Ada Lovelace's diagram from "note G", the first published computer algorithm.
Algorithms, in mathematics and computer science, are an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning. In simple words an algorithm is a step-by-step procedure for calculations.
The issue with AI, to me, is a very simple one. It's like the term algorithm. We watch companies use algorithms, and now AI, as a means of evading responsibility for their actions… If we endorse the view that AI is all-powerful, we are endorsing the view that it can alleviate people of responsibility for their actions—militarily, socioeconomically, whatever. The biggest danger of AI is that we attribute these godlike characteristics to it and therefore let ourselves off the hook. I don't know what the mythological underpinnings of this are, but throughout history there's this tendency of human beings to create false idols, to mold something in our own image and then say we've got godlike powers because we did that.
Mathematics is what we want to keep for ourselves. When playing games, we stick to the rules (or we are changing the game...), but when doing serious mathematics (not executing algorithms) we make up the rules—definitions, axioms... even logics. ...[I]n arithmetic we find prime numbers, which are a whole new 'game'... [T]o identify mathematics with games would be one of those part-for-whole mistakes (like 'all geometry is projective geometry' or 'arithmetic is just logic' from the nineteenth century)... [M]y separation of game analysis from playing games tells... against the analogy of mathematics to the expert play of the game itself.
Robert Spencer David Thomas, "Mathematics is Not a Game But..." (January, 2009) The Mathematical Intelligencer Vol. 31, No. 1, pp. 4-8. Also published in The Best Writing on Mathematics 2010 (2011) pp. 79-88.
Numerical analysis is very much an experimental science.
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