Temporal Framing in Balanced News Coverage of Artificial Intelligence and Public Attitudes

Abstract

This study investigates how balanced news coverage, presenting both the positive and negative aspects of artificial intelligence (AI), may lead to attitudinal changes among the public when it is paired with different temporal frames. Different construal levels associated with temporal distance and evaluations of pros and cons provide a theoretical grounding to understand these dynamics. The results of an online experiment showed that exposure to the near-future temporal framing of AI (vs. distant-future temporal framing) induced greater perceived severity of AI risks. This, in turn, decreased public support for AI development and use. The indirect effect was conditional upon message order such that the effect was only significant when the message was presented in the risk/benefit order. The findings suggest that non-refutational two-sided frames reflecting journalistic norms of balance may lead to public opinion change because the accompanying temporal frames unwittingly impact which side people put more weight on. Thus, the selection of sources and the use of time reference need to be carefully vetted by journalists when reporting controversial science and technology.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 29 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.