What AI regulation is really trying to control
Behind the debate over rules for artificial intelligence lie three distinct concerns: the capabilities of systems, how they are used, and who is accountable when they fail.
Artificial intelligence, semiconductors, software, cybersecurity and technology policy.
Behind the debate over rules for artificial intelligence lie three distinct concerns: the capabilities of systems, how they are used, and who is accountable when they fail.
Building a modern semiconductor plant requires far more than money. It depends on accumulated know-how, specialised suppliers and a production process that tolerates almost no error.
A finding that cannot be repeated is a weak foundation. Researchers are changing how they design, share and review studies to make results sturdier.
Efficiency once trumped everything. Now businesses are paying for resilience — and discovering how hard it is to buy.
Software flaws persist not because nobody knows how to fix them, but because the people who could fix them often do not bear the cost of leaving them unfixed.
Proving that a medicine helps is harder than it sounds. Randomisation, control groups and blinding exist to separate genuine effects from chance, hope and bias.