Creative ML Assemblages: The Interactive Politics of People, Processes, and Products
Open accessAbstract
Creative ML tools are collaborative systems that afford artistic creativity through their myriad interactive relationships. We propose using "assemblage thinking" to support analyses of creative ML by approaching it as a system in which the elements of people, organizations, culture, practices, and technology constantly influence each other. We model these interactions as "coordinating elements" that give rise to the social and political characteristics of a particular creative ML context, and call attention to three dynamic elements of creative ML whose interactions provide unique context for the social impact a particular system has: people, creative processes, and products. As creative assemblages are highly contextual, we present these as analytical concepts that computing researchers can adapt to better understand the functioning of a particular system or phenomena and identify intervention points to foster desired change. This paper contributes to theorizing interactions with AI in the context of art, and how these interactions shape the production of algorithmic art.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Most studies of artists using AI have been either explicitly conducted in the Global North, or agnostic to cultural identity.
“Yet, with the exception of [76, 99], most studies of artists using AI have been either explicitly conducted in the Global North, or agnostic to cultural identity.”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [99]
The Abstract describes creative ML as culturally contextual, but it does not assess where studies of artists using AI were conducted or whether they considered cultural identity. Searches for “Global North,” “cultural identity,” and studies of artists using AI returned references rather than a passage establishing the claimed pattern. (LLM, conf=0.72)
Experimental — accuracy not yet measuredStudying artists' creative adaptations and resistance to dominant technological frames can illuminate how these tools can be remade in ways that contest hegemonic power dynamics and better serve local communities of practice.
“Studying artists creative adaptations and resistance to dominant technological frames can also “illuminate how these tools can be remade in ways that contest hegemonic power dynamics and better serve local communities of practice”[99].”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [99]
The retrieved passages from our copy are chiefly References and the Abstract; none addresses artists’ adaptations or resistance to dominant technological frames as a way to remake tools for local communities. Searches for the quoted wording, “resistance to dominant technological frames,” and “local communities of practice” found no decisive passage from the paper’s body. (LLM, conf=0.70)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 104 · Cited by 6
Research works printed but not linked: 139
- [1][1] Fabien Accominotti. 2009. Creativity from Interaction: Artistic Movements and the Creativity Careers of Modern Painters. Poetics, Vol. 37, 3 (2009), 267--294. https://doi.org/10.1016/j.poetic.2009.03.005 Crossref Google Scholar · DOI
- [4][4] Memo Akten, Rebecca Fiebrink, and Mick Grierson. 2019. Learning to See: You Are What You See. In ACM SIGGRAPH 2019 Art Gallery. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3306211.3320143 Digital Library Google Scholar · DOI
- [6][6] Prithviraj Ammanabrolu, Wesley Cheung, William Broniec, and Mark O. Riedl. 2021. Automated Storytelling via Causal, Commonsense Plot Ordering. Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35, 7 (May 2021), 5859--5867. https://doi.org/10.1609/aaai.v35i7.16733 Crossref Google Scholar · DOI
- [7][7] Louise Amoore. 2020. Cloud Ethics: Algorithms and the Attributes of Ourselves and Others. Duke University Press, Durham, NC. Google Scholar
- [8][8] Ben Anderson and Colin McFarlane. 2011. Assemblage and Geography. Area, Vol. 43, 2 (2011), 124--127. https://www.jstor.org/stable/41240473 Crossref Google Scholar
- [9][9] Claudia Aradau and Tobias Blanke. 2015. The (Big) Data-security Assemblage: Knowledge and Critique. Big Data & Society, Vol. 2, 2 (2015), 1--12. https://doi.org/10.1177/2053951715609066 Crossref Google Scholar · DOI
- [11][11] Sofian Audry. 2021. Art in the Age of Machine Learning. MIT Press, Cambridge, Massachusetts. Crossref Google Scholar
- [12][12] Sofian Audry, Rosalie Dumont-Gagné, and Hugo Scurto. 2020. Behaviour Aesthetics of Reinforcement Learning in a Robotic Art Installation. In 4th NeurIPS Workshop on Machine Learning for Creativity and Design. The Conference and Workshop on Neural Information Processing Systems, Vancouver, Canada, bibinfonumpages3 pages. https://hal.science/hal-03100907 Google Scholar
- [13][13] Tom Baker and Pauline McGuirk. 2017. Assemblage Thinking as Methodology: Commitments and Practices for Critical Policy Research. Territory, Politics, Governance, Vol. 5, 4 (2017), 425--442. https://doi.org/10.1080/21622671.2016.1231631 Crossref Google Scholar · DOI
- [15][15] Karen Barad. 2007. Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning. Duke University Press, Durham, North Carolina. Crossref Google Scholar
- [16][16] Gerald Bartels and Nicolas Bencherki. 2020. Actor-Network-Theory and Creativity Research. Springer, New York, NY, 29--36. Google Scholar
- [17][17] Howard S. Becker. 1982. Art Worlds. University of California Press, Berkeley, CA. Google Scholar
- [18][18] William Bedford. 2015. Montreal Might Eat its Young, but Montreal Won't Break Us Down:' The Co-production of Place, Space and Independent Music in Mile End, 1995--2015. Journal of Urban Cultural Studies, Vol. 2, 3 (2015), 335--345. https://doi.org/10.1386/jucs.2.3.335_1 Crossref Google Scholar · DOI
- [19][19] Ruha Benjamin. 2019. Race After Technology: Abolitionist Tools for the New Jim Code. Polity Press, Cambridge, UK. Crossref Google Scholar
- [20][20] Cynthia L. Bennett and Os Keyes. 2020. What is the Point of Fairness? Disability, AI and the Complexity of Justice. SIGACCESS Access. Comput., Vol. 125, 5, Article 5 (2020), bibinfonumpages1 pages. https://doi.org/10.1145/3386296.3386301 Digital Library Google Scholar · DOI
- [21][21] Tony Bennett. 2013. Thinking (with) Museums: From Exhibitionary Complex to Governmental Assemblage. Wiley Online Library, Hoboken, New Jersey, 3--20. Google Scholar
- [23][23] Neil Brenner, David J. Madden, and David Wachsmuth. 2011. Assemblage Urbanism and the Challenges of Critical Urban Theory. City, Vol. 15, 2 (2011), 225--240. https://doi.org/10.1080/13604813.2011.568717 Crossref Google Scholar · DOI
- [24][24] Taina Bucher. 2018. If... then: Algorithmic Power and Politics. Oxford University Press, New York, NY. Google Scholar
- [25][25] Joy Buolamwini and Timnit Gebru. 2018. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (Proceedings of Machine Learning Research, Vol. 81), Sorelle A. Friedler and Christo Wilson (Eds.). PMLR, New York, NY, USA, 77--91. https://proceedings.mlr.press/v81/buolamwini18a.html Google Scholar
- [26][26] Jack Burnham. 1980. Art and Technology: The Panacea That Failed. In The Myths of Information: Technology and Postindustrial Culture. Coda Press, London, UK, 200--218. Google Scholar
- [27][27] Ronald Burt. 2004. Structural Holes and Good Ideas. Amer. J. Sociology, Vol. 110, 2 (2004), 349--399. https://doi.org/10.1086/421787 Crossref Google Scholar · DOI · Paper page
- [28][28] Baptiste Caramiaux and Marco Donnarumma. 2021. Artificial Intelligence in Music and Performance: A Subjective Art-research Inquiry. Springer, New York, NY, 75--95. Google Scholar
- [29][29] Baptiste Caramiaux and Sarah Fdili Alaoui. 2022. Explorers of Unknown Planets:" Practices and Politics of Artificial Intelligence in Visual Arts. In Proc. ACM Hum.-Comput. Interact., Vol. 6. Association for Computing Machinery, New York, NY, USA, Article 477, bibinfonumpages24 pages. https://doi.org/10.1145/3555578 Digital Library Google Scholar · DOI · Paper page
- [30][30] Gino Cattani, Simone Ferriani, and Paul D. Allison. 2014. Insiders, Outsiders, and the Struggle for Consecration in Cultural Fields: A Core-periphery Perspective. American Sociological Review, Vol. 79, 2 (2014), 258--281. https://doi.org/10.1177/0003122414520960 Crossref Google Scholar · DOI
- [31][31] Eva Cetinic and James She. 2022. Understanding and Creating Art with AI: Review and Outlook. ACM Trans. Multimedia Comput. Commun. Appl., Vol. 18, 2, Article 66 (Feb 2022), bibinfonumpages22 pages. https://doi.org/10.1145/3475799 Digital Library Google Scholar · DOI · Paper page
- [32][32] Minsuk Chang, Stefania Druga, Alexander J. Fiannaca, Pedro Vergani, Chinmay Kulkarni, Carrie J. Cai, and Michael Terry. 2023. The Prompt Artists. In Proceedings of the 15th Conference on Creativity and Cognition (Virtual Event, USA). Association for Computing Machinery, New York, NY, USA, 75--87. https://doi.org/10.1145/3591196.3593515 Digital Library Google Scholar · DOI
- [33][33] Kerry Chappell, Lindsay Hetherington, H Hermione Ruck Keene, Heather Wren, Angelos Alexopoulos, Oded Ben-Horin, Konstantinos Nikolopoulos, Janne Robberstad, Sofoklis Sotiriou, and Franz X. Bogner. 2019. Dialogue and Materiality/Embodiment in Science|Arts Creative Pedagogy: Their Role and Manifestation. Thinking Skills and Creativity, Vol. 31 (2019), 296--322. https://doi.org/10.1016/j.tsc.2018.12.008 Crossref Google Scholar · DOI
- [34][34] Mel Y. Chen. 2012. Animacies: Biopolitics, Racial Mattering, and Queer Affect. Duke University Press, Durham, NC. Google Scholar
- [35][35] Phillipa Chong. 2011. Reading Difference: How Race and Ethnicity Function as Tools for Critical Appraisal. Poetics, Vol. 39, 1 (2011), 64--84. https://doi.org/10.1016/j.poetic.2010.11.003 Crossref Google Scholar · DOI
- [36][36] Phillipa Chong. 2020. Inside the Critics' Circle. Princeton University Press, Princeton, New Jersey. Google Scholar
- [39][39] Adele E Clarke. 2005. Situational Analysis: Grounded Theory After the Postmodern Turn. Sage Publications, Thousand Oaks, California. Crossref Google Scholar
- [41][41] Paul Cohen. 2016. Harold Cohen and AARON. AI Magazine, Vol. 37, 4 (2016), 63--66. https://doi.org/10.1609/aimag.v37i4.2695 Digital Library Google Scholar · DOI
- [44][44] Kate Crawford. 2021. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, New Haven, Connecticut. Google Scholar
- [45][45] Bec Crew. 2020. Google Scholar Reveals its Most Influential Papers for 2020. Nature Index. https://www.nature.com/nature-index/news-blog/google-scholar-reveals-most-influential-papers-research-citations-twenty-twenty Accessed: 2024-02-02. Google Scholar
- [47][47] Alma L Culén, Henry N Mainsah, and Sisse Finken. 2014. Design, Creativity and Human-Computer Interaction Design Education. Journal on Advances in Life Science, Vol. 6, 3&4 (2014), 97--106. Google Scholar
- [48][48] Craig M. Dalton. 2020. Rhizomatic Data Assemblages: Mapping New Possibilities for Urban Housing Data. Urban Geography, Vol. 41, 8 (2020), 1090--1108. https://doi.org/10.1080/02723638.2019.1645553 Crossref Google Scholar · DOI
- [49][49] Antonio Daniele and Yi-Zhe Song. 2019. AI Art = Human. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (Honolulu, HI, USA) (AIES '19). Association for Computing Machinery, New York, NY, USA, 155--161. https://doi.org/10.1145/3306618.3314233 Digital Library Google Scholar · DOI
- [50][50] Manuel DeLanda. 2006. A New Philosophy of Society: Assemblage Theory and Social Complexity. Bloomsbury Publishing, London, U.K. Google Scholar
- [51][51] Giles Deleuze and Felix Guattari. 1987. A Thousand Plateaus: Capitalism and Schizophrenia. Trans. by Massumi, B.)., University of Minnesota, Minneapolis, Minnesota. Google Scholar
- [52][52] Greg d'Eon, Joslin Goh, Kate Larson, and Edith Law. 2019. Paying Crowd Workers for Collaborative Work. Proc. ACM Hum.-Comput. Interact., Vol. 3, CSCW, Article 125 (nov 2019), bibinfonumpages24 pages. https://doi.org/10.1145/3359227 Digital Library Google Scholar · DOI
- [53][53] Terrance DeVries, Ishan Misra, Changhan Wang, and Laurens van der Maaten. 2019. Does Object Recognition Work for Everyone? http://arxiv.org/abs/1906.02659 Google Scholar · arXiv
- [55][55] Steve Dixon. 2015. Digital Performance: A History of New Media in Theater, Dance, Performance Art, and Installation. MIT Press, Cambridge, Massachusetts. Google Scholar
- [56][56] Paul Dourish. 2016. Algorithms and Their Others: Algorithmic Culture in Context. Big Data & Society, Vol. 3, 2 (2016), 1--11. https://doi.org/10.1177/2053951716665128 Crossref Google Scholar · DOI · Paper page
- [57][57] Cameron Duff and Shanti Sumartojo. 2017. Assemblages of Creativity: Material Practices in the Creative Economy. Organization, Vol. 24, 3 (2017), 418--432. https://doi.org/10.1177/1350508416687765 Crossref Google Scholar · DOI
- [60][60] Ahmed M. Elgammal and Babak Saleh. 2015. Quantifying Creativity in Art Networks. showeprint[arXiv]1506.00711 http://arxiv.org/abs/1506.00711 Google Scholar · arXiv
- [62][62] Sarah Fdili Alaoui. 2019. Making an Interactive Dance Piece: Tensions in Integrating Technology in Art. In Proceedings of the 2019 on Designing Interactive Systems Conference (San Diego, CA, USA) (DIS '19). Association for Computing Machinery, New York, NY, USA, 1195--1208. https://doi.org/10.1145/3322276.3322289 Digital Library Google Scholar · DOI
- [63][63] Desiree Fields, David Bissell, and Rachel Macrorie. 2020. Platform Methods: Studying Platform Urbanism Outside the Black Box. Urban Geography, Vol. 41, 3 (2020), 462--468. https://doi.org/10.1080/02723638.2020.1730642 Crossref Google Scholar · DOI
- [65][65] Sisse Finken, Alma Leora Culén, and Andrea Gasparini. 2014. Nurturing Creativity: Assemblages in HCI Design Practices. In Design's Big Debates - DRS International Conference 2014. Design Research Society, Umea, Sweden, 1--14. Google Scholar
- [66][66] Association for Computing Machinery. 1981. SIGGRAPH 1981: Frame Buffer Show. Association for Computing Machinery. https://digitalartarchive.siggraph.org/exhibition/siggraph-1981-frame-buffer-show/ Google Scholar
- [67][67] Association for Computing Machinery. 1992. SIGGRAPH 1992: Art Show. Association for Computing Machinery. https://digitalartarchive.siggraph.org/exhibition/siggraph-1992-art-show/ Google Scholar
- [69][69] Jonas Frich, Michael Mose Biskjaer, and Peter Dalsgaard. 2018. Twenty Years of Creativity Research in Human-Computer Interaction: Current State and Future Directions. In Proceedings of the 2018 Designing Interactive Systems Conference (Hong Kong, China) (DIS '18). Association for Computing Machinery, New York, NY, USA, 1235--1257. https://doi.org/10.1145/3196709.3196732 Digital Library Google Scholar · DOI
- [70][70] Lisa Gitelman. 2013. Raw Data is an Oxymoron. MIT Press, Cambridge, Massachusetts. Crossref Google Scholar
- [71][71] Katherine Giuffre. 1999. Sandpiles of Opportunity: Success in the Art World. Social Forces, Vol. 77, 3 (1999), 815--832. https://doi.org/10.2307/3005962 Crossref Google Scholar · DOI
- [72][72] Vlad P Glua veanu. 2012. What Can Be Done with an Egg? Creativity, Material Objects, and the Theory of Affordances. The Journal of Creative Behavior, Vol. 46, 3 (2012), 192--208. https://doi.org/10.1002/jocb.13 Crossref Google Scholar · DOI
- [73][73] Vlad Petre Glua veanu. 2015. Creativity as a Sociocultural Act. The Journal of Creative Behavior, Vol. 49, 3 (2015), 165--180. https://doi.org/10.1002/jocb.94 Crossref Google Scholar · DOI
- [74][74] Frédéric C. Godart and Charles Galunic. 2019. Explaining the Popularity of Cultural Elements: Networks, Culture, and the Structural Embeddedness of High Fashion Trends. Organization Science, Vol. 30, 1 (2019), 151--1168. https://doi.org/10.1287/orsc.2018.1234 Digital Library Google Scholar · DOI
- [75][75] Gernot Grabher. 2018. Marginality as Strategy: Leveraging Peripherality for Creativity. Environment and Planning A: Economy and Space, Vol. 50, 8 (2018), 1785--1794. https://doi.org/10.1177/0308518X18784021 Crossref Google Scholar · DOI
- [76][76] Alex Hanna and Tina M. Park. 2020. Against Scale: Provocations and Resistances to Scale Thinking. arxiv: 2010.08850 [cs.CY] Google Scholar · arXiv
- [77][77] Donna Haraway. 1997. Modest_Witness@ Second_Millenium: FemaleMan_Meets_OncoMouse: Feminism and Tehnoscience. Routledge, New York, NY. Google Scholar
- [81][81] Kathryn Henne, Renee Shelby, and Jenna Harb. 2021. The Datafication of #MeToo: Whiteness, Racial Capitalism, and Anti-Violence Technologies. Big Data & Society, Vol. 8, 2 (2021), 1--12. https://doi.org/10.1177/20539517211055898 Crossref Google Scholar · DOI
- [82][82] Anna Hickey-Moody and Marissa Willcox. 2019. Entanglements of Difference as Community Togetherness: Faith, Art and Feminism. Social Sciences, Vol. 8, 9 (2019), 1--21. https://doi.org/10.3390/socsci8090264 Crossref Google Scholar · DOI
- [83][83] Hannah Higgins and Douglas Kahn. 2012. Mainframe Experimentalism: Early Computing and the Foundations of the Digital Arts. University of California Press, Berkeley, California. Crossref Google Scholar
- [84][84] Stephanie Hoebeke, Ingri Strand, and Peter Haakonsen. 2021. Programming as a New Creative Material in Art and Design Education. Techne serien - Forskning i slöjdpedagogik och slöjdvetenskap, Vol. 28, 2 (Aug. 2021), 233--240. https://journals.oslomet.no/index.php/techneA/article/view/4325 Google Scholar
- [85][85] Anna Lauren Hoffmann. 2021. Terms of Inclusion: Data, Discourse, Violence. New Media & Society, Vol. 23, 12 (2021), 3539--3556. https://doi.org/10.1177/1461444820958725 Crossref Google Scholar · DOI
- [86][86] Bas Hofstra, Vivek V. Kulkarni, Sebastian Munoz-Najar Galvez, Bryan He, Dan Jurafsky, and Daniel A. McFarland. 2020. The Diversity--Innovation Paradox in Science. Proceedings of the National Academy of Sciences, Vol. 117, 17 (2020), 9284--9291. https://doi.org/10.1073/pnas.1915378117 Crossref Google Scholar · DOI
- [87][87] Cheng-Zhi Anna Huang, Hendrik Vincent Koops, Ed Newton-Rex, Monica Dinculescu, and Carrie J. Cai. 2020. AI Song Contest: Human-AI Co-Creation in Songwriting. showeprint[arXiv]2010.05388 https://arxiv.org/abs/2010.05388 Google Scholar · arXiv
- [90][90] Lise Jaillant. 2022. How Can We Make Born-Digital and Digitised Archives More Accessible? Identifying Obstacles and Solutions. Archival Science, Vol. 22 (2022), 417--436. https://doi.org/10.1007/s10502-022-09390--7 Crossref Google Scholar · DOI
- [91][91] Sheila Jasanoff. 2017. Virtual, Visible, and Actionable: Data Assemblages and the Sightlines of Justice. Big Data & Society, Vol. 4, 2 (2017), 1--15. https://doi.org/10.1177/2053951717724477 Crossref Google Scholar · DOI
- [94][94] Mirabelle Jones, Christina Neumayer, and Irina Shklovski. 2023. Embodying the Algorithm: Exploring Relationships with Large Language Models Through Artistic Performance. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI '23). Association for Computing Machinery, New York, NY, USA, Article 654, bibinfonumpages24 pages. https://doi.org/10.1145/3544548.3580885 Digital Library Google Scholar · DOI
- [96][96] Eden Kinkaid. 2020. Can Assemblage Think Difference? A Feminist Critique of Assemblage Geographies. Progress in Human Geography, Vol. 44, 3 (2020), 457--472. https://doi.org/10.1177/0309132519836162 Crossref Google Scholar · DOI
- [97][97] Rob Kitchin. 2017. Thinking Critically About and Researching Algorithms. Information, Communication & Society, Vol. 20, 1 (2017), 14--29. https://doi.org/10.1080/1369118X.2016.1154087 Crossref Google Scholar · DOI
- [98][98] Yubo Kou and Colin M. Gray. 2017. Supporting Distributed Critique through Interpretation and Sense-Making in an Online Creative Community. Proc. ACM Hum.-Comput. Interact., Vol. 1, CSCW, Article 60 (dec 2017), bibinfonumpages18 pages. https://doi.org/10.1145/3134695 Digital Library Google Scholar · DOI
- [99][99] Bruno Latour. 2007. Reassembling the Social: An Introduction to Actor-Network-Theory. Oxford University Press, Oxford, UK. Crossref Google Scholar
- [100][100] Jennifer C. Lena. 2004. Meaning and Membership: Samples in Rap Music, 1979--1995. Poetics, Vol. 41, 3--4 (2004), 297--310. https://doi.org/10.1016/j.poetic.2004.05.006 Crossref Google Scholar · DOI
- [101][101] Jennifer C. Lena and Danielle J. Lindemann. 2014. Who is an Artist? New Data for an Old Question. Poetics, Vol. 43 (2014), 70--85. https://doi.org/10.1016/j.poetic.2014.01.001 Crossref Google Scholar · DOI
- [102][102] Jennifer C. Lena and Mark C. Pachucki. 2013. The Sincerest Form of Flattery: Innovation, Repetition, and Status in an Art Movement. Poetics, Vol. 41, 3 (2013), 236--264. https://doi.org/10.1016/j.poetic.2013.02.002 Crossref Google Scholar · DOI
- [104][104] Golan Levin and Tega Brain. 2021. Code as Creative Medium: A Handbook for Computational Art and Design. MIT Press, Cambridge, MA. Google Scholar
- [105][105] Tsung-Yi Lin, Michael Maire, Serge J. Belongie, Lubomir D. Bourdev, Ross B. Girshick, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollá r, and C. Lawrence Zitnick. 2014. Microsoft COCO: Common Objects in Context. showeprint[arXiv]1405.0312 http://arxiv.org/abs/1405.0312 Google Scholar · arXiv
- [106][106] Ziwei Liu, Ping Luo, Shi Qiu, Xiaogang Wang, and Xiaoou Tang. 2016. DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Las Vegas, Nevada, 1096--1104. https://doi.org/10.1109/CVPR.2016.124 Crossref Google Scholar · DOI
- [107][107] Michele Loi, Eleonora Viganò, and Lonneke van der Plas. 2020. The Societal and Ethical Relevance of Computational Creativity. showeprint[arXiv]2007.11973 https://arxiv.org/abs/2007.11973 Google Scholar · arXiv
- [108][108] 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 (Honolulu, HI, USA) (CHI '20). Association for Computing Machinery, New York, NY, USA, 1--13. https://doi.org/10.1145/3313831.3376739 Digital Library Google Scholar · DOI · Paper page
- [110][110] Mary Lou Maher. 2010. Evaluating Creativity in Humans, Computers, and Collectively Intelligent Systems. In Proceedings of the 1st DESIRE Network Conference on Creativity and Innovation in Design (Aarhus, Denmark) (DESIRE '10). Desire Network, Lancaster, GBR, 22--28. Digital Library Google Scholar
- [111][111] Lindiwe Brigitte Malobola, Negar Rostamzadeh, and Shakir Mohamed. 2022. se-Shweshwe Inspired Fashion Generation. arxiv: 2203.00435 [cs.CV] Google Scholar · arXiv
- [112][112] Adina Manta. 2018. Demystifying Creativity: An Assemblage Perspective Towards Artistic Creativity. Creativity Studies, Vol. 11, 1 (2018), 85--101. https://doi.org/10.3846/cs.2018.542 Crossref Google Scholar · DOI
- [113][113] Phillip Mar and Kay Anderson. 2010. The Creative Assemblage: Theorizing Contemporary Forms of Arts-based Collaboration. Journal of Cultural Economy, Vol. 3, 1 (2010), 35--51. https://doi.org/10.1080/17530351003617560 Crossref Google Scholar · DOI
- [114][114] Marian Mazzone and Ahmed Elgammal. 2019. Art, Creativity, and the Potential of Artificial Intelligence. Arts, Vol. 8, 1 (2019), 1--9. https://doi.org/10.3390/arts8010026 Crossref Google Scholar · DOI
- [115][115] Eugene McCann and Kevin Ward. 2012. Assembling Urbanism: Following Policies and ?Studying Through' the Sites and Situations of Policy Making. Environment and Planning A, Vol. 44, 1 (2012), 42--51. https://doi.org/10.1068/a44178 Crossref Google Scholar · DOI
- [116][116] Jon McCormack, Oliver Bown, Alan Dorin, Jonathan McCabe, Gordon Monro, and Mitchell Whitelaw. 2014. Ten Questions Concerning Generative Computer Art. Leonardo, Vol. 47, 2 (2014), 135--141. https://www.jstor.org/stable/43834149 Crossref Google Scholar
- [117][117] Patrick W. McCray. 2020. Making Art Work: How Cold War Engineers and Artists Forged a New Creative Culture. MIT Press, Cambridge, Massachusetts. Google Scholar
- [118][118] Colin McFarlane. 2011. Assemblage and Critical Urbanism. City, Vol. 15, 2 (2011), 204--224. https://doi.org/10.1080/13604813.2011.568715 Crossref Google Scholar · DOI
- [119][119] Paul D. Miller. 2008. Sound Unbound: Sampling Digital Music and Culture. MIT Press, Boston, MA. Crossref Google Scholar
- [120][120] Banerjee Mitali and Paul L. Ingram. 2018. Fame as an Illusion of Creativity: Evidence from the Pioneers of Abstract Art. Technical Report 18--74. HEC Paris Research Paper No. SPE-2018--1305, Columbia Business School Research Paper. https://doi.org/10.2139/ssrn.3258318 Crossref Google Scholar · DOI
- [121][121] Andrées Monroy-Hernáandez and Frances Yun. 2012. A Monkey and a Stick Figure: Stories of Remixing and Social Creativity. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work Companion (Seattle, Washington, USA) (CSCW '12). Association for Computing Machinery, New York, NY, USA, 51--52. https://doi.org/10.1145/2141512.2141538 Digital Library Google Scholar · DOI
- [124][124] Michelle Murphy. 2006. Sick Building Syndrome and the Problem of Uncertainty: Environmental Politics, Technoscience, and Women Workers. Duke University Press, Durham, North Carolina. Google Scholar
- [125][125] Laine Nooney. 2023. The Apple II Age: How the Computer Became Personal. University of Chicago Press, Chicago, Illinois. Google Scholar
- [126][126] Jonas Oppenlaender, Aku Visuri, Kristy Milland, Panos Ipeirotis, and Simo Hosio. 2020. What Do Crowd Workers Think About Creative Work?showeprint[arXiv]2002.10887 https://arxiv.org/abs/2002.10887 Google Scholar · arXiv
- [127][127] Pat Pataranutaporn, Valdemar Danry, Joanne Leong, Parinya Punpongsanon, Dan Novy, Pattie Maes, and Misha Sra. 2021. AI-generated Characters for Supporting Personalized Learning and Well-Being. Nature Machine Intelligence, Vol. 3 (2021), 1013--1022. https://doi.org/10.1038/s42256-021-00417--9 Crossref Google Scholar · DOI
- [128][128] Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, and Alex Hanna. 2021. Data and its (Dis) Contents: A Survey of Dataset Development and Use in Machine Learning Research. Patterns, Vol. 2, 11 (2021), 1--14. https://doi.org/10.1016/j.patter.2021.100336 Crossref Google Scholar · DOI · Paper page
- [129][129] Craig Plain. 2007. Build an Affinity for KJ Method. Quality Progress, Vol. 40, 3 (2007), 88. Google Scholar
- [130][130] Matthew Plummer-Fernandez. 2019. The Art of Bots: A Practice-based Study of the Multiplicity, Entanglements and Figuration of Sociocomputational Assemblages. Ph.,D. Dissertation. Goldsmiths, University of London. Google Scholar
- [132][132] Helen Pritchard and Jane Prophet. 2015. Diffractive Art Practices: Computation and the Messy Entanglements Between Mainstream Contemporary Art, and New Media Art. Artnodes: Revista de Arte, Ciencia y Tecnolog'ia, Vol. 0, 15 (2015), 5--14. https://doi.org/10.7238/issn.1695--5951 Crossref Google Scholar · DOI
- [133][133] Jasbir K Puar. 2020. I Would Rather be a Cyborg than a Goddess:" Becoming-Intersectional in Assemblage Theory. In Feminist Theory Reader. Routledge, New York, New York, Chapter 47, 405--415. Google Scholar
- [134][134] Rida Qadri, Renee Shelby, Cynthia L. Bennett, and Emily Denton. 2023. AI's Regimes of Representation: A Community-Centered Study of Text-to-Image Models in South Asia. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (Chicago, IL, USA) (FAccT '23). Association for Computing Machinery, New York, NY, USA, 506--517. https://doi.org/10.1145/3593013.3594016 Digital Library Google Scholar · DOI · Paper page
- [135][135] Emily Rafferty and Becca Pad. 2016. Better Together: A Holistic Approach to Creating a Digital Preservation Policy in an Art Museum. Art Documentation, Vol. 36, 1 (2016), 149--162. https://doi.org/10.1086/691378 Crossref Google Scholar · DOI
- [136][136] Norma M. Rantisi and Deborah Leslie. 2010. Materiality and Creative Production: The Case of the Mile End Neighborhood in Montréal. Environment and Planning A, Vol. 42, 12 (2010), 2824--2841. https://doi.org/10.1068/a4310 Crossref Google Scholar · DOI
- [137][137] Janice Rieger and Megan Strickfaden. 2018. Dis/ordered Assemblages of Disability in Museums. Routledge, London, England, Chapter 4, 48--61. Google Scholar
- [139][139] Gabriel Rossman, Nicole Esparza, and Phillip Bonacich. 2010. I'd Like to Thank the Academy, Team Spillovers, and Network Centrality. American Sociological Review, Vol. 75, 1 (2010), 31--51. https://doi.org/10.1177/0003122409359164 Crossref Google Scholar · DOI
- [140][140] Negar Rostamzadeh, Emily Denton, and Linda Petrini. 2021. Ethics and Creativity in Computer Vision. arxiv: 2112.03111 [cs.CV] Google Scholar · arXiv
- [141][141] Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet, Wojciech Stokowiec, Ying Zhang, Christian Jauvin, and Chris Pal. 2018. Fashion-Gen: The Generative Fashion Dataset and Challenge. arxiv: 1806.08317 [stat.ML] Google Scholar · arXiv
- [144][144] Pedro Sanches, Noura Howell, Vasiliki Tsaknaki, Tom Jenkins, and Karey Helms. 2022. Diffraction-in-Action: Designerly Explorations of Agential Realism Through Lived Data. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 540, bibinfonumpages18 pages. https://doi.org/10.1145/3491102.3502029 Digital Library Google Scholar · DOI
- [145][145] Téo Sanchez. 2023. Examining the Text-to-Image Community of Practice: Why and How Do People Prompt Generative AIs?. In Proceedings of the 15th Conference on Creativity and Cognition (Virtual Event, USA) (C&C '23). Association for Computing Machinery, New York, NY, USA, 43--61. https://doi.org/10.1145/3591196.3593051 Digital Library Google Scholar · DOI
- [147][147] Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev. 2022. LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models. arxiv: 2210.08402 [cs.CV] Google Scholar · arXiv
- [148][148] Hugo Scurto, Baptiste Caramiaux, and Frederic Bevilacqua. 2021. Prototyping Machine Learning Through Diffractive Art Practice. In Designing Interactive Systems Conference 2021 (Virtual Event, USA) (DIS '21). Association for Computing Machinery, New York, NY, USA, 2013--2025. https://doi.org/10.1145/3461778.3462163 Digital Library Google Scholar · DOI
- [149][149] Hugo Scurto and Ludmila Postel. 2023. Soundwalking Deep Latent Spaces. In Proceedings of the 23rd International Conference on New Interfaces for Musical Expression (NIME'23). The International Conference on New Interfaces for Musical Expression, Mexico, Mexico, 1--4. https://hal.science/hal-04108997 Google Scholar
- [150][150] Stoyan V. Sgourev and Niek Althuizen. 2014. Notable" or Not Able" When Are Acts of Inconsistency Rewarded?. American Sociological Review, Vol. 79, 2 (2014), 282--302. https://doi.org/10.1177/0003122414524575 Crossref Google Scholar · DOI
- [151][151] Hanieh Shakeri, Carman Neustaedter, and Steve DiPaola. 2021. SAGA: Collaborative Storytelling with GPT-3. In Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing (Virtual Event, USA) (CSCW '21). Association for Computing Machinery, New York, NY, USA, 163--166. https://doi.org/10.1145/3462204.3481771 Digital Library Google Scholar · DOI · Paper page
- [152][152] Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N'Mah Yilla-Akbari, Jess Gallegos, Andrew Smart, Emilio Garcia, and Gurleen Virk. 2023. Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (Montréal, QC, Canada) (AIES '23). Association for Computing Machinery, New York, NY, USA, 723--741. https://doi.org/10.1145/3600211.3604673 Digital Library Google Scholar · DOI · Paper page
- [153][153] Disha Shrivastava, C. G. Saneem Ahmed, Anirban Laha, and Karthik Sankaranarayanan. 2017. A Machine Learning Approach for Evaluating Creative Artifacts. showeprint[arXiv]1707.05499 http://arxiv.org/abs/1707.05499 Google Scholar · arXiv
- [154][154] Susan Elliott Sim, Marisa Leavitt Cohn, and Kavita Philip. 2009. The Work of Software Development as an Assemblage of Computational Practice. In Proceedings of the 2009 ICSE Workshop on Cooperative and Human Aspects on Software Engineering (CHASE '09). IEEE Computer Society, USA, 92--95. https://doi.org/10.1109/CHASE.2009.5071419 Digital Library Google Scholar · DOI
- [155][155] Geneva Smitherman. 1997. The Chain Remain the Same" Communicative Practices in the Hip Hop Nation. Journal of Black Studies, Vol. 28, 1 (1997), 3--25. https://doi.org/10.1177/002193479702800101 Crossref Google Scholar · DOI
- [158][158] Andreas Spitz and Em?ke Ágnes Horvát. 2014. Measuring Long-Term Impact Based on Network Centrality: Unraveling Cinematic Citations. PloS ONE, Vol. 9, 10 (2014), 1--12. https://doi.org/10.1371/journal.pone.0108857 Crossref Google Scholar · DOI
- [159][159] Ramya Srinivasan and Kanji Uchino. 2020. Biases in Generative Art - A Causal Look from the Lens of Art History. showeprint[arXiv]2010.13266 https://arxiv.org/abs/2010.13266 Google Scholar · arXiv
- [161][161] Luke Stark and Kate Crawford. 2019. The Work of Art in the Age of Artificial Intelligence: What Artists Can Teach us About the Ethics of Data Practice. Surveillance & Society, Vol. 17, 3/4 (2019), 442--455. https://doi.org/10.24908/ss.v17i3/4.10821 Crossref Google Scholar · DOI
- [162][162] Alina Striner, Thomas Röggla, Mikel Zorrilla, Sergio Cabrero Barros, Stefano Masneri, Héctor Rivas Pagador, Irene Calvis, Jie Li, and Pablo Cesar. 2022. The Co-Creation Space: Supporting Asynchronous Artistic Co-Creation Dynamics. In Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing (Virtual Event, Taiwan) (CSCW'22 Companion). Association for Computing Machinery, New York, NY, USA, 18--22. https://doi.org/10.1145/3500868.3559459 Digital Library Google Scholar · DOI
- [163][163] Neural Information Processing Systems. 2022. Competitions. Neural Information Processing Systems. https://nips.cc/virtual/2022/events/competition Google Scholar
- [164][164] Grant D Taylor. 2014. When the Machine Made Art: The Troubled History of Computer Art. Bloomsbury Publishing, New York, New York. Google Scholar
- [166][166] Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, and Asanobu Kitamoto. 2020. KaoKore: A Pre-modern Japanese Art Facial Expression Dataset. showeprint[arXiv]2002.08595 https://arxiv.org/abs/2002.08595 Google Scholar · arXiv
- [167][167] Fran Tonkiss. 2011. Template Urbanism: Four Points About Assemblage. City, Vol. 15, 5 (2011), 584--588. https://doi.org/10.1080/1369118X.2019.1612933 Crossref Google Scholar · DOI
- [168][168] Yu-Shan Tseng. 2022. Assemblage Thinking as a Methodology for Studying Urban AI Phenomena. AI & Society, Vol. 38 (2022), 1099--1110. https://doi.org/10.1007/s00146-022-01500--4 Digital Library Google Scholar · DOI
- [169][169] Emiel van Miltenburg. 2016. Stereotyping and Bias in the Flickr30K Dataset. showeprint[arXiv]1605.06083 http://arxiv.org/abs/1605.06083 Google Scholar · arXiv
- [171][171] Ágnes Horvát. 2019. Gender Differences in the Global Music Industry: Evidence from Musicbrainz and the Echo Nest. Proceedings of the International AAAI Conference on Web and Social Media, Vol. 13, 1 (2019), 517--526. https://doi.org/10.1609/icwsm.v13i01.3249 Crossref Google Scholar · DOI
- [172][172] Emma Waterton and Jason Dittmer. 2014. The Museum as Assemblage: Bringing Forth Affect at the Australian War Memorial. Museum Management and Curatorship, Vol. 29, 2 (2014), 122--139. https://doi.org/10.1080/09647775.2014.888819 Crossref Google Scholar · DOI
- [174][174] Alex Wilkie, William Gaver, Drew Hemment, and Gabriella Giannachi. 2010. Creative Assemblages: Organisation and Outputs of Practice-led Research. Leonardo, Vol. 43, 1 (2010), 98--99. https://doi.org/10.1162/leon.2010.43.1.98 Crossref Google Scholar · DOI
- [175][175] J. Macgregor Wise. 2017. Assemblage. New York University Press, New York, New York, 16--17. Google Scholar
- [176][176] Susan Wright and Cris Shore. 1997. Policy: A New Field of Anthropology. Routledge, London, UK, Chapter 1, 1--39. Google Scholar
- [177][177] Daniel Zhang, Saurabh Mishra, Erik Brynjolfsson, John Etchemendy, Deep Ganguli, Barbara Grosz, Terah Lyons, James Manyika, Juan Carlos Niebles, Michael Sellitto, Yoav Shoham, Jack Clark, and Raymond Perrault. 2021. The AI Index 2021 Annual Report. arxiv: 2103.06312 [cs.AI] Google Scholar · arXiv
- [179][179] Xiaomu Zhou, Mark Ackerman, and Kai Zheng. 2011. CPOE Workarounds, Boundary Objects, and Assemblages. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI '11). Association for Computing Machinery, New York, NY, USA, 3353--3362. https://doi.org/10.1145/1978942.1979439 Digital Library Google Scholar · DOI
- [180][180] Gregory Zobel. 2013. Engaging Complexity in Usability through Assemblage. Commun. Des. Q. Rev, Vol. 1, 3 (Apr 2013), 18--22. https://doi.org/10.1145/2466489.2466494 Digital Library Google Scholar · DOI
- [181][181] Zack Zwiezen. 2022. Rick and Morty Creator Used Controversial AI Art, Voice Acting In New Shooter. Kotaku. https://kotaku.com/high-on-life-justin-roiland-ai-art-rick-morty-1849900835 Accessed: 2024-02-02. io Google Scholar Cited By View all Bomba FDe Angeli A(2026)Agency and authorship in AI artInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2025.103652205:COnline publication date: 27-May-2026 https://dl.acm.org/doi/10.1016/j.ijhcs.2025.103652 Sanchez TDzhimova MHsueh SFdili Alaoui SSungeelee VCaramiaux B(2026)Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine LearningProceedings of the 2026 CHI Conference on Human Factors in Computing Systems10.1145/3772318.3790398(1-17)Online publication date: 13-Apr-2026 https://dl.acm.org/doi/10.1145/3772318.3790398 Lin CLiu C(2026)Artificial creativity and agency negotiation: Understanding AI-generated visual art from artistic practitioners’ perceptionsConvergence: The International Journal of Research into New Media Technologies10.1177/1354856526141731532:3(757-774)Online publication date: 12-Jan-2026 https://doi.org/10.1177/13548565261417315 Show More Cited By Index Terms Index Terms (Premium feature) Creative ML Assemblages: The Interactive Politics of People, Processes, and Products Computing methodologies Artificial intelligence Social and professional topics Recommendations Recommendations (Premium feature) Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction CHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems Understanding how communities experience algorithms is necessary to mitigate potential harmful impacts. This paper presents folk theories of text-to-image (T2I) models to enrich understanding of how artist communities experience creative machine ... Read More "Explorers of Unknown Planets": Practices and Politics of Artificial Intelligence in Visual Arts CSCW Alongside recent advances in artificial intelligence (AI), a new art practice has emerged in recent years that borrows and transforms these advances in the production of artworks. The actors of this emergent practice are coming from contemporary art, ... Read More Artists and AI: Creative Interactions and Tensions CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems Advancements in artificial intelligence (AI) technologies have enabled new forms of artwork production. Artists engaged with AI have developed individual practices within their field. In this paper, we present a qualitative study to explore the tensions ... Read More Comments Comments (Premium feature) Information & Contributors Information Published In cover image Proceedings of the ACM on Human-Computer Interaction Proceedings of the ACM on Human-Computer Interaction Volume 8, Issue CSCW1 CSCW April 2024 · DOI
- Authors
- Shelby, R., Srinivasan, R., Burgdorf, K., Lena, J. C., & Rostamzadeh, N.
- Affiliations
- Australian National University (AU)
- Fujitsu (United States) (US)
- University of Bremen (DE)
- Columbia University (US)
- Google Research, Montréal, Montréal, QC, Canada
- Venue
- Proceedings of the ACM on Human-Computer Interaction
- Published
- 2024-04-17
- Volume
- 8
- Issue
- CSCW1
- Pages
- 1-30
- ISSN
- 2573-0142 (ISSN-L)
- OpenAlex
- W4396230946
- Cited by
- 6
- References
- 104
- Citations by year
- 2026: 1 · 2025: 5
- FWCI
- 23.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the ACM on Human-Computer Interaction (publishedVersion, cc-by)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Keywords
- assemblage theory, algorithmic art, human-AI interaction, collaborative systems, creative process, societal impact of AI, art and technology, intervention points
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review