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"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…

Sohini Upadhyay et al.Harvard University

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.…

Hongjin Lin et al.Harvard University

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…

Angela Mastrianni et al.Drexel University

AI-Assisted Healthcare

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…

Sohini Upadhyay et al.Harvard University

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"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…

Hongjin Lin et al.Harvard University

Session 4e: Navigating AI Ethical Challenges

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…

Naveena Karusala et al.University Of Washington

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…

Zilin Ma et al.Bucknell University

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…

Herman Saksono et al.Northeastern University

Social Support II

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…

Krzysztof Z. Gajos et al.Harvard University

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…

Zilin Ma et al.Bucknell University

"I think we know more than our doctors": How primary caregivers manage care teams with limited disease-related expertise

Healthcare providers play a critical role in the management of a chronic illness by providing education about the disease, recommending treatment options, and developing care plans. However, when managing a rare disease, patients and their primary caregivers often work with healthcare systems that lack the infrastruct…

Maia Jacobs et al.Northwestern University

Health and Caregiving

Automatically Analyzing Brainstorming Language Behavior with Meeter

Studying groups in such complex settings as group brainstorming would be much more informative if there were better tools to study them. Language both influences and indicates group behavior, and we need tools that let us study the content of what is communicated to understand how such dialogue acts as information sha…

Bernd Huber et al.Harvard University

Groups and creativity

Paper Title	Authors	Research Topics
"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…	SU Sohini Upadhyay et al.Harvard University
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.…	HL Hongjin Lin et al.Harvard University
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…	AM Angela Mastrianni et al.Drexel University	AI-Assisted Healthcare
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…	SU Sohini Upadhyay et al.Harvard University
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
"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…	HL Hongjin Lin et al.Harvard University	Session 4e: Navigating AI Ethical Challenges
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…	NK Naveena Karusala et al.University Of Washington
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…	ZM Zilin Ma et al.Bucknell University
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…	HS Herman Saksono et al.Northeastern University	Social Support II
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…	KG Krzysztof Z. Gajos et al.Harvard University
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…	ZM Zilin Ma et al.Bucknell University
"I think we know more than our doctors": How primary caregivers manage care teams with limited disease-related expertise Healthcare providers play a critical role in the management of a chronic illness by providing education about the disease, recommending treatment options, and developing care plans. However, when managing a rare disease, patients and their primary caregivers often work with healthcare systems that lack the infrastruct…	MJ Maia Jacobs et al.Northwestern University	Health and Caregiving
emoji_events Automatically Analyzing Brainstorming Language Behavior with Meeter Studying groups in such complex settings as group brainstorming would be much more informative if there were better tools to study them. Language both influences and indicates group behavior, and we need tools that let us study the content of what is communicated to understand how such dialogue acts as information sha…	BH Bernd Huber et al.Harvard University	Groups and creativity