A Framework for Exploring the Consequences of AI-Mediated Enterprise Knowledge Access and Identifying Risks to Workers
arxiv(2023)
摘要
Organisations generate vast amounts of information, which has resulted in a
long-term research effort into knowledge access systems for enterprise
settings. Recent developments in artificial intelligence, in relation to large
language models, are poised to have significant impact on knowledge access.
This has the potential to shape the workplace and knowledge in new and
unanticipated ways. Many risks can arise from the deployment of these types of
AI systems, due to interactions between the technical system and organisational
power dynamics.
This paper presents the Consequence-Mechanism-Risk framework to identify
risks to workers from AI-mediated enterprise knowledge access systems. We have
drawn on wide-ranging literature detailing risks to workers, and categorised
risks as being to worker value, power, and wellbeing. The contribution of our
framework is to additionally consider (i) the consequences of these systems
that are of moral import: commodification, appropriation, concentration of
power, and marginalisation, and (ii) the mechanisms, which represent how these
consequences may take effect in the system. The mechanisms are a means of
contextualising risk within specific system processes, which is critical for
mitigation. This framework is aimed at helping practitioners involved in the
design and deployment of AI-mediated knowledge access systems to consider the
risks introduced to workers, identify the precise system mechanisms that
introduce those risks and begin to approach mitigation. Future work could apply
this framework to other technological systems to promote the protection of
workers and other groups.
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