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#64: Chat GPT is making you dumber (not a clickbait, there is a research for that)
Chat GPT affects yout ability to think critically! But does it actually make you “dumber,” or does it free up mental bandwidth for more meaningful work?
Together with data scientist Paul Larsen, we unpack recent studies from Microsoft and MIT, real cases from software development and education, and translate it into practical rules: when it’s safe to delegate to AI and when you should deliberately “work the mental muscles” yourself (code review, testing, architectural decisions).
We also touch on the org-level effect: what happens to a team’s skills if engineers become AI babysitters, and how to build proper model monitoring and evaluation instead of endless human-in-the-loop, and what companies can do to minimize risks.
Also in this episode:
- Cognitive offloading vs. genuine cognitive-load savings; why “less mental pain” ≠ “less intelligence.”
- An “error budget” for tasks: where the cost of a mistake is high vs. where AI can operate under monitoring.
- Human-in-the-loop vs. production ML practices: logs, quality metrics, drift, and periodic re-evaluation.
- How the “charming politeness” of chat models lowers skepticism and how to counter it.
- “Dosed” use of assistants: what to do yourself (planning, hypothesis framing) vs. what to hand over to AI.
- Graph-based models in the enterprise: why large companies pick standard, lower-risk use cases.
- Data contracts, CI/CD for data, and “AI for data → better data for AI.”
- Advice for listeners: avoid flattening teams into “assembly & polishing” roles and preserve core competencies.
Show notes:
• Survey of knowledge workers: higher trust in GenAI correlates with less critical-thinking engagement. Microsoft Research
• LLM-assisted writing reduced recall and neural engagement; 83% in the LLM group couldn’t accurately quote their own text. MIT Media Lab
• After habituation to AI support, endoscopists’ without-AI accuracy dropped (−6 percentage points ADR). The Lancet Gastroenterology & Hepatology
• A high-schooler’s first-person account of AI disrupting classroom learning. The Atlantic
• Relational/graph foundation model for enterprise predictive apps; background + papers. Kumo.ai · Research
• GenAI cyber-risk in practice: threat model and developer guidance by Paul Larsen. Article 1 · Article 2
Imkdev is a consultancy for Public Cloud (AWS/GCP), Data/ML, and Platform Engineering. We help companies accelerate delivery, reduce cloud costs, and deploy GenAI safely (while not making you dumber along the way) - from audits and architecture to productionizing models, monitoring, and team training: https://mkdev.me/
Visit mkdev.me and subscribe to MKDEV Dispatch for new episodes and articles: https://mkdev.me/dispatchBuy mkdev merchandise here: https://store.mkdev.me
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By mkdevChat GPT affects yout ability to think critically! But does it actually make you “dumber,” or does it free up mental bandwidth for more meaningful work?
Together with data scientist Paul Larsen, we unpack recent studies from Microsoft and MIT, real cases from software development and education, and translate it into practical rules: when it’s safe to delegate to AI and when you should deliberately “work the mental muscles” yourself (code review, testing, architectural decisions).
We also touch on the org-level effect: what happens to a team’s skills if engineers become AI babysitters, and how to build proper model monitoring and evaluation instead of endless human-in-the-loop, and what companies can do to minimize risks.
Also in this episode:
- Cognitive offloading vs. genuine cognitive-load savings; why “less mental pain” ≠ “less intelligence.”
- An “error budget” for tasks: where the cost of a mistake is high vs. where AI can operate under monitoring.
- Human-in-the-loop vs. production ML practices: logs, quality metrics, drift, and periodic re-evaluation.
- How the “charming politeness” of chat models lowers skepticism and how to counter it.
- “Dosed” use of assistants: what to do yourself (planning, hypothesis framing) vs. what to hand over to AI.
- Graph-based models in the enterprise: why large companies pick standard, lower-risk use cases.
- Data contracts, CI/CD for data, and “AI for data → better data for AI.”
- Advice for listeners: avoid flattening teams into “assembly & polishing” roles and preserve core competencies.
Show notes:
• Survey of knowledge workers: higher trust in GenAI correlates with less critical-thinking engagement. Microsoft Research
• LLM-assisted writing reduced recall and neural engagement; 83% in the LLM group couldn’t accurately quote their own text. MIT Media Lab
• After habituation to AI support, endoscopists’ without-AI accuracy dropped (−6 percentage points ADR). The Lancet Gastroenterology & Hepatology
• A high-schooler’s first-person account of AI disrupting classroom learning. The Atlantic
• Relational/graph foundation model for enterprise predictive apps; background + papers. Kumo.ai · Research
• GenAI cyber-risk in practice: threat model and developer guidance by Paul Larsen. Article 1 · Article 2
Imkdev is a consultancy for Public Cloud (AWS/GCP), Data/ML, and Platform Engineering. We help companies accelerate delivery, reduce cloud costs, and deploy GenAI safely (while not making you dumber along the way) - from audits and architecture to productionizing models, monitoring, and team training: https://mkdev.me/
Visit mkdev.me and subscribe to MKDEV Dispatch for new episodes and articles: https://mkdev.me/dispatchBuy mkdev merchandise here: https://store.mkdev.me