Search Results for author:
Found 4 papers, 0 papers with code
Understanding accountability in algorithmic supply chains
Academic and policy proposals on algorithmic accountability often seek to understand algorithmic systems in their socio-technical context, recognising that they are produced by 'many hands'.
Out of Context: Investigating the Bias and Fairness Concerns of "Artificial Intelligence as a Service"
"AI as a Service" (AIaaS) is a rapidly growing market, offering various plug-and-play AI services and tools.
Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems
This paper introduces reviewability as a framework for improving the accountability of automated and algorithmic decision-making (ADM) involving machine learning.
Decision Provenance: Harnessing data flow for accountable systems
Specifically, given the concerns regarding ever-increasing levels of automated and algorithmic decision-making, and so-called 'algorithmic systems' in general, we propose decision provenance as a concept showing much promise.
