96 citations · 388 across the 37 of their papers we have counts for
39 papers
Beyond the Traceback: Using LLMs for Adaptive Explanations of Programming Errors
Alexandru-Radu Moraru, Shreyan Biswas, Ujwal Gadiraju
Programming error messages are critical for software development, yet they remain difficult for novice programmers to interpret. While Large Language Models (LLMs) can rewrite thes…
The Belief Update Gate: Separating Inertia from Learning in Human-AI Interaction
Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju
Repeated human-AI interaction is often analyzed through pooled belief-updating slopes: users observe AI successes and failures, revise reported beliefs in the feedback-consistent d…
AI at the Front Lines of Platform Governance: Using LLMs to Support Illegal Content Reporting under the Digital Services Act
Marie-Therese Sekwenz, Shreyan Biswas, Rita Hermann-Gsenger +1
Illegal content reporting mechanisms are a key technical and organizational measure through which online platforms address illegal content under the European Union Digital Services…
Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systems
Susanne Gaube, Markus Langer, Tim Miller +17
The use of Artificial Intelligence (AI) in high-risk, decision-making scenarios presents technical, safety, and normative challenges; problems that may only be ameliorated by human…
The Data-Dollars Tradeoff: Privacy Harms vs. Economic Risk in Personalized AI Adoption
Alexander Erlei, Tahir Abbas, Kilian Bizer +1
Privacy concerns significantly impact AI adoption, yet little is known about how information environments shape user responses to data leak threats. We conducted a 2 x 3 between-su…
Belief Updating and Delegation in Multi-Task Human-AI Interaction: Evidence from Controlled Simulations
Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju
Large language models (LLMs) increasingly support heterogeneous tasks within a single interface, requiring users to form, update, and act upon beliefs about one system across domai…
When Life Gives You AI, Will You Turn It Into A Market for Lemons? Understanding How Information Asymmetries About AI System Capabilities Affect Market Outcomes and Adoption
Alexander Erlei, Federico Cau, Radoslav Georgiev +3
AI consumer markets are characterized by severe buyer-supplier market asymmetries. Complex AI systems can appear highly accurate while making costly errors or embedding hidden defe…
Incentive-Tuning: Understanding and Designing Incentives for Empirical Human-AI Decision-Making Studies
Simran Kaur, Sara Salimzadeh, Ujwal Gadiraju
AI has revolutionised decision-making across various fields. Yet human judgement remains paramount for high-stakes decision-making. This has fueled explorations of collaborative de…
From SERPs to Sound: How Search Engine Result Pages and AI-generated Podcasts Interact to Influence User Attitudes on Controversial Topics
Junjie Wang, Gaole He, Alisa Rieger +1
Compared to search engine result pages (SERPs), AI-generated podcasts represent a relatively new and relatively more passive modality of information consumption, delivering narrati…
"Label from Somewhere": Reflexive Annotating for Situated AI Alignment
Anne Arzberger, Celine Offerman, Ujwal Gadiraju +2
AI alignment relies on annotator judgments, yet annotation pipelines often treat annotators as interchangeable, obscuring how their social position shapes annotation. We introduce…
RecQuest: Towards Estimating User Domain Knowledge in Conversational Recommender Systems
Ivica Kostric, Ujwal Gadiraju, Krisztian Balog
The ideal conversational recommender system (CRS) acts like a savvy salesperson, adapting its language and suggestions to a user's expertise level. However, most current systems tr…
Should We Tailor the Talk? Understanding the Impact of Conversational Styles on Preference Elicitation in Conversational Recommender Systems
Ivica Kostric, Krisztian Balog, Ujwal Gadiraju
Conversational recommender systems (CRSs) provide users with an interactive means to express preferences and receive real-time personalized recommendations. The success of these sy…
"Even explanations will not help in trusting [this] fundamentally biased system": A Predictive Policing Case-Study
Siddharth Mehrotra, Ujwal Gadiraju, Eva Bittner +3
In today's society, where Artificial Intelligence (AI) has gained a vital role, concerns regarding user's trust have garnered significant attention. The use of AI systems in high-r…
Quo Vadis, HCOMP? A Review of 12 Years of Research at the Frontier of Human Computation and Crowdsourcing
Jonas Oppenlaender, Ujwal Gadiraju, Simo Hosio
The field of human computation and crowdsourcing has historically studied how tasks can be outsourced to humans. However, many tasks previously distributed to human crowds can toda…
Mind the Gap! Choice Independence in Using Multilingual LLMs for Persuasive Co-Writing Tasks in Different Languages
Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju
Recent advances in generative AI have precipitated a proliferation of novel writing assistants. These systems typically rely on multilingual large language models (LLMs), providing…
Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant
Gaole He, Gianluca Demartini, Ujwal Gadiraju
Since the explosion in popularity of ChatGPT, large language models (LLMs) have continued to impact our everyday lives. Equipped with external tools that are designed for a specifi…
Is Conversational XAI All You Need? Human-AI Decision Making With a Conversational XAI Assistant
Gaole He, Nilay Aishwarya, Ujwal Gadiraju
Explainable artificial intelligence (XAI) methods are being proposed to help interpret and understand how AI systems reach specific predictions. Inspired by prior work on conversat…
Fine-Grained Appropriate Reliance: Human-AI Collaboration with a Multi-Step Transparent Decision Workflow for Complex Task Decomposition
Gaole He, Patrick Hemmer, Michael Vössing +2
In recent years, the rapid development of AI systems has brought about the benefits of intelligent services but also concerns about security and reliability. By fostering appropria…
To Err Is AI! Debugging as an Intervention to Facilitate Appropriate Reliance on AI Systems
Gaole He, Abri Bharos, Ujwal Gadiraju
Powerful predictive AI systems have demonstrated great potential in augmenting human decision making. Recent empirical work has argued that the vision for optimal human-AI collabor…
"Hi. I'm Molly, Your Virtual Interviewer!" -- Exploring the Impact of Race and Gender in AI-powered Virtual Interview Experiences
Shreyan Biswas, Ji-Youn Jung, Abhishek Unnam +3
The persistent issue of human bias in recruitment processes poses a formidable challenge to achieving equitable hiring practices, particularly when influenced by demographic charac…
From Stem to Stern: Contestability Along AI Value Chains
Agathe Balayn, Yulu Pi, David Gray Widder +9
This workshop will grow and consolidate a community of interdisciplinary CSCW researchers focusing on the topic of contestable AI. As an outcome of the workshop, we will synthesize…
Everything We Hear: Towards Tackling Misinformation in Podcasts
Sachin Pathiyan Cherumanal, Ujwal Gadiraju, Damiano Spina
Advances in generative AI, the proliferation of large multimodal models (LMMs), and democratized open access to these technologies have direct implications for the production and d…
Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain
Agathe Balayn, Lorenzo Corti, Fanny Rancourt +2
Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them. Existing works fall short of accounting for t…
An Empirical Exploration of Trust Dynamics in LLM Supply Chains
Agathe Balayn, Mireia Yurrita, Fanny Rancourt +2
With the widespread proliferation of AI systems, trust in AI is an important and timely topic to navigate. Researchers so far have largely employed a myopic view of this relationsh…