TrustworthinessTransparencySafetycs.CY
Finding differences in perspectives between designers and engineers to develop trustworthy AI for autonomous cars
Gustav Jonelid, K. R. Larsson
July 1, 2023
arXiv.org
1 citations
Key Takeaways
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Designers and engineers have fundamentally different perspectives on trustworthy AI for autonomous vehicles, and these divergences need to be actively addressed during development rather than assumed to align naturally.
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Trustworthy AI for autonomous cars requires three interconnected pillars: transparency (understanding how decisions are made), reliability (consistent performance), and safety (preventing harm)—moving beyond simplified ethical frameworks like the trolley problem to address real-world complexity.
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Bridging the gap between design and engineering teams is essential for responsible AI development, as the study identifies specific factors contributing to perspective differences and proposes concrete strategies to minimize these divergences during implementation.
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Ethical AI development requires balancing technological advancement with ethical principles, suggesting that responsible autonomous vehicles cannot be achieved by prioritizing either engineering feasibility or ethical considerations alone, but rather through integrated collaboration.
Abstract
In the context of designing and implementing ethical Artificial Intelligence (AI), varying perspectives exist regarding developing trustworthy AI for autonomous cars. This study sheds light on the differences in perspectives and provides recommendations to minimize such divergences. By exploring the diverse viewpoints, we identify key factors contributing to the differences and propose strategies to bridge the gaps. This study goes beyond the trolley problem to visualize the complex challenges of trustworthy and ethical AI. Three pillars of trustworthy AI have been defined: transparency, reliability, and safety. This research contributes to the field of trustworthy AI for autonomous cars, providing practical recommendations to enhance the development of AI systems that prioritize both technological advancement and ethical principles.