Big data analytics is the secret sauce of the American polity and economy—widely utilized but poorly understood. Organizations use various typesOpens in a new window of big data analytics to make decisions, correlations, and predictions about their constituents or stakeholders. The market for data is big and growing rapidly; it’s estimatedOpens in a new window to hit $100 billion before the end of the decade. But the recipe for data analytics can at times contain a hidden ingredient: bias. Not surprisingly, there is evidenceOpens in a new window that reliance on big data analytical processes can lead to divisive, discriminatory, inequitable, and even dangerous outcomes—collective harms—for some of the people sorted into groups. That needs to change.
Recent Publications
Do AI Chatbot Firms Practice What They Preach?
This study examines whether leading AI chatbot companies implement the responsible AI principles they publicly advocate. The authors used a mixed-methods approach analyzing four major chatbots (ChatGPT, Gemini, Deep Seek, and Grok) across company websites, technical...
China-U.S. Rivalry Will Split the World into Competing AI Camps
The U.S. and China both put forward plans for artificial intelligence last month. The two have long sought to lead on AI, and their competition has led to technological breakthroughs, lower costs, and wider use of the technology. But as their new plans illustrate,...
Taking the Wrong Lesson from China’s AI Strategy
Taking the Wrong Lesson from China’s AI Strategy The United States is mimicking China’s approach to centralized data, risking privacy, security and democratic accountability in the name of AI leadership. Chinese leaders early on recognized the importance of data for...