ABSTRACT
The field of machine learning (ML) has long struggled with a principles-to-practice gap, whereby careful codes and commitments dissipate on their way to practical application. The present work bridges this gap through an applied affordance framework. ‘Affordances’ are how the features of a technology shape, but do not determine, the functions and effects of that technology. Here, I demonstrate the value of an affordance framework as applied to ML, considering ML systems through the prism of design studies. Specifically, I apply the mechanisms and conditions framework of affordances, which models the way technologies request, demand, encourage, discourage, refuse, and allow technical and social outcomes. Illustrated through three case examples across work, policing, and housing justice, the mechanisms and conditions framework reveals the social nature of technical choices, clarifying how and for whom those choices manifest. This approach displaces vagaries and general claims with the particularities of systems in context, empowering critically minded practitioners while holding power—and the systems power relations produce—to account. More broadly, this work pairs the design studies tradition with the ML domain, setting a foundation for deliberate and considered (re)making of sociotechnical futures.
- Schiff, D., Rakova, B., Ayesh, A., Fanti, A. and Lennon, M. Explaining the principles to practices gap in AI. IEEE Technology and Society Magazine, 40, 2 (2021), 81-94.Google ScholarCross Ref
- Morley, J., Floridi, L., Kinsey, L. and Elhalal, A. From what to how: an initial review of publicly available AI ethics tools, methods and research to translate principles into practices. Science and engineering ethics, 26, 4 (2020), 2141-2168.Google Scholar
- Mittelstadt, B. Principles alone cannot guarantee ethical AI. Nature machine intelligence, 1, 11 (2019), 501-507.Google Scholar
- Pucillo, F. and Cascini, G. A framework for user experience, needs and affordances. Design Studies, 35, 2 (2014), 160-179.Google ScholarCross Ref
- Hartson, R. and Pyla, P. S. The UX Book: Process and guidelines for ensuring a quality user experience. Elsevier, Waltham, MA, 2012.Google ScholarDigital Library
- Hildebrandt, M. Smart technologies and the end (s) of law: novel entanglements of law and technology. Edward Elgar Publishing, NY, 2015.Google ScholarCross Ref
- Calo, R. Can Americans resist surveillance. U. Chi. L. Rev., 83 (2016), 23-44.Google Scholar
- Diver, L. Law as a user: design, affordance, and the technological mediation of norms. SCRIPTed, 15 (2018), 4-41.Google ScholarCross Ref
- Norman, D. A. The Design Of Everyday Things. MIT, London, 1998.Google Scholar
- Scacchi, W. Collaboration practices and affordances in free/open source software development. Springer, City, 2010.Google ScholarCross Ref
- Lucchesi, L. R., Kuhnert, P. M., Davis, J. L. and Xie, L. Smallset Timelines: A Visual Representation of Data Preprocessing Decisions. City, 2022.Google Scholar
- Faraj, S. and Azad, B. The materiality of technology: An affordance perspective. Oxford University Press, City, 2012.Google Scholar
- Kaptelinin, V. and Nardi, B. Affordances in HCI: toward a mediated action perspective. City, 2012.Google Scholar
- Hartson, R. Cognitive, physical, sensory, and functional affordances in interaction design. Behaviour & information technology, 22, 5 (2003), 315-338.Google Scholar
- Şahin, E., Cakmak, M., Doğar, M. R., Uğur, E. and Üçoluk, G. To afford or not to afford: A new formalization of affordances toward affordance-based robot control. Adaptive Behavior, 15, 4 (2007), 447-472.Google ScholarDigital Library
- Min, H., Luo, R., Zhu, J. and Bi, S. Affordance research in developmental robotics: A survey. IEEE Transactions on Cognitive and Developmental Systems, 8, 4 (2016), 237-255.Google ScholarCross Ref
- Maier, J. R. and Fadel, G. M. Affordance-based design methods for innovative design, redesign and reverse engineering. Research in Engineering Design, 20, 4 (2009), 225-239.Google Scholar
- Maier, J. R. and Fadel, G. M. Affordance: the fundamental concept in engineering design. American Society of Mechanical Engineers, City, 2001.Google Scholar
- Arbib, M. A. When brains meet buildings. Oxford University Press, Oxford, UK, 2021.Google ScholarCross Ref
- Maier, J. R., Fadel, G. M. and Battisto, D. G. An affordance-based approach to architectural theory, design, and practice. Design Studies, 30, 4 (2009), 393-414.Google ScholarCross Ref
- Koutamanis, A. Buildings and affordances. Springer, City, 2006.Google ScholarCross Ref
- Goodyear, P. Realising the Good University: Social Innovation, Care, Design Justice and Educational Infrastructure. Postdigital Science and Education, 4, 1 (2022), 33-56.Google Scholar
- Cochrane, T. and Bateman, R. Smartphones give you wings: Pedagogical affordances of mobile Web 2.0. Australasian Journal of Educational Technology, 26, 1 (2010).Google ScholarCross Ref
- Dickey, M. D. Teaching in 3D: Pedagogical affordances and constraints of 3D virtual worlds for synchronous distance learning. Distance education, 24, 1 (2010), 105-121.Google Scholar
- Davis, J. L. How Artifacts Afford: The Power and Politics of Everyday Things. MIT Press, Cambridge, MA, 2020.Google ScholarCross Ref
- Chemero, A. An Outline Of A Theory Of Affordances. Ecological Psychology, 15, 2 (2003), 181-195.Google ScholarCross Ref
- Evans, S. K., Pearce, K. E., Vitak, J. and Treem, J. W. Explicating Affordances: A Conceptual Framework For Understanding Affordances In Communication Research. J. Comp.-Med. Commun., 22, 1 (2017), 35-52.Google ScholarDigital Library
- Faraj, S. and Azad, B. The Materiality Of Technology: An Affordance Perspective. Materiality And Organizing: Social Interaction In A Technological World (2012), 237-258.Google Scholar
- Gaver, W. W. Technology Affordances. ACM, City, 1991.Google Scholar
- Gibson, J. The Ecological Approach To Visual Perception: Classic Edition. Psychology Press, New York, 2014 [1979].Google ScholarCross Ref
- Davis, J. L. and Chouinard, J. B. Theorizing Affordances: From Request To Refuse. Bulletin Of Science, Technology & Society, 36, 4 (2016), 241-248.Google Scholar
- Escobar, A. Designs for the pluriverse: Radical interdependence, autonomy, and the making of worlds. Duke University Press, Durham, NC, 2018.Google ScholarCross Ref
- Winner, L. Do Artifacts Have Politics? Daedalus, 109, 1 (1980), 121-136.Google Scholar
- Suchman, L., Blomberg, J., Orr, J. E. and Trigg, R. Reconstructing technologies as social practice. Routledge, City, 2017.Google ScholarCross Ref
- Rosenberger, R. Callous objects: Designs against the homeless. U of Minnesota Press, 2017.Google ScholarCross Ref
- Acquisti, A., Adjerid, I., Balebako, R., Brandimarte, L., Cranor, L. F., Komanduri, S., Leon, P. G., Sadeh, N., Schaub, F. and Sleeper, M. Nudges for privacy and security: Understanding and assisting users’ choices online. ACM Computing Surveys (CSUR), 50, 3 (2017), 1-41.Google ScholarDigital Library
- Roth, L. Looking at Shirley, the ultimate norm: Colour balance, image technologies, and cognitive equity. Canadian Journal of Communication, 34, 1 (2009), 111-136.Google ScholarCross Ref
- Mulvin, D. Proxies: The cultural work of standing in. MIT, Cambridge, MA, 2021.Google Scholar
- Willis, A.-M. Ontological designing. Design philosophy papers, 4, 2 (2006), 69-92.Google Scholar
- Amoore, L. Cloud ethics. Duke University Press, 2020.Google Scholar
- Joyce, K., Smith-Doerr, L., Alegria, S., Bell, S., Cruz, T., Hoffman, S. G., Noble, S. U. and Shestakofsky, B. Toward a Sociology of Artificial Intelligence: A Call for Research on Inequalities and Structural Change. Socius, 7 (2021), 2378023121999581.Google ScholarCross Ref
- D'Ignazio, C. and Klein, L. F. Data feminism. MIT Press, Cambridge, MA, 2020.Google ScholarCross Ref
- Noble, S. U. Algorithms Of Oppression: How Search Engines Reinforce Racism. NYU Press, New York, 2018.Google ScholarCross Ref
- Eubanks, V. Automating Inequality: How High-Tech Tools Profile, Police, And Punish The Poor. St. Martin's Press, New York, 2018.Google Scholar
- O'Neil, C. Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy. Broadway Books, NY, 2016.Google ScholarDigital Library
- Broussard, M. Artificial unintelligence: How computers misunderstand the world. MIT Press, Cambridge, MA, 2018.Google ScholarCross Ref
- Chun, W. H. K. Discriminating data: Correlation, neighborhoods, and the new politics of recognition. MIT Press, Cambridge, MA, 2021.Google ScholarCross Ref
- Davis, J. L., Williams, A. and Yang, M. W. Algorithmic reparation. Big Data & Society, 8, 2 (2021).Google ScholarCross Ref
- Greene, D., Hoffmann, A. L. and Stark, L. Better, nicer, clearer, fairer: A critical assessment of the movement for ethical artificial intelligence and machine learning. City, 2019.Google Scholar
- Ricaurte, P. Ethics for the majority world: AI and the question of violence at scale. Media, Culture & Society (2022).Google Scholar
- Benjamin, R. Viral Justice: How We Grow the World We Want. Princeton University Press, Princeton, NJ, 2022.Google Scholar
- Benjamin, R. Race after technology: Abolitionist tools for the new jim code. Polity, Medford, MA, 2019.Google Scholar
- Costanza-Chock, S. Design justice: Community-led practices to build the worlds we need. MIT Press, Cambridge, MA, 2020.Google ScholarCross Ref
- Norman, D. A. The Psychology Of Everyday Things. Basic Books, New York, 1988.Google Scholar
- Ciavola, B. T. and Gershenson, J. K. Affordance Theory For Engineering Design. Research In Engineering Design, 27, 3 (2016), 251-263.Google Scholar
- Hutchby, I. Technologies, Texts And Affordances. Sociology, 35, 2 (2001), 441-456.Google Scholar
- Ingold, T. Back To The Future With The Theory Of Affordances. Hau: Journal Of Ethnographic Theory, 8, 1-2 (2018), 39-44.Google Scholar
- Maier, J. R. and Fadel, G. M. Affordance-Based Design Methods For Innovative Design, Redesign And Reverse Engineering. Research In Engineering Design, 20, 4 (2009), 225.Google Scholar
- McGrenere, J. and Ho, W. Affordances: Clarifying And Evolving A Concept. City, 2000.Google Scholar
- Schrock, A. R. Communicative Affordances Of Mobile Media: Portability, Availability, Locatability, And Multimediality. International Journal Of Communication, 9 (2015), 18.Google Scholar
- Nagy, P. and Neff, G. Imagined Affordance: Reconstructing A Keyword For Communication Theory. Social Media + Society, 1, 2 (2015), 2056305115603385.Google Scholar
- Dokumaci, A. Activist Affordances: How Disabled People Improvise More Habitable Worlds. Duke University Press, Durham, NC, 2023.Google Scholar
- Hamraie, A. Building access: Universal design and the politics of disability. U of Minnesota Press, Minneapolis, MN, 2017.Google Scholar
- Oliver, M. The Problem With Affordance. E-Learning And Digital Media, 2, 4 (2005), 402-413.Google ScholarCross Ref
- Norman, D. A. The Way I See It: Signifiers, Not Affordances. Interactions, 15, 6 (2008), 18-19.Google Scholar
- Burlamaqui, L. and Dong, A. The Use And Misuse Of The Concept Of Affordance. Springer, City, 2015.Google ScholarCross Ref
- Rigot, A. Design from the Margins. Harvard Belfer Center for Science and International Affairs, 2022.Google Scholar
- Hanna, A., Denton, E., Smart, A. and Smith-Loud, J. Towards a critical race methodology in algorithmic fairness. City, 2020.Google Scholar
- Mohamed, S., Png, M.-T. and Isaac, W. Decolonial AI: Decolonial theory as sociotechnical foresight in artificial intelligence. Philosophy & Technology, 33, 4 (2020), 659-684.Google ScholarCross Ref
- Green, B. Data science as political action: Grounding data science in a politics of justice. Journal of Social Computing, 2, 3 (2021), 249-265.Google ScholarCross Ref
- Delfanti, A. The Warehouse: Workers and Robots at Amazon. Pluto Press, London, UK, 2021.Google ScholarCross Ref
- Delfanti, A. Machinic dispossession and augmented despotism: Digital work in an Amazon warehouse. New Media & Society, 23, 1 (2021), 39-55.Google ScholarCross Ref
- Kassem, S. Labour realities at Amazon and COVID-19: obstacles and collective possibilities for its warehouse workers and MTurk workers. Global Political Economy, 1, 1 (2022), 59-79.Google ScholarCross Ref
- Vallas, S. P., Johnston, H. and Mommadova, Y. Prime Suspect: Mechanisms of Labor Control at Amazon's Warehouses. Work and Occupations (2022), 07308884221106922.Google Scholar
- Ruster, L. Scaling Dignity: An Antidote to Poverty? Wiley Online Library, City, 2020.Google Scholar
- Latonero, M. Governing artificial intelligence: Upholding human rights & dignity. Data & Society, 2018.Google Scholar
- De Stefano, V. ‘Negotiating the algorithm’: Automation, artificial intelligence and labour protection. Artificial Intelligence and Labour Protection (May 16, 2018). Comparative Labor Law & Policy Journal, 41, 1 (2019), 15-47.Google Scholar
- Margulies, M., Egholm, M., Altman, W. E., Attiya, S., Bader, J. S., Bemben, L. A., Berka, J., Braverman, M. S., Chen, Y.-J. and Chen, Z. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 437, 7057 (2005), 376-380.Google ScholarCross Ref
- Rogers, Y.-H. and Venter, J. C. Massively parallel sequencing. Nature, 437, 7057 (2005), 326-327.Google ScholarCross Ref
- Tucker, T., Marra, M. and Friedman, J. M. Massively parallel sequencing: the next big thing in genetic medicine. The American Journal of Human Genetics, 85, 2 (2009), 142-154.Google ScholarCross Ref
- Scudder, N., McNevin, D., Kelty, S. F., Walsh, S. J. and Robertson, J. Massively parallel sequencing and the emergence of forensic genomics: Defining the policy and legal issues for law enforcement. Science & Justice, 58, 2 (2018), 153-158.Google ScholarCross Ref
- Scudder, N., Robertson, J., Kelty, S. F., Walsh, S. J. and McNevin, D. A law enforcement intelligence framework for use in predictive DNA phenotyping. Australian Journal of Forensic Sciences, 51, 1 (2019), 255-258.Google ScholarCross Ref
- Meloni, M. Political biology: Science and social values in human heredity from eugenics to epigenetics. Springer, NY, 2016.Google ScholarCross Ref
- Rutherford, A. Control: The Dark History and Troubling Present of Eugenics. WW Norton, Hachette UK, 2022.Google Scholar
- Brayne, S. Big Data Surveillance: The Case Of Policing. American Sociological Review, 82, 5 (2017), 977-1008.Google ScholarCross Ref
- Brayne, S. Predict and surveil: Data, discretion, and the future of policing. Oxford University Press, Oxford, UK, 2020.Google ScholarCross Ref
- Barabas, C., Virza, M., Dinakar, K., Ito, J. and Zittrain, J. Interventions over predictions: Reframing the ethical debate for actuarial risk assessment. PMLR, City, 2018.Google Scholar
- So, W., Lohia, P., Pimplikar, R., Hosoi, A. E. and D'Ignazio, C. Beyond Fairness: Reparative Algorithms to Address Historical Injustices of Housing Discrimination in the US. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (Seoul, Republic of Korea, 2022). Association for Computing Machinery, [insert City of Publication],[insert 2022 of Publication].Google ScholarDigital Library
- Ehsan, U., Singh, R., Metcalf, J. and Riedl, M. The Algorithmic Imprint. City, 2022.Google Scholar
- Harding, S. G. The feminist standpoint theory reader: Intellectual and political controversies. Routledge, NY, 2004.Google Scholar
Index Terms
- ‘Affordances’ for Machine Learning
Recommendations
Affordances in HCI: toward a mediated action perspective
CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsInterpretations of the concept of "affordances" in HCI are becoming increasingly diverse, extending well beyond the original Gibsonian meaning. We discuss some of the key analyses of affordances in HCI research and make three related claims. First, we ...
Gibsonian Affordances for Roboticists
Using hypersets as an analytic tool, we compare traditionally Gibsonian (Chemero 2003; Turvey 1992) and representationalist (Sahin et al. this issue) understandings of the notion `affordance'. We show that representationalist understandings are ...
Sociomateriality and Information Systems Research: Quantum Radicals and Cartesian Conservatives
This paper provides an elaboration and comparison of two main streams of "sociomateriality" research within Information Systems (IS) discipline. Through the rapid and controversial emergence of discussions around sociomateriality, IS research has become ...
Comments