Brian Jabarian

HC
3papers
1citation
Novelty33%
AI Score33

3 Papers

99.9HCMay 29
AI Behavioral Science

Matthew O. Jackson, Qiaozhu Me, Stephanie W. Wang et al.

We outline a foundation for a new field of ``AI Behavioral Science,'' covering three perspectives. First, as AI becomes ubiquitous and is increasingly proprietary and opaque, it becomes vital to develop techniques for assessing AI behavior. We outline how tools developed to assess people's behaviors by social scientists can be used to assess and infer AI's behaviors biases, tendencies, and heuristics. Second, we also discuss how AI can change the ways in which we learn about human behavior. Beyond its computational power, AI offers new techniques for simulating, inferring, and predicting human behaviors that we outline and discuss. Third, as humans and AI are interacting in increasingly complex and intertwined systems, we need to understand the implications for the resulting economic and political outcomes. We outline issues that are increasingly pressing concerning the future of human-AI interactions and potential changes and disruptions that can ensue.

HCJun 30, 2024
Large Language Models for Behavioral Economics: Internal Validity and Elicitation of Mental Models

Brian Jabarian

In this article, we explore the transformative potential of integrating generative AI, particularly Large Language Models (LLMs), into behavioral and experimental economics to enhance internal validity. By leveraging AI tools, researchers can improve adherence to key exclusion restrictions and in particular ensure the internal validity measures of mental models, which often require human intervention in the incentive mechanism. We present a case study demonstrating how LLMs can enhance experimental design, participant engagement, and the validity of measuring mental models.

THApr 19, 2020
The Moral Burden of Ambiguity Aversion

Brian Jabarian

In their article, "Egalitarianism under Severe Uncertainty", Philosophy and Public Affairs, 46:3, 2018, Thomas Rowe and Alex Voorhoeve develop an original moral decision theory for cases under uncertainty, called "pluralist egalitarianism under uncertainty". In this paper, I firstly sketch their views and arguments. I then elaborate on their moral decision theory by discussing how it applies to choice scenarios in health ethics. Finally, I suggest a new two-stage Ellsberg thought experiment challenging the core of the principle of their theory. In such an experiment pluralist egalitarianism seems to suggest the wrong, morally and rationally speaking, course of action -- no matter whether I consider my thought experiment in a simultaneous or a sequential setting.