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Human-Centered AI (HCAI) is an emerging discipline that aims to create AI systems that amplify [46,45] and augment [47] human abilities and preserve human control in order to make AI partnerships more productive, enjoyable, and fair [19]. Our workshop aims to bring together researchers and practitioners from the NeurIPS and HCI communities and others with convergent interests in HCAI.With an emphasis on diversity and discussion, we will explore research questions that stem from the increasingly wide-spread usage of machine learning algorithms across all areas of society, with a specific focus on understanding both technical and design requirements for HCAI systems, as well as how to evaluate the efficacy and effects of HCAI systems
Mon 7:00 a.m. - 7:35 a.m.
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Welcome, introductions of 40 people, plan for the day
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Discussion
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SlidesLive Video » |
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Mon 7:35 a.m. - 7:55 a.m.
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Keynote:: Cynthia Rudin
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Keynote
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SlidesLive Video » |
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Mon 7:55 a.m. - 8:05 a.m.
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Discussion of keynote
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Discussion
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Mon 8:05 a.m. - 8:10 a.m.
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XAI:: From Human Centered to Interactionist Artificial Intelligence
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Panel Speaker
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SlidesLive Video » |
Andrea Campagner 🔗 |
Mon 8:10 a.m. - 8:15 a.m.
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XAI:: Explainability Pitfalls: Beyond Dark Patterns in Explainable AI
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Panel Speaker
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SlidesLive Video » |
Mark Riedl · Upol Ehsan 🔗 |
Mon 8:15 a.m. - 8:20 a.m.
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XAI:: Beware of the Ostrich Policy: End-Users’ Perceptions Towards Data Transparency and Control
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Panel Speaker
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SlidesLive Video » |
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Mon 8:20 a.m. - 8:25 a.m.
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XAI:: Expose Uncertainty, Instill Distrust, Avoid Explanations: Towards Ethical Guidelines for AI
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Panel Speaker
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SlidesLive Video » |
Claudio Pinhanez 🔗 |
Mon 8:25 a.m. - 8:40 a.m.
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Discussion of panel
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Discussion
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SlidesLive Video » |
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Mon 8:40 a.m. - 8:50 a.m.
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Break
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Mon 8:50 a.m. - 9:10 a.m.
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Keynote:: Barbara Poblete
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Keynote
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SlidesLive Video » |
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Mon 9:10 a.m. - 9:20 a.m.
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Discussion of keynote
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Discussion
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Mon 9:20 a.m. - 9:25 a.m.
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Methods:: Human-AI Collaboration for Experimental Design
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Panel Speaker
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SlidesLive Video » |
Nishtha N. Vaidya 🔗 |
Mon 9:25 a.m. - 9:30 a.m.
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Methods:: How Can Human-Centered Design Shape Data-Centric AI?
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Panel Speaker
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SlidesLive Video » |
Hariharan Subramonyam 🔗 |
Mon 9:30 a.m. - 9:35 a.m.
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Methods:: Stakeholder Participation in AI: Beyond “Add Diverse Stakeholders and Stir”
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Panel Speaker
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SlidesLive Video » |
Qian Yang · Fernando Delgado · Stephen Yang · Michael Madaio 🔗 |
Mon 9:35 a.m. - 9:40 a.m.
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Methods:: Human-centered Evaluation of Dynamic Content
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Panel Speaker
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SlidesLive Video » |
Johannes Schleith 🔗 |
Mon 9:40 a.m. - 9:55 a.m.
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Discussion of panel
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Discussion
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SlidesLive Video » |
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Mon 9:55 a.m. - 10:25 a.m.
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Meal
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Mon 10:25 a.m. - 10:45 a.m.
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Keynote:: Wendy Mackay
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Keynote
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SlidesLive Video » |
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Mon 10:45 a.m. - 10:55 a.m.
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Discussion of keynote
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Discussion
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Mon 10:55 a.m. - 11:00 a.m.
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H+AI:: Modeling Complementarity in Human-AI Collaboration
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Panel Speaker
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SlidesLive Video » |
Hernisa Kacorri 🔗 |
Mon 11:00 a.m. - 11:05 a.m.
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H+AI:: Knowledge Imbalance in AI-Assisted Decision-Making: Collaborating with Non-experts
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Panel Speaker
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SlidesLive Video » |
Catalina Gomez Caballero 🔗 |
Mon 11:05 a.m. - 11:10 a.m.
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H+AI:: Developing Human-Centered Artificial Intelligence through cognitive engineering
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Panel Speaker
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SlidesLive Video » |
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Mon 11:10 a.m. - 11:15 a.m.
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H+AI:: Exploring the Dark Side of Human-AI Interaction
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Panel Speaker
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SlidesLive Video » |
Andrea Rezzani 🔗 |
Mon 11:15 a.m. - 11:30 a.m.
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Discussion of panel
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Discussion
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SlidesLive Video » |
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Mon 11:30 a.m. - 11:40 a.m.
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Break
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Mon 11:40 a.m. - 12:00 p.m.
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Keynote:: Cecilia Aragon
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Keynote
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SlidesLive Video » |
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Mon 12:00 p.m. - 12:10 p.m.
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Discussion of keynote
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Discussion
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Mon 12:10 p.m. - 12:15 p.m.
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Ethics: Can Machine Learning be Moral?
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Panel Speaker
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SlidesLive Video » |
Irina Shklovski · Miguel Sicart 🔗 |
Mon 12:15 p.m. - 12:20 p.m.
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Ethics:: Supporting human flourishing by ensuring human involvement in AI systems
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Panel Speaker
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SlidesLive Video » |
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Mon 12:20 p.m. - 12:25 p.m.
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Ethics:: Improving Ethical Outcomes with Machine-in-the-Loop: Broadening Human Understanding of Data Annotations
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Panel Speaker
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SlidesLive Video » |
Ashis Kumer Biswas · Geeta Verma 🔗 |
Mon 12:25 p.m. - 12:30 p.m.
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Ethics:: The Equity Framework
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Panel Speaker
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SlidesLive Video » |
Keziah Naggita · Julius Aguma 🔗 |
Mon 12:30 p.m. - 12:45 p.m.
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Discussion of panel
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Discussion
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SlidesLive Video » |
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Mon 12:45 p.m. - 12:55 p.m.
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Break
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Mon 12:55 p.m. - 1:00 p.m.
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Fairness:: Individuality in Human-Centered AI
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Panel Speaker
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SlidesLive Video » |
Angel Hsing-Chi Hwang 🔗 |
Mon 1:00 p.m. - 1:05 p.m.
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Fairness:: Assessing Fairness in Practice: AI Teams’ Processes, Challenges, and Needs for Support
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Panel Speaker
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SlidesLive Video » |
Michael Madaio · Hariharan Subramonyam · Jennifer Wortman Vaughan 🔗 |
Mon 1:05 p.m. - 1:10 p.m.
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Fairness:: P4AI: Approaching AI Ethics through Principlism
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Panel Speaker
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SlidesLive Video » |
Mahdi Hosseini · Konstantinos N Plataniotis 🔗 |
Mon 1:10 p.m. - 1:15 p.m.
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Fairness:: Fairness in Practice: Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
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Panel Speaker
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SlidesLive Video » |
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Mon 1:15 p.m. - 1:30 p.m.
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Discussion of panel
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Discussion
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SlidesLive Video » |
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Mon 1:30 p.m. - 2:00 p.m.
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Meal
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Mon 2:00 p.m. - 3:00 p.m.
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Ethics:: Addressing Privacy Threats from Machine Learning
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Poster
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Mary Anne Smart 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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Ethics:: From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: Interpreting Voice Assistant Interaction Quality From Unprompted User Feedback
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Poster
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Pragati Verma 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: Switchboard: Automated News Q&A With an Editor in the Loop
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: Improving mathematical questioning in teacher training
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Poster
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Debajyoti Datta 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: Human-Centered AI: The Case of Machine Translation for Cross-Lingual Teamwork
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: Personalized musically induced emotions of not-so-popular Colombian music
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Poster
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Juan Sebastián S. Gómez-Cañón 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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H+AI:: The Key to an Effective AI-Powered Digital Pathology Establishing a Symbiotic Workflow between Pathologists and Machine
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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Methods:: An Interactive Visualization Tool for Understanding Active Learning
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Poster
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Martin Ester · Jialin Lu 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Taglab: An human-centric AI system for interactive semantic segmentation
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Poster
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Massimiliano Corsini 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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Methods:: How Mock Model Training Enhances User Perceptions of AI Systems
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Improving Human Decision-Making with Machine Learning
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Bringing “conscious” access to micro-credit by enhancing non-traditional financial practices with AI in the Global South
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Qualitative Analysis for Human Centered AI
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Poster
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Orestis Papakyriakopoulos · Elizabeth Watkins · Amy Winecoff · Klaudia Jazwinska 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Considerations for Collaborative Human-AI Decision-Making in Engineering Design
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Poster
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Ananya Nandy 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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Methods:: Understanding Human-like Behavior in Video Game Navigation
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Poster
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Evelyn Zuniga · Stephanie Milani · Katja Hofmann 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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XAI:: Dr Bots: The impact of explanation types on layperson trust in AI-driven symptom checkers
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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XAI:: Case Study on Two XAI Cultures: Non-technical Explanations in Deployed AI System
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Poster
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Mon 2:00 p.m. - 3:00 p.m.
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XAI:: On the transferability of insights from the psychology explanation to explainable AI
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Poster
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Marko Tesic 🔗 |
Mon 2:00 p.m. - 3:00 p.m.
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XAI:: How Does Netflix “Understand” Me?: Exploring End-user Needs to Design Human-centered Explanations
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Poster
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Yoonseo Choi 🔗 |
Mon 3:00 p.m. - 5:00 p.m.
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Discussion, Next steps, Conclusion, End
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Discussion
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SlidesLive Video » |
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Author Information
Michael Muller (IBM Research)
Michael Muller works in the AI Interactions group of IBM Research AI, where his work focuses on the human aspects of data science; ethics and values in applications of AI to human issues; metrics and analytics for enterprise social software applications, with particular application to employee engagement emergent social phenomena in social software. Recognitions include: ACM Distinguished Scientist; SIGCHI Academy; IBM Master Inventor. Steering Committees: EUSSET (European Society for the study of Socially Embedded Technologies); ACM GROUP conference series. Papers co-chair for ECSCW 2019 (European Computer Supported Cooperative Work conference).
Plamen P Angelov (Lancaster University)
Prof. Angelov (MEng 1989, PhD 1993, DSc 2015) is a Fellow of the IEEE, of the IET and of the HEA. His PhD supervisor, Dr. Dimitar P. Filev is now Member of the National Academy of Engineering, USA. Prof. Angelov is Vice President of the International Neural Networks Society (INNS) for Conferences. He has 30 years of professional experience in high level research and holds a Personal Chair in Intelligent Systems at Lancaster University, UK. He founded in 2010 the Intelligent Systems Research group which he led till 2014 when he founded the Data Science group at the School of Computing and Communications before going on sabbatical in 2017 and established LIRA (Lancaster Intelligent, Robotic and Autonomous systems) Research Centre (www.lancaster.ac.uk/lira ) which includes over 40 academics across different Faculties and Departments of the University. He is a founding member of the Data Science Institute and of the CyberSecurity Academic Centre of Excellence at Lancaster. He has authored or co-authored 300 peer-reviewed publications in leading journals, peer-reviewed conference proceedings, 3 granted patents, 3 research monographs (by Wiley, 2012 and Springer, 2002 and 2018) cited over 8800 times with an h-index of 48 and i10-index of 156. His single most cited paper has 940+ citations. He has an active research portfolio in the area of explainable AI, computational intelligence and machine learning and internationally recognised results into online and evolving learning and algorithms for knowledge extraction in the form of human-intelligible rule-based systems. Prof. Angelov leads numerous projects (including several multimillion ones) funded by UK research councils, EU, industry, UK MoD. His research was recognised by ‘The Engineer Innovation and Technology 2008 Special Award’ and ‘For outstanding Services’ (2013) by IEEE and INNS. He is also the founding co-Editor-in-Chief of Springer’s journal on Evolving Systems and Associate Editor of several leading international scientific journals, including IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Soft Computing, etc. He gave over two dozen key note/plenary talks at high profile conferences. Prof. Angelov was General co-Chair of a number of high profile IEEE conferences and is the founding Chair of the Technical Committee on Evolving Intelligent Systems, SMC Society of the IEEE and was previously chairing the Standards Committee of the Computational Intelligent Society of the IEEE (2010-2012). He was also a member of International Program Committee of over 100 international conferences (primarily IEEE).
Shion Guha (University of Toronto)
Marina Kogan (Utah)
Gina Neff (Oxford Internet Institute)
Nuria Oliver (Data-Pop Alliance & Vodafone Institute)
Manuel Rodriguez (Max Planck Institute for Software Systems)
Adrian Weller (Cambridge, Alan Turing Institute)
Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, where he is also a Turing Fellow leading work on safe and ethical AI. He is a Principal Research Fellow in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. He serves on several boards including the Centre for Data Ethics and Innovation. Previously, Adrian held senior roles in finance.
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