Anecdotally, I had a very strange experience with LinkedIn. I went to stay with my friend in another country for a few days and upon returning home, LinkedIn recommended his father as a connection - despite me never electronically contacting him. The friend I stayed with doesn't have LinkedIn nor have I contacted him over email or similar. My guess is that it must have been location based or because I connected to their WiFi - very weird.
> (1) Make an ernest attempt to use ML, algorithms to identify their customers who are using those leaked datasets Facebook negligently exposed and help devalue the data, instead of eagerly selling them targeted advertising services? I don't know if they did this, but it sure seems doubtful.
How could they do that? The cat is out of the bag and FB aren't going to have any knowledge about where that data is now. Have there been reports of it getting out from CA?
> (2) Quickly and openly disclose the extent of the leaked data
I think some caution is a good idea, they don't want to get the numbers wrong - although they are making steps in the right direction with the message to 87 million on their news feeds.
The article seems to spin it as being part of the CA study, apart from the small commentary towards the end. Has anyone seen the text of the message FB has shown to the affected 87 million and does it explicitly mention private messages?
People may put all manner of things in private repos that they don't want to be made public, so github shouldn't just expose them to the outside world.
Nice work! I just noticed a bug though, trying to go to the next page of system software that is sorted by votes doesn't work. Instead of going to the next page, the first page is reloaded with /NaN appended to the URL, as such: