Tag Archives: Google is Evil

Tax Evader Google Exploits Refugee Crisis

It pains me to comment on the tense and tragic refugee crisis in Europe—I try not to make a bad situation worse. (And don’t get me started on the deeply immoral and Unamerican US migration policy.)

Unfortunately, Google, which scoffs as paying taxes to public authorities who are dealing with the refugee crisis in Europe, has added insult to injury with a pubic relations campaign called “Project Reconnect”.

Instead of providing badly needed money, food, shelter, and everything else, Google is providing cheap web books (“Managed Chromebooks”).


The donors “believe that access to Internet resources is key to connecting refugees to their new communities.” (Actually, they need safety and homes and some say to make a living.)

By the way, the price tag for these devices is about one minute of Google’s income, and a tiny fragment of the taxes they have avoided in the affected countries.

Google is Evil.


Google is Evil: The Soundtrack

Google Music has grand plans. Evil plans.  (To be fair, they are not alone.)

Google Music aims “to provide music to make the things we do every day, better. Waking up, working out, commuting: everything can be better with the right tunes. Music will now use contextual information—day of the week, time of day, and device, for starters—to figure out what you’re doing and what you might want to listen to. Then, you’ll get a playlist full of songs perfectly tuned not just for you, but for right now.” (quote from from “Google Music Crunches Your Data to Craft Perfect Playlists“)

Really? Good luck with that.

Obviously I haven’t tried this, but I can make a few straightforward critiques.

First: no, you do not have permission to track me this way. Not. A. Chance.

Second: even if you have a bunch of context and history, I defy you to know what I want to listen to right now. If I don’t know what I want, how can an algorithm know?

What does “better” mean anyway? There are an infinite number of things I might hear next, and some sub-infinity of them will be “good” in different ways.  What in the heck is the algorithm optimizing here?

Third: this is a preposterous and idiotic thing to want to try to do.   What problem do they think they are solving?


David Pierce reports in Wired, Google Music “designed to help people who don’t know what to listen to, or who keep listening to the same 12 songs every day because discovering good new music is too much effort. “They have no idea how to DJ for themselves,” [Google project manager Elias] Roman says, so Google is doing that for them.

Even if this situation is a real problem (which I doubt), the cure is worse than the disease. Turning my choice over to an opaque and exploitative algorithm can’t be anything but bad for you, even if it works, which is won’t.

Instead of only 12 songs you like, you get dozens of songs the algorithm says you should like.


Just say no.

RIP Google Glass

We see today that Google has ended the Google Glass program after nearly two years.  As Stephen Cass noted, Glass was not anywhere to be seen at CES this year, and there weren’t any ‘clones’ either.  Not at all a good sign, and a spectacular fall from grace.

Good riddance.

Perhaps Google actually was paying attention to the blizzard of pushback on this thing.  The also probably discovered that it is harder than they thought to make useful things out of such a small device.  And perhaps some grown ups (and lawyers) pointed out the grievous liability issues of mass distribution of a very dangerous product.

More likely, Google intends to focus on the most promising markets, which will be industrial and medical practice.  These can be legitimate and pro-social uses for this technology, so more power to them if that’s what they are up to.

Overall, the program was strange and very unfortunate.  This was a pseudo-beta, pseudo-release, accompanied by absurd levels of PR and hype.  I don’t think the approach really worked, except to make Glass famous in ways Google doesn’t necessarily want.

But the public release was quite evidently premature, and raised false hopes in their staff and anyone who built products for Glass.  This will leave a sour taste in a lot of people’s mouths.

It’s really not good when your critics and happy and your ardent friends are unhappy with you.

Science Article on “Big Data Hubris”

No Big Data story is more famous than Google’s claim to be able to track flu outbreaks in real time, much faster than conventional public health surveillance.

In Science, Lazar and colleagues present an analysis and critique of this claim and the actual performance of the Google Flu Trends.

Their finding is that the Google Flu Trends (GFT) consistently over estimates the incidence of flu. In other words, the real time trigger is “too sensitive”, beating the conventional signals in part by “crying wolf”.

These errors are quite important, because this kind of real time prediction is supposed to enable resources to be swiftly deployed, to react to epidemics much quicker than the slower conventional methods allow. But if the real time prediction is a false positive, these resources will be misallocated, and the deployment effort wasted or misdirected.

To the extent that these errors can be assessed (see below), they appear to be due to the use of poor correlates. The GFT is based on analysis of search terms thought to be related to (i.e., correlated with) the outbreak of flu, such as queries about symptoms and medications. This query behavior is only partly driven by actual symptoms, it may, for instance, be triggered by “winter”. (No points will be awarded for detecting winter via Google searches.) It is also possible that social phenomena, such as media hype, can increase interest and fears regardless of symptoms.

Obviously, not everything accurately predicts the actual outbreak of flu. Worse, the dataset contains 50 million terms, while the data to predict is a few thousand points—overfitting is almost guaranteed.

The errors in GFT’s predictions were quite substantial. In fact, the “bad old” conventional reporting, though not real time, was more accurate than GFT for projecting the actual occurrence of flu. This should not be a surprise, since these projections were carefully designed.

Naturally, combining GFT or similar data with other surveillance will be even better than either alone. GFT would also be more useful if commonly used statistical methods were used to model and reduce errors.

But, there are problems in any attempt to use the GFT itself as real data

The GFT is irreproducible, because it has never been adequately reported. The data is unavailable for study, and the algorithms are closed and ever changing. The GFT could not be published in any reputable scientific journal, and it is difficult to see how you could validate it.

This critique extends to most many large data studies: however spectacular the headlines, it is difficult to make useful technology out of opaque, semi-magical, processes. I have remarked on the psychology of Big Data, offering a secular form of prophecy. Lazar et al call this tendency “Big Data Hubris”: big data is always better.

This also demonstrates the reason why we need publicly sponsored science: however wonderful this technology might be, it is owned by Google (or Facebook or Twitter, or whoever, and they release only what they wish to let out.  We have no way to replicate, compare, or even understand exactly what they did.  Whatever this is, it isn’t science (and it isn’t transparent).  Is it evil?  Possibly.

I see the GFT is an example of Google’s overall attitude. A love for quick and dirty methods based on unquestioned assumptions that more data is better than anything else, even careful theory and modeling. “Open source” that enables people access to selected data, but complete opaqueness about the actual data and algorithms. “Trust us” is not really good enough for data science.

I would also comment that in GFT and elsewhere, Google has touted the importance of empirical data and analytics, to understand health and safety (and selling advertising). But in the case of Google Glass, the company has not presented any data at all to demonstrate that the device is safe to use, or even useful.  We have been given lots of hype and anecdotes, which their data scientists must cringe at.

As I have pointed out sever times, there is really strong reason to worry that Glass is really bad for people, possibly producing eye damage, and almost certainly causing distraction. Yet Google has presented no data, and has never publicly said that it has ever collected or intends to collect such data.

Combining these cases, we see a cavalier and selfish attitude toward science and public safety. A major, monopolistic, for profit company has a right to act these ways.  But if it does, then it better not BS about “not being evil”, because they are, at best, selfish and amoral (just as a capitalist company should be).


David Lazer, Ryan Kennedy, Gary King, and Alessandro Vespignani. 2014. The Parable of Google Flu: Traps in Big Data Analysis. Science 343, no. 14 March: 1203-1205. Copy at http://j.mp/1ii4ETo



Google Glass Distracts Drivers: It’s Not Even Debatable

This is absurd.

On NPR Aarti Shahani asks “Does Google Glass Distract Drivers?“, as if there is any actual debate to be had. Duh. Of course it dos.

The report makes clear that while user’s believe they aren’t impaired (which is, if anything, evidence that they are, in fact, impaired), and Google is evilly lobbying to make sure they can kill as many people as possible with their moneymaking scheme, actual scientists who have studied attention are very clear:  Glass should not be worn while driving.

Look, we know that any multitasking distracts the driver.Period.

Google Glass absolutely should not be worn while driving or operating any dangerous equipment (including jackhammers, firearms, chainsaws, or motor vehicles).

Please, please, please, don’t wear Google Glass while driving.

Personally, I’d recommend not wearing it while interacting with loved ones, but that’s your funeral.

Google:  once again, I challenge you to provide evidence that this product is safe to use. You know–like actual data.

If you need some help to test this, call me.  Please.

For the record, from Google Glass FAQ:

Q: Can I use Glass while driving or bicycling?

A:  It depends on where you are and how you use it.
{…}don’t hurt yourself or others by failing to pay attention to the road.[…}

For goodness sakeGoogle, stop being stupid and evil at the same time.  It is not possible to drive safely using Glass, and you know it very well.