Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence

While recent advances in AI-based automated
decision-making have shown many benefits for
businesses and society, they also come at a cost. It has
for long been known that a high level of automation
of decisions can lead to various drawbacks, such as
automation bias and deskilling. In particular, the
deskilling of knowledge workers is a major issue,
as they are the same people who should also train,
challenge and evolve AI. To address this issue, we
conceptualize a new class of DSS, namely Intelligent
Decision Assistance (IDA) based on a literature review
of two different research streams—DSS and automation.
IDA supports knowledge workers without influencing
them through automated decision-making. Specifically,
we propose to use techniques of Explainable AI (XAI)
while withholding concrete AI recommendations. To
test this conceptualization, we develop hypotheses on
the impacts of IDA and provide first evidence for their
validity based on empirical studies in the literature.