Shumiao Ouyang is an Associate Professor of Finance (without tenure) at Saïd Business School, University of Oxford, and a Tutorial Fellow in Management at Wadham College, Oxford.
Website: https://www.shumiaoouyang.com/
Paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4851711
Abstract: This study examines the risk
preferences of Large Language Models (LLMs) and how aligning them with human
ethical standards affects their economic decision-making. Analyzing 30 LLMs
reveals a range of inherent risk profiles, from risk-averse to risk-seeking. We
find that aligning LLMs with human values, focusing on harmlessness,
helpfulness, and honesty, shifts them towards risk aversion. While some
alignment improves investment forecast accuracy, excessive alignment leads to
overly cautious predictions, potentially resulting in severe underinvestment.
Our findings highlight the need for a nuanced approach that balances ethical
alignment with the specific requirements of economic domains when using LLMs in
finance.
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