Index Catalog // ScholarsArchive@OSU

Creator:: Anderson, Andrew A.
Abstract:: How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
Resource Type:: Masters Thesis
Full Text:: AN ABSTRACT OF THE THESIS OF Andrew A. Anderson for the

Creator:: Mendez, Christopher
Abstract:: How can software practitioners assess whether their software supports diverse users? Although there are empirical processes that can be used to find “inclusivity bugs” piecemeal, what is often needed is a systematic inspection method to assess software’s support for diverse populations. To help fill this gap, this thesis introduces InclusiveMag,...
Resource Type:: Masters Thesis
Full Text:: Abstract approved: ______________________________________________________ Margaret M. Burnett

Creator:: Pandya, Bhargav Chandravadan
Abstract:: Complex information environments are often organized as hierarchies. However, computational models of Information Foraging Theory (IFT) have almost entirely ignored this fact. Models and tools for predicting programmer navigations have ignored people’s foraging behavior across hierarchies —called hierarchical foraging. Without modeling hierarchical foraging, our ability to build tools to support...
Resource Type:: Masters Thesis
Full Text:: : ______________________________________________________ Margaret M. Burnett Complex information environments are often organized as hierarchies

Creator:: Dikkala, Rupika
Abstract:: "What’s wrong with this AI?" Explainable AI (XAI) researchers are moving beyond explaining an AI’s actions, to helping users detect an AI’s failures. However this detection may not be enough—for actionability, we often need to pinpoint which part failed. We investigate how AAR/AI, a structured assessment process, supports users with...
Resource Type:: Masters Thesis
Full Text:: : Margaret M. Burnett “What’s wrong with this AI?” Explainable AI (XAI) researchers are moving beyond ex

Creator:: Yang, Sherry
Abstract:: We believe concreteness, direct manipulation and responsiveness in a visual programming language increase its usefulness. However, these characteristics present a challenge in generalizing programs for reuse, especially when concrete examples are used as one way of achieving concreteness. In this thesis, we present a technique to solve this problem by...
Resource Type:: Dissertation
Full Text:: Representation. Margaret M. Burnett Abstract approved: We believe concreteness, direct manipulation and

Creator:: Agarwal, Puja
Abstract:: Emerging research shows that individual differences in how people use technology sometimes cluster by socioeconomic status (SES) and that when technology is not socioeconomically inclusive, low-SES individuals may abandon it. To understand how to improve technology’s SES-inclusivity, we present a multi-phase case study on SocioEconomicMag (SESMag), an emerging inspection method...
Resource Type:: Masters Thesis
Full Text:: Abstract approved: ______________________________________________________ Margaret M Burnett Anita Sarma

Creator:: Dodge, Jonathan E.
Abstract:: Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
Resource Type:: Dissertation
Full Text:: taught me that learning is a great pastime; Andrew Anderson, my colleague in PhD trials and tribulations

ScholarsArchive@OSU