This Week in AI

5 curated reads for the week of March 23, 2026

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0 of 5 read this week

Business8 minGood for Sunday

What 81,000 people want from AI

Anthropic

Anthropic used an “AI interviewer” to collect open-ended interviews at massive scale from 80,508 Claude users across 159 countries and 70 languages. The value here isn’t just the headline count—it’s a grounded map of what people actually want (time savings, better work, life management) alongside what they fear (jobs, reliability, loss of control), which is more actionable than generic “AI optimism vs doom” debates.

#adoption#work#society

Business6 minGood for midweek

Reimagine learning and development for the AI age

McKinsey

McKinsey argues the biggest scaling constraint isn’t model access—it’s workforce capability and operating-model design. The practical guidance is to move learning into the flow of work, make managers the multiplier (not the bottleneck), and tie skilling to measurable business outcomes instead of generic “AI literacy.”

#skills#workforce#change

Business12 minGood for Sunday

Geopolitics and the geometry of global trade: 2026 update

McKinsey Global Institute

MGI’s update frames global trade around three forces: geopolitical “tariff splashes,” AI-driven demand shifts, and the ripple effects across supply chains. The AI-adjacent value is concrete: semiconductors and data-center equipment show up as strategic trade flows, which turns compute capacity into a budgeting + procurement + geopolitics problem—not just a technical one.

#geopolitics#datacenters#semiconductors

Models6 minGood for Friday

Measuring progress toward AGI: A cognitive framework

Google DeepMind (Google Blog)

DeepMind proposes a cognitive-science-inspired taxonomy (abilities like memory, reasoning, executive function, social cognition) and a protocol for benchmarking models against human performance distributions. The important stance is measurement: before arguing “how close to AGI,” we need shared evaluation language and better tests for missing abilities.

#evaluation#benchmarks#agi

Regulation7 minGood for Friday

Analyzing the passage of state-level AI bills

Brookings Institution

Brookings analyzes what predicts whether state AI bills get introduced and whether they actually pass, highlighting that outcomes depend heavily on political and coalition dynamics—not just policy text quality. Useful if you’re trying to forecast where compliance requirements will show up first in the U.S. and how fragmented the near-term landscape may get.

#policy#states#governance

Going Deeper

Optional reads for those who want more. (Some may be behind a paywall)

How we monitor internal coding agents for misalignmentOpenAIConcrete “agent monitoring” mechanics: what gets reviewed, what triggers alerts, and what they’ve observed in internal deployments.
Where to look for generative AI risksMIT SloanA clean managerial taxonomy (embedded vs enacted risk) and a practical inventory + ownership approach.
How Reco transforms security alerts using Amazon BedrockAWS Machine Learning BlogA realistic production case study showing how LLMs add value in security ops (triage + narrative + prioritization) without claiming full automation.