We’re Measuring AI on the Wrong Ruler

Psychology Today

by John Nosta

February 24, 2026

AI-Generated Deep Dive Summary

The article challenges the common assumption that artificial intelligence (AI) and human intelligence can be measured on the same scale. While debates about AI often focus on whether machines are "smarter" than humans, this approach overlooks critical differences between human cognition and machine computation. Human thought is shaped by lived experience, consequences, and personal growth, whereas AI operates through statistical patterns and lacks biography or temporal continuity. The article highlights that AI excels at specific tasks, like arithmetic or route planning, but these optimizations don't equate to superior intelligence. For example, while AI can generate convincing language or solve problems, its "thinking" is consequence-free and lacks the depth of human reasoning. This distinction matters because conflating the two creates misleading comparisons—AI appears superhuman due to measurable outputs, while humans seem inefficient because they hesitate, revise, and learn from mistakes. The article suggests rethinking how we compare AI and human intelligence by focusing on their unique strengths rather than a single metric of "smartness." Human cognition is shaped by emotions, experiences, and ethical considerations, whereas AI operates within predefined datasets. This shift in perspective could help clarify AI's role and preserve the complexity of human thought, fostering healthier interactions with technology while acknowledging its limitations. For readers interested in health and mental health, this reframing matters because it influences how we perceive AI's impact on decision-making, creativity, or even mental health support systems. By recognizing the differences between human and machine cognition, we can better understand how to integrate AI into our lives without losing sight of what makes human intelligence unique—its depth, nuance, and ability to adapt through lived experience. Ultimately, the article calls for a more precise understanding of AI's capabilities and limitations, emphasizing that its power lies in specific optimizations rather

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Originally published on Psychology Today on 2/24/2026