Algorithms tell you how to vote. Algorithms can revoke your driver’s license and terminate your disability benefits. Algorithms predict crimes. Algorithms ensured you didn’t hear about #FreddieGray on Twitter. Algorithms are everywhere, and, to hear critics, they are trouble. What’s the problem? Critics allege that algorithms are opaque, automatic, emotionless, and impersonal, and that they separate decision-makers from the consequences of their actions. Algorithms cannot appreciate the context of structural discrimination, are trained on flawed datasets, and are ruining lives everywhere. There needs to be algorithmic accountability. Otherwise, who is to blame when a computational process suddenly deprives someone of his or her rights and livelihood?
But at heart, criticism of algorithmic decision-making makes an age-old argument about impersonal, automatic corporate and government bureaucracy. The machine like bureaucracy has simply become the machine. Instead of a quest for accountability, much of the rhetoric and discourse about algorithms amounts to a surrender—an unwillingness to fight the ideas and bureaucratic logic driving the algorithms that critics find so creepy and problematic. Algorithmic transparency and accountability can only be achieved if critics understand that transparency (no modifier is needed) is the issue. If the problem is that a bureaucratic system is impersonal, unaccountable, creepy, and has a flawed or biased decision criteria, then why fetishize and render mysterious the mere mechanical instrument of the system’s will ?
(Score: 2) by rts008 on Thursday May 21 2015, @06:10PM
You have an excellent point, and I consider it a very valid one. It is indeed all too easy to get caught up like that!
That is one of the reasons that I value websites like this very one we are on now.
Despite it's faults, the SN community is pretty knowledgeable and diverse in many areas/fields, and some interesting 'flamewars', debates, and discussions often occur. I find that actually helpful, especially when links/citations are included in the comments.
That makes it easier to learn about different viewpoints and motives and other information.
I can then do the research and make up my own mind, determine if it is important to/for me, or even decide that it's too early to decide-need more info because of the discussions and links I find here,(and other places) and I really like that.
Sometimes it can get difficult to to create algorithms to 'recognize the signal', 'filter the noise from the signal', and then 'decode the signal', but overall, most of us muddle by with that fairly well. ;-)