Why AI Owners and AI Users Have Conflicting Interests?
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IP compliance requirements on generative AI reduce the readily and cheaply available amount of training data, with a few consequences on how product development and product operations are done.
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As currently drafted (2024), the Algorithmic Accountability Act does not require the algorithms and training data used in an AI System to be available for audit. (See my notes on the Act, starting with the one here.) The way that an auditor learns about the AI System is from documented impact assessments, which involve descriptions…
AI Compliance at Scale via Embedded Data Governance
There are, roughly speaking, three problems to solve for an Artificial Intelligence system to comply with AI regulations in China (see the note here) and likely future regulation in the USA (see the notes on the Algorithmic Accountability Act, starting here): Using available, large-scale crawled web/Internet data is a low-cost (it’s all relative) approach to…
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On how not to deteriorate the decision-maker’s intrinsic motivation to make good decisions.
Incentives: Components of Incentive Mechanisms
An incentive mechanism is used to influence behavior. What are the components of an incentive mechanism, and how is that related to decision governance?
When Is a Career Resilient to AI?
The short answer: careers that reward creative problem solving in domains with scarce knowledge. Let’s unpack that.