Data Quality & AI Quality Are not Independent

How does the #quality of your #data affect the #design of your #AI ? pic.twitter.com/gFBo0JviLp
— ivanjureta (@ivanjureta) February 13, 2018
Just like l’art pour l’art, or art for the sake of art was the bohemian creed in the 19th century, it looks like there’s an “AI for the sake of AI” creed now when building general-purpose AI systems based on Large Language Models. Let’s say that the aim for a sustainable business are happy, paying,…
Definitions of the concepts derived from the goal concept (including functional and nonfunctional goal, hardgoal, and softgoal) used in requirements engineering are discussed, and precise (and, when appropriate, mathematical) definitions are suggested. The concept of satisficing, associated to softgoals is revisited. A softgoal is satisficed when thresholds of some precise criteria are reached. Satisficing does…
The Algorithmic Accountability Act (2022 and 2023) applies to many more settings than what is in early 2024 considered as Artificial Intelligence. It applies across all kinds of software products, or more generally, products and services which rely in any way on algorithms to support decision making. This makes it necessary for any product manager…
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?
A “Requirements Loop” is an evidence-supported explanation of How observed events in an environment have led or are leading to the creation and persistence of those requirements, How to change the environment in order to satisfy the requirements in the future, and How to measure the change in the environment, in order to evaluate the…