Workshop Schedule

  1. Introduction (1 pm - 1:20 pm)


  2. Keynote (1:25 pm - 2:10 pm)

    3. Jiqun Liu

    Keynote Topic: Bias-Aware User Modeling and Human-Centered Fairness Evaluation in Search and Recommendation.


    Abstract

    As artificial intelligence (AI) assisted search and recommender systems have become ubiquitous in workplaces and everyday lives, understanding and accounting for fairness has gained increasing attention in the design and evaluation of such systems. While there is a growing body of computing research on measuring system fairness and biases associated with data and algorithms, the impact of human biases that go beyond traditional machine learning (ML) pipelines still remain understudied. Our studies seek to develop a two-sided fairness framework that not only characterizes data and algorithmic biases, but also highlights the cognitive and perceptual biases that may exacerbate system biases and lead to unfair decisions. Within the framework, we also analyze the interactions between human and system biases in search and recommendation episodes. Built upon the two-sided framework, our research synthesizes intervention and intelligent nudging strategies applied in cognitive and algorithmic debiasing, and also proposes novel goals and measures for evaluating the performance of systems in addressing and proactively mitigating the risks associated with biases in data, algorithms, and bounded rationality. Our research uniquely integrates the insights regarding human biases and system biases into a cohesive framework and extends the concept of fairness from human-centered perspective. The extended fairness framework better reflects the challenges and opportunities in users' interactions with search and recommender systems of varying modalities. Adopting the two-sided approach in information system design has the potential to enhancing both the effectiveness in online debiasing and the usefulness to boundedly rational users engaging in information-intensive decision-making.

    Short bio

    Jiqun Liu is currently an assistant professor of data science and affiliated assistant professor of psychology at the University of Oklahoma. He directs the OU human-computer interaction and recommendation (HCIR) Lab where he advises students from different levels and backgrounds on intelligent search and recommendation, human-centered computing, and ethical AI research. His current research program focuses on the intersection of human-AI interaction, machine learning, and cognitive psychology. His work applies the knowledge learned about people interacting with information in user modeling, adaptive search recommendation, bias-aware system evaluation and intelligent nudging. His recent studies have been supported by grants from National Science Foundation (NSF) and have been published at leading computer and data science venues. His recent work on user modeling, interface design, and human-centered system evaluation has also been presented in the research monograph entitled “A behavioral economics approach to interactive information retrieval: Understanding and supporting boundedly rational users”, published by Springer Nature in March 2023.

  3. Lightning Talks (2:15 pm - 2:45 pm)

      4. Session 1 - Cognitive Biases in Human-AI Collaboration

    • Understanding and Mitigating Cognitive Biases in Human-AI Collaboration. Tobias Grundgeiger (Julius-Maximilians-Universität Würzburg). Onsite presentation. [Paper]
    • Designing Agency-Preserving Reflection Systems to Support Reappraisal of Social Biases. Seraphina Yong (University of Minnesota). Onsite presentation. [Paper]
    • Understanding and handling cognitive biases in de-biasing: Insights from applied AI research and data quality management. Simon David Hirsbrunner (University of Tübingen), Lou Therese Brandner (University of Tübingen). Onsite presentation. [Paper]
    • The Role of Bounded Rationality in Human-AI Collaboration. Harmanpreet Kaur (University of Minnesota). Onsite presentation. [Paper]
    • Cognitive Bias in Conversational Information Access: Challenges and Opportunities. Kaixin Ji (RMIT University), Sachin Pathiyan Cherumanal (RMIT University). Virtual presentation. [Paper] [Video]
    • Understanding Roles of Cognitive Biases in Large Language Model-Supported Knowledge-based Tasks. Qingxiaoyang Zhu (University of California, Davis), Jingchao Fang (University of California, Davis), and Jingxian Liao (University of California, Davis). Onsite presentation. [Paper]
    • Critically Speculating Interventions for Addressing Cognitive Biases when Consuming (Mis)Information. Gionnieve Lim (Singapore University of Technology and Design), Simon T. Perrault (Singapore University of Technology and Design). Onsite presentation. [Paper]

      • Session 2 - Bias Detection and Mitigation in AI Systems

    • BiasEye: A Bias-Aware Real-time Interactive Material Screening System for Impartial Candidate Assessment. Qianyu Liu (Shanghaitech University), Haoran Jiang (Shanghaitech University), Qiushi Han (Sun Yat-Sen University), Zhenhui Peng (Sun Yat-sen University), Quan Li (Shanghaitech University). Virtual presentation. [Paper]
    • What the Annotator Does Not Know, Can Harm Us. Sanjana Gautam (Pennsylvania State University). Onsite presentation. [Paper]
    • Is AI Mimicry Leading to Disappointment? James Simpson (Macquarie University). Onsite presentation. [Paper]
    • BIASeD: Bringing Irrationality into Automated System Design. Aditya Gulati (ELLIS Alicante), Miguel Angel Lozano (Universidad de Alicante), Bruno Lepri (Fondazione Bruno Kessler), Nuria Oliver (ELLIS Alicante). Virtual presentation. [Paper]

      • Session 3 - Gender Bias and Social Interaction with AI

    • Exploring Gender Biases in Language Patterns of Human-Conversational Agent Conversations. Weizi Liu (University of Illinois at Urbana-Champaign). Virtual presentation. [Paper]
    • Exploring the Feasibility and Implications of Digital Work-Spouses. Thomas Rasser (TU Wien). Virtual presentation. [Paper]
    • Towards Measuring Sensitivity of Psychometrics in Crowdsourcing Tasks: Engaging with Fact-checked Content Online. Stanislaus Krisna (RMIT University), Danula Hettiachchi (RMIT University), and Damiano Spina (RMIT University). Virtual presentation. [Paper] [Video]

  4. Brainstorming Activity and Knowledge Synthesis (3:00 pm - 4:50 pm)

    • Brief participants about tasks (3:00 pm - 3:05 pm)
    • Brain Storming 1 (3:05 pm - 3:30 pm)
    • Knowledge Synthesis (3:30 pm - 3:55 pm)
    • Break (3:55 pm - 4:00 pm)
    • Brain Storming 2 (4:00 pm - 4:25 pm)
    • Knowledge Synthesis (4:25 pm - 4:50 pm)

  5. Closing Remarks (4:50 pm - 5:00 pm)

Hybrid Participation

General Info

  1. This workshop allows both in-person and virtual participation. Please refer below to in-person and remote participation.
  2. Registration: Please register with CSCW conference. The registration type differs form in-person participation and remote participation.
  3. The schedule of our workshop is available here.
  4. For ease of communication, we use Slack to track your comments and questions in each session. Please join our Slack channel, which will be available soon.
  5. Q&A Sessions: For each session in our workshop, please leave your comments / questions in the corresponding slack channel / Zoom message.
  6. All accepted workshop papers and preview videos will be released on our website.

In-Person Participation

  1. The workshop will be colocated with CSCW 2023 at the Hyatt Regency Minneapolis Hotel in Minneapolis, MN, USA.
  2. Health and Safety: Comply with local health and safety guidelines related to COVID-19 or any other relevant concerns. Implement appropriate measures such as social distancing, mandatory mask-wearing, hand sanitization stations, or vaccination requirements, as necessary.
  3. Presentation Setup: Test the setup in advance to ensure everything is functioning properly.

Remote Participation

  1. Online platform: the virtual session is mainly hosted on Zoom, while we use Slack for asynchronous communication and regular chat.
  2. Technical Requirements: participants are encouraged to join the workshop from a quiet and distraction-free environment. In the meeting, please ensure that you have access to a stable internet connection, a webcam, and a microphone.