The article draws parallels between the early internet era and the current landscape of artificial intelligence, highlighting the dichotomy of optimism and pessimism surrounding AI's impact on employment and productivity. It explores how different industries will experience varying outcomes based on the balance between unmet demand and automation capabilities. Historical perspectives on past technological shifts provide context for understanding AI's potential future.

• Radiology jobs and pay grew despite predictions AI would replace radiologists, because Jevons Paradox kicked in—cheaper/faster scans increased overall demand for imaging.
• Whether AI creates or destroys jobs in an industry depends on whether demand is already saturated: textiles boomed then crashed once automation met demand, while motor vehicles kept growing because demand stayed unmet.
• Job displacement risk is concentrated in repetitive, easily automated tasks rather than complex expert work.
• Software engineering faces a unique open question: automating app development could hit a demand saturation point, unlike other tech-driven fields.