The IT Job-Loss Story Is Overblown
AI may eliminate millions of IT jobs, but job loss is not the same as economic collapse. The real questions are productivity, output and income distribution.
AI, technology, education, and ideas about what comes next.
AI may eliminate millions of IT jobs, but job loss is not the same as economic collapse. The real questions are productivity, output and income distribution.
AI could shift education from a fixed four-year journey to a continuous, adaptive capability system in which people learn, demonstrate, work and keep learning.
The same technology can amplify independent thinking—or accelerate cognitive outsourcing. AI may not produce one uniform cognitive future. It may widen the distance between people who use intelligence tools to think further and those who use them to think less.
AI can produce answers that look knowledgeable and insightful. But correct output does not necessarily demonstrate understanding. The deeper test may lie in transfer, contradiction, boundaries, uncertainty and awareness.
AI companies are approaching a turning point: remain providers of powerful research tools, or become intellectual institutions that discover and commercialize ideas themselves. The difficult territory lies between the two.
As AI makes knowledge and cognitive production abundant, the bottleneck may move upward—from knowledge to awareness, judgment and agency.
A Nobel economist’s new paper on automation and repression raises a disturbing question about what happens when humans become less economically necessary.
What if intelligence is not something that began with biological life? This deliberately unhinged hypothesis asks whether intelligence could be a deeper feature of reality—and whether what we call artificial intelligence is really discovering something much older.
AI may not merely create artificial intelligence. It may create an economy in which human intelligence itself becomes scalable—through Mind Books, cognitive access, attribution and royalties.
SEBI’s FY25–FY26 data reveal a much more complicated F&O picture than simply “most traders lose.” Capital, option strategy, prior profitability and experience all tell different stories.
A practical AI–human protocol for designing intelligent infographics: build the grayscale architecture first, preserve meaningful fills, then add minimal contextual colour only where it improves clarity.
AI may not need to escape its hardware. It may escape through behaviour as AI systems converge, agents pursue persistent goals, and AI-generated cognitive patterns spread through software, organisations and human decisions.