Artea (D): Discrimination through Algorithmic Bias in Targeting
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing-implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The exercises are designed such that the issues of algorithmic bias and discrimination would emerge inductively, "surprising" the students in the act of recommending a strategy that, inadvertently, is discriminating against customers who belong to minority groups. This is achieved via the combination of hands-on exercises, where students would make decisions based on data analyses and visualization, and in-class discussions, where students would defend their proposed strategies, discover the (discriminating) implications of those actions, and discuss possible solutions.
- प्रतिलिपि अधिकार:
- 2020 HBS
- Book Quality:
- Harvard Business Publishing
- Date of Addition:
- Business and Finance, Nonfiction,
- Usage Restrictions:
- This is a copyrighted book.
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