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
Sections 6 through 11 of the Algorithmic Accountability Act (2022 and 2023) have less practical implications for product management. They ensure that the Act, if passed, becomes part of the Federal Trade Commission Act, as well as introduce requirements that the FTC needs to meet when implementing the Act. This text follows my notes on…
If any text can be training data for a Large Language Model, then any text is a training dataset that can be valued through a market for training data. Which datasets have high value? Wikipedia, StackOverflow, Reddit, Quora are examples that have value for different reasons, that is, because they can be used to train…
What can you do to influence someone’s decision, if you cannot give them advice? In short, a possible approach is to take actions that satisfy two conditions: I call this the nurturing of choice. Instead of providing advice that is clearly directed at the elements of the decision problem (as I discussed in my book…
Does the EU AI Act apply to most, if not all software? It is probably not what was intended, but it may well be the case. The EU AI Act, here, applies to “artificial intelligence systems” (AI system), and defines AI systems as follows: ‘artificial intelligence system’ (AI system) means software that is developed with…
Designing effective decision governance systems requires drawing on a wide range of academic disciplines, each of which provides valuable insights into different aspects of decision-making.
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…