Tag Archive: Artificial intelligence

Chinese Government Guidance Funds

Ngor Luong, Zachary Arnold, and Ben Murphy
| March 2021

The Chinese government is pouring money into public-private investment funds, known as guidance funds, to advance China’s strategic and emerging technologies, including artificial intelligence. These funds are mobilizing massive amounts of capital from public and private sources—prompting both concern and skepticism among outside observers. This overview presents essential findings from our full-length report on these funds, analyzing the guidance fund model, its intended benefits and weaknesses, and its long-term prospects for success.

Understanding Chinese Government Guidance Funds

Ngor Luong, Zachary Arnold, and Ben Murphy
| March 2021

China’s government is using public-private investment funds, known as guidance funds, to deploy massive amounts of capital in support of strategic and emerging technologies, including artificial intelligence. Drawing exclusively on Chinese-language sources, this report explores how guidance funds raise and deploy capital, manage their investment, and interact with public and private actors. The guidance fund model is no silver bullet, but it has many advantages over traditional industrial policy mechanisms.

AI Verification

Matthew Mittelsteadt
| February 2021

The rapid integration of artificial intelligence into military systems raises critical questions of ethics, design and safety. While many states and organizations have called for some form of “AI arms control,” few have discussed the technical details of verifying countries’ compliance with these regulations. This brief offers a starting point, defining the goals of “AI verification” and proposing several mechanisms to support arms inspections and continuous verification.

Using Machine Learning to Fill Gaps in Chinese AI Market Data

Zachary Arnold, Joanne Boisson, Lorenzo Bongiovanni, Daniel Chou, Carrie Peelman, and Ilya Rahkovsky
| February 2021

In this proof-of-concept project, CSET and Amplyfi Ltd. used machine learning models and Chinese-language web data to identify Chinese companies active in artificial intelligence. Most of these companies were not labeled or described as AI-related in two high-quality commercial datasets. The authors' findings show that using structured data alone—even from the best providers—will yield an incomplete picture of the Chinese AI landscape.

From China to San Francisco: The Location of Investors in Top U.S. AI Startups

Rebecca Kagan, Rebecca Gelles, and Zachary Arnold
| February 2021

Foreign investors comprise a significant portion of investors in top U.S. AI startups, with China as the leading location. The authors analyze investment data in the U.S. AI startup ecosystem both domestically and abroad, outlining the sources of global investment.

Corporate Investors in Top U.S. AI Startups

Rebecca Kagan, Rebecca Gelles, and Zachary Arnold
| February 2021

Corporate investors are a significant player in the U.S. AI startup ecosystem, funding 71 percent of top U.S. AI startups. The authors analyze the trends in top corporate funders and the startups receiving corporate money.

Comparing Corporate and University Publication Activity in AI/ML

Simon Rodriguez, Tim Hwang, and Rebecca Gelles
| January 2021

Based on news coverage alone, it can seem as if corporations dominate the research on artificial intelligence and machine learning when compared to the work of universities and academia. Authors Simon Rodriguez, Tim Hwang and Rebecca Gelles analyze the data over the past decade of research publications and find that, in fact, universities are the more dominant producers of AI papers. They also find that while corporations do tend to generate more citations to the work they publish in the field, these “high performing” papers are most frequently cross-collaborations with university labs.

The U.S. AI Workforce

Diana Gehlhaus and Santiago Mutis
| January 2021

As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.

AI and the Future of Cyber Competition

Wyatt Hoffman
| January 2021

As states turn to AI to gain an edge in cyber competition, it will change the cat-and-mouse game between cyber attackers and defenders. Embracing machine learning systems for cyber defense could drive more aggressive and destabilizing engagements between states. Wyatt Hoffman writes that cyber competition already has the ingredients needed for escalation to real-world violence, even if these ingredients have yet to come together in the right conditions.

The strategic and security implications of AI

Towards Data Science
| January 7, 2021

CSET Director of Strategy Helen Toner sits down with Towards Data Science podcast to discuss the vulnerabilities and security implications of artificial intelligence.