AI chauffeurs as the future of car
transportation
Finding the interactions between social cognition, trust, and cultural context, in regards to the acceptance of fully-autonomous cars
Jan Bogdan Ryzynski S3567338 Master Thesis Marketing Management
Agenda
1. Introduction 2. Key concepts
3. Research questions
4. Academic and managerial relevance 5. Conceptual model and hypotheses 6. Methodology
7. Results
Introduction
● Car automation keeps progressing (Bloomberg 2018)
● The end goal of car industry is a fully-autonomous car
● Fully-autonomous cars are controlled by AI, humans are just
passengers
Introduction
● Mixed results of research about the acceptance of
fully-autonomous cars (Maurer et al. 2016)
● Trust decreases as car automation progresses (Rödel et al. 2014)
● Anthropomorphism of AI can increase trust in fully-autonomous
cars (Waytz et al. 2014)
● So far the main focus of fully-autonomous car research has been
Key concepts
● Warmth and competence are universal dimensions that are used
to judge others → determine trust (Fiske et al. 2007)
● Warmth is focused on intentions, competence on performance ● Artificial beings are judged the same way as humans (Demeure et al. 2012) ● Communication of AI should match expectations of a user to
create trust (Nowak and Biocca 2003)
Key concepts
● Cultures build trust differently (Doney et al. 1998)
● Differences between cultures can be determined by the level of
their cultural context (Hall 1976)
● Low cultural context countries are individualistic, focused on
performance, prefer straight-forward communication (Würtz 2005)
● High cultural context countries are group oriented, focused on
Research questions
● RQ1: How does the social cognition focus of a fully-autonomous
car AI affect the trust, and subsequently, the acceptance of fully-autonomous cars?
● RQ2: How does the cultural context affect the relation between
Academic and managerial relevance
1. Academic
● Provides a deeper understanding of trust in fully-autonomous
cars research
● Shows the importance of non-technological aspects in
fully-autonomous cars research
2. Managerial
● Proposes a design of AI which leads to the acceptance of
Conceptual model and hypotheses
● H1: Warmth focused AI
(vs. competence) leads to a higher acceptance of fully-autonomous cars.
● H1.2: Trust mediates the
Conceptual model and hypotheses
● H2.1: Low cultural context
interaction with a competence focused car AI has a more positive effect on perceived trust, than an interaction with a warmth focused one.
● H2.2: High cultural context
interaction with a warmth focused car AI has a more positive effect on perceived trust, than an interaction with a competence focused one.
● H3: The configuration of competence focused car AI and low cultural
Methodology
● Two survey designs, one with car A (warmth focused), one with
car B (competence focused) → between subjects design
● Warmth and competence manipulated by the description of AI
communication
Results
● Manipulation of warmth failed
● Car AI type had an effect on the acceptance of fully-autonomous cars
Mean Standard deviation F-statistic Significance
Warmth car A 5.1256 1.20042 2.675 0.104
Warmth car B 4.7890 1.25198
Mean of acceptance F-statistic Significance Partial Eta squared
Warmth focused 4.5092 13.542 0.000 0.087
Results
● Trust mediation was successful
Effect R Rsq. F-statistic
Car AI type on trust (effect a) 0.6368** 0.2717** 0.0738** 11.3162**
Trust on acceptance (effect b) 0.8047** 0.8016** 0.6425** 126.7012**
Car AI type on acceptance (effect c) 0.7186** 0.2951** 0.0871** 13.5424**
Results
● Moderation by cultural context was partially successful
Effect p
Cultural context * car AI type -0.1218 0.0246
Car AI type effect at -1 SD. cultural context 1.0838 0.0001
Car AI type effect at mean cultural context 0.6597 0.0006
Results
H1.1: Warmth focused AI (vs. competence) leads to a higher
acceptance of fully-autonomous cars.
Rejected – competence focused car AI leads on average to a
higher acceptance
H1.2: Trust mediates the effect of the AI character focus on the
acceptance of fully-autonomous cars.
Confirmed – there is a full mediation, as the effect of car AI
focus on the acceptance of fully-autonomous cars is no longer significant while including the trust mediator
H2.1: Low cultural context interaction with a competence focused
car AI has a more positive effect on perceived trust, than an interaction with a warmth focused one.
Confirmed – the effect of a competence focused car AI on trust
is even higher than a warmth focused one when at a low cultural context level
H2.2: High cultural context interaction with a warmth focused car
AI has a more positive effect on perceived trust, than an interaction with a competence focused one.
Rejected – cultural context moderation is not significant at a high
cultural context level
H3: The configuration of a competence focused car AI and low
cultural context will lead to the highest acceptance of fully-autonomous cars out of all of the hypothesised combinations.
Confirmed – out of all testable (significant) combinations of the
Discussion and limitations
1. Discussion
● Trust is of great importance for fully-autonomous cars research,
as it mediates the effect of car AI on its acceptance
● Together they explain 64% of variance
● Perceived competence of car AI increases trust
● Perceived competence of car AI can be increased just by the way
Discussion and limitations
● The lower the level of cultural context, the higher the trust of a
competence focused AI
● Higher levels of cultural context do not lead to a significant
moderation
Discussion and limitations
2. Limitations
● Failed manipulation of warmth limited the social cognition
relevance of findings
● Very young demographics → over 50% below the age of 24
● Mostly international students → could skew their openness and
cultural context
● Almost 50% of respondents scored the same on the cultural
References
● Welch, D. (2018). Who's Winning the Self-Driving Car Race? (accessed January 14, 2019), [available at: https://www.bloomberg.com/news/features/2018-05-07/who-s-winning-the-selfdriving-car-race]
● Davies, A. (2018). The Wired guide to self-driving cars. (accessed January 14, 2019), [available at: https://www.wired.com/story/guide-self-driving-cars/]
● Maurer, M., Gerdes, J. C., Lenz, B., & Winner, H. (2016). Autonomous driving Springer.
● Rödel, C., Stadler, S., Meschtscherjakov, A., & Tscheligi, M. (2014). (2014). Towards autonomous cars: the effect of autonomy levels on acceptance and user experience. Paper presented at the Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 1-8.
● Waytz, A., Heafner, J., & Epley, N. (2014). The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle. Journal of Experimental Social Psychology, 52, 113-117.
● Fiske, S. T., Cuddy, A. J., & Glick, P. (2007). Universal dimensions of social cognition: Warmth and competence. Trends in Cognitive Sciences, 11(2), 77-83.
● Demeure, V., Niewiadomski, R., & Pelachaud, C. (2012). How is believability of a virtual agent related to warmth, competence, personification, and embodiment? Presence: Teleoperators and Virtual Environments, 20(5), 431-448.
● Nowak, K. L., & Biocca, F. (2003). The effect of the agency and anthropomorphism on users' sense of telepresence, copresence, and social presence in virtual environments. Presence: Teleoperators & Virtual Environments, 12(5), 481-494.
● Lee, J. D., & Seppelt, B. D. (2009). Human factors in automation design. Springer handbook of automation (pp. 417-436) Springer. ● Doney, P. M., Cannon, J. P., & Mullen, M. R. (1998). Understanding the influence of national culture on the development of trust.
Academy of Management Review, 23(3), 601-620. ● Hall, E. (1976). Beyond culture. New York: Anchor Book
