Explainable AI: A Diverse Stakeholder Perspective
Paper i proceeding, 2024

Artificial Intelligence (AI) is increasingly integral for doing classification and prediction tasks across various fields, including healthcare, legal systems, autonomous vehicles, and financial services [1]. As such, stakeholders such as system developers, system operators, end-users necessitate varying levels of explanations for the decisions proposed by these AI systems to enhance their trust and reliability in these systems, and use these systems in practice. The growing reliance on AI as a decision-support tool in these critical areas underscores the need for AI systems to be explainable development process and architecture, comprehensible to their users, ensuring their use is safe, responsible, and in compliance with legal standards.

Författare

Umm-E-Habiba

Universität Stuttgart

Khan Mohammad Habibullah

Software Engineering 1

Göteborgs universitet

Proceedings of the IEEE International Conference on Requirements Engineering

1090705X (ISSN) 23326441 (eISSN)

494-495
9798350395112 (ISBN)

32nd IEEE International Requirements Engineering Conference, RE 2024
Reykjavik, Iceland,

Ämneskategorier

Data- och informationsvetenskap

Naturresursteknik

DOI

10.1109/RE59067.2024.00060

Mer information

Senast uppdaterat

2024-09-20