AI and Personalization

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL AI and Personalization 30 Pages Posted: 10 Jun 2022 See all articles by Omid RafieianOmid RafieianCornell University - Cornell Tech NYCHema YoganarasimhanUniversity of Washington Date Written: May 30, 2022 Abstract This paper reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies -- the Direct method, the Inverse Propensity Score estimator, and the Doubly Robust method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research. Keywords: Personalization, Machine Learning, AI, Consumer Welfare, Privacy, Fairness, Polarization Suggested Citation: Suggested Citation Rafieian, Omid and Yoganarasimhan, Hema, AI and Personalization (May 30, 2022). Available at SSRN: https://ssrn.com/abstract=4123356 Omid Rafieian (Contact Author) Cornell University - Cornell Tech NYC ( email ) 111 8th Avenue #302New York, NY 10011United States Hema Yoganarasimhan University of Washington ( email ) 481 Paccar HallSeattle, WA 98195United States HOME PAGE: http://faculty.washington.edu/hemay/ Download This Paper Open PDF in Browser Do you have a job opening that you would like to promote on SSRN? Place Job Opening Paper statistics Downloads 3 Abstract Views 15 PlumX Metrics Related eJournals Marketing Science eJournal Follow Marketing Science eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 1,015 PAPERS 2,428 Machine Learning eJournal Follow Machine Learning eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 388 PAPERS 4,353 Quantitative Marketing eJournal Follow Quantitative Marketing eJournal Subscribe to this fee journal for more curated articles on this topic FOLLOWERS 382 PAPERS 1,863 Feedback Feedback to SSRN Feedback (required) Email (required) Submit If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday. Submit a Paper Section 508 Text Only Pages SSRN Quick Links SSRN Solutions Research Paper Series Conference Papers Partners in Publishing Jobs & Announcements Newsletter Sign Up SSRN Rankings Top Papers Top Authors Top Organizations About SSRN SSRN Objectives Network Directors Presidential Letter Announcements Contact us FAQs Copyright Terms and Conditions Privacy Policy We use cookies to help provide and enhance our service and tailor content. To learn more, visit Cookie Settings. This page was processed by aws-apollo5 in 0.370 seconds