And nothing of value was lost.

It's a damn sight better than the nothing that exists today.

I'd rather lose those few (allegedly) "good" posts than read any more trolls. If it's too hard tell the difference between an semi-literate rant over "how angles save my sole" and a troll, the world isn't any worse off for not having the rant.

Despite the apparent similarities, Twitter is not a legally protected soap box in the public square. It's a private service, and they can censor anyone they want for any reason. Trolls can run off and join trolltalk.com if they want their own voice.

My real name is Fake Steve Jobs. Now what do I do?

I've lived my whole life in the Minneapolis area, and with global warming plus all the skyways connecting the downtown buildings, weather is almost a non-factor for most of the time. Snow happens here like it does in most of the country, only we're better prepared so it isn't a big deal to us. I'm tapping this on a warm bus on my way home, and while traffic is bad ...

Oh, my. The bus just passed a wreck where the fire department and state patrol are prying some guy out of an SUV that he wrapped around a snow covered guard rail.

Holy shit, there goes my whole argument about how great this place is to live.

I think the question of long-term stability is only relevant if you're thinking of investing in one of these companies. It in no way impacts me as a rider as I'm not establishing a long-term relationship with any of them. I don't care who picks me up and drives me to the airport. I don't care if the next guy to pick me up at the airport and bring me home works for the same company who drove me to the airport. And from the quotes I've gotten, Uber isn't a bargain, so they're not even differentiating themselves from livery companies on price. All other things being equal, I'll choose a regulated company over an unregulated company (for the same reasons you listed.)

I consider Uber and Lyft to be almost ephemeral: they exist today, they might not exist tomorrow. I know Uber is trying to establish a brand image of a company that is reliable and safe and app-enabled and cool and trendy. But because of the way I use taxis, their stability is unimportant to me.

They could certainly send 50 times as many messages, but they'll improve their return on investment if they target all of them at people who are more susceptible to their message in the first place. Given the cost of the Big Data systems they may only be able to afford to send 10 times as many instead of 50 times, but as long as their message is 5% effective instead of 0.1%, it's still a vast improvement on ROI.

That's a great question. Do you think 80% accuracy is good enough for medical use? If you're a doctor facing an unfamiliar situation, and your data says treatment X helped 40% of patients it was tried on, treatment Y helped 35% of them, and all other treatments (Z, W, etc.) helped no more than 30%, but you know the data might only be 80% accurate, what treatment do you choose? Are those ratios even meaningful in the presence of so many errors?

Consider the case where the patient's condition is critical, and you don't have time for additional evaluation. Is X always the best choice? What if your specialty makes you better than average at treatment Y? Maybe that 20% inaccuracy works in favor of the doctor who has the right experience.

It could it be used for ill, too. What if you know you'll get paid more by the insurance company for all the extra tests required to do treatment Y? You could justify part of your decision based on the uncertainty of the data.

In the end, historical data is just one factor out of many that goes into each of these decisions. Inaccurate data may lead to suboptimal decisions, so it can't be the only factor.

You seem to be belaboring this mistaken impression that analyzing Big Data somehow replaces thinking in the board room. It does not. Big Data is a tool that can help provide evidence of what people have done in the past, statistically correlated to potential causes. Big Data doesn't decide "hey, let's buy GM." People make those decisions, and they try to make them based on the information they have -- and Big Data can be a good source of that info. But people can be idiots, they can be talented, they can be anywhere on the spectrum. Do not blame the tool, or the accuracy of the tool, just because it's capable of being swung by an unqualified, incompetent idiot.

As a friend of mine is wont to say, "A fool with a tool is still a fool."

When you're dealing with statistics, you ought to recognize that 92% accuracy is a huge improvement over a random distribution. You do not use big data to select a target for a sniper rifle, you use it to point a shotgun.

And just like your faulty GM CEO analogy (I assume you felt the need to apply a car analogy for the benefit of the slashdot crowd) only an idiot would send someone off in the woods blindfolded and have him fire his shotgun in a random direction hoping to bring home some kind of food animal. You still have to know what you're hunting for, you still have to know how to hunt, you still have to make wise decisions. It's just a tool, not a sage.

The difference between "92% accurate" and "accurate enough for my task" are profound.

If you were using these kind of analytics to bill your customers, 92% would be hideously inaccurate. You'd face lawsuits on a daily basis, and you wouldn't survive a month in business. So the easy answer is, "this would be the wrong tool for billing."

But if you're advertising, you know the rates at which people bite on your message. Perhaps only 0.1% of random people are going to respond, but of people who are interested, 5.0% might bite. If you have the choice between sending the message to 10000 random people, or to 217 targeted people (only 92% of whom may be your target audience), both groups will deliver the same 10 hits. Let's say the cost per message is $10.00 per thousand views. The first wave of advertising cost you $100. The second costs you $2.17. Big Data, with all of its inaccuracies, still improves your results by a wide margin.

Way too often people like this point out that perfection is impossible. They presume that "because it's not perfect, it's useless." The answer is not always to focus on becoming more accurate, but to choose the right tool for the job, and to learn how to recognize when it's good enough to be usable. At that point you learn how to cope with the inaccuracy and derive the maximum benefits possible given what you have.

I don't think this is related to the difference between special purpose use, or general purpose use. I think the problem is like anything else in education - parental involvement will increase children's learning. If the parent works with them to learn how to use the device, I'd bet their scores would go up, similar to a parent who reads to their child or helps them with math homework.

If the parent says "I don't have to teach them anything, the school gave them a computer for that", or "I can't teach them how to use the computer because I don't know how to use it", that child's education is going to suffer. Being computer-illiterate might simply be the current excuse for parents to ignore their children.

Money. More specifically, revenue from advertisers. Once they had the motive, it's pretty easy to justify the means to the end.

From who? Thirteen enraged nerds on Slashdot? Their average customer doesn't understand the difference between their phone and their browser; they certainly won't get up in arms over a "super-cookie".

Verizon could easily afford to piss off every paranoiac on the planet, and they'd still have so much money they'll need to buy another dump truck to haul this month's profit to the bank. They have no real reason to change, so I'd recommend a strategy other than OMGPANIC!

Yeah, the more I dig into it, the more it looks like an investigative tool than an evidence analysis tool. That's pretty cool, but as you say, it looks a lot like Wireshark. Still, when you're facing an unknown attacker, it may not hurt to have a couple different views on the problem.