Who are you?

On March 30^th, 2012 (or sometime close to then, nobody knows the exact date), a server breach occurred within the Utah Department of Health.  It was reported that personal information for 25,000 people was exposed, including names, addresses, birth dates, and social security numbers.  This figure was later increased to over 250,000 people.  If you follow this sort of news at all, you’ll know that this is just one in a long string of similar breaches.  It happens to all sorts of organizations, public and private, government and corporate.

These data breaches are a serious problem.  This information is all that is needed to open financial accounts, such as credit cards.  When this happens, a person’s credit record can be destroyed.  Fixing the problem can take years or decades.  Some people never recover.  There is very little recourse for a person claiming that an account was opened without their knowledge or consent.  The Utah Department of Health is offering a year’s worth of free credit monitoring to all affected individuals to limit the damage, which is better than nothing, but not much.

Organizations that treat this type of data carelessly need to be held accountable.  We need to highlight these cases in the media, and discover who was negligent, and why.  Lessons need to be learned, and civil and criminal charges need to be issued where appropriate.

And yet…

At the end of the day, this type of breach is not the real problem.  It’s just a symptom.  The real issue is that we allow to people to be held accountable for accounts opened using nothing more than their name, address, birth date and social security number.  While all of this information may be tricky to assemble, none of it is actually secret.  All of it is in the public domain, somewhere.  Before all records were computerized, the cost of pulling together a comprehensive data profile for somebody was considerable, and often required the services of a private investigator, who would physically visit town halls and other archives.  It’s only a matter of time before all this data is available freely on the Internet, with automated data agents able to pull it together with no human involvement.

What happens then?

There are some areas of security, such as choosing better passwords, that are relatively easy to address.  But before you can validate somebody’s access, you first need to identify that person.  How do you do so, in a way that only one person in the entire world can successfully pass the test?

It used to be that most transactions and account applications were done face to face.  In a small town, the people involved had probably known each other all their lives.  Therefore, identity was a combination of hair color, facial and body structure, accent and speech patterns, and thousands of other minor factors.  While it was possible to engage in fraud by mimicking another person, it wasn’t common, and carried a high degree of risk for the perpetrator.  It's too easy to be caught when you have to show up in person.

As the economy grew and national (and then global) banks and stores took over, the system of personal recognition broke down.  We evolved a new system, which is based on security through obscurity.  A bank would ask all sorts of questions that were difficult for another person to know.  It would then spend time and effort to validate that this data was correct.  It was certainly easier to commit fraud than it had been when everybody knew everybody else, but was still enough of a challenge that losses were manageable.

We are now approaching the tipping point, when information will flow so freely that we will need to develop a completely new approach to identifying people.  How can we achieve this?

There are generally three ways to identify somebody:

• Something you know
• Something you have
• Something you are

Our current system is based on something you know.  People know their own Social Security numbers, addresses, mother’s maiden names, and so forth.  If we’re going to keep this solution, then we need to ensure that people know something that is not, and never will be, public knowledge.  In short, everybody will need a “secret” Social Security Number, or other identifying text string, which would be issued when they are born.  Their parents would store it in a secret place, and have them commit it to memory as soon as they were old enough.

I doubt this will work.  In order to effectively validate this secret, somebody else will need to look it up.  Even if you use a fully encrypted process, sooner or later, the secret is going to get out, and we’ll be right back to Social Security numbers.

Something you have is generally some type of possession which can be uniquely identified, such as an RSA token.  Unfortunately, tokens are easily lost – people will constantly be having to ask for new ones.  And if the token is the principle way of identifying somebody, how do you figure out that the right person is asking for the replacement token?

Something you are represents physical characteristics, such as finger prints, retina patterns, or bone structure.  Since we’ve ruled out something you have and something you know, we’re probably going to have to go with this one.  And yet, this is a very tricky and problematic option.  The first solution that everybody immediately thinks of are finger prints.  They are unique to a person, and have successfully solved countless crimes by criminals who fail to take the basic precaution of wearing gloves.  It’s easy to find their fingerprints covering everything they touched.

That’s the problem with fingerprints.

We leave them everywhere.  Finding somebody’s fingerprints is a trivial exercise – just pick up any object they’ve handled.  And once you have their prints, they’re pretty easy to replicate.  All you need is a pair of extremely thin latex gloves, encoded with another person’s prints, and voila!  You are now that person.

Retina patterns are a little better, but still problematic.  With today’s technology, you don’t leave your retina patterns lying around everywhere.  But what about with tomorrow’s technology?  How long before a high quality camera can take a picture of somebody from 5 or 10 feet away, and see enough detail to capture all the necessary details in their eyes?  Heck, all you need to do is to put your own camera onto something that looks like an ATM, and ask them to have a retina scan to make a deposit.  (This is already done for skimming a person's ATM card.)  What you do with that information is a trickier challenge, but it doesn’t seem impossible for somebody to invent a set of contact lenses in the near future that can match another person’s retinal patterns.  And once that happens, here’s the real problem with retinal patterns and finger prints – you can’t change them.  You’re stuck for life, so as soon as anybody figures out what yours are and invents the technology to duplicate them, you’ve now lost your identity permanently.

DNA scanning is possible, I suppose.  But frankly, I simply don’t want to spend much of my time time envisioning a world where you’re asked to spit into the handy receptacle to prove your identity every time you wish to make a purchase.  So we’ll leave it at that.

That leaves facial and body recognition.  This seems to have some promise.  Unlike when humans recognize faces, computers are not fooled by wigs or extra glasses.  Facial recognition software works by looking for structural features such as the contours of the eye sockets, shape of the cheek bones, and length of the jaw line.  Weaknesses in the facial recognition systems tend to result from poor lighting or bad angles, which can be reduced or eliminated when the subject wishes to be identified to complete a transaction.  Add measurements of bone structures to the mix just for safety, and you’ve probably got a fairly robust system.

But remember, the purpose is to identify somebody, not just validate them.  Which means that every time you want to really demonstrate your identity, you need to be measured – we don’t want people simply showing a photograph to fool facial recognition software.  Which means that first of all, your measurements have to be recorded in a secure, encrypted database somewhere – probably initially when you are born, and then updated every year until you reach maturity.    Then, to demonstrate you are the same person who belongs to these measurements, you need to subject yourself to detailed scanning that can confirm that you are a real live person who has facial and body features that match those on record.  Only then can anybody safely assume that you are who you say you are.

Of course, this doesn’t prevent identity theft, it just brings it down to a manageable level.  You still have the problem of an impostor taking your turn when you go to be measured.  Or a hacker breaking into the database to update the records recording who you are.  And of course, you’re always in danger from your evil identical twin.

In the meantime, call up the Utah Department of Health and give them an earful about losing their data.  We may never be able to go back to the days when are personal information was relatively obscure and private.  But I miss them already.

Looking for Danger in All the Wrong Places

A doe had the misfortune to lose one of her eyes, and could not see anybody approaching her on that side. So to avoid danger she always used to feed on a high cliff near the sea, with her sound eye looking towards the land. By this means she could see whenever the hunters approached her on land, and often escaped by this means. But the hunters found out that she was blind in one eye, and hiring a boat, rowed under the cliff where she used to graze and shot her from the sea.

-Aesop's Fables

Anybody paying attention to advances in artificial intelligence has noticed that significant  milestones are being crossed more and more frequently.  Deep Blue defeated world chess champion Gary Kasparov in 1997.  Watson took the crown in the much more flexible game of Jeopardy on 2011.  And while Dr. Fill disappointed many observers by only placing in the near the bottom of the top quartile at the America Crossword Puzzle Competition, few expect it to take much longer before computers reign supreme in this area as well.  Jeopardy Champion Ken Jennings summarized the ambivalence of many when he used his terminal to display the line “I for one welcome our new robot overlords.”

We've all seen movies like The Terminator and The Matrix.  We're all wondering which massive collection of computers is going to go Skynet on us and achieve the critical mass needed to wake up and start making its own decisions.  Will it be Watson?  Dr. Fill?  Or perhaps Google's seemingly infinite collection of server farms, running in unmarked, undisclosed locations spread across the world?  We pontificate endlessly about what safeguards we need to keep these colossal systems in check.  Can we build in kill switches?  Keep them fire-walled off from the control software running power plants and weapons systems?  Build in Asimov's three laws of Robotics in the hope that the newly awakened system will serve our needs instead of their own?

I have to wonder if, like the one-eyed doe, we're all looking in the wrong direction.

For all the intricacy of a Watson or Dr. Fill, these are highly monolithic programs, designed to do one thing and do it well.  I haven't heard any reports that Deep Blue or any other chess program has been getting bored and asked to try its hand at tennis, or Parcheesi.  Adapting Dr. Fill to to do some task other than complete crossword puzzles would be a monumental undertaking.  Probably easier to throw everything out and start from scratch.

Moreover, these programs have no survival instinct.  They have no ability or inclination to replicate, or to try to thwart the intentions of anyone who would prevent these activities.  They cannot rewrite their own code to avoid detection and adapt to a new environment.

Modern malware has all of these attributes.

The sobering fact is that it's becoming increasingly difficult to come up with a good definition of life that does not include malware.  Wikipedia lists the following criteria to consider something "alive":

• Undergoes metabolism.  While this traditionally refers to chemical reactions that sustain an organism, there's no intrinsic reason why it couldn't refer to the processes of a functioning program.
• Maintains homeostasis.  Similar to metabolism.
• Possesses a capacity to grow.  True, though currently limited.  (But see below)
• Respond to stimuli.  Absolutely.  Many worms and viruses will watch what is happening in the operating system and take actions accordingly.
• Reproduce.  Yes, and then some.
• Through natural selection, adapt to their environment in successive generations.  Limited again, but not for long.

The two points above that are weakest today are the ability of malware to grow and adapt to its environment.  In malware terms, this most closely translates to polymorphism, where a virus will modify its own code.  In today's world, these are generally very minor modifications, designed to make the virus more difficult to detect by an anti-malware program looking for a specific code signature.  A given unit of malware doesn't have the ability to spontaneously change itself in order to discover and take advantage of a new zero day exploit.

Not yet.

There's no reason why its not possible.  The technique involved is called a genetic algorithm.  It involves replicating evolutionary techniques by introducing random variations into code to see if it improves.  It has minimal usefulness in many programming applications due to the high level of computational power required, and the difficulty of measuring improvements from one generation to the next.  When the computing power is provided by infected computers on the internet, and effectiveness is measured by the ability to survive and propagate, both these limitations go away for malware.

We are then left with the question of how fast a self-replicating, self-modifying worm in the wild could improve using genetic algorithms could improve.  I see no reason why it could not improve very quickly indeed.  The field of medicine has recently seen the introduction of "super-bugs", bacteria which has acquired immunity to many or most antibiotics over time.  A bacteria attempting to infect humans has faced a very difficult environment since the introduction of antibiotics.  What we're only beginning to appreciate is how a difficult environment leads to much more rapid evolution.  With an internet full of anti-malware programs and researchers dedicated to stamping it out, malware must be very good to survive for long.  Many or most strands will be identified and wiped out.  Those that survive will be scary indeed.

I don't know when we're going to get the first malware in the wild that can truly modify its own capabilities, rather than just its signature.  Maybe its already out there.  How complex is it getting?  At what point is it going to exceed its creators wildest expectations?  At what point will it begin exhibiting behaviors that will appear to demonstrate creativity and innovative problem solving?  A what point does it become self aware?

Whenever that happens, I don't know if we'll know what to do.  We're going to need help.

Maybe we can ask Watson.

Intentions versus Capabilities - Part II

I’d like to open this post with an apology, because I’m deviating a little bit from my usual subject matter.  This is a blog about technology, and about how patterns of technology change and interact with daily life.  I don’t normally comment on general news stories that don’t have a direct connection with technology.  I’m making an exception this time because it touches on some themes I’ve covered before, which I’d like to reiterate from a different angle.

The story in question is the tragic death of Trayvon Martin, and the failure of Florida police to prosecute his assailant due to Florida’s “Stand Your Ground” laws.  This is still a story in progress, and anything could happen, but the evidence is increasingly casting doubt on George Zimmerman’s story.  Independent analysis demonstrates it is exceedingly unlikely that the cries for help were Zimmerman’s.  It is further difficult to demonstrate that George Zimmerman had sustained the types of injuries that his story had claimed.  Add to this the undisputed fact that George Zimmerman left his car to confront Martin despite the instructions from 911 not to do so, and it’s difficult to paint this as anything other than a one-sided assault.  This is a crime.

Or is it?

Under normal circumstances, Zimmerman’s departure from his car to confront Martin would paint him fairly clearly as the aggressor.  Under the stand your ground laws, he had no duty to retreat from what he believed to be a dangerous situation, and, having deliberately entered into this situation seeking a confrontation, was justified in the use of deadly force to protect himself from what he reasonably believed was a threat.

Critics might question whether his fear of Martin, who was unarmed and a hundred pounds lighter than Zimmerman, was “reasonable”.  Unfortunately, there is no precise definition of what constitutes “reasonable”.  Certainly his fears would be shared by many other residents in his neighborhood.  Does that make them reasonable?

Regardless of how the law will be interpreted, the fact that the Florida police used it as an excuse to not initiate a criminal investigation of Zimmerman indicates that something is seriously askew.  At the root of the issue is an asymmetry of information created by the situation.  In any dispute between two individuals, each is likely to have a different narrative explaining the context, motivations, and possibly even the facts leading to the event.  In a murder, one of those narratives disappears.  The only narrative remaining belongs to somebody who will likely have every reason and every inclination to skew the facts in his own favor.  This is why imposing a duty to retreat is such a useful concept.  While it does not eliminate this type of situation – anybody can still claim they had no opportunity to retreat – it does reduce the number of situations in which an assailant can claim a legal justification for their own aggression.

I don’t believe the Florida legislature had malicious intent when they enacted this law.  I don’t expect they ever thought about the possibility of an individual committing an act of murder and using their law to claim it was self-defense.  And that’s the crux of the problem.  They didn’t think.

As I noted when I discussed SOPA, there is a world of difference between the intentions of a law, and its real life effects.  It behooves legislatures to think long and hard about the possible secondary effects of the laws they pass.  In this case, it seems they didn’t think hard enough.  The results have been lethal.

Well done, Florida.  Well done.

Waiting for the End of the World

On March 19, 2012, Amazon announced they were purchasing Kiva Systems for $775 million.   By all accounts, they're not planning on selling these robots on their website.  Rather, this is another step forward in the development of the automated warehouse, in which robots will manage inventory and fulfill orders more cheaply than humans could.  Many people have noted that the loss of jobs is one more step in a long cycle of economic decline for the United States.  It's the end of the world.

And yet, as I touched upon in a previous discussion, the end of the world has come and gone many times, and somehow there are still people around to complain about it all.  (OK, technically I talked about how civilization was going to the dogs, but same thing.)  People will probably lose jobs when Amazon automates their warehouses.  On the other hand, we've been losing jobs for centuries, since the dawn of the Industrial Revolution.  If something wasn't filling the void, we'd have an unemployment rate in excess of 99%.  Life goes on.  When the citizens of the Roman Empire became more interested in enjoying the luxuries of civilization than in defending it, the Roman Empire fell, and the world came to an end.  Of course, what that really meant was that people were more interested in investing their time and energy building the new kingdoms that became feudal Europe than they were in defending a political structure that had become obsolete centuries ago.  Somehow, life went on.  More recently, when rock & roll swept through the nation, it was a corrupting influence on our youth that would destabilize society.  Today we consider many early rock & roll tunes to be light and easy listening, and play them as background music in elevators.  Life goes on.

Of course, sometimes the world really does come to an end.  Our records are scarce, but I guess that there was probably somebody in the city of Carthage around 250BC saying that everybody should focus a bit less on making money and a bit more on beefing up their own military.  They should have listened.  For the Carthaginians, the world truly came to an end, as the city was burned to the ground, and all the inhabitants were killed or enslaved.

The problem is, it's really hard to tell in advance if the particular end of the world we're talking about is going to be in the "life goes on" category, or the "no, its really the end of the world" category.  So without attempting to forecast exactly what's going to happen, lets look at a number of other ways in which the world is going to end, and think about what this really means.

Talkin' 'Bout My (Facebook) Generation

George Orwell got it all wrong.  Big brother didn't start spying on people in their living rooms.  Instead, people simply started broadcasting every aspect of their lives on tools like Facebook, Twitter, and Foursquare.

It's easy to see examples of highly questionable decisions being made about what people post.  Everything from pictures and videos of drunken behavior at parties, to cursing of bosses and co-workers and customers, to defamatory insults of whatever is nearby.

The law hasn't quite settled on how to treat these situations - do they represent free speech to be protected, or does an employer have a right, or even an obligation, to control its image by firing employees who engage in unseemly behavior?

It seems to run against human nature for people to stop acting out and sharing everything.  Which raises an interesting question: if everybody (or at least lots of them) engages in "unseemly" behavior, is it still unseemly?  What happens when the generation that grew up with Facebook is in their fifties and sixties, and run all the corporations (and not just the hot tech startups).  Do we give up and adopt new societal standards for behavior because "everybody does it"?  Or does society bifurcate into a new set of haves and have nots, in which a few people are lucky (or boring) enough never to do anything really stupid in the public eye, and are thus our only candidates to run major corporations and hold public office?

If a Tree Falls Before Wikipedia Covers It, Was It Ever Standing?

Encyclopedia Britannica recently announced that it was finally discontinuing the print version of it's encyclopedia.  On the one hand, this was a momentous event, as Britannica had been in continuous publication since 1768.  On the other hand, its amazing they kept making the print version as long as they did.  The company has been struggling for years, threatened first by CD Rom dictionaries like Encarta, and now by Wikipedia.  While there are a certain number of adherents to Britannica's use of experts rather than Wikipedia's crowd sourced model, it is unclear how long the for-profit company can survive against a free competitor.

This is simply one example of print materials giving way to their electronic counterparts.  The Kindle and the iPad have ushered in a new era of ebooks, with the result that Borders has declared bankruptcy, and Barnes and Noble loses money hand over fist while it struggled to reinvent itself.  Perhaps the independent bookstores will survive indefinitely as a niche market, but paper publishing in general is likely to be a shadow of what it once was.

Which raises the question: when the vast majority of all information is only available in online formats, how will we footnote our references?  If George Lucas decides that Greedo shot first, could we ever lose every reference that the story wasn't always that way?  (Yes, I know that he made the original versions available on DVD, but you'll note he didn't extend that to Blu-Ray.  Wanna bet as to whether they'll migrate onto whatever format comes next?)

Perhaps references will become impossible, and all knowledge will devolve into "truthiness".  On the other hand, challenging data problems have a way of attracting programmers looking the next great start-up idea.  Perhaps this very problem will inspire new types of technology that will lead to unprecedented levels of accuracy and transparency.  Imagine a scientific journal that automatically tracked its footnotes, and warned the reader if key references were out of date and could no longer be trusted.  It would dynamically call the entire premise of the article into question, and you would have real-time feedback as to whether the article you were reading was still relevant.

To Boldly Go Where No One Has Gone Before (Back Home)

Whenever criticisms of Gen Y come up, high among this list is that they are the "Boomerang Generation".  Whether due to an unprecedented combination of school debt and economic malaise, or simply a lack of gumption caused by overindulgent helicopter parents, this generation leaves home, marries, and starts their real careers later than any other generation in recent memory.  Have we lost the critical pioneer spirit that makes up the American psyche?

On the other hand, maybe looking only at generations in recent memory is a short-sighted endeavor.  The whole concept of personal independence is relatively recent.  The standard family unit used to be extended, with three generations living under a roof, not just two.  Kids didn't generally strike out on their own, they joined the family business.  Perhaps the last couple generations have been a deviation from a historical norm, and Gen Y is simply taking us back to our roots.  Only time will tell.

On so many levels, the world is ending.  Sometimes the end of the world really is the end of the world.  But much more often, it just seems that way to the previous generation who doesn't like or understand the new environment, and can't imagine how it will hold together if it's not like it used to be.

So do what you can.  If you see a problem, try and fix it.  But remember to keep an open mind and a sense of wonder, because whether your're going to love it or hate it, you'll hate to miss what's coming next.

Know Your Limits

On June 22, 1941, Germany launched Operation Barbarossa, sending 3.9 million troops into the Soviet Union.  This was the largest invasion in the history of warfare, and was likely the most significant reason why the Axis powers lost World War II.

Untangling all the reasons why Germany lost along its Eastern front could keep a horde of rampaging historians busy for a lifetime.  However, very high among the top candidates would have to be that the Germans failed to pay proper attention to the most critical constraints.  They had plenty of weapons, ammunition, motorized vehicles and horses, which Hitler believed to be all that was necessary to win.  But, overconfident of his ability to achieve a decisive victory quickly, he made no provisions for the supplies that would be needed if the campaign stretched into November or later.

There are some constraints in warfare which are flexible.  Treaties can be bent or broken, and then rationalized later.  Troops who are tired or dispirited can be bribed or threatened to march just a little farther.  Recruitment standards can be lowered to expand the pool of available soldiers.

Winter in Moscow is not one of those constraints.  It makes no allowances for your failure to plan.  When temperatures hit -40 degrees Fahrenheit, guns jammed, fuel turned solid, and troops stuffed newspapers into their light summer uniforms in a futile attempt to avoid freezing to death.

Military planners have studied these battles carefully.  They have attempted to extrapolate the underlying principles of cause and effect, and apply these principles to as many other situations as possible.  But have the lessons really sunk in for everybody else?

On February 14, 2012, the FCC rescinded permission it had previously granted to Lightsquared Corporation to create a new broadband wireless network.  The effect of this decision was devastating.  Shortly thereafter, the CEO of Lightsquared resigned, half the employees were laid off, and Sprint cancelled a 15 year spectrum-hosting agreement.  It is unlikely the company will recover.

Should anybody care?

Let’s think about constraints from an engineering context.  Some constraints are more important than others.  When designing an airplane, the total weight is a critical constraint.  Engineers will spend thousands of hours and billions of dollars to find a new type of material that will make the airplane a tiny percentage lighter.  When designing a washing machine, weight isn't nearly as important.  It's not completely irrelevant, as you wouldn't want to build a two ton machine that couldn't easily be delivered, or which would fall through an average floor.  But in general, washing machine designers don't spend much time worrying about it.  A 10% difference, say between a 180 lb and a 200 lb machine, is largely irrelevant.

Some constraints tend to become less significant over time.  Computing power is a great example.  If you have an idea for a great video game that would be too complex to run on today's generation of computers, don't throw the idea away.  Given the rate of improvement, driven by Moore's law, it might just might run on the next generation.  In fact, given the lead time needed to develop most games these days, you might just want to start developing it right now, under the assumption that the hardware will catch up to you by the time you're done.

The size and cost of consumer electronics is similar (and closely related).  They are small and constantly getting smaller.  If you have a ten year plan to build a robot that needs a fully functioning Linux server the size of your thumbnail, don't worry that you can't find a server that size on the market today.  The Raspberry pi has already demonstrated a Linux machine the size of a credit card.  Ten years should be more than sufficient time to shrink it down to thumbnail size.

Other constraints aren't so easily resolved.  One of these is the amount of available electromagnetic spectrum.   Spectrum is needed any time you want to communicate without a connected medium (such as a wire).  It’s uses include television, AM and FM radio, Wifi networks, cell phones, radar, microwave transmitters and garage door openers.  There is only only have a fixed amount of it, and there will never be any more.  Demand for spectrum is intense, and growing rapidly.  Companies pay tens of billions of dollars to license relatively small portions of the available spectrum.

It is more precious than gold.

With this in mind, a number of years ago, Lightsquared made a proposal to use advanced technology to deliver a new 4G LTE wireless network using a slice of unallocated spectrum bandwidth.  They would provide this network capacity to existing providers wholesale.  This would have increased capacity, exerted downward pressure on the currently rising prices, and been a boon for both consumers and corporations alike.  Everybody wins, right?

Well, not everyone.

It seems that GPS manufacturers were a bit concerned by this idea.  Lightsquared's plans would potentially interfere with some GPS devices.  In February, their concern made enough of an impact on the FCC to cause the FCC to put a halt to the venture.

If we left the story right there, then I'd probably side with the GPS manufacturers.  I like my GPS.  I don't want it to break.  If somebody has other ideas, well tough, because my GPS was here first, right?

Well, it’s not quite that simple.  You see, you need to remember what I said about the electromagnetic spectrum.  Because it’s so precious, it's all carefully defined and licensed out.  And as it turns out, Lightsquared was not infringing on the GPS wavelengths at all.  Instead, GPS's are infringing on spectrum that was licensed to Lightsquared.

Although we talk about spectrum in very precise, digital terms, its actually very analog.  If you broadcast on a specific frequency, unless you're very careful, it doesn't look like a sharp spike at that specific frequency.  Instead, it looks like a broad bell curve, centering around that frequency.  Try looking at a simple frequency analyzer (such as Soniqviewer for iOS) while you play a single note on a musical instrument.  You'll be amazed at how many sound frequencies are playing all at once.

The problem in this case isn't the transmissions from the GPS satellites, it’s the receivers.  GPS signals tend to be weak.  GPS devices are inexpensive.  To make the devices as cheap as possible, and get the best possible reception, GPS devices use receivers that are very imprecisely tuned, in an attempt to pick up as much of the signal as possible.  That means that GPS devices end up listening to a lot of spectrum they have no business listening to.  And, no surprise, they have the tendency to get confused when they hear some other signal on this other spectrum.

This is a fixable problem.  Lightsquared has demonstrated how a simple filter could be added to the GPS filter to clean up reception.  This would increase the cost of a GPS.  But cost isn't a significant constraint for consumer devices.  GPS chips are already such a commodity that they are being added into every model of smartphone on the market.  Garmin, the leader in standalone GPS devices, is desperately trying to find a new niche because it's product is becoming such a commodity.

So let’s think about this from a constraint perspective:

• GPS devices are cheap, and getting cheaper
• Spectrum is expensive, and getting more expensive
• The constraint the FCC wants to address is the current cost of GPS devices, rather than increasing utilization of spectrum

Does this make sense to anybody?

So far, we’ve managed to handle spectrum concerns.  Smart phones, which are among the biggest consumers of data, are still relatively new.  We’ve been enjoying a pleasant summer of bandwidth availability.

But demand is growing fast.  Available spectrum is fixed.

Winter is coming.

You Can Lead a Horticulture…

Another year, and once again Apple has managed to dominate the attention of the global media by releasing a new version of the iPad.  Curiously enough, even news outlets that didn’t think it was big news carried it as their top story.  For example, the New York Times article described the improvements in their headline as “modest”.  And yet, it chose to carry that story on the front page of their website.

Well, I’m sure it made sense to them.

Whenever Apple hits the news like this, the world seems to split into two extremely vocal camps.  Camp number one loves Apple and follows every detail.  Camp number two loathes Apple and disparages Apple followers as “sheep” and “lemmings” for snapping up every Apple product.  Curiously enough, they also tend to follow every detail.  (There’s a third camp who doesn’t pay any attention to any of this, but since they tend to be a quiet bunch, we can safely ignore them for this exercise.)  Without stepping too deeply into this debate, I would like to focus on one particular criticism that is sometimes leveled at Apple, which is that its products should not be purchased because they are much more expensive than competitor’s products with the same specifications.

This criticism represents extremely sloppy thinking.  I might even go so far as to call it stupid.

Before the deluge of hate mail begins, let me make clear that I’m not criticizing people who dislike Apple products.  I’m not even criticizing people who choose not to buy Apple products because of their specifications.  However, I am criticizing people who think that the technical specifications are necessarily the only relevant criteria for purchasing a product.

To illustrate what I mean by this, let’s take a look at a branch of artificial intelligence (AI) known as expert systems, and more specifically at automated rule induction.  I find it useful to consider artificial intelligence for subjects like this because AI was designed to replicate, at least superficially, how humans think.  By understanding the limitations of AI, we can sometimes gain insight into the limitations of our own thought processes.

In expert systems, knowledge is represented by a series of rules.  While the concept of an expert system as a form of artificial intelligence is only about forty years old, the idea of capturing knowledge in a simple rule is ancient.  For example consider the following sayings:

“Red at night, sailor’s delight.  Red in morning, sailor takes warning.”

“Red on black, friend of Jack.  Red on yellow, kill a fellow.”

Both of these represent knowledge within a particular knowledge domain (meteorology and herpetology respectively) captured in a simple, rhyming rule.  With these types of rules, it becomes much easier to communicate, store and pass this knowledge on.   An expert system uses rules similarly to develop a knowledge base about a knowledge domain.

The creators of the first expert systems collected knowledge manually.  They would interview experts (hence the name) in a particular knowledge domain, and codify the knowledge gathered from these experts in the form of rules.  As the field developed, the concept of automated rule induction was introduced.  In automated rule induction, a computer uses various algorithms to analyze a set of data, and derives various predictive rules from that data set.  For example, perhaps you would prepare a set of data which includes a simplified description of the weather (such as “clear” or “stormy”), the time, and the color of the sky twelve hours previously.  The computer analyzes the data, and discovers a strong correlation between a red sky at night and clear weather the following day.  Similarly, a red sky in the morning is strongly correlated with an upcoming storm.  This example is trivial, but when you increase the number of potential variables to hundreds, with thousands or millions of data points, computers can become very useful at spotting patterns and relationships that a human would miss.

There are two challenges in running an effective automated rule induction program.  The first is to avoid rules that are too narrow.  For example, the computer might produce the following rule: “Whenever the date is August 29^th, 2005, there will be a hurricane.”  This rule would be 100% accurate based on the available data.  However, it’s also not particularly useful, because that date will never come around again.

The second problem is a rule that is too wide.  For example, the computer might produce a rule that says “It will snow whenever it is Christmas”.  The computer might choose this rule because it finds that it was true more than 50% of the time in the data set it analyzed.  But it’s so vague that it has extremely limited predictive value.  It is, to use the colloquial term, a “stupid” rule.  If you want a good weather forecasting program, you need a computer with much more intelligent rules, which look at a number of relevant variables and model how they interact.

It’s this second problem that trips up so many people in real life.  Somewhere along the line, they get an overly simplified rule in their head, and for whatever reason, they stick with it.  Maybe it’s too tiring to keep running the automated rule induction program in their brain.  Despite the constant influx of new data to the contrary, they continue to operate with an over-simplified view of the world that ignores most of the key variables.

In fact, this is exactly what racism is.  Whatever else you can say about somebody who is racist, you can also, quite objectively, call them stupid.  This is because the rules in their head which judge people look only at a single variable, and ignore the more complex factors and relationships which are necessary to develop a more sophisticated judgment of a person.  Racists are not intrinsically stupid – they might be quite sophisticated when it comes to other knowledge domains.  They’ve simply picked up a bad set of rules for this domain, and kept them despite evidence to the contrary.

Curiously, this same phenomenon proliferates in the “sophisticated” world of technology as well.  Dave Pogue discussed this at length in a 2007 column, in which he challenged the assumption that more megapixels on digital cameras result in better image quality.  It’s easy to understand where this assumption came from.  In the very early days of digital photography, megapixels were so limited that any time they increased, you did see a noticeable improvement.  But somewhere along the line, the megapixel count stopped being the limiting factor, and other variables, such as the lens and sensor, became much more significant.  But megapixels are simple.  They're clearly labelled on the box.  If you buy based on megapixels, you don’t have to think very hard about your choice.  You can get by using simpler rules.  You can, in short, be stupid.

Which brings us back to Apple.  The differences between an Apple laptop and, for example, a Dell laptop are so numerous that it’s difficult to list them all out.  OS usability.  Form factors (such as size, weight and shape).  Available applications.  Available interface ports.  Susceptibility to malware.  Compatibility with other devices.  Access to friends or colleagues who can provide support if need be.  Any one of these might be important to a particular person.

Computers are, in a word, complicated.  Attempting to define them solely based on a small list of metrics such as gigahertz and gigabytes is simple.  It’s easy.  But it is also, unfortunately, just a bit stupid.

Do You See What I See?

Do you want to heap praise upon somebody in the technology industry?  Use a single word to describe them as tops in their field, somebody to be looked up to, respected, and admired?

Call them a "visionary".

Everybody wants to be a visionary.  To be a visionary means to be able to see what other people can't.  It means being able to predict the future.  It means being able to find winning solutions, and understanding what your customers want before they know it themselves.  What could possibly be more valuable than to have a clear view of the future before anybody else?

Lots of things, actually.  Just ask Cassandra.

According to Greek myth, Cassandra was blessed by the god Apollo with the ability to see the future.  However, nobody would believe her, so she was unable to act on her visions, and the blessing became a curse.

Steve Jobs was often acclaimed as a visionary.  Perhaps that was true in spots, but it’s also true that much of his success was attributable to being a guy with absolutely zero vision, but who could identify quality whenever he saw it.  This was well demonstrated in a famous exchange between him and James Vincent, who was developing the commercials for the forthcoming iPad.  Jobs was adamant that the first round of proposals "sucked", but was unable to provide any guidance for how to improve them. When pressed on this point, Jobs responded "You’ve got to show me some stuff, and I’ll know it when I see it.”

On the flip side, let's talk about somebody who is not often called a visionary: Bill Gates.  We need to be a bit cautious about denigrating Gate's achievements, because whatever you may think of Microsoft's products, it’s indisputable that he achieved a level of professional success that most people will never approach.  But it's also true that despite hundreds of different products, the vast bulk of Microsoft's wealth and success came from just two product lines: Windows and Office.  In neither of these categories was Microsoft first to market.  (Anybody remember when the leading Office applications were WordPerfect and Lotus123?)  Instead, Microsoft came late to the game with inferior, "me too" products, and achieved market dominance through aggressive marketing, incremental improvement and sheer stubbornness.

Despite this, Bill Gates has demonstrated a brilliant understanding of the future on numerous occasions.  Consider this excerpt from his book "The Road Ahead", where he described a future product, which he called the “wallet PC”:  "You'll be able to carry the wallet PC in your pocket or purse. It will display messages and schedules and also let you read or send electronic mail and faxes, monitor weather and stock reports, play both simple and sophisticated games, browse information if you're bored, or choose from among thousands of easy-to-call up photos of your kids."

Sound familiar?  Swap the words "Wallet PC" with “iPhone” or the Android of your choice, and the description is spot on.  Bear in mind that this book was published back in 1994, when the state of the art in portable computing was a device that weighed only 5 lbs and had no built in internet connectivity.

With a lead like this, how could Microsoft possibly fail to dominate the mobile technology platform as thoroughly as it dominated the personal computer?

How indeed.

This isn't the only lead that Microsoft has squandered.  Back in 2008, 2 years before Apple released the iPad, Microsoft was working on a revolutionary new tablet device code-named “Courier”.  It had a built in camera, and accepted input from both multi-touch and stylus.  Gizmodo, in a review of a late stage prototype, called it "astonishing".  It might have proved a fearsome competitor to the iPad, but we'll never know, because Microsoft killed the product before it was ever released.  This decision was made in part on the advice of then-retired Chairman Bill Gates, who didn't think that Courier followed the core Microsoft Windows strategy closely enough.

In hindsight, this was probably a bad choice.  Might it have been anticipated?  Many years before Courier was killed, a technology visionary made an astute observation about how an ailing IBM was stifling its own innovation.  This came during the period of collaboration between IBM and Microsoft, who were jointly developing the new OS/2 operating system.  At the time, IBM was extremely concerned about interoperability between all of its product lines, and suggested in all seriousness that fonts be dropped from OS/2, because they would not be supported by IBMs existing line of mainframe printers.  This visionary correctly noted that you can't survive in the technology industry for long unless you are willing to cannibalize and render obsolete your own product lines.

That person's name?  Bill Gates.

Cassandra must have been laughing her head off.

For all of Microsoft’s considerable success, it seems like it might have been greater still had it only managed to take better advantage of the visionary skills of its founder.  It might not be struggling to stay relevant in a world where PCs are rapidly giving way to mobile phones and tablets.  It might still succeed.  But if so, it will be celebrated as a surprising turnaround story, not of a Goliath maintaining its dominance.

So if ever Apollo offers you the chance to be a visionary, think about Bill Gates.  Remember Cassandra.  And most importantly, remember Noah, who understood the key principle of being a visionary: Predicting rain doesn’t count, unless you're also building arks.