Krzysztof Z. Gajos

schoolHarvard Universitybar_chart#674 Global Rank

Total Papers

HCI Rank

#674

Research Areas

Years Active

Recent Publications

"It just requires so much more creativity": Barriers and Workarounds to Gathering Information for AI Contestation

Gathering information about AI systems is essential for contesting their use; it forms the basis of arguments about how AI is causing harm. Information thus plays a central role for advocates like lawyers, journalists, and auditors contesting harmful AI systems. However, there is little systematic understanding of how…

CHI '26CorrespondingAI Ethics, Fairness & Accountability +2

Funding AI for Good: A Call for Meaningful Engagement

Artificial Intelligence for Social Good (AI4SG) is a growing area that explores AI's potential to address social issues, such as public health. Yet prior work has shown limited evidence of its tangible benefits for intended communities, and projects frequently face real-world deployment and sustainability challenges.…

CSCW '255th+ AuthorAI-Assisted Healthcare

To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events

AI-enabled decision-support systems aim to help medical providers rapidly make decisions with limited information during medical emergencies. A critical challenge in developing these systems is supporting providers in interpreting the system output to make optimal treatment decisions. In this study, we designed and ev…

IUI '25CorrespondingExplainable AI (XAI) +1

Counterfactual Explanations May Not Be the Best Algorithmic Recourse Approach

Algorithmic recourse is a rapidly developing subfield in explainable AI (XAI) concerned with providing individuals subject to adverse high-stakes algorithmic outcomes with explanations indicating how to reverse said outcomes. While XAI research in the machine learning community doesn't confine itself to counterfactual…

CSCW '24CorrespondingSession 4e: Navigating AI Ethical Challenges

"Come to us first": Centering Community Organizations in Artificial Intelligence for Social Good Partnerships

Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of scholarship and applied programs exploring AI technologies' potential to tackle social issues, emphasizing interdisciplinary partnerships with community organizations, such as non-profits and international organizations. What are the need…

CHI '24CorrespondingAI Ethics, Fairness & Accountability +2

Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public Services

Policymakers have established that the ability to contest decisions made by or with algorithms is core to responsible artificial intelligence (AI). However, there has been a disconnect between research on contestability of algorithms, and what the situated practice of contestation looks like in contexts across the wor…

CHI '24CorrespondingConversational Chatbots +3

Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support

LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support for this demographic. We interviewed 18 LGBTQ+ and 13 non-LGBTQ+ participant…

CSCW '23CorrespondingSocial Support II

Evaluating Similarity Variables for Peer Matching in Digital Health Storytelling

Peer matching can enhance the impact of social health technologies. By matching similar peers, online health communities can optimally facilitate social modeling that supports positive health attitudes and moods. However, little work has examined how to operationalize similarities in digital health tools, thus limitin…

IUI '221st AuthorExplainable AI (XAI) +1

Do people engage cognitively with AI? Impact of AI assistance on incidental learning

When people receive advice while making difficult decisions, they often make better decisions in the moment and also increase their knowledge in the process. However, such incidental learning can only occur when people cognitively engage with the information they receive and process this information carefully and thou…

CHI '22CorrespondingAlgorithmic Fairness & Bias +1

Not Just a Preference: Reducing Biased Decision-making on Dating Websites

As dating websites are becoming an essential part of how people meet intimate and romantic partners, it is vital to design these systems to be resistant to, or at least do not amplify, bias and discrimination. Instead, the results of our online experiment with a simulated dating website, demonstrate that popular datin…

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