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I do not sell such software. You blame companies, but is that to mean that engineers are supposed to turn a blind eye to ethical issues in the products their e

I do not sell such software. You blame companies, but is that to mean that engineers are supposed to turn a blind eye to ethical issues in the products their employers sell? Other engineering disciplins whole-heartedly disagree. Regulation is besides the point. The comment I replied to said that software engineers have never held the belief that their algorithms aren't biased and I was simply pointing out that that is either false on a large scale or those engineers are complicit with the use of their software in unethical ways because of those bias issues in the software.

throwawaygh 6y ago
> but is that to mean that engineers are supposed to turn a blind eye to ethical issues in the products their employers sell? Those engineers understand the obvious problems with facial recognition software. Everyone does. The engineers building this software don't need philosophical training. Instead, they need a personal/professional ethics (or, in lieu of such self-regulatory instincts, government regulation). Again, neither of those presents a philosophical problem. > Other engineering disciplins whole-heartedly disagree. Regulation is besides the point. I disagree. Other engineers disagree precisely because they operate in highly regulated disciplines. PE codes of ethics are not (just) personal ethical commitments; rather, they are (also) backed by the force of law. BTW, lots of engineers build WMDs.
throwaway894345 6y ago
I think it's helpful to talk about "bias issues" specifically. When we talk about them in the abstract, they always seem to carry this boogeyman-ish quality, but when we talk about them as concrete instances, we can almost always (and rather easily) come up with concrete mitigations. For example, some people have rightly expressed concern about statistical models of criminality derived from law enforcement data, so we augment and weigh that data with other sources, such as victim surveys, hospital records, and so forth. Of course, that doesn't eliminate all bias (we can never completely eliminate bias) but it's a significant improvement, especially when the alternative to "using a formal statistical model" is "using law enforcement officers' personal judgment". We can also make available certain information about the training data set and the methodology to provide an audit trail. Very rarely are these ethical issues really as insurmountable as critics seem to imply when they speak about "biased algorithms" in the abstract.

throwawaygh 6y ago

> but is that to mean that engineers are supposed to turn a blind eye to ethical issues in the products their employers sell? Those engineers understand the obvious problems with facial recognition software. Everyone does. The engineers building this software don't need philosophical training. Instead, they need a personal/professional ethics (or, in lieu of such self-regulatory instincts, government regulation). Again, neither of those presents a philosophical problem. > Other engineering disciplins whole-heartedly disagree. Regulation is besides the point. I disagree. Other engineers disagree precisely because they operate in highly regulated disciplines. PE codes of ethics are not (just) personal ethical commitments; rather, they are (also) backed by the force of law. BTW, lots of engineers build WMDs.

throwaway894345 6y ago

I think it's helpful to talk about "bias issues" specifically. When we talk about them in the abstract, they always seem to carry this boogeyman-ish quality, but when we talk about them as concrete instances, we can almost always (and rather easily) come up with concrete mitigations. For example, some people have rightly expressed concern about statistical models of criminality derived from law enforcement data, so we augment and weigh that data with other sources, such as victim surveys, hospital records, and so forth. Of course, that doesn't eliminate all bias (we can never completely eliminate bias) but it's a significant improvement, especially when the alternative to "using a formal statistical model" is "using law enforcement officers' personal judgment". We can also make available certain information about the training data set and the methodology to provide an audit trail. Very rarely are these ethical issues really as insurmountable as critics seem to imply when they speak about "biased algorithms" in the abstract.