Beyond Accuracy: How Humans Evaluate Legally Correct but Socially Controversial Legal Advice from Machines
arXiv:2607.05680v1 Announce Type: cross Abstract: AI systems are increasingly used to provide legal advice, raising questions about whether laypeople accept guidance from algorithms--especially when that advice is legally correct but socially controversial. We report a preregistered survey experiment with 3,348 adults in mainland China examining how people evaluate identical legal advice when it is attributed either to an AI system or to a human lawyer, and when it is accompanied by reasoning or not. Contrary to expectations of algorithm aversion, attribution to an AI system has no net effect
The proliferation of AI systems in sensitive domains like legal advice necessitates understanding human perception and acceptance, particularly when AI outputs are controversial.
This research provides crucial insights into the human-AI interaction in high-stakes fields, revealing whether the 'algorithm aversion' hypothesis holds when legal accuracy conflicts with social norms.
The perceived acceptance of AI-generated legal advice, even in controversial contexts, challenges assumptions about inherent human distrust of algorithms, especially when compared to human experts.
- · AI legal tech companies
- · Governments deploying AI legal tools
- · Citizens receiving legal advice
- · Legal professionals relying solely on human-centric trust models
- · Advocates of strict algorithm aversion
Increased confidence in deploying AI systems for legal advisory roles where outputs might be socially sensitive but legally sound.
Potential for broader public adoption and reliance on AI across other professional services, reducing the friction typically associated with algorithmic decision-making.
Re-evaluation of regulatory frameworks for AI in sensitive sectors, possibly shifting focus from 'algorithm aversion' to other ethical or societal impact considerations.
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Read at arXiv cs.AI