Search Results for author: Krzysztof Z. Gajos

Found 6 papers, 0 papers with code

Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning

no code implementations9 Mar 2024 Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Susan A. Murphy, Krzysztof Z. Gajos

Across two experiments (N=316 and N=964), our results demonstrated that people interacting with policies optimized for accuracy achieve significantly better accuracy -- and even human-AI complementarity -- compared to those interacting with any other type of AI support.

Decision Making Offline RL +1

Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning

no code implementations11 Feb 2022 Krzysztof Z. Gajos, Lena Mamykina

We hypothesize that learning gains in this condition were due to deeper engagement with explanations needed to arrive at the decisions.

To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making

no code implementations19 Feb 2021 Zana Buçinca, Maja Barbara Malaya, Krzysztof Z. Gajos

To audit our work for intervention-generated inequalities, we investigated whether our interventions benefited equally people with different levels of Need for Cognition (i. e., motivation to engage in effortful mental activities).

Decision Making

Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems

no code implementations22 Jan 2020 Zana Buçinca, Phoebe Lin, Krzysztof Z. Gajos, Elena L. Glassman

The results of our experiments demonstrate that evaluations with proxy tasks did not predict the results of the evaluations with the actual decision-making tasks.

Decision Making Explainable Artificial Intelligence (XAI)

BubbleView: an interface for crowdsourcing image importance maps and tracking visual attention

no code implementations16 Feb 2017 Nam Wook Kim, Zoya Bylinskii, Michelle A. Borkin, Krzysztof Z. Gajos, Aude Oliva, Fredo Durand, Hanspeter Pfister

In this paper, we present BubbleView, an alternative methodology for eye tracking using discrete mouse clicks to measure which information people consciously choose to examine.

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