aiqbench analysis
This research highlights how historical rhetorical strategies from the 1950s continue to shape modern AI discourse by blurring the line between technical function and human-like capability. By exposing this "strategic ambiguity," the study urges a more precise vocabulary that distinguishes between machine execution and genuine cognition, which is essential for accurate public understanding of AI limits.
Carnegie Mellon and Pitt historians question if AI ‘thinks’ like us
Carnegie Mellon’s Christopher Phillips and Pitt’s Alison Langmead trace AI language to the 1950s, finding “strategic ambiguity” in how we describe its capabilities.
Carnegie Mellon University historian Christopher Phillips and University of Pittsburgh’s Alison Langmead challenge conventional thinking about artificial intelligence with research tracing current AI rhetoric back to the 1950s. Their new paper in IEEE Annals of the History of Computing argues that discussions about AI reveal more about how humans discuss technology than the technology itself. “We use words like ‘smart,’ ‘read,’ ‘write’ and ‘think’ very differently when we’re talking about humans than when we’re talking about computers,” Phillips said, questioning why the same terms are applied to both. Langmead and Phillips suggest a broader conversation is needed to clarify what computers can and cannot…
Excerpt shown under the publisher's RSS terms · 104 words · full text and figures are on the publisher's site
Related coverage
Does AI need an antitrust exemption so it doesn’t kill everyone????
The Verge · Sep 19, 2026
Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye
Import AI · Aug 24, 2026
Following the questions where they lead
MIT News · Jul 17, 2026
The Alignment Journal: Organization, Personnel, and Scope
AI Alignment Forum · Sep 1, 2026