It's kinda understandable, though. Whenever the services of Google, Facebook, etc. behave in an inscrutable, nonsensical, or offensive way, they blame it on their "algorithm" (for a recent example, see https://www.theguardian.com/us-news/2017/oct/06/youtube-alte...). That's really the only context where the term "algorithm" surfaces in mainstream discussion.
ML has had a lot of successes, but one of its failures has been more unpredictability on the level of individuals and events that people actually experience.
Maybe if humans took responsibility for the algorithms they created and didn't shrug and say, "It's the algorithm" then "the algorithm" wouldn't be the antagonists in this story.
Even in that light, algorithms aren't the enemy: models are. If I build a predictive model that harms people, then my model is the cause of harm, not the fact that I built it using random-forest or CNN.
You should get used to that. When technology does harm, then the creators of this technology will point to the algorithm, the same way that Google talks about an algorithm as being a living thing. Of course, whenever they do good things, then the merit goes to the (human) creators of the algorithm -- in fact, to the founder(s) of the company that created the algorithm.
Throughout most of history rules and laws were enforced by a combination of "the letter of the law" and "the spirit of the law". The latter being shorthand for the role of human discretion.
Algorithms completely obliterate the latter - increasingly turning previously flexible systems into the equivalent of zero-tolerance-policy schools, where human discretion has no role to play. This is a problem because many laws on the books were written with the assumption that "the spirit of the law" would be a guiding principle when "the letter of the law" is unclear.
As a trivial example of this going terribly wrong, consider Youtube's copyright enforcement algorithms. Copyright was clearly designed with many loopholes for fair use to allow culture to move forward. Youtube's algorithms ignore all of this, changing the effective meaning of copyright on the site from one where the rights of the copyright owner are balanced with the rights of critics, commenters, and other creators to one where the rights of copyright owners are the only ones that matter.
Now imagine this kind of algorithmic enforcement applied to traffic laws, HR rules, or insurance policies and you can see why people might be nervous about "algorithms". Algorithms neither think nor feel and have no empathy. It's the ultimate actualization of the dystopia in the movie Brazil where the world is a cold, unfeeling, bureaucratic nightmare. Except where human bureaucrats at least need to sleep sometimes, computerized ones never rest.
"Now imagine this kind of algorithmic enforcement applied to traffic laws"
We already have this in the form of red light cameras which have been shown to cause rear-end accidents at traffic lights:
"There have been concerns that red light cameras scare drivers (who want to avoid a ticket) into more sudden stops, which may increase the risk of rear-end collisions."[1]
"the authors of the study found a statistically significant, but still smaller, reduction in angle and turning injury crashes by 15 percent, as well as 'a statistically significant increase of 22 percent in rear-end injury collisions."[2]
In short, there situations where the humans involved would all agree on what a "correct" driving response would be, but the presence of the algorithm (the camera, the ticket, the court, etc.) forces another action - and sometimes that action can be bewildering to other participants.
I write a faulty policy that harms people. I encode it as an algorithm, implement it as a program, and deploy it on a wide scale. Now it's automated and distributed, and it is harming people. Where is the fault --- in the program? in the algorithm? Or in the policy? Where do we fix the problem?
IMO, we are quick to blame inanimate constructs, when people and their policies are the source of fault. Vilifying "algorithms" only serves to distract from root causes.
The argument I'm making is that when it comes to "human systems" like communities it's not possible to write a complete, consistent, and fair policy that can be unambiguously interpreted (i.e. by a computer). This is why Hacker News still has moderators and is not strictly governed by algorithms.
"Fairness" has always been heavily contextual, and the idea that it can be distilled to a matter of "if A and B then C" is folly. Even pure math can't reach the combination of completeness and consistency you assume is possible: https://en.m.wikipedia.org/wiki/Gödel%27s_incompleteness_the...
> Vilifying "algorithms" only serves to distract from root causes.
But that's the goal of some actors. They want to misdirect attention and responsibility away from themselves when their creations misbehave.
The root cause is no-one is really at the wheel once the algorithm goes into production to provide human discretion. For instance, pretty much the entire consumer facing apparatus of Google and Facebook consists of "algorithms" and there's no one empowered to call when they go wrong. Fixing that would cost money that the tech giants don't want to spend.
The point seems to be that is you limit your policy to something that can be reasonably be encoded as an algorithm and implemented as a program then you're by definition limited to write faulty policies that can't be flexible enough and will harm people.
I.e., that if you're choosing to use an algorithm for your policy, then this means that you will write harmful policies, and the choice to use an algorithm at all, any algorithm, is morally flawed and should be vilified - to motivate you and others to write policies that include appropriate flexibility, arbitration, human evaluation, overrides and thus can't be implemented as a scalable algorithm/program. Well, not unless we get superhuman general AI systems.
Algorithm is an ambiguous word, but when people refer to them in the scary context, they are particularly talking about the kinds of algorithms the giants use to analyze and predict behavior. My only concern is that the word itself becomes associated with that one use case, which would be kind of sad because algorithms make up pretty much all software period.
It's quite not, actually. Humans have the ability to see nuance in things. Computers currently don't. So you see things like Google banning developers for innocuous violations of the rules, whereas humans (assuming they were given enough time to properly review) wouldn't give 3 strikes just because they saw the same violation 3 times.
No, that really is the definition of an algorithm.
Algorithms and computers are NOT inextricably linked. Just because software often uses algorithms to define behaviour, doesn't mean algorithms cannot mean other things.
Everyday people couldn't even tell you the definition of "algorithm", even then, they wouldn't recognize that algorithms are not only encoded into chips but also business process, legal compliance, etc.
ML has had a lot of successes, but one of its failures has been more unpredictability on the level of individuals and events that people actually experience.