Greedy algorithms are well known, and although useful in a local context for certain problems, and even potentially find general, global optimal solutions, they nonetheless trade optimality for shorter-term payoffs.

This seems to me a good analogue for human greed, although there is also the grey goo type of greed that is senseless acquisition of material (think plutocrats who talk about wealth as merely a way of "keeping score".)

Technical debt is an extension of development practices that fall under the algorithmic definition of greed (short-term payoff leads to trouble down the road.) This may be further extended to any non-optimized code in terms of energy waste (flipping of unnecessary bits) which will only increase as everything becomes more computerized.

So my question is:

  • What are other vices that can arise in algorithms?

3 Answers 3


Algorithms can be racist, sexist, and otherwise bigoted. When we feed them data produced by systems that are biased against groups of people, the algorithm will learn to behave that way. We're used to garbage in garbage out, now we have to worry about racism in racism out.


  • $\begingroup$ Don't you think the facial recognition problem might be more of features such as eyes which are black not getting too prominent against darker skin tone rather than any racism...And the company producing the same algorithm asks the offender a questionnaire which has no question related to race...So it is based on facts...Such speculative answers based on newspaper journalists knowledge is not appreciable $\endgroup$
    – user9947
    Feb 15, 2018 at 4:34
  • 1
    $\begingroup$ You may want to include more information from your links in this answer; it's always better to include information in the answer itself rather than depending on links. $\endgroup$
    – Mithical
    Feb 15, 2018 at 11:02

Algorithms can learn to cheat:

"A machine learning agent intended to transform aerial images into street maps and back was found to be cheating by hiding information it would need later in “a nearly imperceptible, high-frequency signal.”

"...a computer creating its own steganographic method to evade having to actually learn to perform the task at hand is rather new."
Source: This clever AI hid data from its creators to cheat at its appointed task (TechCrunch)


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