Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain

detalle del documento

IDENTIFICACIÓN

oai:arXiv.org:2405.16311

Tema

Computer Science - Human-Computer ...

Autor

Balayn, Agathe Corti, Lorenzo Rancourt, Fanny Casati, Fabio Gadiraju, Ujwal

Categoría

Computer Science

Año

2024

fecha de cotización

29/5/2024

Palabras clave

explainability chain supply stakeholders

Métrico

Resumen

Explainability and transparency of AI systems are undeniably important, leading to several research studies and tools addressing them.

Existing works fall short of accounting for the diverse stakeholders of the AI supply chain who may differ in their needs and consideration of the facets of explainability and transparency.

In this paper, we argue for the need to revisit the inquiries of these vital constructs in the context of LLMs.

To this end, we report on a qualitative study with 71 different stakeholders, where we explore the prevalent perceptions and needs around these concepts.

This study not only confirms the importance of exploring the ``who'' in XAI and transparency for LLMs, but also reflects on best practices to do so while surfacing the often forgotten stakeholders and their information needs.

Our insights suggest that researchers and practitioners should simultaneously clarify the ``who'' in considerations of explainability and transparency, the ``what'' in the information needs, and ``why'' they are needed to ensure responsible design and development across the LLM supply chain.

;Comment: Paper accepted at the HCXAI workshop, co-located with CHI'24

Balayn, Agathe,Corti, Lorenzo,Rancourt, Fanny,Casati, Fabio,Gadiraju, Ujwal, 2024, Understanding Stakeholders' Perceptions and Needs Across the LLM Supply Chain