סדנת מחקר בהשתתפות פרופ' אורן בר גיל

סדנת מחקר בהשתתפות פרופ' אורן בר – גיל בנושא Topics in US Contract Law.

AI-powered algorithms match different consumers with different products. When consumers are sophisticated (in S markets), algorithmic targeting is welfare enhancing, as it allows for a better matching between products and consumers. If some consumers like tablets and other consumers like laptops, algorithmic targeting can help both to get what they want. When consumers are unsophisticated (in U markets), algorithmic targeting might harm biased consumers by offering them an inferior product whose benefits they overestimate. Consumers might be offered an outmoded laptop at an inflated price, and they might like what they see. These biased consumers are harmed, relative to a pre-algorithmic, no-differentiation world, where the superior product would have been offered to all consumers. But even in U markets with overestimated benefits, algorithmic targeting is not always harmful. Specifically, targeting can help consumers, if in the pre-algorithmic, no-differentiation world sellers would offer only the inferior product to the biased consumers, at an inflated price. (In this case, algorithmic targeting helps the unbiased consumers, and does not harm the biased consumers.) In U markets where some consumers underestimate the benefit from a superior product, algorithmic targeting helps consumers because, in a pre-algorithmic, no-differentiation world either (i) the inferior product would have been offered to all consumers; or (ii) the superior product would have been offered at a price that completely excludes biased consumers from the market (whereas targeting allows biased consumers to at least get the inferior product).

המפגש יתקיים ביום שני, 15.7.2024 בשעה 16:15 בחדר הסמינרים של מרכז מיתר, הפקולטה למשפטים.