Document Type
Article
Publication Date
5-15-2021
Department
Computer Engineering and Computer Science
Abstract
One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents. This paper explores how decision matrix algorithms, via the belief-desire-intention model for autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for the values of explainability and verifiability. In doing so, this research adopts the Value Sensitive Design (VSD) approach as a principled framework for the incorporation of such values within design. VSD is recognized as a potential starting point that offers a systematic way for engineering teams to formally incorporate existing technical solutions within ethical design, while simultaneously remaining pliable to emerging issues and needs. It is concluded that the VSD methodology offers at least a strong enough foundation from which designers can begin to anticipate design needs and formulate salient design flows that can be adapted to the changing ethical landscapes required for utilisation in autonomous vehicles.
Original Publication Information
Umbrello, S., Yampolskiy, R.V. Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles. Int J of Soc Robotics (2021). https://doi.org/10.1007/s12369-021-00790-w
ThinkIR Citation
Umbrello, Steven and Yampolskiy, Roman V., "Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles" (2021). Faculty Scholarship. 554.
https://ir.library.louisville.edu/faculty/554
DOI
10.1007/s12369-021-00790-w
ORCID
0000-0001-9637-1161
Comments
© The Author(s) 2021
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