Abstract
Human organizations’ adoption of the paradigm of the Fourth Industrial Revolution is associated with the growth of techno-empowerment, which is the process of transferring autonomy in decision-making to intelligent machines. Particular persuasive strategies have been identified that may coax people to use intelligent devices. However, there is a substantial research gap regarding what antecedents influence human intention to assign decision-making autonomy to artificial agents. In this study, ethological and evolutionary concepts are applied to explain the drivers for autonomous assistants’ techno-empowerment. The method used in the study was a 4 × 2 between-subject experiment made with 278 persons. The research tool used to collect the data was an online survey. The results show that more positive attitudes and higher trust, perceived usefulness, and perceived ease of use are correlated with higher intention to allow the autonomous assistant independence in decision-making. Second, the results suggest that the more human-like a non-human agent is, the higher the intention to empower it—but only if this agent simultaneously provides functional and visual anthropomorphic cues explainable by the mimicry effect.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Fig1_HTML.png)
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Abe R (2019) Introducing autonomous buses and taxis: quantifying the potential benefits in Japanese transportation systems. Transport Res A Policy Practice 126:94–113
Ahmad W, Mohamad N, Rizal A (2020) Understanding user emotions through interaction with persuasive technology. Int J Adv Comput Sci Appl. https://doi.org/10.14569/IJACSA.2020.0110926
Akerkar R (2019) Artificial intelligence for business. Springer, New York
Aleshinloye KD, Woosnam KM, Tasci ADA, Ramkissoon H (2021) Antecedents and outcomes of resident empowerment through tourism. J Travel Res. https://doi.org/10.1177/0047287521990437
Aly S, Tyrychtr J, Vrana I (2021) Optimizing design of smart workplace through multi-objective programming. Appl Sci 11(7):3042
Appelbaum SH, Karasek R, Lapointe F, Quelch K (2015) Employee empowerment: factors affecting the consequent success or failure (Part II). Ind Commer Train 47(1):23–30
Bansal P, Kockelman KM (2018) Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation 45:641–675
Barnes C, Mertens DM (2008) An ethical agenda in disability research: rhetoric or reality. In: Mertens DM, Ginsberg PE (eds) The handbook of social research ethics. SAGE, London, pp 485–493
Benzidia S, Makaoui N, Bentahara O (2021) The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. Technol Forecast Soc Change 165:120557
Bickmore TW, Caruso L, Clough-Gorr K, Heeren T (2005) ‘It’s just like you talk to a friend’ relational agents for older adults. Interact Comput 17(6):711–735
Borau S, Otterbring T, Laporte S, FossoWamba S (2021) The most human bot: female gendering increases humanness perceptions of bots and acceptance of AI. Psychol Mark. https://doi.org/10.1002/mar.21480
Bromuri S, Henkel AP, Iren D, Urovi V (2020) Using AI to predict service agent stress from emotion patterns in service interactions. J Serv Manage. https://doi.org/10.1108/JOSM-06-2019-0163
Brooks, B. (2021). Get ready for self-driving banks. Financial Times. Retrieved from https://www.ft.com/content/c1caca5b-01f7-41be-85a4-3ecb883f2417
Chartrand TL, Bargh JA (1999) The chameleon effect: the perception–behavior link and social interaction. J Pers Soc Psychol 76(6):893–910
Chaudhuri T, Yeatts DE, Cready CM (2013) Nurse aide decision making in nursing homes: factors affecting empowerment. J Clin Nurs 22(17–18):2572–2585
Cheung MFY, To WM (2017) The influence of the propensity to trust on mobile users’ attitudes toward in-app advertisements: an extension of the theory of planned behavior. Comput Hum Behav 76:102–111
Chung TS, Wedel M, Rust RT (2016) Adaptive personalization using social networks. J Acad Mark Sci 44(1):66–87
Dalziell AH, Welbergen JA (2016) Mimicry for all modalities. Ecol Lett 19(6):609–619
Damioli G, Van Roy V, Vertesy D (2021) The impact of artificial intelligence on labor productivity. Eurasian Bus Rev 11:1–25
Daugherty PR, Wilson HJ (2018) Human + machine: reimagining work in the age of AI. Harvard Business Review Press, Harvard
Davis FD, Bagozzi R, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manage Sci 35:982–1003
Evertsz R, Thangarajah J, Yadav N, Ly T (2015) A framework for modelling tactical decision-making in autonomous systems. J Syst Softw 110:222–238
Eyssel F, Hegel F, Horstmann G, Wagner C (2010) Anthropomorphic inferences from emotional nonverbal cues: a case study. In: 19th international symposium in robot and human interactive communication. IEEE, pp 646–651
Fischer K, Lohan K, Foth K (2012) Levels of embodiment: Linguistic analyses of factors influencing HRI. In: 7th ACM/IEEE international conference on human‐robot interaction. IEEE, pp 463–470
Fogg BJ (2003) Persuasive technology: using computers to change what we think and do. Morgan Kaufmann Publishers, Boston
Goddard MA, Davies ZG, Guenat S, Ferguson MJ, Fisher JC, Akanni A, Antoniou C (2021) A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems. Nat Ecol Evol 5(2):219–230
Haboucha CJ, Ishaq R, Shiftan Y (2017) User preferences regarding autonomous vehicles. Transp Res C 78:37–49
Hancock PA (2016) Imposing limits on autonomous systems. Ergonomics 60(2):284–291
Horton RP, Buck T, Waterson PE, Clegg CW (2001) Explaining intranet use with the technology acceptance model. J Inf Technol 16(4):237–249
Huang MH, Rust RT (2021) A strategic framework for artificial intelligence in marketing. J Acad Mark Sci 49:30–50
Hudson J, Orviska M, Hunady J (2019) People’s attitudes to autonomous vehicles. Transport Res A Policy Pract 121:164–176. https://doi.org/10.1016/j.tra.2018.08.018
Hulse LM, Xie H, Galea ER (2018) Perceptions of autonomous vehicles: relationships with road users, risk, gender and age. Saf Sci 102:1–13
Ivanov S, Webster C (2018) Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies—a cost-benefit analysis. In: Marinov V, Vodenska M, Assenova MDE (eds) Traditions and innovations in contemporary tourism. Cambridge Scholars Publishing, pp 190–203
Joo J, Sang Y (2013) Exploring Koreans’ smartphone usage: an integrated model of the technology acceptance model and uses and gratifications theory. Comput Hum Behav 29(6):2512–2518
Karimi L, Leggat SG, Bartram T, Afshari L, Sarkeshik S, Verulava T (2021) Emotional intelligence: predictor of employees’ wellbeing, quality of patient care, and psychological empowerment. BMC Psychol. https://doi.org/10.1186/s40359-021-00593-8
Kędzierski J, Kaczmarek P, Dziergwa M, Tchoń K (2015) Design for a robotic companion. Int J Humanoid Rob 12(01):1550007
Kessel RT (2005) Apparent reliability: conditions for reliance on supervised automation. Defence R&D Canada, Atlantic
Khalili H, Sameti A, Sheybani H (2016) A study on the effect of empowerment on customer orientation of employees. Glob Bus Rev 17(1):38–50. https://doi.org/10.1177/0972150915610674
Lai PC (2017) Security as an extension to TAM Model: consumers’ intention to use a single platform E-Payment. Asia-Pac J Manage Res Innov 13(3–4):110–119. https://doi.org/10.1177/2319510x18776405
Lee S, Kim Y, Kahng H, Lee S, Chung S, Cheong T, Shin K, Park J, Kim SB (2019) Intelligent traffic control for autonomous vehicle systems based on machine learning. Expert Syst Appl. https://doi.org/10.1016/j.eswa.2019.113074
MacDonald S, MacIntyre P (1997) The generic job satisfaction scale: scale development and its correlates. Employee Assist Q 13(2):1–16
Makridakis S (2017) The forthcoming artificial intelligence (AI) revolution: its impact on society and firms. Futures 90:46–60
McKnight DH, Carter M, Thatcher JB, Clay PF (2011) Trust in a specific technology. ACM Trans Manage Inf Syst 2(2):1–25. https://doi.org/10.1145/1985347.1985353
McLain D, Hackman K (1999) Trust, risk, and decision-making in organizational change. Public Adm Q 23(2):152–176
McPherson M, Smith-Lovin L, Cook JM (2001) Birds of a feather: homophily in social networks. Ann Rev Sociol 27:415–444
Mendling J, Recker J, Reijers HA, Leopold H (2019) An empirical review of the connection between model viewer characteristics and the comprehension of conceptual process models. Inf Syst Front 21(5):1111–1135
Modliński A, Gladden M (2021a) An organizational metaphor for the 4th industrial revolution: the organization as Cyborg. World Futures. https://doi.org/10.1080/02604027.2021.1996187
Modliński A, Gladden M (2021b) Applying Ethology to design human-oriented technology. An experimental study on the signalling role of the labelling effect. Human Technology 17(2)
Modliński A, Skowroński D (2021). Robopowers? The phenomenon of techno-empowerment in the socio-organizational context (submitted paper)
Modlinski A, Fortuna P, Rożnowski B (2022) Human–machine trans roles conflict in the organization: how sensitive are customers to intelligent robots replacing the human workforce? Int J Consum Stud. https://doi.org/10.1111/ijcs.12811
Modliński A, Gwiaździński E, Karpińska-Krakowiak M (2022) The effects of religiosity and gender on attitudes and trust toward autonomous vehicles. J High Technol Manage Res 33(1)
Molina-Mula J, Gallo-Estrada J (2020) Impact of nurse-patient relationship on quality of care and patient autonomy in decision-making. Int J Environ Res Public Health 17(3):835
Mori M, MacDorman K, Kageki N (2012) The uncanny valley [from the field]. IEEE Robot Autom Mag 19(2):98–100
Nass C, Moon Y (2000) Machines and mindlessness: social responses to computers. J Soc Issues 56(1):81–103. https://doi.org/10.1111/0022-4537.00153
Natarajan M, Gombolay M (2020). Effects of anthropomorphism and accountability on trust in human robot interaction. In: Proceedings of the 2020 ACM/IEEE international conference on HRI. ACM/IEEE, pp 33–42
Nysveen H, Pederson PE, Thorbjørnsen H (2005) Intentions to use mobile services: antecedents and cross-service comparisons. JAMS 33(3):330–346
Oinas-Kukkonen H, Harjumaa M (2008) A systematic framework for designing and evaluating persuasive systems. In: Oinas-Kukkonen H, Hasle P, Harjumaa M, Segerståhl K, Øhrstrøm P (eds) Persuasive technology. PERSUASIVE 2008. Lecture notes in computer science, vol 5033. Springer, Berlin, Heidelberg
Pak R, Fink N, Price M, Bass B, Sturre L (2012) Decision support aids with anthropomorphic characteristics influence trust and performance in younger and older adults. Ergonomics 55(9):1059–1072
Phillips-Wren G, Jain L (2006) Artificial Intelligence for Decision Making. In: Gabrys B, Howlett RJ, Jain LC (eds) Knowledge-based intelligent information and engineering systems. KES 2006. Lecture notes in computer science, vol 4252. Springer, Berlin, Heidelberg
Pillai R, Sivathanu B (2020) Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking Int J. https://doi.org/10.1108/bij-04-2020-0186
Qiu L, Benbasat I (2009) Evaluating anthropomorphic product recommendation agents: a social relationship perspective to designing information systems”. J Manage Inf Syst 25(4):145–182
Ritvo H (2007) On the animal turn. Daedalus 136(4):118–122
Ruijten PA, Haans A, Ham J, Midden CJ (2019) Perceived humanlikeness of social robots: testing the Rasch model as a method for measuring anthropomorphism. Int J Soc Robot 11(3):477–494
Salazar J, Pfaffenberg C, Salazar L (2006) Locus of control vs. employee empowerment and the relationship with hotel managers’ job satisfaction. J Hum Resour Hospital Tour 5(1):1–15
Salloum SA, Al-Emran M (2019) Factors affecting the adoption of e-payment systems by university students: extending the TAM with trust. Int J Electron Bus 14(4):371
Sarter NB, Woods DD (1997) Team play with a powerful and independent agent: operational experiences and automation surprises on the Airbus A-320. Hum Factors 39(4):553–569
Shaffer VA, Probst CA, Merkle EC, Arkes HR, Medow MA (2013) Why do patients derogate physicians who use a computer-based diagnostic support system? Med Decis Making 33(1):108–118
Siegall M, Gardner S (2000) Contextual factors of psychological empowerment. Pers Rev 29(6):703–722
Sohrabpour V, Oghazi P, Toorajipour R, Nazarpour A (2020) Export sales forecasting using artificial intelligence. Technol Forecast Soc Chang. https://doi.org/10.1016/j.techfore.2020.120480
Spreitzer GM (1995) Psychological empowerment in the workplace: dimensions, measurement, and validation. Acad Manage J 38:1442–1465
Venkatesh V, Morris M, Davis GB, Davis F (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425. https://doi.org/10.2307/30036540
Virmani A (2002) A new development paradigm: employment, entitlement and empowerment. Glob Bus Rev 3(2):225–245
Watson DP, Scheidt DH (2005) Autonomous systems. Johns Hopkins APL Techn Dig 26(4)
Welz A (2020) Decoy tactics: can fake concrete penguins help save the real thing? Retrieved from https://www.theguardian.com/environment/2020/apr/15/decoy-tactics-can-fake-concrete-penguins-help-save-the-real-thing-aoe
Wood W (2000) Attitude change: persuasion and social influence. Annu Rev Psychol 51:539–570
Wu L-H, Wu L-C, Chang S-C (2016) Exploring consumers’ intention to accept smartwatch. Comput Hum Behav 64:383–392
Wynhoff I, van Langevelde F (2017) Phengaris (Maculinea) teleius butterflies select host plants close to Myrmica ants for oviposition, but P. nausithous do not. Entomol Exp Appl 165(1):9–18
Xu K, Lombard M (2017) Persuasive computing: feeling peer pressure from multiple computer agents. Comp Hum Behav 74:152–162
Yam KC, Bigman YE, Tang PM, Ilies R, De Cremer D, Soh H, Gray K (2020) Robots at work: people prefer—and forgive—service robots with perceived feelings. J Appl Psychol. https://doi.org/10.1037/apl0000834
Zhang F (2021) Construction of internal management system of business strategic planning based on artificial intelligence. IseB. https://doi.org/10.1007/s10257-021-00510-x
Zhao S (2003) Toward a taxonomy of copresence. Presence Teleoper Virtual Environ 12(5):445–455
Ziamou P, Ratneshwar S (2003) Innovations in product functionality: when and why are explicit comparisons effective. J Market 67:49–61
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix 1 Experimental stimuli
Appendix 1 Experimental stimuli
![figure a](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figa_HTML.png)
![figure b](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figb_HTML.png)
![figure c](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figc_HTML.png)
![figure d](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figd_HTML.png)
![figure e](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Fige_HTML.png)
![figure f](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figf_HTML.png)
![figure g](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figg_HTML.png)
.
![figure h](http://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs00146-022-01534-8/MediaObjects/146_2022_1534_Figh_HTML.png)
Rights and permissions
About this article
Cite this article
Modliński, A. The psychological and ethological antecedents of human consent to techno-empowerment of autonomous office assistants. AI & Soc 38, 647–663 (2023). https://doi.org/10.1007/s00146-022-01534-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00146-022-01534-8