Algorithms can be greedy. What are some other algorithmic vices? 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?
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.

See:
Facial Recognition Is Accurate, if You’re a White Guy
Rise of the Racist Robots – how AI is Learning all our Worst Impulses