Quality Assurance for AI: An Inevitable Tradeoff

How do you ensure #quality of a #service which uses #AI for #personalization? #QA in that case is all about risk management. pic.twitter.com/IdKcY5noBL
— ivanjureta (@ivanjureta) January 31, 2018
“Objective”, as in, for example, “what I’m saying is objective”, or “that statement is objective”, or “we need objective criteria when making these decisions”, is a complicated term. It takes a lot of effort to make sure it is understood as intended (or closely enough). It is therefore a costly word to use. Why is…
If AI is made for profit, then should its design be confidential? This choice is part of AI product strategy. The decision on this depends on the following at least. What is the relationship of each of these to AI confidentiality? Correctness: The more likely the AI / algorithm is to make errors, the more…
The overall objective of Requirements Engineering is to specify, in a systematic way, a system that satisfies the expectations of its stakeholders. Despite tremendous effort in the field, recent studies demonstrate this is objective is not always achieved. In this paper, we discuss one particularly challenging factor to Requirements Engineering projects, namely the change of…
Over the last decade, online social networks (OSNs) have been growing quickly to become some of the largest systems in use. Their users are sharing more and more content, and in turn have access to vast amounts of information from and about each other. This increases the risk of information overload for every user. We…
In the context of human decision making, a decision is a commitment to a course of action (see the note here); it involves mental states that lead to specific actions. An AI system, as long as it is a combination of statistical learning algorithms and/or logic, and data, cannot have mental states in the same…