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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: 3, Interesting) by Non Sequor on Thursday May 21 2015, @06:34PM
This problem already existed in legal theory. Bright line tests are clearer on what is and isn't allowed but ignore mitigating concerns on borderline cases. Balancing tests explicitly invoke a subjective comparison of multiple factors but people do not like trying to guess what someone else's subjective decision will be.
Ultimately it's all governed by Kolmogorov complexity. Every problem has a complexity and every algorithm has a complexity. If you use an algorithm that is simpler than the problem, the quotient of the two leaves a residual problem. How manageable is the implementation of the algorithm and how troubling is the residual problem? There is no a priori answer to that question.
Write your congressman. Tell him he sucks.
(Score: 2) by sjames on Thursday May 21 2015, @08:44PM
The problem is that reality is sufficiently complex that there is always a residual problem. As long as we recognize that in the form of making sure someone always has the authority to decide against the algorithmic result and that that person's attention can be called to any disputed case, it can be OK. Unfortunately, instead bureaucracies (government or corporate) are very careful to put up a wall of card flippers to thoroughly isolate anyone with a modicum of authority from the customer.
(Score: 2) by Non Sequor on Thursday May 21 2015, @11:56PM
You're still describing residual problems. These institutions have operational dogmas put in place in response to past problems.
Write your congressman. Tell him he sucks.
(Score: 2) by hendrikboom on Friday May 22 2015, @03:08PM
A wise friend of mine once noted that no bureaucracy can work without the presence of people capable of breaking the rules.