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CII:Trustworthy AI and Software in Cars




Informationen zur Arbeit

Abschlussarbeitstyp: Master
Betreuer: Maximilian Renner
Forschungsgruppe: Critical Information Infrastructures

Archivierungsnummer: 4661
Abschlussarbeitsstatus: Offen
Beginn: 10. Januar 2022
Abgabe: unbekannt

Weitere Informationen

Background:

By 2025 every new vehicle sold will be connected to the Internet. Furthermore, by 2030 every new vehicle will be able to drive autonomously on the highway, and finally, by 2040, the first fully automated vehicles (Level 5) are offered in the market. Besides, Elon Musk says that by the end of 2020, the hardware of Tesla's cars will already be designed for autonomous driving, and only software updates will be needed. Nowadays, vehicles are connected via the Internet, which enables on-demand software updates and communication with other vehicles, the infrastructure, or the OEM. Customers are already familiar with cars and build up knowledge-based trust in the vehicle. To enable the full functionalities of connected vehicles up to autonomous driving, customers have to trust the integration of AI and software application within the vehicle. Thus, customers need knowledge-based trust and transparency in the functionality of the technology. We want to find out which characteristics may help to increase customer trust in AI which enables autonomous driving functionalities

Objective(s):

Through the upcoming appearance of AI and software in automotive vehicles, the challenge of creating widespread acceptance and trust in these technologies is becoming increasingly critical. This topic, however, is an umbrella topic whereas the specific goal of the thesis is definded in a first kickoff meeting

Research Method:

Expert Interviews or Literature Review

Literature:

  • D. H. McKnight, M. Carter, J. B. Thatcher, and P. F. Clay, "Trust in a specific technology," ACM Transactions on Management Information Systems, vol. 2, no. 2, pp. 1-25, 2011, doi: 10.1145/1985347.1985353.
  • J. Lansing and A. Sunyaev, "Trust in Cloud Computing: Conceptual Typology and Trust-Building Antecedents," ACM SIGMIS Database, vol. 47, pp. 58-96, 06/24 2016, doi: 10.1145/2963175.2963179.
  • K. Shin, D., “User Perceptions of Algorithmic Decisions in the Personalized AI System:Perceptual Evaluation of Fairness, Accountability, Transparency, and Explainability”, Journal of Broadcasting & Electronic Media, 64(4), 2020, pp. 541-565.
  • Hengstler, M., E. Enkel, and S. Duelli, “Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices”, Technological Forecasting and Social Change, 105, 2016, pp. 105-120.