200 citations · 865 across the 29 of their papers we have counts for
29 papers
Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge
Anna Kawakami, Luke Guerdan, Yanghuidi Cheng +6
A growing body of research has explored how to support humans in making better use of AI-based decision support, including via training and onboarding. Existing research has focuse…
Nip it in the Bud: Moderation Strategies in Open Source Software Projects and the Role of Bots
Jane Hsieh, Joselyn Kim, Laura Dabbish +1
Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and mo…
Organizational Bulk Email Systems: Their Role and Performance in Remote Work
Ruoyan Kong, Haiyi Zhu, Joseph A. Konstan
The COVID-19 pandemic has forced many employees to work from home. Organizational bulk emails now play a critical role to reach employees with central information in this work-from…
Shaping Online Dialogue: Examining How Community Rules Affect Discussion Structures on Reddit
Anna Fang, Wenjie Yang, Haiyi Zhu
Community rules play a key part in enabling or constraining the behaviors of members in online communities. However, little is unknown regarding whether and to what degree changing…
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs
Tongshuang Wu, Haiyi Zhu, Maya Albayrak +21
LLMs have shown promise in replicating human-like behavior in crowdsourcing tasks that were previously thought to be exclusive to human abilities. However, current efforts focus ma…
Designing Individualized Policy and Technology Interventions to Improve Gig Work Conditions
Jane Hsieh, Oluwatobi Adisa, Sachi Bafna +1
The gig economy is characterized by short-term contract work completed by independent workers who are paid to perform "gigs", and who have control over when, whether and how they c…
Seeing Seeds Beyond Weeds: Green Teaming Generative AI for Beneficial Uses
Logan Stapleton, Jordan Taylor, Sarah Fox +2
Large generative AI models (GMs) like GPT and DALL-E are trained to generate content for general, wide-ranging purposes. GM content filters are generalized to filter out content wh…
Recentering Validity Considerations through Early-Stage Deliberations Around AI and Policy Design
Anna Kawakami, Amanda Coston, Haiyi Zhu +2
AI-based decision-making tools are rapidly spreading across a range of real-world, complex domains like healthcare, criminal justice, and child welfare. A growing body of research…
Agent-based Simulation for Online Mental Health Matching
Yuhan Liu, Anna Fang, Glen Moriarty +2
Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key…
Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Services
Tzu-Sheng Kuo, Hong Shen, Jisoo Geum +4
Recent years have seen growing adoption of AI-based decision-support systems (ADS) in homeless services, yet we know little about stakeholder desires and concerns surrounding their…
Navigating Multi-Stakeholder Incentives and Preferences: Co-Designing Alternatives for the Future of Gig Worker Well-Being
Jane Hsieh, Miranda Karger, Lucas Zagal +1
Gig workers, and the products and services they provide, play an increasingly ubiquitous role in our daily lives. But despite growing evidence suggesting that worker well-being in…
Towards a Learner-Centered Explainable AI: Lessons from the learning sciences
Anna Kawakami, Luke Guerdan, Yang Cheng +8
In this short paper, we argue for a refocusing of XAI around human learning goals. Drawing upon approaches and theories from the learning sciences, we propose a framework for the l…
A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms
Amanda Coston, Anna Kawakami, Haiyi Zhu +2
Recent research increasingly brings to question the appropriateness of using predictive tools in complex, real-world tasks. While a growing body of work has explored ways to improv…
Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders
Logan Stapleton, Min Hun Lee, Diana Qing +5
Child welfare agencies across the United States are turning to data-driven predictive technologies (commonly called predictive analytics) which use government administrative data t…
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee +4
Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML practitioners assess and address unfairness in their systems. However, there has…
A Little Too Personal: Effects of Standardization versus Personalization on Job Acquisition, Work Completion, and Revenue for Online Freelancers
Jane Hsieh, Yili Hong, Gordon Burtch +1
As more individuals consider permanently working from home, the online labor market continues to grow as an alternative working environment. While the flexibility and autonomy of t…
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
Anna Kawakami, Venkatesh Sivaraman, Hao-Fei Cheng +7
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is cr…
A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms
Nil-Jana Akpinar, Manish Nagireddy, Logan Stapleton +4
Motivated by the growing importance of reducing unfairness in ML predictions, Fair-ML researchers have presented an extensive suite of algorithmic 'fairness-enhancing' remedies. Mo…
Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems
Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang +4
Recent work in fair machine learning has proposed dozens of technical definitions of algorithmic fairness and methods for enforcing these definitions. However, we still lack an und…
"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment
Dakuo Wang, Liuping Wang, Zhan Zhang +5
Artificial intelligence (AI) technology has been increasingly used in the implementation of advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential u…
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation
Hong Shen, Wesley Hanwen Deng, Aditi Chattopadhyay +3
Recently, there have been increasing calls for computer science curricula to complement existing technical training with topics related to Fairness, Accountability, Transparency, a…
Learning to Ignore: A Case Study of Organization-Wide Bulk Email Effectiveness
Ruoyan Kong, Haiyi Zhu, Joseph A. Konstan
Bulk email is a primary communication channel within organizations, with all-company emails and regular newsletters serving as a mechanism for making employees aware of policies an…
Factors Influencing Perceived Fairness in Algorithmic Decision-Making: Algorithm Outcomes, Development Procedures, and Individual Differences
Ruotong Wang, F. Maxwell Harper, Haiyi Zhu
Algorithmic decision-making systems are increasingly used throughout the public and private sectors to make important decisions or assist humans in making these decisions with real…
Race, Gender and Beauty: The Effect of Information Provision on Online Hiring Biases
Weiwen Leung, Zheng Zhang, Daviti Jibuti +5
We conduct a study of hiring bias on a simulation platform where we ask Amazon MTurk participants to make hiring decisions for a mathematically intensive task. Our findings suggest…