Thaler and Sunstein (2008) defined nudge, as "any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives." As can be seen from this definition, humans (or decision makers) and organizations (both government and private) use nudges to influence the behavior of target populations. The central idea is that small changes to the environment in which citizens make decisions, such as placing healthy food close to supermarket checkouts, rather than banning junk food, can achieve desirable changes in behavior. Thus, nudges are typically small changes to the environment that are easy and inexpensive to implement. On the other hand, nudging is defined as the "systematic and evidence-based development and implementation of nudges in creating behavior change." On the other hand, Wikipedia defines personalization as "tailoring a service or a product to accommodate specific individuals, sometimes tied to groups or segments of individuals. A wide variety of organizations use personalization to improve customer satisfaction, digital sales conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization is a key element in social media and recommender systems." Data driven approaches are increasingly being adopted in personalization and nudging tasks across a wide spectrum of applicaitons.
AI is becoming a big part of nudging and personalization, and this workshop seeks to explore the state of the art in AI based systems and applications of nudging and personalization. This workshop seeks to build a new community around AI for nudging and personalization and provide a platform for exploring the state of the art in AI/ML/DS based systems and applications of digital nudging and personalization. The intended audience for this workshop are researchers from academia, government, and domain sciences, and practitioners dealing with developing AI technologies that impact human behavior based on nudging theory and personalization.
Behavioral Science + AI
|Ranga Raju Vatsavai
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