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Reframing Deception for Human-Centered AI
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“Sweet deception fosters positive and deep engagement in human-AI relationships, building trust and a sense of connection (Umbrello and Natale, 2024).”
From I love you, my AI companion! Do you? Perspectives from the Triangular Theory of Love and Attachment Theory (2026) · cites this paper as Umbrello and Natale, 2024
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I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 3×
“Strong deception can easily be activated in CAI and other conversational agents; in fact, these can potentially be programmed to pass as humans, as Alan Turing [75] already envisioned for the design of the imitation game or Turing Test.”
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · cited 2×
“…for processes like Z-Inspection®, not only permits but supports the creation of reliable, safe, and trustworthy CAI systems across all levels of abstraction 5 by targeting each level rather than a unitary top-down approach that would be, at best, ineffective if not outright impossible to achieve.”
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452
Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
Shneiderman, B. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1741118 · Cited by 1,743
Sustainable AI: AI for sustainability and the sustainability of AI
van Wynsberghe, A. (2021) · AI and Ethics · doi:10.1007/s43681-021-00043-6 · Cited by 939
My Chatbot Companion - a Study of Human-Chatbot Relationships
Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102601 · Cited by 797 · cited 1×
“Examples of banal deception include the reactions evoked by specific choices in the characterisation of CAI, but also by companion chatbots such as Replika [65] or social robots [10].”
Shneiderman, B. (2020) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3419764 · Cited by 768
Meaningful Human Control over Autonomous Systems: A Philosophical Account
Santoni de Sio, F., & van den Hoven, J. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00015 · Cited by 566
Ethics and Privacy in AI and Big Data: Implementing Responsible Research and Innovation
Stahl, B. C., & Wright, D. (2018) · IEEE Security & Privacy · doi:10.1109/msp.2018.2701164 · Cited by 374
Don’t ask if artificial intelligence is good or fair, ask how it shifts power
Kalluri, P. (2020) · Nature · doi:10.1038/d41586-020-02003-2 · Cited by 213
Research works printed but not linked: 71
- Baker-Brunnbauer J (2021) TAII framework for trustworthy AI systems. ROBONOMICS J Automat Economy. https://journal.robonomics.science/index.php/rj/article/view/17
- Bench-Capon TJ (2020) Ethical approaches and autonomous systems. Artif Intell 281:103239. https://doi.org/10.1016/j.artint.2020.103239 · DOI
- Billig M (1995) Banal nationalism. Sage, London
- Burton S, Habli I, Lawton T, McDermid J, Morgan P, Porter Z (2020) Mind the gaps: assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artif Intell 279:103201. https://doi.org/10.1016/j.artint.2019.103201 · DOI
- Calvo RA, Peters D, Vold K, Ryan RM (2020) Supporting human autonomy in AI systems: a framework for ethical enquiry. In: Ethics of digital well-being (pp 31–54). Springer, Cham. https://doi.org/10.1007/978-3-030-50585-1_2 · DOI
- Castelfranchi C, Tan Y (2001) Trust and deception in virtual societies. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3614-5 · DOI
- Caudwell C, Lacey C (2019) What do home robots want? The ambivalent power of cuteness in robotic relationships. Convergence 41(8):1176–1191. https://doi.org/10.1177/1354856519837792 · DOI
- Chakraborti T, Kambhampati S (2018) Algorithms for the greater good! on mental modeling and acceptable symbiosis in human-AI collaboration. arXiv:1801.09854 · arXiv
- Chun WHK (2004) On software, or the persistence of visual knowledge. Grey Room 18:26–51. · DOI
- Coeckelbergh M (2018) How to describe and evaluate “deception” phenomena: recasting the metaphysics, ethics, and politics of ICTs in terms of magic and performance and taking a relational and narrative turn. Ethics Inf Technol 20(2):71–85. https://doi.org/10.1007/s10676-017-9441-5 · DOI
- Danaher J (2020) Robot betrayal: a guide to the ethics of robotic deception. Ethics Inf Technol 22(2):117–128. https://doi.org/10.1007/s10676-019-09520-3 · DOI
- Dazeley R, Vamplew P, Foale C, Young C, Aryal S, Cruz F (2021) Levels of explainable artificial intelligence for human-aligned conversational explanations. Artif Intell 299:103525. https://doi.org/10.1016/j.artint.2021.103525 · DOI
- de Graaf MMA, Allouch SB (2013) Exploring influencing variables for the acceptance of social robots. Robot Auton Syst 61(12):1476–1486. https://doi.org/10.1016/j.robot.2013.07.007 · DOI · Paper page
- DePaulo BM, Kirkendol SE, Kashy DA, Wyer MM, Epstein JA (1996) Lying in everyday life. J Personal Soc Psychol 70(5):979–995. https://doi.org/10.1037/0022-3514.70.5.979 · DOI
- Donath J (2018) The robot dog fetches for whom? In: Papacharissi Z (ed) A networked self and human augmentics, artificial intelligence, sentience. Routledge, London, pp 10–24 · DOI
- Emslie K (2024) LLM hallucinations: a bug or a feature? Communications of the ACM. Retrieved 11 June 2024, from https://cacm.acm.org/news/llm-hallucinations-a-bug-or-a-feature/
- European Commission, Directorate-General for Communications Networks, Content and Technology (2019) Ethics guidelines for trustworthy AI, Publications Office. https://doi.org/10.2759/346720 · DOI
- Fogg BJ (2003) Persuasive technology: using computers to change what we think and do. Morgan Kaufmann, Burlington · DOI · Paper page
- Gehl RW, Bakardjieva M (2016) Socialbots and their friends: digital media and the automation of sociality. Routledge, London · DOI
- Guzman AL (2015) Imagining the voice in the machine: the ontology of digital social agents. PhD Dissertation, University of Illinois at Chicago
- Guzman AL, Lewis SC (2019) Artificial intelligence and communication: a human–machine communication research agenda. New Media Soc 22(1): 70–86. https://doi.org/10.1177/1461444819858691 · DOI
- Hakim FZM, Indrayani LM, Amalia RM (2019) A dialogic analysis of compliment strategies employed by replika chatbot. Adv Soc Sci Educ Hum Res 279:266–271. https://doi.org/10.2991/icalc-18.2019.38 · DOI
- Helberger N, Karppinen K, D’acunto L (2018) Exposure diversity as a design principle for recommender systems. Inf Commun Soc 21(2):191–207. https://doi.org/10.1080/1369118X.2016.1271900 · DOI
- Henrickson L (2021) Reading computer-generated texts. Cambridge University Press, Cambridge · DOI
- Herzfeld N (2023) Is your computer lying? AI and deception. Sophia, 1–14. · DOI
- Hoffman D (2019) The case against reality: why evolution hid the truth from our eyes. Norton & Company, New York
- Kircher K, Larsson A, Hultgren JA (2013) Tactical driving behavior with different levels of automation. IEEE Trans Intell Transp Syst 15(1):158–167. https://doi.org/10.1109/TITS.2013.2277725 · DOI
- Lakoff G, Johnson M (1980) Metaphors we live by. University of Chicago Press, Chicago
- Laurel B (1991) Computers as Theatre. Addison-Wesley, Boston
- Lei X, Tu GH, Liu AX, Ali K, Li CY, Xie T (2017) The insecurity of home digital voice assistants-Amazon Alexa as a case study. arXiv preprint arXiv:1712.03327 · arXiv
- Leveson N (2011) Engineering a safer world: systems thinking applied to safety. MIT Press, Cambridge
- Masters P, Smith W, Sonenberg L, Kirley M (2021) Characterising deception in AI: a survey. In: Sarkadi S, Wright B, Masters P, McBurney P (eds) Deceptive AI. DeceptECAI DeceptAI 2020 2021. Commun Comput Inf Sci, vol 1296. Cham, Springer. https://doi.org/10.1007/978-3-030-91779-1_1 · DOI
- Mclean G, Osei-frimpong K (2019) Hey Alexa … examine the variables influencing the use of artificial intelligent in-home voice assistants. Comput Hum Behav 99:28–37. https://doi.org/10.1016/j.chb.2019.05.009 · DOI · Paper page
- Milano S, Taddeo M, Floridi L (2020) Recommender systems and their ethical challenges. AI Soc 35(4):957–967. https://doi.org/10.1007/s00146-020-00950-y · DOI · Paper page
- Natale S (2021) Deceitful media: artificial intelligence and social life after the turing test. Oxford University Press, New York · DOI · Paper page
- Natale S (2023) AI, human-machine communication and deception. In: Guzman A, McEwen R, Jones S (eds) The Sage Handbook of Human-Machine Communication. Sage, London, pp 401–408 · DOI
- O’Leary DE (2019) Google’s duplex: pretending to be human. Intell Syst Account Finance Manag 26(1):46–53. https://doi.org/10.1002/isaf.1443 · DOI
- Olney J (1972) Metaphors of self: the meaning of autobiography. Princeton University Press, Princeton
- Sarkadi S, Wright B, Masters P, McBurney P (2021) Deceptive AI. Springer, Cham · DOI
- Sætra HS (2021) Social robot deception and the culture of trust. Paladyn J Behav Robot 12(1):276–286. https://doi.org/10.1515/pjbr-2021-0021 · DOI
- Schiller A, McMahon J (2019) Alexa, alert me when the revolution comes: gender, affect, and labor in the age of home-based artificial intelligence. New Polit Sci 41(2):173–191. https://doi.org/10.1080/07393148.2019.1595288 · DOI · Paper page
- Schoenhofer SO, van Wynsberghe A, Boykin A (2019) Engaging robots as nursing partners in caring: nursing as caring meets care-centered value-sensitive design. Int J Human Car 23(2): 157–167. https://doi.org/10.20467/1091-5710.23.2.157 · DOI
- Shneiderman B (1986) Designing the user interface: strategies for effective human-computer interaction, 1st edn. Addison-Wesley, Boston
- Shneiderman B (2022) Human-centered AI. Oxford University Press, Oxford · DOI
- Shneiderman B, Plaisant C, Cohen M, Jacobs S, Elmqvist N (2016) Designing the user interface: strategies for effective human-computer interaction, 6th edn. Pearson, Boston
- Schuetzler RM, Grimes GM, Giboney JS (2019) The effect of conversational agent skill on user behavior during deception. Comput Hum Behav 97:250–259. https://doi.org/10.1016/j.chb.2019.03.033 · DOI · Paper page
- Seppelt B, Reimer B, Angell L, Seaman S (2017) Considering the human across levels of automation: Implications for reliance. In: Proceedings of the ninth international driving symposium on human factors in driver assessment, training and vehicle design (pp 228–234). https://doi.org/10.17077/drivingassessment.1640 · DOI
- Smits M, van Goor H, Kallewaard JW, Verbeek PP, Ludden GD (2022) Evaluating value mediation in patients with chronic low-back pain using virtual reality: contributions for empirical research in value sensitive design. Health Technol. https://doi.org/10.1007/s12553-022-00671-w · DOI
- Sugianto N, Tjondronegoro D, Stockdale R, Yuwono EI (2021) Privacy-preserving AI-enabled video surveillance for social distancing: responsible design and deployment for public spaces. Inf Technol People Vol Ahead-of-print No Ahead-of-print. https://doi.org/10.1108/ITP-07-2020-0534 · DOI
- Sweeney M (2017) The Ms. Dewey “experience”: technoculture, gender, and race. In: Daniels J, Gregory K, McMillan Cottom T (eds) Digital sociologies, pp 401–420. Bristol, Policy Press · DOI
- Tarakji KG, Zaidi AM, Zweibel SL, Varma N, Sears SF, Allred J et al (2021) Performance of first pacemaker to use smart device app for remote monitoring. Heart Rhythm O2 2(5): 463–471. https://doi.org/10.1016/j.hroo.2021.07.008 · DOI
- Thaler RH, Sunstein CR (2008) Nudge: improving decisions about health, wealth, and happiness. Yale University Press, Cambridge
- Thimbleby H (2020) Fix IT: stories from healthcare IT. Oxford University Press, Oxford
- Umbrello S (2021) Coupling levels of abstraction in understanding meaningful human control of autonomous weapons: a two-tiered approach. Ethics Inf Technol 23(3):455–464. https://doi.org/10.1007/s10676-021-09588-w · DOI
- Umbrello S (2021) Towards a Value Sensitive Design Framework for Attaining Meaningful Human Control over Autonomous Weapons Systems (PhD). Northwestern Italian Philosophy Consortium (Consorzio FINO). https://doi.org/10.13140/RG.2.2.20431.41128 · DOI
- Umbrello S (2022) The role of engineers in harmonising human values for AI systems design. J Respons Technol 10:100031. https://doi.org/10.1016/j.jrt.2022.100031 · DOI
- Umbrello S, Capasso M, Balistreri M, Pirni A, Merenda F (2021) Value sensitive design to achieve the UN SDGs with AI: a case of elderly care robots. Mind Mach 31(3):395–419. https://doi.org/10.1007/s11023-021-09561-y · DOI
- Umbrello S, Van de Poel I (2021) Mapping value sensitive design onto AI for social good principles. AI and Ethics 1(3):283–296. https://doi.org/10.1007/s43681-021-00038-3 · DOI · Paper page
- Umbrello S, Yampolskiy RV (2022) Designing AI for explainability and verifiability: a value sensitive design approach to avoid artificial stupidity in autonomous vehicles. Int J Soc Robot 14(2), 313–322. https://doi.org/10.1007/s12369-021-00790-w · DOI
- Umbres R (2017) Deception as exploitative social agency. In: Enfield NJ, Kockelman P (eds) Distributed agency (pp 243–251). Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780190457204.003.0025 · DOI
- United Nations. General Assembly (1949) Universal declaration of human rights (Vol. 3381). Department of State, United States of America
- Van den Hoven J, Lokhorst GJ, Van de Poel I (2012) Engineering and the problem of moral overload. Sci Eng Ethics 18(1):143–155. https://doi.org/10.1007/s11948-011-9277-z · DOI · Paper page
- van de Poel I (2020) Embedding values in artificial intelligence (AI) systems. Mind Mach 30(3):385–409. https://doi.org/10.1007/s11023-020-09537-4 · DOI · Paper page
- Wenskovitch J, Zhou M, Collins C, Chang R, Dowling M, Endert A, Xu K (2020) Putting the “i” in interaction: interactive interfaces personalized to individuals. IEEE Comput Graphics Appl 40(3):73–82. https://doi.org/10.1109/MCG.2020.2982465 · DOI
- Wilks Y (2019) Artificial intelligence: modern magic or dangerous future? Icon Books, London
- Woods HS (2018) Asking more of Siri and Alexa: feminine persona in service of surveillance capitalism. Crit Stud Media Commun 35(4):334–349. https://doi.org/10.1080/15295036.2018.1488082 · DOI
- Wrathall MA (2010) Heidegger and unconcealment: truth, language, and history. Cambridge University Press, Cambridge · DOI
- Young L (2019) ‘I’m a cloud of infinitesimal data computation’ when machines talk back: an interview with Deborah Harrison, one of the personality designers of Microsoft’s Cortana AI. Archit Des 89(1):112–117. https://doi.org/10.1002/ad.2398 · DOI
- Zhan X, Xu Y, Sarkadi S (2023) Deceptive AI ecosystems: the case of ChatGPT. In: Proceedings of the 5th international conference on conversational user interfaces, pp 1–6. https://doi.org/10.1145/3571884.3603754 · DOI
- Zicari RV, Brodersen J, Brusseau J, Düdder B, Eichhorn T, Ivanov T et al (2021) Z-Inspection®: a process to assess trustworthy AI. IEEE Trans Technol Soc 2(2):83–97. https://doi.org/10.1109/TTS.2021.3066209 · DOI · Paper page
- Zicari RV, Ahmed S, Amann J, Braun SA, Brodersen J, Bruneault F et al (2021) Co-design of a trustworthy AI system in healthcare: deep learning based skin lesion classifier. Front Hum Dyn. https://doi.org/10.3389/fhumd.2021.688152 · DOI
Cited by
Sorted by citations
Ng, P. M. L., Wan, C., Lee, D., Garnelo-Gomez, I., & Lau, M. M. (2026) · Internet Research · doi:10.1108/intr-11-2024-1783 · Cited by 27
Ponce Rojo, A., Fontaines-Ruiz, T., Bracho, A. S., & Cánquiz Rincón, L. (2025) · Education Sciences · doi:10.3390/educsci15091134 · Cited by 11
Metadata
- Authors
- Umbrello, S., & Natale, S.
- ORCID
- Umbrello, Steven
- Venue
- International Journal of Social Robotics
- Published
- 2024-10-25
- Volume
- 16
- Issue
- 11-12
- Pages
- 2223-2241
- ISSN
- 1875-4791
- 1875-4805
- Cited by
- 23
- References
- 16
- Language
- en
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