education
Personalised Explanation Is Not the Same as Learning
An explanation can adapt to a learner's question, but durable learning still requires retrieval, practice, feedback and independent use of the idea.
Topic by Sami Mechkor
Artificial Intelligence
Writing by Sami Mechkor about artificial intelligence, human judgment, useful capability and responsible progress.
Artificial intelligence can extend access to explanation, analysis and creative tools. Its public value depends on more than model capability: systems must be understandable, dependable and designed around the people who use or are affected by them.
Questions that matter
This topic examines AI without treating optimism and responsibility as opposites. The important questions concern what a system enables, where it can fail, how people retain agency and which uses genuinely improve human life.
- How can AI expand human potential?
- Where must human judgment remain decisive?
- What makes an AI system dependable in practice?
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Why Physical Intelligence Is Harder Than It Looks
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Faster Discovery Still Needs Careful Verification
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Computing Limits Shape Artificial Intelligence
AI capability is bounded by computation, memory, data movement, energy and latency, making system design as important as model ideas in practical use.
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How AI Can Support Curiosity Without Doing the Thinking
AI can help learners explore questions, compare examples and find starting points when its design preserves inquiry, effort and independent judgment.
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Sami Mechkor on practical AI responsibility, evaluation, governance, human control and measurable safeguards.
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Sami Mechkor on human agency, dignity and the purposes that should guide advanced technology.
The Future
Future-oriented essays by Sami Mechkor about uncertainty, institutions and choices made in the present.