Browse Comments — Clean (de-noised)

Clara Hawking Don Kilburg, Ph.D. I thought his section on human rights was rather good. Worth a read in full.

When I was a child our parish priest had a monopoly on interpreting the Pope's writings

This is why experienced developers get better AI results than beginners.

Every strong AI workflow starts with structure and patience.

The craftsmanship shows up less in the prompt and more in how well you manage iteration, validation, and scope control across steps. That is usually where the real skill difference emerges, not in model choice or prompt style.

There is a subtle assumption here that frustration comes from misunderstanding the tool, when often it comes from underestimating how much judgment is still required. AI does not remove the hard parts, it compresses them into tighter cycles that demand more attention, not less.

This perfectly describes the difference between experimenting and actually building useful products.

This is exactly how real developers use AI. Small steps, testing, and constant refining.

AI industry uses the Jio model of dependency. Give products at very cheap rates make them dependent and charge higher and higher.

The question also extends to how the control is done, how much of AI are we implementing in our lives? Who controls that? Healthcare is a field that benefits the most from AI, and we need more people there but does it make more money....

Brilliant Pascal. Whether or universal basic income is a great way to motivate someone, and whether it leads to fulfilling lives is not really the question. Can we extract the wealth from the West Coast is actually the question, and Warren Buffett seems to have an idea for that too. Probably not under the current administration though.

Pascal BORNET part of this awareness that we champion, is understanding that AI is not just a resource. It is a new environment for human cognition. And the implications of a small group controlling a cognitive environment are unknown, at best.

This is the correction phase of the AI hype cycle that many experienced engineers expected. AI absolutely boosts productivity, but “replace engineers” was always a flawed framing. Engineering is not just code generation — it’s architecture, trade-offs, debugging ambiguous failures, domain understanding, operational ownership, and long-term maintainability. What many companies underestimated:• Token economics at enterprise scale• Context-window inefficiencies on large codebases• Human review overhead• Hallucination-driven rework• The cost of bad architectural decisions generated confidently at high speed The real winning model is likely to be:Small, highly skilled engineering teams + AI augmentation — not AI replacing teams entirely. The companies getting the best ROI from AI today are usually the ones using it as a force multiplier for senior engineers, not as a wholesale substitute for engineering judgment.

The people getting amazing AI results usually have strong systems behind them.

Clara, I’m curious how you think institutions can practically preserve that kind of humane reflection as AI systems scale so quickly, while geopolitical tensions, sometimes shaped by misinterpreted religions and religious influence, continue to rise.

I also come to the world of AI in education via Theology, and also value the time to read closely. I'm not at all surprised by the number of philosophy, theology and ethics folks doing this work in education.

A desperate attempt maybe to stay relevant in topics they know nothing about. AI use and consequences are ethical topics, not religious ones.

Yes, lots of rethinking to do. At the school of collective intelligence in Rabat they are doing a wonderful seminar on AI and learning that I sadly cannot attend and they have been sharing interesting articles on learning in the teams chat I follow while I grade the 30 essays from my class: · AI-induced never-skilling in medical education: · On the opposite side of the debate, the historical development of ‘cognitive offloading’ in education systems · On what we mean by learning: Deescalating the AI Learning Debate - by Nick Potkalitsky

The best builders know prompting is only one small part of the process.

No AI worries here!