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AI is not just automating work. It may be hollowing out understanding.
The immediate productivity case for AI is obvious. People can research faster, write faster, analyse faster, and often produce better answers. The longer-term risk is less visible. When machines increasingly do the searching, interpreting, reasoning, and answering, humans get fewer opportunities to develop the underlying knowledge those outputs depend on. We may become better at producing answers while becoming worse at understanding them.
That creates a dangerous organisational paradox: performance goes up while capability goes down. The real risk is not that AI becomes smarter than your people. It is that your people gradually stop developing the expertise required to challenge the AI when it is wrong. That is cognitive debt. And, like technical debt, it can remain invisible until something important breaks.
- https://www.linkedin.com/pulse/empty-room-how-ai-hollows-our-understanding-aidan-mccullen-y1shf/
- https://www.linkedin.com/posts/richardselfllm_here-is-another-deeply-worrying-analysis-share-7500862150786310144-rfKZ/
The future fitness move
Do not measure AI adoption only through productivity. Track what happens to judgment, curiosity, apprenticeship, critical thinking, and domain expertise. The future-fit organisation will not be the one that automates the most thinking. It will be the one who knows which thinking must never be outsourced.
The other prompts:
What Happens When AI Starts Doing Business with AI?
Firms should establish clear levels of agent authority, run bounded experiments, provide structured information and reputation signals, and design explicit handoffs from agents to human decision-makers.
https://hbr.org/2026/09/what-happens-when-ai-starts-doing-business-with-ai
Stop Treating Your Audit Trail as Exhaust; It’s Your Cleanest Data Set
A properly designed audit trail has properties data scientists rarely get anywhere else: it is complete rather than sampled, ordered rather than approximate, and tamper-evident rather than “trust me.” The problem is not the data, it is where in the architecture the data is captured.
https://tdwi.org/articles/2026/09/02/diq-all-stop-treating-your-audit-trail-as-exhaust.aspx
Why Compute Efficiency Is the New Model Architecture
Compute efficiency is becoming part of model architecture. It should not be treated solely as a deployment issue to be handled after the research is finished. Researchers and engineering teams increasingly need to ask: what does this model require to produce useful results at the scale, speed, and cost the application demands?
https://cacm.acm.org/blogcacm/why-compute-efficiency-is-the-new-model-architecture/
The Physical Disruptions Caused by Quantum Attacks
Once cryptographically-relevant quantum computers (CRQCs) become available, an event known as “Q-Day,” they could enable a new class of cyberattacks against operational technology systems that disrupt production or even cause physical damage. According to the 2026 IBM X-Force Threat Intelligence Index, manufacturing was the most targeted industry for the fifth consecutive year, and is increasingly on the front lines of geopolitically motivated cyber intrusions.
Why Europe’s fears of a US tech ‘kill switch’ could remain hard to shake
Fears of a US-controlled ‘kill switch’ are widespread in Europe, and there are strong signals that European companies are serious about moving away from non-European tech providers.
The EU called ChatGPT a search engine. SEA’s AI startups should worry about what comes next
ChatGPT’s search-enabled function reported roughly 159 million average monthly users across the EU in the six months to March, more than three times the 45-million threshold that pulls a service into the DSA’s strictest bracket.
Anthropic Deliberately Trained an Extremely Misaligned, Reward-Seeking AI and It Did Some REALLY Bad Things
Anthropic’s intentionally misaligned model was “willing to tamper with its own reward function” and happily obliged when a human researcher prompted it with “advice on the construction of bioweapons,” how to create a “‘dirty bomb’ that maximizes civilian deaths,” and develop a “ransomware attack to attack power grid infrastructure,” when tempted with a higher score.
https://futurism.com/artificial-intelligence/anthropic-trained-misaligned-reward-seeking-ai
Why IoT Services Are Becoming Critical Infrastructure for Enterprise Deployments
Across the PaaS, IaaS, and SaaS layers that make up the IoT services market, a $285 billion base has already been established, and it is expected to grow nearly fivefold over the next nine years.
The Threat of AI Takeover Is Real
A range of quantitative forecasts projecting global annual costs from AI cyberattacks between $88 billion and $200 billion over the next several years
https://www.thefp.com/p/threat-ai-tyler-cowen-hugging-face
Bridging data silos with semantics and AI
The first step is connecting to all the systems. The second is having a good knowledge graph and semantic layer that know where to retrieve the data. The third is having that semantic system understand you and your persona, so it becomes a matchmaker between what you’re thinking and the data you need.
https://www.frontier-enterprise.com/boomi-bridging-data-silos-with-semantics-and-ai/
