Critics on AI

会議の名前
CHI 2025
AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue
要旨

This paper examines the potential for localized adaptation, appropriation and re-imagination of AI for non-western cultural expression, using the Persian Gulf as a case. Using sociologist Howard Becker’s concept of 'art worlds' as a situated lens to evaluate generative AI, we set up an eight week experimentation and dialogue between artists, art historians and curators. Our project reveals how local art worlds 1) can appropriate AI tools to address contextual and cultural needs; 2) develop "hacks'' to adapt AI for culturally-specific capabilities; and 3) can be a site for imagining alternative technological trajectories. We thus showcase the importance of expanding the scope of AI evaluations to include the social dynamics AI operates in and its contexts of use. We also reflect on the power that local communities may have to interrupt AI with more culturally-relevant orientations and to offer visions for redesigning AI for non-Western creativity.

著者
Rida Qadri
Google Research, San Francisco, California, United States
Piotr Mirowski
DeepMind, London, United Kingdom
Remi Denton
Google, New York, New York, United States
DOI

10.1145/3706598.3714049

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714049

動画
"Ethics is not neutral": Understanding Ethical and Responsible AI Design from the Lenses of Black Youth
要旨

The rise of generative AI has brought a host of challenges for historically marginalized groups, including increased surveillance, AI-mediated racism, and algorithmic inequity. While stakeholders emphasize ethical and responsible AI that is safe, anti-discriminatory, and "protects human dignity", the centrality of anti-Blackness in the design, development, and deployment of AI systems coupled with race-evasive approaches to defining and advancing ethical, equitable, and ‘human-centered’ technologies have exacerbated racial oppression. We present three case studies of speculative technologies designed by Black youth in a college bridge, summer course that examine ethical and responsible AI in their everyday lives. From a bottom-up approach, we infringe upon this broader discourse to provide an initial grounding of responsible and ethical AI as well as discuss the criticality of Black, historically anchored, culturally-situated lenses to offer justice-oriented design principles that can guide the teaching, learning, and design of technology.

著者
Tiera Tanksley
UCLA, Los Angeles , California, United States
Angela D. R. Smith
University of Texas at Austin, Austin, Texas, United States
Saloni Sharma
University of Texas at Austin, Austin, Texas, United States
Earl W. Huff
The University of Texas at Austin, Austin, Texas, United States
DOI

10.1145/3706598.3713510

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713510

動画
Copying style, Extracting value: Illustrators’ Perception of AI Style Transfer and its Impact on Creative Labor
要旨

Generative text-to-image models are disrupting the lives of creative professionals. Specifically, illustrators are threatened by models that claim to extract and reproduce their style. Yet, research on style transfer has rarely focused on their perspectives. We provided four illustrators with a model fine-tuned to their style and conducted semi-structured interviews about the model’s successes, limitations, and potential uses. Evaluating their output, artists reported that style transfer successfully copies aesthetic fragments but is limited by content-style disentanglement and lacks the crucial emergent quality of their style. They also deemed the others’ copies more successful. Understanding the results of style transfer as “boundary objects,” we analyze how they can simultaneously be considered unsuccessful by artists and poised to replace their work by others. We connect our findings to critical HCI frameworks, demonstrating that style transfer, rather than merely a Creativity Support Tool, should also be understood as a supply chain optimization one.

著者
Julien Porquet
University of Cambridge, Cambridge, United Kingdom
Sitong Wang
Columbia University, New York, New York, United States
Lydia B. Chilton
Columbia University, New York, New York, United States
DOI

10.1145/3706598.3713854

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713854

動画
Empowering Adults with AI Literacy: Using Short Videos to Transform Understanding and Harness Fear for Critical Thinking
要旨

Despite the importance of AI literacy for both children and adults, adults have been understudied. We developed short videos for adults that provided training on the basics of AI understanding, use, and evaluation. In an online experiment, 94 adults aged 30-49 were randomly assigned in a 1:2 ratio to view either short videos on AI history (control group) or AI literacy training videos (treatment group). The results showed that the intervention significantly improved people’s self-efficacy of AI use but not in AI understanding or evaluation. Interestingly, participants’ fears of AI bias, privacy violations, and job replacement increased after the training, although they remained below the midpoints. We argue that the heightened fear in the treatment group reflects a foundation for critical thinking skills, as it moves them closer to a more calibrated, moderate level of fear. Therefore, this study uniquely contributes by utilizing short-form experiential content to both educate and foster a more informed, critical interaction with AI technologies. The implications of designing AI literacy educational materials for adults were discussed.

受賞
Honorable Mention
著者
Huajie Cao
Michigan State University, East Lansing, Michigan, United States
Hee Rin Lee
Michigan State University, East Lansing, Michigan, United States
Wei Peng
Michigan State University, East Lansing, Michigan, United States
DOI

10.1145/3706598.3713254

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713254

動画
How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About It
要旨

The energy cost of developing and deploying Generative AI (GenAI) models has exploded with their mass adoption, as has the ensuing carbon emissions. The climate impact of this is currently unknown. In Human-Computer Interaction, GenAI models are rarely trained but often used. Based on detailed review of 282 papers, we estimate this footprint from energy consumption of the total use of GenAI for CHI 2024 research as between 10,769.63 and 10,925.12 kg CO2e — equal to driving a car for more than 100,000 km. We show that in CHI research, GenAI is most often used for Prototyping, Evaluation & User studies, and that Data Collection and Fine-tuning models incurs the highest CO2st. We find that CHI submissions are unlikely to report GenAI use transparently, which makes precise calculations difficult. By measuring the usage of a subset of the papers on local hardware, we obtain estimations of the energy consumption and carbon footprint. Based on this evidence, we discuss and demonstrate ways to mitigate the issues of GenAI carbon footprint and lack of transparency.

著者
Nanna Inie
IT University of Copenhagen, Copenhagen, Denmark
Jeanette Falk
Aalborg University, Copenhagen, Denmark
Raghavendra Selvan
University of Copenhagen, Copenhagen, Denmark
DOI

10.1145/3706598.3714227

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714227

動画
Fictional Failures and Real-World Lessons: Ethical Speculation Through Design Fiction on Emotional Support Conversational AI
要旨

Conversational artificial intelligence (CAI), which replicates human-to-human interaction as human-to-machine, is increasingly developed to address insufficient access to healthcare. In this paper, we use design fiction methods to speculate on ethical consequences of CAI that offers emotional support to complement or replace mental healthcare. Through a near-future news article about a fictional, failed CAI, we explore safety and privacy concerns associated with mismatches between what an emotional support CAI is advertised to do, what it technically can do, and how it is likely to be used. We pose the following questions to researchers, regulators, and developers: How might we jointly and effectively address the anticipatable safety and privacy risks that emotional support CAI pose, including formalizing ethical speculation processes? What streamlined and practically feasible measures can efficiently account for the most dangerous harms? How might differing stakeholder expectations about the CAI be bridged? Finally, in what scenarios is the decision not to design a CAI tool the most ethical or safest option? Content advisement: Contains discussion of disordered eating behaviors and intimate partner violence.

著者
Faye Kollig
University of Colorado Boulder, Boulder, Colorado, United States
Jessica Pater
Parkview Health, Fort Wayne, Indiana, United States
Fayika Farhat Nova
Parkview Health, Fort Wayne, Indiana, United States
Casey Fiesler
University of Colorado, Boulder, Colorado, United States
DOI

10.1145/3706598.3713322

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713322

動画
Generative AI as a Playful yet Offensive Tourist: Exploring Tensions Between Playful Features and Citizen Concerns in Designing Urban Play
要旨

Play is pivotal in fostering the emotional, social, and cultural dimensions of urban spaces. While generative AI (GAI) potentially supports playful urban interaction, a balanced and critical approach to the design opportunities and challenges is needed. This work develops iWonder, an image-to-image GAI tool engaging fourteen designers in urban explorations to identify GAI's playful features and create design ideas. Fourteen citizens then evaluated these ideas, providing expectations and critical concerns from a bottom-up perspective. Our findings reveal the dynamic interplay between users, GAI, and urban contexts, highlighting GAI's potential to facilitate playful urban experiences through generative agency, meaningful unpredictability, social performativity, and the associated offensive qualities. We propose design considerations to address citizen concerns and the `tourist metaphor' to deepen our understanding of GAI's impacts, offering insights to enhance cities' socio-cultural fabric. Overall, this research contributes to the effort to harness GAI's capabilities for urban enrichment.

著者
Peng-Kai Hung
Eindhoven University of Technology, Eindhoven, Netherlands
Janet Yi-Ching Huang
Eindhoven University of Technology, Eindhoven, Netherlands
Rung-Huei Liang
National Taiwan University of Science and Technology, Taipei, Taiwan
Stephan Wensveen
Eindhoven University of Technology, Eindhoven, Netherlands
DOI

10.1145/3706598.3713137

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713137

動画