How Data Availability and Cost Relate to AI Differentiation?

When someone pitches me an #ai/#MachineLearning idea, I always (also) ask about #data availability, data cost, and how they relate to their product differentiation and #aitechnology. Here’s how I see them, roughly speaking. #strategy #AIstrategy #AIeconomics pic.twitter.com/v6yb8JOHwi
— ivanjureta (@ivanjureta) February 19, 2018
I use “depth of expertise” as a data quality dimension of AI training datasets. It describes how much a dataset reflects of expertise in a knowledge domain. This is not a common data quality dimension used in other contexts, and I haven’t seen it as such in discussions of, say, quality of data used for…
Is it one that led to the best outcome? Or one that integrates all the relevant and available information? Maybe one that is liked by a majority? If decision governance is followed to the letter, will that guarantee a high quality decision? The quality of a decision depends on the following: The reason a decision…
If competence shortens learning, then its value is proportional to the cost of learning, that is, of iterations that would have been needed to achieve the effects of competence, but without having access to it.
In the creator economy, the creative individual sells content. The more attention the content captures, the more valuable it is. The incentive for the creator is status and payment for consumption of their content. Distribution channels are Internet platforms, where content is delivered as intended by the author, the platform does not transform it (other…
Should the explanations that an Artificial Intelligence system provides for its recommendations, or decisions, meet a higher standard than explanations for the same, that a human expert would be able to provide? I wrote separately, here, about conditions that good explanations need to satisfy. These conditions are very hard to satisfy, and in particular the…