“How AI Fails Us,” Divya Siddarth, Daron Acemoglu, Danielle Allen, Kate Crawford, James Evans, Michael Jordan, E. Glen Weyl (December 1, 2021).
The dominant vision of artificial intelligence imagines a future of large-scale autonomous systems outperforming
humans in an increasing range of fields. This “actually existing AI” vision misconstrues intelligence as autonomous
rather than social and relational. It is both unproductive and dangerous, optimizing for artificial metrics of human
replication rather than for systemic augmentation, and tending to concentrate power, resources, and decision-making
in an engineering elite. Alternative visions based on participating in and augmenting human creativity and cooperation
have a long history and underlie many celebrated digital technologies such as personal computers and the internet.
Researchers and funders should redirect focus from centralized autonomous general intelligence to a plurality of
established and emerging approaches that extend cooperative and augmentative traditions as seen in successes such
as Taiwan’s digital democracy project and collective intelligence platforms like Wikipedia. We conclude with a concrete
set of recommendations and a survey of alternative traditions.
[W]e find everywhere men of mechanical genius, of great general acuteness, and discriminative understanding,
who make no scruple in pronouncing the Automaton—a pure machine, unconnected with human agency in its
movements—and consequently, beyond all comparison, the most astonishing of the inventions of mankind.
—Edgar Allen Poe, Maelzel’s Chess Player (1836)