Stanford University: Industrialization of AI and Mounting Ethical Concerns

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).

The field of artificial intelligence (AI) is at a critical crossroad, according to the 2022 AI Index, an annual study of AI impact and progress at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) led by an independent and interdisciplinary group of experts from across academia and industry: 2021 saw the globalization and industrialization of AI intensify, while the ethical and regulatory issues of these technologies multiplied.

“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.”

The 2022 AI Index is one of the most comprehensive reports about AI to date. It measures and evaluates the rapid rate of AI advancement via a cross-sector lens, from research and development to technical performance and ethics, AI policy and governance, the economy and education, and more. The goal of the annual report is to ground the conversation about AI in data, enabling decision makers to take meaningful action to advance AI responsibly and ethically with humans in mind.

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%.
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.
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. For example, the index significantly expanded the number of metrics in the technical performance chapter, added a new survey of researchers specializing in robotics around the world, and broadened its tracking of global AI legislation records to 25 countries.

The original analysis also includes a new chapter on technical AI ethics—surveying metrics used to assess bias in large language models and dissecting research trends of AI fairness, transparency, and accountability (FAccT) at the annual FAccT and NeurIPS conferences.

“As AI systems become increasingly more capable, it becomes critical to measure and understand the ways in which they can perpetuate harm,” says Helen Ngo, an AI Index-affiliated researcher and co-author of the chapter. “This new chapter provides a starting point to track the performance of state-of-the-art systems along ethical dimensions and provides researchers, practitioners, and policymakers with an initial set of quantifiable metrics to track over time.”

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