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来源类型Working Paper
规范类型报告
DOI10.3386/w25976
来源IDWorking Paper 25976
How do Humans Interact with Algorithms? Experimental Evidence from Health Insurance
M. Kate Bundorf; Maria Polyakova; Ming Tai-Seale
发表日期2019-06-24
出版年2019
语种英语
摘要Algorithms are increasingly available to help consumers make purchasing decisions. How does algorithmic advice affect human decisions and what types of consumers are likely to use such advice? We use data from a randomized controlled trial of algorithmic advice in the context of prescription drug insurance to examine these questions. We propose that algorithmic recommendations can affect decision-making by influencing consumer beliefs about either product features (learning) or how to value those features (interpretation). We use data from the trial to estimate the importance of each mechanism. We find evidence that algorithms influence choices through both channels. Further, we document substantial selection into the use of algorithmic expert advice. Consumers who we predict would have responded more to algorithmic advice were less likely to demand it. Our results raise concerns regarding the ability of algorithmic advice to alter consumer preferences as well as the distributional implications of greater access to algorithmic advice.
主题Microeconomics ; Households and Firms ; Economics of Information ; Behavioral Economics ; Financial Economics ; Financial Institutions ; Public Economics ; National Fiscal Issues ; Health, Education, and Welfare ; Health
URLhttps://www.nber.org/papers/w25976
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/583650
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M. Kate Bundorf,Maria Polyakova,Ming Tai-Seale. How do Humans Interact with Algorithms? Experimental Evidence from Health Insurance. 2019.
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