  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 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.
