In recent years, artificial intelligence (AI) decision-making and autonomous systems became an integrated part of the economy, industry, and society. The evolving economy of the human-AI ecosystem raising concerns regarding the risks and values inherited in AI systems. My research on planning and decision making in oversubscribed systems investigates the dynamics of creation and exchange of values and points out some gaps in perception of cost-value, knowledge, space and time dimensions. In this blog, I would like to suggest a deeper look at the role of data in the decision-making process and to provide some of the observations from my recent paper on “Economics of Human-AI Ecosystem: Value Bias and Lost Utility in Multi-Dimensional Gaps” (2018).
Sometimes there is no credit for being right. In many cases, there is a big difference between being right and making the right things happen.
Suppose you see a disaster coming, and you are right about that disaster, it is going to happen. Here are two decisions you can consider: 1) Be right, or; 2) Try to be wrong, and make the right thing happen. But Caution; by striving to prevent bad predictions come to true you prove yourself being wrong.
What is it being right in time perspective? Should we strive to be right now or should we focus on doing right and being right in (future) retrospective?