96 citations · 388 across the 37 of their papers we have counts for
23 papers · 1 filter
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…
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…
"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…
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…
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…
"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…
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…
The State of Pilot Study Reporting in Crowdsourcing: A Reflection on Best Practices and Guidelines
Jonas Oppenlaender, Tahir Abbas, Ujwal Gadiraju
Pilot studies are an essential cornerstone of the design of crowdsourcing campaigns, yet they are often only mentioned in passing in the scholarly literature. A lack of details sur…
Power-up! What Can Generative Models Do for Human Computation Workflows?
Garrett Allen, Gaole He, Ujwal Gadiraju
We are amidst an explosion of artificial intelligence research, particularly around large language models (LLMs). These models have a range of applications across domains like medi…
Generating Process-Centric Explanations to Enable Contestability in Algorithmic Decision-Making: Challenges and Opportunities
Mireia Yurrita, Agathe Balayn, Ujwal Gadiraju
Human-AI decision making is becoming increasingly ubiquitous, and explanations have been proposed to facilitate better Human-AI interactions. Recent research has investigated the p…
Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems
Gaole He, Lucie Kuiper, Ujwal Gadiraju
The dazzling promises of AI systems to augment humans in various tasks hinge on whether humans can appropriately rely on them. Recent research has shown that appropriate reliance i…
Using Conversational Artificial Intelligence to Support Children's Search in the Classroom
Garrett Allen, Jie Yang, Maria Soledad Pera +1
We present pathways of investigation regarding conversational user interfaces (CUIs) for children in the classroom. We highlight anticipated challenges to be addressed in order to…
Revealing the Role of User Moods in Struggling Search Tasks
Luyan Xu, Xuan Zhou, Ujwal Gadiraju
User-centered approaches have been extensively studied and used in the area of struggling search. Related research has targeted key aspects of users such as user satisfaction or fr…
Detecting, Understanding and Supporting Everyday Learning in Web Search
Ran Yu, Ujwal Gadiraju, Stefan Dietze
Web search is among the most ubiquitous online activities, commonly used to acquire new knowledge and to satisfy learning-related objectives through informational search sessions.…
Predicting User Knowledge Gain in Informational Search Sessions
Ran Yu, Ujwal Gadiraju, Peter Holtz +3
Web search is frequently used by people to acquire new knowledge and to satisfy learning-related objectives. In this context, informational search missions with an intention to obt…