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GenAICHI 2023: Generative AI and HCI at CHI 2023

Published: 19 April 2023 Publication History

Abstract

This workshop applies human centered themes to a new and powerful technology, generative artificial intelligence (AI). Unlike AI systems that produce decisions or descriptions, generative AI systems can produce new and creative content that can include images, texts, music, video, code, and other forms of design. The results are often similar to results produced by humans. However, it is not yet clear how humans make sense of generative AI algorithms or their outcomes. It is also not yet clear how humans can control and more generally, interact with, these powerful capabilities in ethical ways. Finally, it is not clear what kinds of collaboration patterns will emerge when creative humans and creative technologies work together.
Following a successful workshop in 2022, we convene the interdisciplinary research domain of generative AI and HCI. Participation in this invitational workshop is open to seasoned scholars and early career researchers. We solicit descriptions of completed projects, works-in-progress, and provocations. Together we will develop theories and practices in this intriguing new domain.

References

[1]
Lisa C Adams, Felix Busch, Daniel Truhn, Marcus R Makowski, Hugo JWL Aerts, and Keno K Bressem. 2022. What Does DALL-E 2 Know About Radiology?arXiv preprint arXiv:2209.13696(2022).
[2]
Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N Bennett, Kori Inkpen, 2019. Guidelines for human-AI interaction. In Proceedings of the 2019 chi conference on human factors in computing systems. 1–13.
[3]
Cecilia Aragon, Clayton Hutto, Andy Echenique, Brittany Fiore-Gartland, Yun Huang, Jinyoung Kim, Gina Neff, Wanli Xing, and Joseph Bayer. 2016. Developing a research agenda for human-centered data science. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion. 529–535.
[4]
Anon. at DeMilked.com. 2020. Here’s How 20 Famous Historical And Fictional Figures ‘Really’ Looked Like. Retrieved Oct 4, 2022 from https://www.demilked.com/historical-figures-recreated-bas-uterwijk/
[5]
Shraddha Barke, Michael B James, and Nadia Polikarpova. 2022. Grounded Copilot: How Programmers Interact with Code-Generating Models. arXiv preprint arXiv:2206.15000(2022).
[6]
Su Lin Blodgett, Q Vera Liao, Alexandra Olteanu, Rada Mihalcea, Michael Muller, Morgan Klaus Scheuerman, Chenhao Tan, and Qian Yang. 2022. Responsible Language Technologies: Foreseeing and Mitigating Harms. In CHI Conference on Human Factors in Computing Systems Extended Abstracts. 1–3.
[7]
Terence Broad, Sebastian Berns, Simon Colton, and Mick Grierson. 2021. Active Divergence with Generative Deep Learning–A Survey and Taxonomy. arXiv preprint arXiv:2107.05599(2021).
[8]
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, 2021. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374(2021).
[9]
Katherine Crowson. 2021. Introduction to VQGAN CLIP. Google Docs. https://docs.google.com/document/d/1Lu7XPRKlNhBQjcKr8k8qRzUzbBW7kzxb5Vu72GMRn2E/edit
[10]
Katherine Crowson. 2021. Rivers Have Wings. https://twitter.com/RiversHaveWings
[11]
Jay L Cunningham, Gabrielle Benabdallah, Daniela K Rosner, and Alex S Taylor. 2022. On the Grounds of Solutionism: Ontologies of Blackness and HCI. ACM Transactions on Computer-Human Interaction (2022).
[12]
Nicholas Davis. 2013. Human-computer co-creativity: Blending human and computational creativity. In Doctoral Consortium of the Ninth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (Boston, Massachusetts, USA, October 14-18,). AAAI, 9–12.
[13]
Nicholas Davis, Chih-PIn Hsiao, Kunwar Yashraj Singh, Lisa Li, and Brian Magerko. 2016. Empirically studying participatory sense-making in abstract drawing with a co-creative cognitive agent. In Proceedings of the 21st International Conference on Intelligent User Interfaces. 196–207.
[14]
Bestiario del Hypogripho. 2021. Ayuda:Generar imágenes con VQGAN CLIP/English. https://tuscriaturas.miraheze.org/w/index.php?title=Ayuda:Generar_imágenes_con_VQGAN CLIP/English
[15]
Sebastian Deterding, Jonathan Hook, Rebecca Fiebrink, Marco Gillies, Jeremy Gow, Memo Akten, Gillian Smith, Antonios Liapis, and Kate Compton. 2017. Mixed-initiative creative interfaces. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. 628–635.
[16]
Upol Ehsan, Philipp Wintersberger, Q Vera Liao, Martina Mara, Marc Streit, Sandra Wachter, Andreas Riener, and Mark O Riedl. 2021. Operationalizing Human-Centered Perspectives in Explainable AI. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. 1–6.
[17]
Ahmed Elgammal, Bingchen Liu, and Kunpeng Song. 2020. Sketch-to-Art: synthesizing stylized art images from hand-drawn sketches with no semantic labeling. In ACM SIGGRAPH 2020 Real-Time Live!1–1.
[18]
Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, and Adam Roberts. 2019. GANSynth: Adversarial Neural Audio Synthesis. In Proceedings of the International Conference on Learning Representations. https://openreview.net/pdf?id=H1xQVn09FX
[19]
Patricia Garcia, Tonia Sutherland, Marika Cifor, Anita Say Chan, Lauren Klein, Catherine D’Ignazio, and Niloufar Salehi. 2020. No: critical refusal as feminist data practice. In Conference Companion Publication of the 2020 on Computer Supported Cooperative Work and Social Computing. 199–202.
[20]
Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2015. A Neural Algorithm of Artistic Style. arxiv:1508.06576 [cs.CV]
[21]
Pablo Gervás. 2001. An Expert System for the Composition of Formal Spanish Poetry. In Applications and Innovations in Intelligent Systems VIII, Ann Macintosh, Mike Moulton, and Frans Coenen (Eds.). Springer London, London, 19–32.
[22]
Werner Geyer, Lydia B Chilton, Justin D Weisz, and Mary Lou Maher. 2021. HAI-GEN 2021: 2nd Workshop on Human-AI Co-Creation with Generative Models. In 26th International Conference on Intelligent User Interfaces. 15–17.
[23]
GitHub. 2022. GitHub Copilot - Your AI pair programmer. Retrieved September, 2022 from https://github.com/features/copilot/
[24]
Anna Lauren Hoffmann. 2021. Even when you are a solution you are a problem: An uncomfortable reflection on feminist data ethics. Global Perspectives 2, 1 (2021).
[25]
Stephanie Houde, Vera Liao, Jacquelyn Martino, Michael Muller, David Piorkowski, John Richards, Justin Weisz, and Yunfeng Zhang. 2020. Business (mis) use cases of generative AI. arXiv preprint arXiv:2003.07679(2020).
[26]
Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Ian Simon, Curtis Hawthorne, Andrew Dai, Matt Hoffman, Monica Dinculescu, and Douglas Eck. 2019. Music Transformer: Generating Music with Long-Term Structure. https://arxiv.org/abs/1809.04281
[27]
Justin. 2021. Somewhere Systems Twitter. https://twitter.com/somewheresy
[28]
Anna Kantosalo, Jukka M. Toivanen, Ping Xiao, and Hannu Toivonen. 2014. From Isolation to Involvement: Adapting Machine Creativity Software to Support Human-Computer Co-Creation. In Proceedings of the Fifth International Conference on Computational Creativity, Ljubljana, Slovenia. 1–7. http://computationalcreativity.net/iccc2014/wp-content/uploads/2014/06/1.1_Kantosalo.pdf
[29]
Pegah Karimi, Kaz Grace, Mary Lou Maher, and Nick Davis. 2018. Evaluating Creativity in Computational Co-Creative Systems. In Proceedings of the 2018 international conference on computational creativity, Vol. 147. Citeseer.
[30]
Pegah Karimi, Mary Lou Maher, Nick Davis, and Kaz Grace. 2019. Deep Learning in a Computational Model for Conceptual Shifts in a Co-Creative Design System. In Proceedings of the 2019 international conference on computational creativity, Vol. 147. Citeseer.
[31]
Marina Kogan, Aaron Halfaker, Shion Guha, Cecilia Aragon, Michael Muller, and Stuart Geiger. 2020. Mapping Out Human-Centered Data Science: Methods, Approaches, and Best Practices. In Companion of the 2020 ACM International Conference on Supporting Group Work. 151–156.
[32]
Harsh Kumar, Ilya Musabirov, Jiakai Shi, Adele Lauzon, Kwan Kiu Choy, Ofek Gross, Dana Kulzhabayeva, and Joseph Jay Williams. 2022. Exploring The Design of Prompts For Applying GPT-3 based Chatbots: A Mental Wellbeing Case Study on Mechanical Turk. arXiv preprint arXiv:2209.11344(2022).
[33]
Mina Lee, Percy Liang, and Qian Yang. 2022. Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities. In CHI Conference on Human Factors in Computing Systems. 1–19.
[34]
Ryan Louie, Andy Coenen, Cheng Zhi Huang, Michael Terry, and Carrie J Cai. 2020. Novice-AI music co-creation via AI-steering tools for deep generative models. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–13.
[35]
Mary Lou Maher, Katherine Brady, and Douglas H Fisher. 2013. Computational models of surprise in evaluating creative design. In Proceedings of the fourth international conference on computational creativity, Vol. 147. Citeseer.
[36]
Charles Patrick Martin, Fabio Morreale, Benedikte Wallace, and Hugo Scurto. 2021. Critical Perspectives on AI/ML in Musical Interfaces. Workshop at NIME 2021. https://critical-ml-music-interfaces.github.io
[37]
Justin Matejka, Michael Glueck, Erin Bradner, Ali Hashemi, Tovi Grossman, and George Fitzmaurice. 2018. Dream Lens : Exploration and Visualization of Large-Scale Generative Design Datasets. (2018), 1–12.
[38]
Justin Matejka, Michael Glueck, Erin Bradner, Ali Hashemi, Tovi Grossman, and George Fitzmaurice. 2018. Dream Lens: Exploration and Visualization of Large-Scale Generative Design Datasets. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3173574.3173943
[39]
Michael Muller, Cecilia Aragon, Shion Guha, Marina Kogan, Gina Neff, Cathrine Seidelin, Katie Shilton, and Anissa Tanweer. 2020. Interrogating Data Science. In Conference Companion Publication of the 2020 on Computer Supported Cooperative Work and Social Computing. 467–473.
[40]
Michael Muller, Lydia Chilton, Anna Kantosalo, Mary Lou Maher, Charles Patrick Martin, and Greg Walsh. 2022. GenAICHI: Generative AI and Computer Human Interaction. Retrieved Oct 4, 2022 from https://sites.google.com/view/genaichi2022/home
[41]
Michael Muller, Melanie Feinberg, Timothy George, Steven J Jackson, Bonnie E John, Mary Beth Kery, and Samir Passi. 2019. Human-centered study of data science work practices. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. 1–8.
[42]
Michael Muller, Steven Ross, Stephanie Houde, Mayank Agarwal, Fernando Martinez, John Richards, Kartik Talamadupula, and Justin D Weisz. 2022. Drinking Chai with Your (AI) Programming Partner: A Design Fiction about Generative AI for Software Engineering. HAI-GEN Workshop at IUI 2022: 3rd Workshop on Human-AI Co-Creation with Generative Models (2022). https://hai-gen.github.io/2022/
[43]
Michael Muller, April Y. Wang, Steven I. Ross, Justin D. Weisz, Mayank Agarwal, Kartik Talamadupula, Stephanie Houde, Fernando Martinez, John Richards, Jaimie Drozdal, Xie Lui, David Piorkowski, and Dakuo Wang. 2021. How data scientists improve generated code documentation in Jupyter notebooks. Retrieved October 5, 2021 from https://hai-gen2021.github.io/program/
[44]
NeurIPS. 2019. Machine Learning for Creativity and Design. Retrieved Oct 10, 2021 from https://neurips2019creativity.github.io/
[45]
AkshatKumar Nigam, Robert Pollice, Mario Krenn, Gabriel dos Passos Gomes, and Alan Aspuru-Guzik. 2021. Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES. Chemical science (2021).
[46]
Amin Heyrani Nobari, Muhammad Fathy Rashad, and Faez Ahmed. 2021. Creativegan: editing generative adversarial networks for creative design synthesis. arXiv preprint arXiv:2103.06242(2021).
[47]
NPR. 2021. Team uses AI to complete Beethoven’s unfinished masterpiece. NPR (Oct 2021). https://www.npr.org/2021/10/02/1042742330/team-uses-ai-to-complete-beethovens-unfinished-masterpiece
[48]
Jonas Oppenlaender. 2022. The Creativity of Text-based Generative Art. arXiv preprint arXiv:2206.02904(2022).
[49]
Rafael PÉrez Ý PÉrez and Mike Sharples. 2001. MEXICA: A computer model of a cognitive account of creative writing. Journal of Experimental & Theoretical Artificial Intelligence 13, 2(2001), 119–139. https://doi.org/10.1080/09528130010029820 arXiv:https://doi.org/10.1080/09528130010029820
[50]
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. arxiv:2103.00020 [cs.CV]
[51]
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021. Zero-Shot Text-to-Image Generation. arxiv:2102.12092 [cs.CV]
[52]
Reddit 2021. r/bigsleep: A subreddit for AI imagery generated from text descriptions.https://www.reddit.com/r/bigsleep/
[53]
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022. High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 10684–10695.
[54]
Mark A. Runco and Garrett J. Jaeger. 2012. The Standard Definition of Creativity. Creativity Research Journal 24, 1 (2012), 92–96. https://doi.org/10.1080/10400419.2012.650092 arXiv:https://doi.org/10.1080/10400419.2012.650092
[55]
Advait Sarkar, Andrew D. Gordon, Carina Negreanu, Christian Poelitz, Sruti Srinivasa Ragavan, and Ben Zorn. 2022. What is it like to program with Artificial Intelligence?https://arxiv.org/abs/2208.06213v1
[56]
Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, and Camille Couprie. 2018. Design: Design inspiration from generative networks. In Proceedings of the European Conference on Computer Vision (ECCV) Workshops. 0–0.
[57]
Isabella Seeber, Eva Bittner, Robert O Briggs, Triparna De Vreede, Gert-Jan De Vreede, Aaron Elkins, Ronald Maier, Alexander B Merz, Sarah Oeste-Reiß, Nils Randrup, 2020. Machines as teammates: A research agenda on AI in team collaboration. Information & management 57, 2 (2020), 103174.
[58]
Ben Shneiderman. 2007. Creativity support tools: Accelerating discovery and innovation. Commun. ACM 50, 12 (2007), 20–32.
[59]
Angie Spoto and Natalia Oleynik. [n. d.]. Library of Mixed Initiative Creative Interfaces. Retrieved Oct 10, 2021 from http://mici.codingconduct.cc/
[60]
Ivo Swartjes and Mariët Theune. 2009. Iterative authoring using story generation feedback: debugging or co-creation?. In Joint International Conference on Interactive Digital Storytelling. Springer, 62–73.
[61]
ICCC’21 The Twelfth International Conference on Computational Creativity. 2021. Second Workshop on the Future of Co-Creative Systems. Retrieved Oct 11, 2021 from https://computationalcreativity.net/iccc21/wfccs/
[62]
M Onat Topal, Anil Bas, and Imke van Heerden. 2021. Exploring transformers in natural language generation: Gpt, bert, and xlnet. arXiv preprint arXiv:2102.08036(2021).
[63]
Twitter 2021. VQGANCLIP Hashtag. https://twitter.com/hashtag/vqganclip?src=hashtag_click
[64]
@someheresy Twitter. 2021. VQGAN CLIP Colab Notebook. https://colab.research.google.com/drive/1_4Jl0a7WIJeqy5LTjPJfZOwMZopG5C-W?usp=sharing#scrollTo=ZdlpRFL8UAlW
[65]
Quentin Vanhaelen, Yen-Chu Lin, and Alex Zhavoronkov. 2020. The advent of generative chemistry. ACS Medicinal Chemistry Letters 11, 8 (2020), 1496–1505.
[66]
Benedikte Wallace, Charles Patrick Martin, Jim Tørresen, and Kristian Nymoen. 2021. Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks. In Artificial Intelligence in Music, Sound, Art and Design: 10th International Conference, EvoMUSART 2021. Springer International Publishing, 344–359. https://doi.org/10.1007/978-3-030-72914-1_23
[67]
April Yi Wang, Dakuo Wang, Jaimie Drozdal, Michael Muller, Soya Park, Justin D Weisz, Xuye Liu, Lingfei Wu, and Casey Dugan. 2021. Themisto: Towards Automated Documentation Generation in Computational Notebooks. arXiv preprint arXiv:2102.12592(2021).
[68]
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, 2022. Taxonomy of risks posed by language models. In 2022 ACM Conference on Fairness, Accountability, and Transparency. 214–229.
[69]
Justin D Weisz, Michael Muller, Stephanie Houde, John Richards, Steven I Ross, Fernando Martinez, Mayank Agarwal, and Kartik Talamadupula. 2021. Perfection Not Required? Human-AI Partnerships in Code Translation. In 26th International Conference on Intelligent User Interfaces. 402–412.
[70]
Georgios N Yannakakis, Antonios Liapis, and Constantine Alexopoulos. 2014. Mixed-initiative co-creativity. In Proceedings of the 9th International Conference on the Foundations of Digital Games, FDG 2014 (Liberty of the Seas, Caribbean, April 3-7).
[71]
Yijun Zhou, Yuki Koyama, Masataka Goto, and Takeo Igarashi. 2020. Generative Melody Composition with Human-in-the-Loop Bayesian Optimization. arXiv preprint arXiv:2010.03190(2020).

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cover image ACM Conferences
CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
April 2023
3914 pages
ISBN:9781450394222
DOI:10.1145/3544549
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 19 April 2023

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Author Tags

  1. Bias
  2. Design
  3. Generative AI
  4. Uncertainty.

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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