The Industrial Revolution was the birthplace of social science as we know it. Entire disciplines such as sociology, political science and economics came into being to analyze enormous social challenges and guide public debate on how to respond. Other social sciences such as psychology and cognitive science followed to study closely how the effects of this revolution were changing us at the individual level.
As we face a new revolution ushered in by artificial intelligence, these disciplines are poorly situated to provide guidance. The Trump administration has slashed federal funding for the social and behavioral sciences, while private funding for certain A.I.-related work has skyrocketed. The result is that many social scientists have left academia and traditional research institutions for A.I. firms that are effectively building out their own social science programs — which threaten to favor the ambitions of A.I.’s creators over the public’s interests.
To navigate the shock waves of A.I., we must restore social science research as an enterprise that starts from the public interest.
Nineteenth-century industrialization led to a series of huge social upheavals in which people left agrarian lives in the countryside for jobs in cities. Subjects were increasingly becoming citizens who could vote and influence policy to some degree and were educated in government-funded schools.
Not all of this was pretty. Workers endured terrible living conditions, while rapidly growing cities became cesspits of crime and disease. Politics was ravaged by conflict between those who wanted political and economic revolution and those who called for violent repression of these movements. Liberals, socialists and conservatives worried that these tensions would tear society apart.
The fear that machines were wrecking society created political demand for reliable information on what was happening on the ground and how people were living. In Britain, where the Industrial Revolution began, the journalist Henry Mayhew calculated that hundreds of Londoners made their living gathering bones, rags and cigar ends from the street, as well as dog excrement for tanneries. Commissions of inquiry and censuses followed and gathered information on working conditions and education. Politicians, lawyers and bureaucrats debated whether allowing poor people to vote would lead to disaster.
Social science research arose to study these issues in a more rigorous fashion. Economists studied markets, political scientists studied politics and the state, sociologists studied changing society, and psychologists studied minds. Though these investigations had flaws and were sometimes biased, together they rebuilt our public understanding of what was necessary and possible.
It is hard to imagine how the global economy could have been constructed without economists’ insight into how trade leaves countries better off, or how the modern federal government would have been created if political science professors had not argued for accountable public administration. Sociologists’ ideas about networks helped inspire Google search, and psychologists developed the neural networks that now power A.I.
Under the Trump administration, the National Science Foundation, which funds most social science research in the United States, is making no grants to traditional sociology, economics or political science investigations, as part of a larger effort to dismantle the agency’s work in these subjects entirely.
Meanwhile, both OpenAI and Anthropic want social scientists to provide guidance on how society can help displaced workers, reshape tax systems, modernize income support and perhaps even start thinking about some public ownership of A.I. The OpenAI Foundation, which owns a 26 percent stake in OpenAI, has committed $250 million to projects for understanding and supporting the transition to an A.I.-centered economy and sharing its gains. Anthropic is giving $200 million for “ambitious external research on interventions to prepare society for the economic impacts of A.I.” Together, that is more than double the $216 million that the N.S.F. budgeted for the social sciences in 2024, before any administrative change.
This social science may be rigorous, and the companies may be looking for honest answers to these questions. But there’s no doubt the questions are shaped by their interests and beliefs. As citizens organize against local data centers, and as Democratic and Republican politicians scramble to attract their votes, the labs are not asking for research on whether the shift to A.I. is a good thing or how it ought to be deployed. They are more interested in smoothing the A.I. transition than questioning it.
A world where there is no N.S.F. funding for social science, but where the A.I. industry funds research generously, will inevitably skew public debate. Fixing this problem is hard. But lawmakers could press the administration to reverse its funding decisions on social science research. More immediately, if the A.I. labs want to do their own social science or provide funding to others, they should create decision-making bodies composed of independent experts who aren’t beholden to company interests, and whose perspectives better reflect the public’s own questions and concerns. That would sacrifice control, but gain public legitimacy.
Those steps could help move the social sciences back to addressing the most pressing dilemmas of the A.I. age. Which jobs will A.I. replace and disrupt? How will our economy change? How will personal and intimate relationships be transformed? Can A.I. persuade humans to change their views? If it can, will that enhance or hinder democracy and the flow of facts and information?
Henry Farrell is a professor of democracy and international affairs at Johns Hopkins University. Alison Gopnik is a professor of psychology and a member of the Berkeley A.I. research group at the University of California, Berkeley. James Evans is a professor of sociology and data science at the University of Chicago. All are external faculty at the Santa Fe Institute.
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