# Check out my new paper on “Economics of Human-AI Ecosystem: Value Bias and Lost Utility in Multi-Dimensional Gaps”

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. This paper [1] investigates the dynamics of creation and exchange of values and points out gaps in perception of cost-value, knowledge, space and time dimensions. It shows aspects of value bias in human perception of achievements and costs that encoded in AI systems. It also proposes rethinking hard goals definitions and cost-optimal problem-solving principles in the lens of effectiveness and efficiency in the development of trusted machines. The paper suggests a value-driven with cost awareness strategy and principles for problem-solving and planning of effective research progress to address real-world problems that involve diverse forms of achievements, investments, and survival scenarios.

The relation of information and knowledge modeled in
the in DIKW hierarchy (data – information – knowledge –
wisdom)

Different dimensions of costs and values

Types of utilities and examples for creating positive and negative utility

[1] D. Muller, “Economics of human-ai ecosystem: value bias and lost utility in multi-dimensional gap,” Arxiv preprint arxiv:1811.06606, 2018.
[Bibtex]
@article{mullerEconomicsHAI2018,
title={Economics of Human-AI Ecosystem: Value Bias and Lost Utility in Multi-Dimensional Gap},
author={Muller, Daniel},
journal={arXiv preprint arXiv:1811.06606},
year={2018}
}