[zaroth]

This is Facebook. Is has a tremendous effect on peoples lives. And that's precisely why it's worth $100B. This is nothing more than a tweak in their ranking algorithm -- much larger and even targeted/dynamic modifications occur all the time. How can a reasonable person be upset by this?

If the study is unethical by any reasonable standard, does this amount to condemning the whole company, even the whole industry? Because if this is unethical, you are calling out an extremely widespread practice...

[zAy0LfpBZLC8mAC]

How can a reasonable person not be upset about someone intentionally making people feel bad without their consent?

$foodcompany recently mixed some small amounts of a known poison into their product to see how their customers would react. This is nothing more than a tweak in their recipe - much larger modifications occur all the time. How can a reasonable person be upset by this?

[nl]

I'd normally be with you in defending Facebook here, but in this case the ethics really are questionable.

They designed an experiment where there was a serious hypothesis that it could lead to depression in the people subject to it. That has the potential to be actually harmful.

I still defend Facebook's right to do research, but they need to take more care to avoid harm.

The industry as a whole doesn't perform experiments designed to depress people. There could be other unethical experiments too, but they need to be judged on a case by case basis.

[3rd3]

There is no difference between tinkering with an algorithm with the intention to negatively influence people's emotions and tinkering with an algorithm to make it work better?

[zaroth]

Who is to say those two statements are at odds with one another?

Also, almost every A/B which results in a measurable impact in user response will have done so by positively vs. negatively impacting the users' emotions on the A/B legs of the study.

But more to the point, this is not even a fair characterization of what Facebook did. The made a tweak to their ranking algorithm which they deployed to 1/2500 of their users. Much later they discovered there was a extremely small but measurable impact to those users' engagement, and the types of words they included in their subsequent posts. They actually didn't know at all ahead of time what the effect would be, and in fact the effect they observed was the opposite of the widespread expectation.