Haddow, Gillian

Williams, Robin

Galanos, Vasileios

2023-03-16T11:51:21Z

2023-03-16T11:51:21Z

2023-07-13

Artificial intelligence’s (AI) distinctiveness as a technoscientific field that imitates the ability to think went through a resurgence of interest post-2010, attracting a flood of scientific and popular expectations as to its utopian or dystopian transformative consequences. This thesis offers observations about the formation and dynamics of expectations based on documentary material from the previous periods of perceived AI hype (1960-1975 and 1980-1990, including in-between periods of perceived dormancy), and 25 interviews with UK-based AI specialists, directly involved with its development, who commented on the issues during the crucial period of uncertainty (2017-2019) and intense negotiation through which AI gained momentum prior to its regulation and relatively stabilised new rounds of long-term investment (2020-2021). This examination applies and contributes to longitudinal studies in the sociology of expectations (SoE) and studies of experience and expertise (SEE) frameworks, proposing a historical sociology of expertise and expectations framework. The research questions, focusing on the interplay between hype mobilisation and governance, are: (1) What is the relationship between AI practical development and the broader expectational environment, in terms of funding and conceptualisation of AI? (2) To what extent does informal and non-developer assessment of expectations influence formal articulations of foresight? (3) What can historical examinations of AI’s conceptual and promissory settings tell about the current rebranding of AI? The following contributions are made: (1) I extend SEE by paying greater attention to the interplay between technoscientific experts and wider collective arenas of discourse amongst non-specialists and showing how AI’s contemporary research cultures are overwhelmingly influenced by the hype environment but also contribute to it. This further highlights the interaction between competing rationales focusing on exploratory, curiosity-driven scientific research against exploitation-oriented strategies at formal and informal levels. (2) I suggest benefits of examining promissory environments in AI and related technoscientific fields longitudinally, treating contemporary expectations as historical products of sociotechnical trajectories through an authoritative historical reading of AI’s shifting conceptualisation and attached expectations as a response to availability of funding and broader national imaginaries. This comes with the benefit of better perceiving technological hype as migrating from social group to social group instead of fading through reductionist cycles of disillusionment; either by rebranding of technical operations, or by the investigation of a given field by non-technical practitioners. It also sensitises to critically examine broader social expectations as factors for shifts in perception about theoretical/basic science research transforming into applied technological fields. Finally, (3) I offer a model for understanding the significance of interplay between conceptualisations, promising, and motivations across groups within competing dynamics of collective and individual expectations and diverse sources of expertise.

https://hdl.handle.net/1842/40420

http://dx.doi.org/10.7488/era/3188

en

The University of Edinburgh

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Galanos, V. (2019). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management 57, 101994, 1- 47

Galanos, V. (2014). Beyond Information Revolution: Postlude to a Past Future. Master Thesis. Retrieved 03-09- 2021 from https://www.academia.edu/12120426/Beyond_Information_Revolution_Postlude_to_a_Past_Future_Vassili s_Galanos

Galanos, V. (2017). Singularitarianism and Schizophrenia. AI & Society 32, 573–590

Galanos, V. (2018). Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide. Kreps et al. (eds) 13th IFIP TC 9 International Conference on Human Choice and Computers. HCC13 2018. Held at the 24th IFIP World Computer Congress. WCC 2018. Poznan. Poland. September 19–21. 2018. Proceedings. Switzerland: Springer Nature. 359-373.

Galanos, V. (2019). Exploring expanding expertise: artificial intelligence as an existential threat and the role of prestigious commentators, 2014–2018. Technology Analysis & Strategic Management 31(4), 421-432.

Galanos, V. (2019). Teratological Aspects in Artificial Intelligence and Robotics: From Monstrous Threats to Rorschach Opportunities" In Diego Compagna and Stefanie Steinhart (eds.) Monsters, Monstrosities, and the Monstrous in Culture and Society. Delaware and Malaga: Vernon Press. pp. 103-129.

Galanos, V. (2020). Tekken’s Mokujin and the Disjunctive Synthesis of Gender Performativity. Press Start 6(1), n.p

Galanos, V. (2022). Nomadic artificial Intelligence and Royal Research Councils: Curiosity-Driven Research Against Imperatives Implying Imperialism. In: Tinnirello, M. (ed.). The Global Politics of Artificial Intelligence. Taylor & Francis – CRC Press

Galanos, V. (2022). Longitudinal Hype: Terminologies Fade, Promises Stay – An Essay Review on The Robots Are Among Us (1955) and 2062: The World that AI Made (2018). Interfaces: Essays and Reviews on Computing and Culture 3, Charles Babbage Institute, University of Minnesota, 73-87

Galanos, V. (2022). Why so Few AI Practitioners in Ai Policy? Specialist Views on Questions of Control, Regulation, and an Updated Paradox of Participation. Specialist Views on Questions of Control, Regulation, and an Updated Paradox of Participation. SSRN preprint. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4213120

artificial intelligence

sociology of expectations

studies of expertise and experience

expertise

interviews

history of science

historical sociology

hype

digital technology

information and communication technologies

machine learning

Expectations and expertise in artificial intelligence: specialist views and historical perspectives on conceptualisation, promise, and funding

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy