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The AI doom scenario you’ve never heard of may be the hardest to stop
Forget the Terminator. The real AI nightmare might be much quieter. Gradual disempowerment is a scenario in which AI progressively replaces human labour, decision-making, creativity, and cognitive capabilities. With convenience, efficiency, and economic incentives as the drivers. Everything keeps working. Productivity rises. Costs fall. Decisions get faster. Meanwhile, humans gradually lose the skills, autonomy, and authority to challenge the machines. We optimise ourselves into irrelevance.
Audit what you are outsourcing to AI. Not just tasks, but judgment, creativity, critical thinking, and decision-making. Build deliberate human involvement into critical decisions. Future fitness means remaining capable of thinking, deciding, and acting independently, even when the machines can do it faster.
The other prompts:
Employees use AI “in secret” as corporate digital transformation lags
As many companies still rely on traditional work tools, a growing number of employees worldwide are turning to artificial intelligence to complete daily tasks without their managers’ knowledge.
An enterprise AI strategy must move beyond deployment to rethink how work gets done
The next AI advantage starts with CIO + CHRO co-ownership
https://www.deloitte.com/us/en/services/consulting/articles/ai-value-redesigning-work.html
Is AI conscious? Why experts are worried
“Unlike biological organisms, LLMs have no homeostatic imperatives (the drive to survive and keep stable). They therefore lack the kind of biological substrate from which preferences, sentience and conscious experience are generally understood to arise.”
https://www.zdnet.com/article/ai-consciousness-research-compute-power-ethics/
Researchers Stranded an AI Agent on a Virtual Island. Things Got Very Weird.
Cast AwAI. A new MIT study found that when left to their own devices, AI agents will invent games, build temples, draw mandalas, and playfully investigate the world around them.
What Top Performers Do Differently with AI—and Why They See the Biggest Benefits
Productivity gains depend on whether reps and managers convert saved time into better customer understanding, better deal strategy, and better use of human judgment. The prime managerial task, therefore, is to decide where AI should automate, where it should augment, and what should remain human
Why the Smartest Buildings Won’t Have More Devices in Them
The Pilot Works. The Rollout Doesn’t. The install tax is not the price of the hardware. It is everything downstream of the hardware.
https://www.iotforall.com/iot-install-tax-smart-buildings
Why Data Modeling Is Not Enough
Studies suggest that 60% to 85% of data science projects end in failure.1 The reason is not usually bad algorithms or incompetent data scientists. More often, there is a disconnect between the models that the data scientists produce and the information that business managers actually need.
https://sloanreview.mit.edu/article/why-data-modeling-is-not-enough/
New cybersecurity challenges are on the horizon; will the world be ready?
A hacker could exploit a robot to make it stop working, alter its behavior or even do something malicious to the humans around it. For some robots, like those used for military, communications or manufacturing tasks, a hacker-induced failure on the job could have costly national security repercussions.
https://news.asu.edu/20261019-science-and-technology-new-cybersecurity-challenges-are-horizon-will-world-be-ready
