Following an analysis of existing AI-related exchange-traded funds (ETFs), we reveal the selection criteria for determining which stocks qualify as AI-related are often opaque and rely on vague phrases and subjective judgments. This paper proposes a new, objective, data-driven approach using natural language processing (NLP) techniques to classify AI stocks by analyzing annual 10-K filings from 3,395 NASDAQ-listed firms between 2011 and 2023. This analysis quantifies each company's engagement with AI through binary indicators and weighted AI scores based on the frequency and context of AI-related terms. Using these metrics, we construct four AI stock indices-the Equally Weighted AI Index (AII), the Size-Weighted AI Index (SAII), and two Time-Discounted AI Indices (TAII05 and TAII5X)-offering different perspectives on AI investment. We validate our methodology through an event study on the launch of OpenAI's ChatGPT, demonstrating that companies with higher AI engagement saw significantly greater positive abnormal returns, with analyses supporting the predictive power of our AI measures. Our indices perform on par with or surpass 14 existing AI-themed ETFs and the Nasdaq Composite Index in risk-return profiles, market responsiveness, and overall performance, achieving higher average daily returns and risk-adjusted metrics without increased volatility. These results suggest our NLP-based approach offers a reliable, market-responsive, and cost-effective alternative to existing AI-related ETF products. Our innovative methodology can also guide investors, asset managers, and policymakers in using corporate data to construct other thematic portfolios, contributing to a more transparent, data-driven, and competitive approach.

This paper presents the latest version of the Global AI Vibrancy Tool (GVT), an interactive suite of visualizations designed to facilitate the comparison of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that allow users to conduct in-depth country-level comparisons and longitudinal analyses of AI-related metrics, all based on publicly available data. By providing a transparent assessment of national progress in AI, it serves the diverse needs of policymakers, industry leaders, researchers, and the general public. Using weights for indicators and pillars developed by AI Index's panel of experts and combined into an index, the Global AI Vibrancy Ranking for 2023 places the United States first by a significant margin, followed by China and the United Kingdom. The ranking also highlights the rise of smaller nations such as Singapore when evaluated on both absolute and per capita bases. The tool offers three sub-indices for evaluating Global AI Vibrancy along different dimensions: the Innovation Index, the Economic Competitiveness Index, and the Policy, Governance, and Public Engagement Index.

I just completed more than 20 in-depth interviews with HR Technology vendors to understand their AI strategies. And as I describe in the video below, I believe the results will be dramatic. Not only are vendors reinventing their offerings, new AI-centric systems have a completely different architecture, user interface, and design. While it's still early days, I believe AI (and Generative AI in particular) is going to radically change the HR Tech landscape. Not only will systems be intelligent by design, they will have powerful conversational user interfaces, they will embed multiple AI models, and new disruptors will appear.

For years now, the Institute for Human-Centered Artificial Intelligence at Stanford has been releasing its AI Index on an annual basis. Tapping into the expertise available within academic and private organizations, the Index provides a detailed snapshot of the trends in AI and the road ahead. With AI occupying center stage for the past few months, the AI Index is a valuable resource to see what the future holds. To begin with, the report highlights the dramatic shift in the release of AI models. While until a few years ago, it was academia that led the development of large models, now it is the industry that is leading the charge.

Did you miss a session at the Data Summit? Private investors are pouring more money into AI startups than ever before. At the same time, AI systems are becoming more affordable to train -- at least when it comes to certain tasks, like object classification. Troubling, though, language models in the same vein as OpenAI's GPT-3 are exhibiting greater bias and generating more toxic text than the simpler models that preceded them. Those are the top-level findings of the 2022 AI Index report out of Stanford's Institute for Human-Centered AI (HAI), an academic research center focused on the human impact of AI technologies.

Earlier this month, Brookings Metro published a data-driven snapshot of the growth and geography of the emerging artificial intelligence (AI) economy in the United States. Employing seven basic measures of AI research and commercial activity, the report benchmarked U.S. metropolitan areas on the basis of their core AI assets and capabilities as they stand now. Here, we look at the report's most important takeaways through five charts. The AI industry is growing rapidly, with AI-related projects accounting for a substantially larger share of federal research and development expenditures at U.S. colleges and universities. Similarly, newly founded firms that provide AI solutions of all tech startups expanded to more than 5%, from less than 1% a decade ago.

Global executives fear the increased utilization of AI as the industry is still uncertain about the intelligent technology's full capabilities and potential With the accelerated pace of digital marketing, enterprises have already begun to make decisions about adopting AI-driven solutions. A recent US Policy report'National Security Commission on Artificial Intelligence' states that Americans have not yet understood the exact consequences of AI adoption on their national security, welfare and economy. The 756 pages report underlines the fact that while AI should benefit the country, it should also defend it against AI's destructive capabilities. True, there is undiscovered knowledge that might reveal overwhelming possibilities. Experts also reflect on Open AI's CLIP and Facebook's new AI-model SEER.

China has overtaken the United States in total number of AI research citations, fewer AI startups are receiving funding, and Congress is talking about AI more than ever. Those are three major trends highlighted in the 2021 AI Index, an annual report released today by Stanford University. Now in its fourth year, the AI Index attempts to document advances in artificial intelligence, as well as the technology's impact on education, startups, and government policy. The report details progress in the performance of major subdomains of AI, like deep learning, image recognition, and object detection, as well as in areas like protein folding. The AI Index is compiled by the Stanford Institute for Human-Centered Artificial Intelligence and an 11-member steering committee, with contributors from Harvard University, OECD, the Partnership on AI, and SRI International.

Artificial intelligence is becoming a true industry, with all the pluses and minuses that entails, according to a sweeping new report.Why it matters: AI is now in nearly every area of business, with the pandemic pushing even more investment in drug design and medicine. But as the technology matures, challenges around ethics and diversity grow.Stay on top of the latest market trends and economic insights with Axios Markets. Subscribe for freeDriving the news: This morning, the Stanford Institute for Human-Centered Artificial Intelligence (HAI) released its annual AI Index, a top overview of the current state of the field.A majority of North American AI Ph.D.s — 65% — now go into industry, up from 44% in 2010, a sign of the growing role that large companies are playing both in AI research and implementation."The striking thing to me is that AI is moving from a research phase to much more of an industrial practice," says Erik Brynjolfsson, a senior fellow at HAI and director of the Stanford Digital Economy Lab.By the numbers: Even with the pandemic, private AI investment grew by 9.3% in 2020, a bigger increase than in 2019.For the third year in a row, however, the number of newly funded companies decreased, a sign that "we're moving from pure research and exploratory small startups to industrial-stage companies," says Brynjolfsson.While academia remains the single-biggest source worldwide for peer-reviewed AI papers, corporate-affiliated research now represents nearly a fifth of all papers in the U.S., making it the second-biggest source.The drug and medical industries took in by far the biggest share of overall AI private investment in 2020, absorbing more than $13.8 billion — 4.5 times greater than in 2019 and nearly three times more than the next category of autonomous vehicles.The catch: While the field has experienced sudden busts in the past — the "AI winters" that vaporized funding — there's little indication such a collapse is on the horizon. But industrialization comes with its own growing pains.Cutting-edge AI increasingly requires huge amounts of computing and data, which puts more power in the hands of fewer big players.Conversely, the commoditization of AI technologies like facial recognition means more players in the field, both domestically and internationally, which makes it more difficult to regulate their use. As AI grows, the ethical challenges embedded in the field — and the fact that 45% of new AI Ph.D.s are white, compared to just about 2% who are Black — will mean "there's a new frontier of potential privacy violations and other abuses," says Brynjolfsson.The AI Index found that while the field of AI ethics is growing, the interest level of big companies is still "disappointingly small," says Brynjolfsson.Details: Those growing pains are at play in one of the most exciting applications in AI today: massive text-generating models. Systems like OpenAI's GPT-3, released last year, swallow hundreds of billions of words along the way to producing original text that can be eerily human-like in its execution.Text-generating AI models could help polish human-written resumes for job search, but could also potentially be used to spam corporate competitors with realistic computer-generated applicants, not to mention warp our shared reality."What we increasingly have with these models is a double-edged sword," says Kristin Tynski, a co-founder and senior VP at Fractl, a data-driven marketing company.What to watch: The growing geopolitical AI competition between the U.S. and China.The National Security Commission on Artificial Intelligence warned in a major report this week that "China possesses the might, talent, and ambition to surpass the United States as the world’s leader in AI in the next decade if current trends do not change.""We don’t have to go to war with China," former Google CEO Eric Schmidt, who chaired the committee that authored the report, told my Axios colleague Ina Fried. "We do need to be competitive."Yes, but: While researchers in China publish the most AI papers, the U.S. still leads on quality, according to the Stanford survey.And while a majority of AI Ph.D.s in the U.S. are from abroad, more than 80% remain in the country when they take jobs — a sign of the lasting attraction of the U.S. tech sector.The bottom line: AI still has a long way to go, but the challenges the field faces are shifting from what it can do to what it should do.Like this article? Get more from Axios and subscribe to Axios Markets for free.

This year's report shows a maturing industry, significant private investment, and rising competition between China and the U.S. The last decade was a pivotal one for the AI industry, and 2020 saw AI substantially increase its impact on the world despite the chaos brought about by the COVID pandemic: Technologists made significant strides in massive language and generative models; the United States witnessed its first drop in AI hiring ever – pointing to a maturation of the industry – while hiring around the world increased; more dollars flowed to government use of AI than ever before, while colleges and universities offered students double the AI courses from a few years ago. These are just some of the findings from the 2021 AI Index, an annual study of AI impact and progress developed by an interdisciplinary team at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) in partnership with organizations from industry, academia, and government. "The impact of AI this past year was both societal and economic, driven by the increasingly rapid progress of the technology itself," said AI Index co-chair Jack Clark. "With the AI Index, we can actually measure and evaluate the changes, enabling leaders and decision makers to take meaningful action to advance AI responsibly and ethically with humans in mind." The 2021 AI Index is one of the most comprehensive reports about AI to date, analyzing and distilling patterns about AI's impact on everything from national economies to job growth to the analysis of technical progress within AI research itself, and analysis of the diversity (or lack of) among the people who create AI systems.