Algorithm Aversion and Self-driving Cars

DOI

10.2991/aebmr.k.220307.077How to use a DOI?

Keywords

Algorithm Aversion; Self-driving car; behavioral economics; experiment proposal

Abstract

Algorithm aversion is the phenomenon that humans tend to resist using algorithms for assisting decision-making, and this aversion has affected the application and spreading of autonomous vehicles, which deploy algorithms. This paper will at first shortly review the researches about algorithm aversion, by mainly referring to the literature review by Burton, Stein and Jensen’s in 2020, to address three causes and general solutions for autonomous vehicles industry to alleviate algorithm aversion, the case of Tesla company will occasionally be taken as an example to make detail explanation. Then the article suggests several policies that self-driving car companies can adopt to alleviate influences such as possible sales decline and customers’ complaints brought by algorithm aversion, then propose an experiment to verify if these policies are reasonable and feasible, and will finally discuss the limitations of the proposal and this paper and some works that can be done in the future.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Yuze Kang
PY  - 2022
DA  - 2022/03/26
TI  - Algorithm Aversion and Self-driving Cars
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 481
EP  - 485
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.077
DO  - 10.2991/aebmr.k.220307.077
ID  - Kang2022
ER  -