Review
Jul 2026
Beyond Accuracy: How Humans Evaluate Legally Correct but Socially Controversial Legal Advice from Machines
It is suggested that public responses to AI legal advisors are shaped not by rigid attitudes toward automation, but by the balancing of competing normative expectations, which have implications for theories of algorithm aversion and the design of AI recommendation systems in normatively salient domains.
B. Chen, Zhi-Yu Li
· arXiv.org · 0 citations