Matthew Tokson, Associate Dean for Research at the University of Utah S.J. Quinney College of Law, argues in a short SSRN paper that humans are very poor at predicting how technologies will be built and used. He warns that today’s quick judgments about artificial intelligence (AI) are likely to be wrong.
Cautionary historical examples
Tokson cites several historical cases that illustrate how experts have repeatedly mispredicted technological developments and their consequences:
- Many prominent scientists — including Albert Einstein, Niels Bohr, and Robert Oppenheimer — were skeptical that nuclear fission could be achieved in the years immediately before it happened.
- Nobel Prize–winning economist Paul Krugman once compared the potential impact of the internet to that of the fax machine, suggesting it would not be substantially greater.
- Some technologists expected the internet to ultimately promote democracy rather than strengthen autocratic regimes.
- Despite decades of mounting evidence, many scholars in human sciences either rejected human-caused climate change or significantly underestimated its effects.
Why this matters now
The principal lesson of the paper is that both those who are skeptical that AI could bring major economic changes and those who believe AI’s effects will be universally beneficial are likely to be wrong. Tokson writes, “History does not support complacency about the future impacts of AI.” He notes that historically, optimists have often misjudged the social ramifications of new technologies or the strategic benefits of developing dangerous new weapons, while skeptics have tended to underestimate the likelihood and impact of novel innovations on humanity.
Tokson’s short essay serves as a reminder to approach current rapid judgments about AI with caution and to draw on historical examples to acknowledge the deep uncertainty in forecasting the societal consequences of technological change.
