Globe.AI

UW researchers have broad expertise in the design and development of AI & culture from fields as diverse as NLP and ML to human-computer interaction (HCI), psychology, information & communication technology for development (ICTD) and science and technology studies. Our center additionally brings together expertise in quantitative and qualitative research, from large-scale online studies and development of new AI methods to interviews and design fiction.

Below is a select list of our ongoing research, intended to convey the types of questions our work currently tackles. Note that the direction of this work may change depending on input from the advisory board.

Understanding and designing for culture in AI

"NLPositionality: Characterizing design biases of datasets and models.". Santy, Sebastin, Jenny T. Liang, Ronan Le Bras, Katharina Reinecke, and Maarten Sap. ACL 2023. Outstanding paper award. PDF
“Passing the Buck to AI: How Individuals’ Decision-Making Patterns Affect Reliance on AI”. Mei, Katelyn, Rock Y. Pang, Alex Lyford, Lucy L. Wang, and Katharina Reinecke. Under submission.
“Digital Culture Shock: Who Creates Technology and Why it Matters”. Katharina Reinecke. Princeton University Press. In press.
“Hey Google, Talk Like Issa”: Black Voiced Digital Assistants and the Reshaping of Racial Labor”. Golden M. Owens. (Sounding Out, 2021)
“From Maid to Machine: Her, Hegemony and the Uncanny Female Servant.”. Golden M. Owens, Journal of Cinema and Media Studies (forthcoming)
“Cultural Values and Their Effects on Attitudes and Reliance on AI”. Mei, Katelyn, Nigini Oliveira, Rodolfo Barragan, Yulia Tsvetkov, Andrew Meltzoff, Maarten Sap, Katharina Reinecke. Under submission.
“Global social media design: Bridging differences across cultures.”Huatong Sun (2020). New York: Oxford University Press. NCTE Best Book in Technical or Scientific Communication Award, CCCC Advancement of Knowledge Award, CCCC Research Impact Award
“Cross-cultural technology design: Creating culture-sensitive technology for local users.”. Huatong Sun (2012). New York: Oxford University Press. NCTE Best Book in Technical or Scientific Communication Award.
Technical Communication 64(2): Special Issue on “Localizing User Experience: Strategies, practices, and techniques for culturally sensitive design.”. Sun, Huatong. & Getto, G. Eds. (2017).
Special Issue of Journal of Rhetoric, Professional Communication & Globalization 8(1): “Designing for Everyday Life in a Global Context.”. Getto, G. & Sun, Huatong. Eds. (2017).
Binding the material and the discursive with a relational approach of affordancesHuatong Sun & William Hart-Davidson. ACM SIGCHI 2014, 3533-3542.

Teaching AI systems to learn cultural values

Toward Morality in a Machine: Implicit Learning of Human Value Systems by an AI through Inverse Reinforcement Learning. Nigini Oliveira, Jasmine Li, Koosha Khalvati, Rodolfo Cortes Barragan, Katharina Reinecke, Andrew N. Meltzoff, and Rajesh P. N. Rao.

Auditing of Problematic Socio-Cultural Behaviors in Large Language Models

Biased AI can Influence Political Decision-Making. Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson, Yejin Choi, Daniel W. Fisher, Jennifer Pan, Yulia Tsvetkov, Katharina Reinecke. In submission.
“They are uncultured": Unveiling Covert Harms and Social Threats in LLM Generated Conversations. Preetam Dammu, Hayoung Jung, Anjali Singh, Monojit Choudhury, Tanu Mitra.

Studying AI ethically and at scale

“Passing the Buck to AI: How Individuals’ Decision-Making Patterns Affect Reliance on AI”. Mei, Katelyn, Rock Y. Pang, Alex Lyford, Lucy L. Wang, and Katharina Reinecke. Under submission.
“Cultural Values and Their Effects on Attitudes and Reliance on AI”. Mei, Katelyn, Nigini Oliveira, Rodolfo Barragan, Yulia Tsvetkov, Andrew Meltzoff, Maarten Sap, Katharina Reinecke. Under submission.
"LabintheWild: Conducting Large-Scale Online Experiments With Uncompensated Samples". Katharina Reinecke and Krzysztof Gajos. Computer Supported Cooperative Work and Social Computing (CSCW), 2015.
“Bridging Cultural Differences with Critical Design in a Globalized World” (course). Huatong Sun. ACM SIGCHI 2022, 2023, 2024.
Renji gongxie jisuan (“Human-Engaged Computing”). Xiangshi Ren, Zhiyong Fu, Xiaojuan Ma, Jianmin Wang, Huatong Sun, Xiaojun Yuan, & Chen Wang (2024). Tsinghua University Press.

Understanding and Leveraging AI for educational purposes in various cultures

Co-ML: Collaborative Machine Learning Model Building for Developing Dataset Design Practices. Tiffany Tseng, Matt J. Davidson, Luis Morales-Navarro, Jennifer King Chen, Victoria Delaney, Mark Leibowitz, Jazbo Beason, R. Benjamin Shapiro (2024). ACM Transactions on Computing Education.
Taking play and tinkering seriously in AI education: cases from Drag vs AI teen workshops. Janet Ruppert, Diego Velazquez-Ramos, Ricarose Roque, R Benjamin Shapiro (2023). Learning, Media and Technology.
Opportunities and Challenges for Enacting Equity and Justice-centered CS Learning In ``Drag vs. AI'' Workshops. Janet Ruppert, Ricarose Roque, R. Benjamin Shapiro (2022). Proceedings of the 2022 Conference of the International Society of the Learning Sciences.