本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2008
摘要
There is a wealth of research demonstrating that 智能體s process 資訊 with the aid of categories. In this paper we study this phenomenon in two parts. First, we build a model of how experiences are sorted into categories and how categorization affects decision making. Second, in a series of results that partly characterize an optimal categorization, we show that specific biases emerge from categorization. For instance, types of experiences and objects that are less frequent in the 族群 tend to be more coarsely categorized and lumped together. As a result, decision makers make less accurate predictions when confronted with such objects. This can result in discrimination against minority groups even when there is no malevolent taste for discrimination. However, such comparative statics are highly s
※ 此為已發表論文，全文需透過期刊付費取得