Automation Bias
Automation Bias is the tendency to over-rely on automated systems and algorithms, trusting their outputs even when they conflict with other evidence or human judgment. First documented by researchers at NASA in the 1990s, this mental model explains why pilots crash planes despite clear warning signs, why traders lose fortunes by blindly following algorithms, and why users trust AI-generated content without verification. Understanding Automation Bias allows organizations to design safer human-machine systems and individuals to maintain critical thinking in an increasingly automated world.
Moore's Law
Moore's Law is the observation by Intel co-founder Gordon Moore (1965) that the number of transistors on a microchip doubles approximately every two years, while the cost remains constant. This empirical regularity drove exponential improvement in computing power for 60 years and is the underlying engine of the digital revolution. Understanding Moore's Law and its limits is essential for technology strategy, product roadmapping, and investment analysis.
Path Dependency
Path Dependency describes how historical choices constrain future options — even when better alternatives now exist. The current state of a system reflects not just the best available choice today, but the accumulated weight of decisions made in the past under different conditions. QWERTY keyboards, VHS over Betamax, Windows dominance, and most technology standards exhibit path dependency.