It is common for observers to compare machine intelligence with individual human intelligence, but this tendency can narrow and distort understanding. Rather, this paper suggests that machines, bureaucracies and markets can usefully be regarded as a set of artificial intelligences that have been invented to complement the limited abilities of individual human minds to discern patterns in large amounts of data. This approach opens an array of possibilities for insight and future investigation.

Progress in artificial intelligence has led to growing concern about the capabilities of AI-powered surveillance systems. This data brief uses bibliometric analysis to chart recent trends in visual surveillance research — what share of overall computer vision research it comprises, which countries are leading the way, and how things have varied over time.

Drawing from their report "Small Data's Big AI Potential," CSET's Helen Toner and Husanjot Chahal discuss why smaller data approaches to AI can be helpful and how this approach can be applied within Europe.

In their op-ed for Scientific American, Husanjot Chahal and Helen Toner argue how small data can assist AI breakthroughs.

AI technologies will likely alter great power competitions in foundational ways, changing both how nations create power and their motives for wielding it against one another. This paper is a first step toward thinking more expansively about AI & national power and seeking pragmatic insights for long-term U.S. competition with authoritarian governments.

Sara Abdulla was a Data Research Analyst at CSET.

CSET Founding Director Jason Matheny presented the keynote address at the virtual colloquium on the future of data science and the implications for privacy and national security hosted by the National Academies of Sciences, Engineering, and Medicine.

Plus: CA firefighters use AI, Rep. McCaul introduces export control bill and State Department issues guidance on surveillance technology

One sentence summarizes the complexities of modern artificial intelligence: Machine learning systems use computing power to execute algorithms that learn from data. This AI triad of computing power, algorithms, and data offers a framework for decision-making in national security policy.