Why AI Projects Fail: The Human Factors Analysis
Most AI implementations fail not because the technology doesn't work, but because organizations treat them as technology projects instead of people projects. This analysis reveals the four human factors that destroy 80% of AI initiatives.
The Design Problem We Call User Resistance
Recent research analyzing 63 studies reveals that what we call "user resistance" to technology isn't about fear of change—it's valuable feedback about design failures that make work harder, strip away meaningful judgment, ignore human workflows, and break essential collaboration.
The False Promise of AI Deregulation
The House's proposed decade-long ban on state AI regulation creates a dangerous oversight vacuum just when we need thoughtful rules to ensure AI systems serve human needs rather than exploit our vulnerabilities.
The Stakeholder Alignment Problem in Healthcare AI
As healthcare AI systems become increasingly autonomous, the real risk isn't technical failure but successful optimization for misaligned objectives.
The Creation Problem: How Social Platforms Disincentivize Production
Social platforms profit from consumption while systematically creating barriers to creation—revealing a structural misalignment between business models and human creative drive.
