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Towards More Task-Generalized And Explainable Ai Through Psychometrics, Alec Braynen Nov 2022

Towards More Task-Generalized And Explainable Ai Through Psychometrics, Alec Braynen

USF Tampa Graduate Theses and Dissertations

In this work, we propose that adopting the methods, principles, and guidelines of the field of psychometrics can help the Artificial Intelligence (AI) community to build more task-generalizable and explainable AI. Three arguments are presented and explored. These arguments are that psychometrics can help by providing 1) a framework for formulating better datasets, 2) psychometric AI data that can lead to models of generalization in AI, and 3) explainable AI through more informative evaluations.

A review of psychometrics and psychological generalization is performed, along with an overview of evaluation, generalization, and explainability in AI. Various ideas are presented throughout for …


Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana Jun 2021

Data-Driven Studies On Social Networks: Privacy And Simulation, Yasanka Sameera Horawalavithana

USF Tampa Graduate Theses and Dissertations

Social media datasets are fundamental to understanding a variety of phenomena, such as epidemics, adoption of behavior, crowd management, and political uprisings. At the same time, many such datasets capturing computer-mediated social interactions are recorded nowadays by individual researchers or by organizations. However, while the need for real social graphs and the supply of such datasets are well established, the flow of data from data owners to researchers is significantly hampered by privacy risks: even when humans’ identities are removed, or data is anonymized to some extent, studies have proven repeatedly that re-identifying anonymized user identities (i.e., de-anonymization) is doable …