has soared—more than 30 times higher than in 2015, showing a compound annual growth rate of 76.9%.

A.I. is becoming more democratized and yet simultaneously more centralized in the top American and Chinese corporations. It’s adoption in society, industry, the Cloud and business has also accelerated very rapidly.

A.I Publications Show China and America Working Together on Research

The United States and China had the greatest number of cross-country collaborations in AI publications from 2010 to 2021, increasing five times since 2010. The collaboration between the two countries produced 2.7 times more publications than between the United Kingdom and China—the second highest on the list.

You will notice a lot of Chinese last names of researchers at the top U.S. Universities leading the most important research today in A.I. We have to ponder what this means for the future of A.I., both in terms of patents, new startups and the incredible collaboration in society and academia that’s also fueling the A.I. boom to come.

Top Takeaways

Growing Ethical highlights in A.I’s capabilities

At the same time, the report also highlights growing research and concerns on ethical issues as well as regulatory interests associated with AI in 2021: 

  • Large language and multimodal language-vision models are excelling on technical benchmarks, but just as their performance increases, so do their ethical issues, like the generation of toxic text.
  • Research on fairness and transparency in AI has exploded since 2014, with a fivefold increase in publications on related topics over the past four years.
  • Industry has increased its involvement in AI ethics, with 71% more publications affiliated with industry at top conferences from 2018 to 2021. 
  • The United States has seen a sharp increase in the number of proposed bills related to AI; lawmakers proposed 130 laws in 2021, compared with just 1 in 2015. However, the number of bills passed remains low, with only 2% ultimately becoming law in the past six years.
  • Globally, AI regulation continues to expand. Since 2015, 18 times more bills related to AI were passed into law in legislatures of 25 countries around the world and mentions of AI in legislative proceedings also grew 7.7 times in the past six years.

If you don’t understand the amount of Research and patents China is involved with in A.I. you don’t understand the future of A.I.

The AI Index partners with organizations across sectors, including the Center for Security and Emerging Technology at Georgetown University, LinkedIn, and Bloomberg Government, to track the progress of artificial intelligence. In addition, the 2022 report also introduces more self-collected data and original analysis than any previous editions.

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The U.S. vs. China Narrative Is Complicated

How do you reconcile the supposed cold Tech War with how much the U.S. and China is actually collaborating in A.I. research in our top academic institutions? China’s increasing focus and talent in A.I. research is clearly driving a lot of the pace of innovation.

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2021 was essentially a year where the U.S. and China never worked so hard together on A.I. research and bleeding edge work in multiple fields of A.I. and applied engineering.

Read A.I’s Ethical Growing Pains

I myself have noticed companies like Microsoft have really doubled down on A.I. research. China’s ascent in A.I. really isn’t well documented by the American mainstream news, and I sometimes wonder what this is when the data tells us that when it comes to cross-country collaborations on publications, China and the United States produce more than twice as many as the next pairing, China and the United Kingdom. 10x is a lot.

China’s Grand Obsession with A.I Patents

China dominates the world on number of patents applied for; the report states that China accounted for 52 percent of global patent filings in 2021. However, many of those filings may have been somewhat aspirational.

  • China believes in A.I patents, which have yet for the most part borne fruit.
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China Catching up in A.I Publication Quantity, not Necessarily Quality

While China leads on number of publications, publication citations, and conference publications, the United States still leads on citations of conference publications, showing that prestigious papers from U.S. researchers are still having an outsized impact.

The Computer Vision Plateau

  • The field of computer vision has been advancing so rapidly, it’s been hard to keep up with news of the latest accomplishments. The AI Index shows that computer vision systems are tremendously good at tasks involving static images such as object classification and facial recognition, and they’re getting better at video tasks such as classifying activities.
  • The field of computer vision has been advancing so rapidly, it’s been hard to keep up with news of the latest accomplishments. The AI Index shows that computer vision systems are tremendously good at tasks involving static images such as object classification and facial recognition, and they’re getting better at video tasks such as classifying activities.

The graph that best demonstrates this is perhaps this one:

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A.I. Adoption Explosion

What are the top skills most requested by employers?

The share of AI job postings among all job postings in 2021 was greatest for machine learning skills (0.6% of all job postings), followed by artificial intelligence (0.33%), neural networks (0.16%), and natural language processing (0.13%). Postings for AI jobs in machine learning and artificial intelligence have significantly increased in the past couple of years. Machine learning jobs are at nearly three times the level they reached in 2018, while artificial intelligence jobs are at around 1.5 times the level.

  • Machine Learning – 1
  • Artificial Intelligence – 2
  • Neural Networks – 3
  • Natural language processing -4

As A.I. adoption in manufacturing increases, global policy makers are scrambling to enact laws that make sense and determine ethical policies. There’s a huge amount of interest in AI ethics right now, as judged by participation in meetings like the ACM conference on Fairness, Accountability, and Transparency (FAccT) and ethics-related workshops at NeurIPS. For those who haven’t heard of FAccT, the report notes that it was one of the first major conferences to focus on sociotechnical analysis of algorithms.

The number of new A.I. PhDs also demonstrates the uptake of A.I in academic and industry (and even Government).

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As you can see, since 2015 there’s a noticeable spike in the number of new AI PhDs.

As the Stanford Index points out, As AI systems develop more impressive capability, they also produce more harm, and with great power comes great responsibility.

A,I. Ethical Growing Pains

Dangers and Concerns of A.I.’s Pace of Adoption

In an environment of hype and funding, there’s been far less serious soul searching about the future impact of A.I. at scale. Think about it, the field of AI has grown, researchers have proudly measured and reported AI systems’ increasingly impressive technical capabilities. But researchers have been much slower to measure AI’s harms, let alone publish papers about them. There’s a significant disconnect.

Although AI ethics is a relatively nascent field, its importance and recent growth is a focus in the 2022. China too appears to be taking AI ethics more seriously as of 2021. Late last year, China’s Ministry of Science and Technology issued guidelines on artificial intelligence ethics. The European Union had issued a preliminary draft of AI-related rules in April 2021, but we’ve seen nothing final. The U.S. appears to be the laggard in A.I regulation, by a pretty wide margin as of 2022.

This is problematic of course since it’s in the U.S. where there appears to be the biggest concentration of talent, funding and acquisition power in terms of the centralization around A.I. The Stanford Index curiously did not talk much about this.

Instead it appears the U.S. has taken instead an academic curiosity about A.I ethics. If the number of peer-reviewed publications on a topic is a good measure of engagement in a particular field of research, then AI ethics is undergoing a bit of a boom. For example, at NeurIPS, one of the largest AI conferences, the number of accepted papers about certain hot topics in AI ethics (interpretability, explainability, causation, fairness, bias and privacy) has steadily increased in recent years.

It’s somewhat bizarre that the U.S. Government is so behind the curve in A.I. regulation, no doubt influenced by BigTech lobbyists. Many BigTech companies now have lucrative contracts with the Pentagon and the U.S. Defense community further complicating things.

Companies in the AI space are starting to take AI ethics seriously, as indicated by the growing proportion of peer-reviewed AI ethics papers they have submitted to FAccT each year. This trend suggests that industry players are going beyond just issuing AI standards – a relatively insignificant step that many companies have taken in recent years. Cleary there’s some bottleneck in U.S. regulation of A.I. that we can speculate upon further.

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Inclusion in A.I.

A serious diversity shortage

Among new AI PhDs from 2010 to 2020 who are U.S. residents, the largest percentage has been non-Hispanic white and Asian—65.2% and 18.8% on average. By comparison, around 1.5% were Black or African American (non-Hispanic) and 2.9% were Hispanic on average over the past 11 years. In the past decade, the percentage of new Black or African American and Hispanic computing PhDs dropped significantly. 

The Talent by ethnicity is truly disappointing in the U.S. As someone who covers inclusion and diversity in tech, it’s not exactly surprising:

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So the A.I. field is more or less led by white and asian Males, much like Silicon Valley’s leaders, and most especially the Venture Capital structure of Silicon Valley itself. That’s not exactly representative of the consumers, people, citizens and future descendants A.I. tools will serve. For bias and policy, this has huge ramifications that the U.S. isn’t talking about. Even when America is unique in its political spectrum of racial and ethnic divisions and systematic inequality.

Private investment booms

In 2021, global private investment in AI totaled around $93.5 billion, which is more than double the total private investment in 2020. That marks the greatest year-over-year increase since 2014 (when investment from 2013 to 2014 more than doubled).

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This is not surprising with the liquidity boom of the Fed’s radical QE policies that increases money supply in the area of plus 30% in the U.S. economy.

Where is research concentrated in AI?

More scholars are focusing on pattern recognition and machine learning. Publications in these two areas have more than doubled since 2015. Other areas strongly influenced by deep learning, such as computer vision, data mining and natural language processing, have shown smaller increases.

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