The future of online trust (and why Deepfake is advancing it)
Open accessAbstract
Trust has become a first-order concept in AI, urging experts to call for measures ensuring AI is 'trustworthy'. The danger of untrustworthy AI often culminates with Deepfake, perceived as unprecedented threat for democracies and online trust, through its potential to back sophisticated disinformation campaigns. Little work has, however, been dedicated to the examination of the concept of trust, what undermines the arguments supporting such initiatives. By investigating the concept of trust and its evolutions, this paper ultimately defends a non-intuitive position: Deepfake is not only incapable of contributing to such an end, but also offers a unique opportunity to transition towards a framework of social trust better suited for the challenges entailed by the digital age. Discussing the dilemmas traditional societies had to overcome to establish social trust and the evolution of their solution across modernity, I come to reject rational choice theories to model trust and to distinguish an 'instrumental rationality' and a 'social rationality'. This allows me to refute the argument which holds Deepfake to be a threat to online trust. In contrast, I argue that Deepfake may even support a transition from instrumental to social rationality, better suited for making decisions in the digital age.
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Informational trust arises as people expect greater benefit from believing information and shared facts than from having to fact-check everything themselves.
“informational trust arises as people expect greater benefit from believing information and shared facts than from having to fact-check everything themselves”
From Deepfakes and Democracy (Theory): How Synthetic Audio-Visual Media for Disinformation and Hate Speech Threaten Core Democratic Functions (2022) · cites this paper as Etienne, 2021
In “The modern conception of trust grounded in rational choice theory” (page unavailable), the paper gives the example of trusting a newspaper because checking every fact oneself would cost more than the information is worth. But in “The fundamental distinction between trust and reliance” (page unavailable), it argues that this kind of cost-benefit reasoning describes reliance, not trust itself. The claim presents the example as a general account of how informational trust arises, which the paper does not endorse. (LLM, conf=0.86)
Experimental — accuracy not yet measuredDeepfake technology has the potential to bring forth major business opportunities for content creation and engagement.
“But, simultaneously, this emerging technology has the potential to bring forth major business opportunities for content creation and engagement (Etienne, 2021; Farish, 2020; Kietzmann et al., 2020).”
From Deepfakes: Deceptions, mitigations, and opportunities (2023) · cites this paper as Etienne, 2021
In “Deepfake is not a threat for democracies” (page unavailable), Etienne says deepfakes have applications in internet memes, art and cinema, which supports their use in content creation. Our copy does not describe major business opportunities or opportunities for engagement. (LLM, conf=0.79)
Experimental — accuracy not yet measuredGiven rapid development of deepfake technologies that can generate human-like narratives using NLP such as GPT-3, it is reasonable to expect that integration of such technologies with deepfakes will only contribute to an increase in marketplace deception.
“Additionally, given the rapid development of deepfake technologies that can generate human-like narratives using natural language processing (NLP) such as GPT-3 (a text-generation model), it is reasonable to expect that the integration of such technologies with deepfakes will only contribute to an increase in marketplace deception (Etienne, 2021; Kietzmann et al., 2020; Westerlund, 2019).”
From Deepfakes: Deceptions, mitigations, and opportunities (2023) · cites this paper as Etienne, 2021
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredSocietal trust also reflects people's wish to build relationships with other people and their prioritization of this over other available information in decision-making.
“Etienne (2021, 557) argues that societal trust also reflects peoples’ wish to build relationships with other people, and their prioritization thereof over other available information in decision-making.”
From Deepfakes and Democracy (Theory): How Synthetic Audio-Visual Media for Disinformation and Hate Speech Threaten Core Democratic Functions (2022) · cites this paper as Etienne, 2021
Trust is not just a means to an end but an end in itself.
“Trust, then, is not just a means to an end but an end in itself.”
From Deepfakes and Democracy (Theory): How Synthetic Audio-Visual Media for Disinformation and Hate Speech Threaten Core Democratic Functions (2022) · cites this paper as Etienne, 2021
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Cites
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Masood, M., Nawaz, M., Malik, K. M., Javed, A., Irtaza, A., & Malik, H. (2023) · Applied Intelligence · doi:10.1007/s10489-022-03766-z · Cited by 543 · see citing works
Deepfakes: Deceptions, mitigations, and opportunities
Mustak, M., Salminen, J., Mäntymäki, M., Rahman, A., & Dwivedi, Y. K. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2022.113368 · Cited by 209 · see citing works
A Survey on the Detection and Impacts of Deepfakes in Visual, Audio, and Textual Formats
Mubarak, R., Alsboui, T., Alshaikh, O., Inuwa-Dutse, I., Khan, S., & Parkinson, S. (2023) · IEEE Access · doi:10.1109/access.2023.3344653 · Cited by 132 · see citing works
Pawelec, M. (2022) · Digital Society · doi:10.1007/s44206-022-00010-6 · Cited by 131 · see citing works
“1 3 Digital Society (2022) 1:19 Page 7 of 37 19 In a recent contribution, Etienne (2021) argues that deepfakes do not threaten but may rather increase online trust (I engage with this argument in footnote 20).”
BackgroundInfluentialTwomey, J., Ching, D., Aylett, M. P., Quayle, M., Linehan, C., & Murphy, G. (2023) · PLOS ONE · doi:10.1371/journal.pone.0291668 · Cited by 87 · see citing works
- Authors
- Etienne, H.
- Affiliations
- École Normale Supérieure - PSL (FR)
- Corresponding author
- Etienne, Hubert
- ORCID
- Etienne, Hubert
- Venue
- AI and Ethics
- Published
- 2021-06-28
- Volume
- 1
- Issue
- 4
- Pages
- 553-562
- ISSN
- 2730-5953 (ISSN-L)
- 2730-5961
- PMC
- PMC8237779
- OpenAlex
- W3176830021
- Cited by
- 41
- References
- 1
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 10 · 2023: 8 · 2022: 6
- FWCI
- 7.50
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- AI and Ethics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Access Control and Trust
- Keywords
- online trust, deepfakes, social trust, instrumental rationality, social rationality, rational choice theory, disinformation, trustworthy AI, threats to democracy, digital era
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