Art to science

Google contact lens: it won’t work.

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Time to debunk another widely covered press story about wonderful new inventions coming from a tech giant. Ars Technica had one of many articles about Google’s “announcement” of a blood glucose sensor in a contact lens. The discussion after the article is good, as often happens with Ars. Here’s my quick explanation of why the concept will fail. Unfortunately.

Non-invasive glucose testing is the perennial “pot of gold at the end of the rainbow.” Google is not the first to try using tears; the others have failed, and they will too. They say it is “5 years away,” which is equivalent to saying “We have not yet tested it on real diabetics.” 

The problem is basically that tears won’t track blood glucose levels closely. Tears are secreted by the lacrimal gland. I’ve never studied it, but the composition of its secretion is sure to depend on a multitude of variables. (Think: sweat, saliva, etc.) Even if a relationship exists and can be quantified  “on average,” there will be lags.

It’s possible that a device like this could supplement other measurement systems.  But nothing will be as good as actual blood measurements.  Therefore finger sticks will always be needed for calibration. The best realistic case is that a contact lens device could serve as an early warning; but finger sticks will still be needed for validation before taking any action.

via Google introduces smart contact lens project to measure glucose levels | Ars Technica.

NYT review of photo drone recommends illegal and unsafe behavior

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This review really missed the boat on both law and safety issues for drones. Some of what it discussed is illegal (unfortunately – I think the present law against commercial use of UAVs is too strong). A lot of it is unsafe, or rather it will be unsafe in the hands of newbies who buy this expensive but very-easy-to-use piece of technology.    Review – The Phantom 2 Vision Photo Drone From DJI – NYTimes.com.

If you have the $1200 for one of these undeniably cool machines, and the interest, the best approach is simple: buy one, and give it to me.  More seriously, here’s some good advice about learning to do photography with these.  It’s written for photographers who fundamentally are not interested in the flying part, and it’s not nearly “sufficient” for safety, but it gives a good idea of what you are in for.

Here are two videos of idiots flying these vehicles and having nasty crashes.  After the break: my two exchanges with the NY Times about the article.

Continue reading →

Amazon is blowing smoke about drone delivery

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Amazon Delivers Some Pie in the Sky – NYTimes.com.

I’m not impressed by Google’s “aerial delivery.” It’s easy to demonstrate a show system. But it will be very hard to create a safe system that can deliver loads of a few pounds, at a distance of even a few miles, much less the 10 that Jeff Bezos apparently claimed. Or to deliver to a specific person in an apartment building.

Here’s a quick response I wrote on Andrew McAfee’s page about this.

I’m skeptical. There are real safety issues here, as well as weight/payload/power issues. To deliver a 2kg package 30 km will take a vehicle gross weight > 6 kg (rough numbers). And helicopters, unlike fixed wing,  are “fail-dangerous.” Not to mention problems of delivering to a specific person in an urban environment. So I call “pie-in-the-sky” on this.

I see others are being skeptical because of regulatory problems. Yet other countries are way ahead of U.S. on regulation, and I don’t think regulation is the fundamental problem. The real problems include safety and payload:

  • Helicopters (actually, multirotors) have very limited endurance and therefore range. You can put a big battery on them, but then you need a bigger machine to carry the weight.
  • They have limited payload. Four ounces is no problem; but 5 pounds requires, right now, a machine with a total span of about three feet.
  • At least six motors and props will be needed (called a hexacopter). Otherwise, failure of a single engine would cause an immediate crash. Even with six or more rotors, a total power failure, or a guidance  failure, causes a crash. In a crash, the operator has  zero control on where the machine ends up. This is unlike an aircraft.
  • A machine this size that crashes is big enough to kill someone underneath. Especially if some of the motors are still operating. Even professionals are very careful about what they fly over. You can see videos on Youtube of idiots flying over crowded beaches, but a few people have been badly hurt this way, and the number will grow.
  • Navigation using programmed routes is straightforward in clear areas, by using GPS-based-autopilots. But with obstacles (trees, buildings) a lot of development work remains. This problem, unlike the others, will be solved eventually by Moore’s Law.
  • If you use an aircraft (wings) instead of a copter, many of the safety issues get much better. But on the other hand, you need a much larger area to land in. You can’t land in someone’s back yard.

Most of these problems are due to laws of physics, not the capability of current electronics. In short, delivering packages is an active area of R&D, but it will be feasible only in  situations where it is almost useless:

  • When you will be flying in unpopulated areas
  • When you can afford to crash, and lose, a few percent of your vehicles.
  • When the load is small, and the range is short.

There may be  some cases that fit this description, but very few. For the next 5+ years, using drones for that don’t have to land remotely – mainly for remote sensing – is going to be the only practical application. Unless you have a military budget, of course.

 

A column on over-hyping of medical “breakthroughs”

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This column in Scientific American from a 30-year veteran of science journalism has some good perspective on the ongoing controversy about non-replicability of so many scientific results. I wish I knew a system solution.

Discussing his findings in Scientific American two years ago, Ioannidis writes: “False positives and exaggerated results in peer-reviewed scientific studies have reached epidemic proportions in recent years. The problem is rampant in economics, the social sciences and even the natural sciences, but it is particularly egregious in biomedicine.”

A Dig Through Old Files Reminds Me Why I’m So Critical of Science — blogs.scientificamerican.com 

How useful is data mining without human judgment?

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A recent exchange on Mathbabe’s blog about the meaning of Big Data led me to some insights about where decisions need human judgment and analysis, and where we can turn decisions over to automated data mining. For example, serving up “you might also like X” in a web store will work a lot better than estimating how many people have flu. Why?

Here’s what I wrote. (Not clear if her WordPress interface picked it up.)

Cathy, big data in your sense does not work widely. If you say that “no human judgment is needed,” this is approximately equivalent to “the relationships do not need to be supported by causal theory, just by raw correlation.” This works great in certain domains. But the underlying correlations have to be changing relatively slowly, compared to the amount of data that is available. With enough data for “this month,” an empirical relationship which holds for multiple months can be data mined  (discovered) and used to make decisions, without human judgment.

But many of the world’s important problems don’t have that much stability. For example trying to use searches to track the spread of an annual flu, at the state-by-state level, won’t be very reliable without human judgement. The correlation between search terms and flu incidence in 2012 is not likely to be the same in 2013. One reason is that news cycles very from year to year, so in some years people are more frightened of the flu than other years, and do more searches. Consider the following experiment: use the “big data relationships” from 2010, to track the incidence of flu in 2014. It won’t work very well, will it?
On the other hand, if you could get accurate weekly data about flu incidence, the same methods might work much better. Using the correlations between search terms and flu in November might give reasonably accurate estimates in December.

Automated systems based on data mining are a form of closed-loop decision systems. (Closed loop basically means “no human in the loop.”) Closed-loop feedback works great under certain conditions, and very poorly under others. A key difference is whether the system designer has sufficient (accurate) knowledge about the system’s true behavior.

Once again “it all comes back to knowledge.”

NOT FLYING BY THE BOOK: SLOW ADOPTION OF CHECKLISTS AND PROCEDURES IN WW2 AVIATION.

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This is the “entry page” for my paper on the slow adoption of better flying methods in WW 2. Please link to this page, rather than to the actual PDF, which I will be updating.  Here is the paper itself. (July 19 version)

In the late 1930s, US military aviators in the American Army and Navy began using aviation checklists. Checklist became part of a new paradigm for how to fly, which I call Standard Procedure Flying, colloquially known as “flying by the book.” It consisted of elaborate standardized procedures for many activities, checklists to ensure they key steps had been done, and quantitative tables and formulas that specified the best settings, under different conditions, for speed, engine RPM, gasoline/air mixture, engine cooling, and many other parameters. This new paradigm had a major influence on reducing aviation accidents and increasing military effectiveness during World War II, particularly because of the rapidly increasing complexity of military aircraft, and the huge number of new pilots. Continue reading →

Changing flying from a craft to a science: what went right, and what went wrong, in World War II

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I have just finished  a working paper called  NOT FLYING BY THE BOOK: SLOW ADOPTION OF CHECKLISTS AND PROCEDURES IN WW2 AVIATION. It tells how, in 1937 shortly before World War 2,  the American air forces invented a much better way to train new pilots, and to fly complex aircraft and missions. What they invented is now used all over the world, by all licensed pilots and military aviators. But during the war, even American pilots resisted switching to the new way of flying. The only full-speed adopters were the strategic bombing forces attacking Germany and Japan. The US Navy, despite being one of the 1937 inventors, did not fully make the switch until after 1960!

Precise flying was a matter of life or death.

Precise flying was a matter of life or death.