How Data Availability and Cost Relate to AI Differentiation?
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Algorithmic Accountability Act for AI Product Managers: Section 4
Section 4 provides requirements that influence how to do the impact assessment of an automated decision system on consumers/users. This text follows my notes on Sections 1 and 2, and Section 3 of the Algorithmic Accountability Act (2022 and 2023). When (if?) the Act becomes law, it will apply across all kinds of software products,…
What Is Evidence?
There is no single definition of the term “evidence”, and trying to make one isn’t the purpose of this text. But there are ways of telling if something might be evidence, and knowing when it clearly isn’t. Such knowledge helps you develop a taste, so to speak, in evidence. Isn’t that valuable, given how frequently you may be giving evidence to support your ideas, and how frequently others do the same to you?
Algorithmic Accountability Act of 2022 and AI Design
The Algorithmic Accountability Act of 2022, here, is a very interesting text if you need to design or govern a process for the design of software that involves some form of AI. The Act has no concept of AI, but of Automated Decision System, defined as follows. Section 2 (2): “The term “automated decision system”…
Can Decision Autonomy of an AI Be Distinguished from Malfunction?
I wrote in another note (here) that AI cannot decide autonomously because it does not have self-made preferences. I argued that its preferences are always a reflection of those that its designers wanted it to exhibit, or that reflect patterns in training data. The irony with this argument is that if an AI is making…
Private Data Use Consent as a Generative AI Compliance Requirement
In a previous note, here, I wrote that one of the requirements for Generative AI products/services in China is that if it uses data that contains personal information, the consent of the holder of the personal information needs to be obtained. It seems self-evident that this needs to be a requirement. It is also not…