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Editing Bay

This Sunday, NBC is scheduled to air an interview of the highly political, self-described “performance artist” Alex Jones by former Fox anchor Megyn Kelly. Alex Jones, if you’re not aware, has built an empire using fear to sell dietary supplements, all the while “playing a character”, according to his lawyer.

The interview had already received quite a lot of news coverage, even before airing, because some – particularly Sandy Hook Elementary parents who lost children in the shooting there – have criticized NBC for granting a platform to as incendiary and controversial a figure as Jones, whose livelihood rests on making outlandish claims as part of a snake oil selling act.

Now, it seems Mr. Jones recorded pre-interview phone calls and, ultimately, the entire interview with Ms. Kelly. He has started selectively releasing audio from those encounters as part of his InfoWars program, applying his own spin, and if he’s telling the truth about having all that audio, this will undoubtedly serve as cannon fodder for his bombastic rants for quite some time.

NBC finds itself in a bit of a minefield here, particularly since mainstream media are already under fire for shaping, as much as reporting, the news. Jones will be able to endlessly claim that his words were twisted, through editing, and NBC will be on the defensive, because some of what he says will undoubtedly be true. Perhaps they gambled that this would be Jones’ strategy, and feel that it will boost their brand awareness. Time will tell if it’s a net loss or gain, from their perspective.

Editing is a necessary part of the process of tailoring news for particular media, in order to fit content into the allotted length (for example, to be within an hour long show), and also as a way for journalists to distill the complex into bite-sized chunks for easy digestion. Editorial selection is necessary in order to highlight which aspects of a story are important, separating the wheat from the chaff. Any way you slice it, though, editing is necessarily an objective process, one fraught with difficulty when it comes to maintaining neutrality.

The thing is, through mobile and online channels, NBC has endless space and time, so there’s not really a reason anymore to hold back the raw data. Jones says he will use his recordings of the interview to illustrate where NBC made cuts to further an agenda, but my question is: in this day and age, why doesn’t NBC just release the whole interview itself? It goes for this interview, but for all interviews, news organizations like NBC could simply stream an edited version alongside the uncut interview, on their websites and mobile channels, so that interested parties could decide for themselves which points raised (or behavior shown) during the discussion are important to them.

EpiPen Auto Injector

This story about Mylan executives raising EpiPen prices astronomically high while also raising their own pay serves to illustrate why ideological approaches to running the healthcare industry are misguided. Healthcare cannot be solved by the free market, and it cannot be solved by government.

Healthcare is an area where the private sector and public tax dollars need to work together. Why? Because incentives are everything. Human beings work toward incentives, both consciously and subconsciously, and so in any system, the intended or unintended system of incentives need to be considered when setting policy.

The ideal incentive in running a business, or bringing a product to market, is to make money. Sure, companies might talk a big game about how they want to change the world, and sometimes they really do, but these concerns are secondary to their main goal of operating at a profit. The ideal incentive for health care providers, however, ought to be to make people healthier. Cost should not exist among their concerns. A healthier population means a stronger, more productive society.

These two incentives are not always compatible, as evidenced by this EpiPen story.

There is a critical role in the healthcare system for private enterprise. Developing drugs requires organizations that move more nimbly and efficiently than government ever could. Innovations in healthcare (new equipment, software, training strategies) are much more likely to arise from private sector disruptors and new advances in technology. Free market competition, were it allowed, could lower prices for all sorts of routine medical procedures (an example: there is no reason why you shouldn’t be able to walk into a lab in a shopping mall and pay $20 to have a blood test done, with results automatically made available online to you and your doctor). Mechanical items related to people’s treatment should be sold openly in stores with no “medical industry markup”. A $5 piece of plastic should cost $5, no matter whether you use it in your kitchen, or in your CPAP machine.

But then, there are instances where free market incentives are unaligned with healthcare incentives, and here, government should take up the slack. Imagine developing a drug that requires a billion in R&D, but for a disease that only affects 5 people out of a million. That’s bad business, unless you know those afflicted can pay you a lot of money for this drug. Should these people be condemned to a horrible life, or even death, because they were unfortunate enough to have a rare condition? This is an instance where the government could supplement R&D costs, or offer a significant prize for a private solution, in the way they have in other industries, like aerospace. Coupled with ideas like that, through legislation, government needs to set rigid guidelines for any company working in the healthcare space (since they are, in a manner similar to telecommunications companies, operating in an area related to the public good).

In the USA, the real obstacle to progress is private insurance companies. Private insurers have taken over the entirety of the healthcare market (in fact, Obamacare mandates this to be true), and they are the reason for astronomical increase in prices. Think of it like this: if you broke your leg, and you knew the cost to put you in a cast and take x-rays was $500, would you even need insurance to cover this scenario? Probably not…you could pay for this like you pay for a car repair, or home repair. That’s no good for insurers, and this is the reason it costs thousands of dollars in the USA to handle even mundane medical situations. They have adjusted the incentives in the market to raise prices in order that their product becomes necessary (and then the other part of their profit strategy is fighting to deny payment when people request it).

Insurance makes sense as security in the face of extraordinary events. If something (e.g., a house catching on fire) happens very infrequently, then fire insurers can collect a small premium from a lot of people who likely won’t need it, which more than offsets their payouts when stuff does happen. This is how they make money; it’s up to the consumer to mitigate that risk with a fire insurance payment, or not. Insurance was never designed to be a credit card for routine procedures, and by using it in this way, we are misusing it. The results are clear: the USA now spends about 1/6th of its GDP on health, far more than any one else, and at the same time, life expectancy has not been going up as much as it has in other rich countries.

The USA needs to get serious about reducing insurers’ role in the system, while at the same time filling the gaps with targeted uses of the free market (encouraging competition where profit and wellness converge), and using the government where those incentives diverge. And then, the government needs to legislate against excessive profiteering (two Tylenol in a hospital should not cost $20, just as an EpiPen should not cost $600). They need to demand certain standards of excellence for any company operating in the space, and offer incentives for solving difficult medical challenges.

In short, government and business need to start working together and realize that a healthy population benefits us all.

unisex bathroom

Much ado about toilets.

Recently, in the United States, there has been a lot of bickering about bathrooms. A few U.S. states enacted laws – which have predictably backfired – dictating that people can only use the bathroom corresponding to their “biological gender”. These laws are clearly aimed at transgendered persons (perhaps more accurately they reflect a stubborn refusal to admit that gender, like almost everything in life, is more complex than a simple binary).

(The “biological gender” bit of course begs the question of where the hell intersex individuals – formerly known as hermaphrodites, for those behind on the lingo – are supposed to take a piss…outside? But I digress.)

Male/female bathrooms are a relatively new phenomenon.

Law professor Terry Kogan points out that gendered bathrooms only started to appear in America in the late 1800s anyway. The question of why they appeared is an interesting one, and having researched the issue, he concluded that these laws were rooted in the so-called “separate spheres ideology”, which I will break down into slightly blunter language: keeping women in their place.

The 1800s saw an expansion in the stifling of female sexuality that we’re still stuck with in so many ways, from misogynistic talk of fathers with shotguns preventing their daughters from getting laid (how creepy…saving them for themselves?), to of course slut-shaming women who want to actually have an enjoyable sex life. Segregated bathrooms were essentially one more way to “protect the virtue of women”, as if women are in the first place possessive of some unique virtue that needs protecting.

There are a lot of things we had in the 1800s that we have safely left behind. Horses and buggies, slavery, genocide against Native Americans, using morphine to shut up crying babies…those are a few of the things that come to mind. Maybe treating women as helpless creatures that need to be wrapped in cotton wool like porcelain dolls, and demonizing them because they want a good shag every now and then, are things we could leave behind as well? Just a thought.

Everybody uses a gender-neutral bathroom regularly anyway.

I wonder how many houses and apartments I’ve visited in my lifetime. If I think of all the friends I had as a kid, growing up in a few different towns, and then as an adult in five different cities, counting all the parties and dinners and hangouts and so forth I’ve attended…it is certainly in the hundreds, and might well be in the thousands. In all those visits to people’s houses, you know what I have not seen, even one time? A gendered bathroom.

If I’ve asked to use the bathroom, they’ve simply pointed me in the direction of the nearest one, or the public one. There was not once a question about my biological identity. No one asked me to drop my pants before determining where I’d take a piss. We are all quite clearly able to use the same toilets, and it is clear that gendered public bathrooms need not exist for any reason other than our own collective “uptight-ness” around the idea of sexuality and gender.

It’s not rocket science, just a bit of work.

The most frustrating thing about debates like this is that the solution is dead simple. Privacy while using the toilet is desirable, and sometimes we may need to change clothes or deal with other personal issues in public. So we need individual spaces. Having this while accommodating intersex and other trans individuals only requires a bit of elbow grease. First, slap up some thin walls around toilets. Nothing fancy, but get rid of those shitty metal “stalls” with glory holes drilled in them, and a foot of open space underneath. Replace them with walls or dividers that stretch from floor to ceiling. Privacy problem solved: you can take your dump in peace, and more importantly no one has to see that you’re playing Candy Crush while you’re doing it.

Opponents bring up safety as an issue, even though statistics show that actually most violence in restrooms is against transgender people, the very people who would benefit from reconfiguration. But let’s address the fake safety issue anyway: once you have created a truly private space around each toilet, you can now remove the door to the bathroom completely. This means that the entryway to the bathroom can be largely visible to the rest of the establishment, meaning if anyone gets cornered, they can call for help and others in the vicinity can see inside, and easily come to their aid. Also, noting as I have in the past that half of millenials don’t see gender as a binary concept, these problems will lessen with time.

With private toilets, we can now put the sinks in a common area. It doesn’t even need to be in a “room” to begin with; it can be out there in the open (there is no need for privacy when you’re washing your hands). I’ve been to plenty of bars and restaurants in my lifetime with this setup, and have not once seen a problem. In practical terms, in most places these changes would mean knocking down a wall, creating a common area between the two former rooms, et voilà! Problem solved. In cases where they already have more than one separated, single person bathroom, all they would have to do is change signs. There is no reason for single person bathrooms to be gendered in the first place. (I wonder why already private bathrooms need to be gendered…maybe this was simply an invention of lazy women who got tired of the toilet seat being up?)

Businesses and other organizations may complain that these reconfigurations would cost money, or more basically, that it’s a pain in the ass. I do not disagree with either of those complaints. But you know what? My answer to that is: oh well. Progress costs money and effort sometimes. Society has made these requests before, for example when installing wheelchair ramps, or retrofitting sidewalks and buses to be wheelchair accessible. Do you think that cost some money and effort? Of course it did, but the end result is that some people who previously couldn’t get from point A to point B now can, and that seems worthwhile.

So instead of looking at this as extra work to create something new, consider the history of how gendered bathrooms came to be in the first place, and look at it instead as correcting an error we collectively made 150 years ago that didn’t need to be made in the first place.

Jill Stein

Voters in the Democratic Party have spoken. Once again, Democrats voted to maintain their party’s stance as a pro-war champion of multinational corporations. This shouldn’t be a surprise, since this is what they have represented for the past 50 years, but this was the first election in recent memory where the party came close to electing someone who considers all human life an important thing worth protecting. Alas, it didn’t work out that way. The voters chose as strong a supporter of the military-industrial complex and multinational corporations as was available in any party: Hillary Clinton.

She is someone who didn’t support gay marriage until 2013, when she was laying groundwork for a Presidential run. She admires Henry Kissinger and his disastrous foreign policy approach, one that is rooted in a fundamental lack of respect for human dignity. She has written off large swaths of the population when it suits her, whether referring to black youth as “super-predators”, or laughing about bombing Libya: “we came, we saw, he died“. (After Qaddafi was beaten and sodomized with a bayonet.) Clinton eagerly supported military action in Libya, even after the failure of a very similar game plan in Iraq, so in addition to her apparent disregard for human beings living anywhere she feels there are “strategic interests”, she displays an inability to learn from history. That is a dangerous quality in a leader.

The Republicans, for their part, voted for a candidate who calls for less war, and more diplomacy. Yes, despite his bombastic rhetoric, Donald Trump actually argues against destabilizing governments and regime change through war. He argues the U.S. should pursue a policy of stability in the Middle East. This is commendable. But out of the other side of his mouth, he advocates killing terrorists’ families (i.e., genocide). Along the way in his campaign, he’s pined for the “good-old days” when disruptors were carried out on stretchers, has labeled Mexicans as rapists, and has said that he advocates barring Muslims from entering the United States. He also argues strongly that the USA’s foreign policy should be “America first” all the time, which is not the language of someone who respects other cultures. To put it more bluntly, these opinions appear to be fueled in part by bigotry.

So in the two major parties, what we have are two candidates who openly show they do not believe that all human lives are worth the same amount. The most basic precept in the idea of human rights is rejected by both of them. Hillary believes any human life in the way of her “strategic interests” is worth eliminating or marginalizing, and Donald has displayed the attitude that there should be one set of rules for the (white?) majority, and different rules for any other group (Mexicans, Muslims, journalists) that he deems problematic. Both of these candidates’ ideals are borne of privilege; they consider themselves and their group above that of anyone else who gets in their way.

If one fundamentally agrees (as I do) that a human life is a human life is a human life, then it becomes impossible to vote for either of these depraved power-seekers while at the same time maintaining a healthy conscience.

Luckily, that is not a choice one has to make, because there are two other candidates on almost all state ballots who do not display the same contempt for humanity. Both candidates argue for less war, and for an America that operates as a good citizen in the world, pursuing its own national interest in a way that is minimally disruptive to (or even supportive of) people living elsewhere. Those candidates are Jill Stein and Gary Johnson.

Jill Stein

Dr. Jill Stein is a physician and activist who has been the Green Party candidate for President, and for Governor of Massachusetts. She has advocated for campaign finance reform, and environmental issues. Her foray into “third party” politics began when Massachusetts Democrats repealed the Clean Election Law, after a childish and protracted battle against it, even though Massachusetts voters were overwhelmingly (2 to 1) in favor. Lately, she has attempted to offer herself as a “Plan B” option for Bernie Sanders voters, and indeed she supports many positions similar to Sanders’, including his compassionate foreign policy agenda.

On the topic of foreign policy, she has said “We need a foreign policy based on international law, human rights, and diplomacy, instead of militarism.” This sounds like a United States that works with the rest of the world to develop consensus, rather than dictating terms at the end of the gun barrel. In that statement is an implicit understanding that people are people, that Americans are no more or less “worthy” than anyone else. This, again, is the essence of human rights.

Gary Johnson

Gary Johnson served two terms as Governor of New Mexico, and is once again running as the Libertarian Party candidate. In 2012, the Libertarians garnered more than a million votes, which stands as a record for the party. As governor, Johnson vetoed a lot of legislation that crossed his desk, supporting his idea that “Although I do not believe that government is ill-intentioned, I strongly believe in less government.”

Johnson approaches foreign policy from the point of view of non-interventionism, without being isolationist. He has described himself as a “skeptic” in this sphere, meaning that he would weigh actions against possible unintended consequences. For a practical application of what this means, consider his views on dealing with North Korea: “we need to ally with China” to persuade China “through diplomacy to deal with what is a regional crisis.” Similarly to Dr. Stein, this is someone openly discussing working with a potential rival, rather than castigating them, or advocating unilateral military action. He has said he supports military action when attacked, but that otherwise it should be well measured, and in all cases the Congress should formally declare war.

How To Support Third Parties

For those who value human rights and international peace, generally speaking, they may want to support one of these candidates. Furthermore, in a year where both big party candidates are deeply disliked, it may be a more opportune time than ever to register disgust with the two major parties. The most obvious ways are to advocate for them, give them money, and vote for them. If any party receives even 5% of the vote, they are eligible for federal matching funds in 2020. That means neither of these parties need to come anywhere close to winning to have a game-changing future.

Still, even among those dissatisfied with the major party choices, there are some who feel that Clinton’s fervor with respect to destabilizing foreign governments is too big a problem for national and international security, and therefore they want to vote for Trump. And on the other side, there are those who worry that Trump himself, even though he doesn’t yet have an actual body count (like Clinton), is nevertheless scary because his rhetoric seems to shift on a daily or weekly basis, and judging by his comments, he is relatively hostile to nonwhites. So those voters want to vote for a known quantity who they feel will maintain the status quo.

In this case, if one feels that they can’t give the Greens or Libertarians their vote, how about giving them some money instead? Consider that the Democrats and Republicans are filthy stinking rich. They already represent the will of huge multinational corporations and billionaires. They already have operatives and SuperPACs with millions at their disposal working on their behalf. Your money is a pittance to them.

Donations to the Greens or Libertarians could make a difference. It would allow them to raise their profiles in this election and beyond, paving the way for future acceptance of political views that take a more inclusive stance in terms of how the United States projects its power worldwide. It may allow those parties to field more candidates at lower levels throughout the country, thereby introducing more points of view to the political process at all levels. It may even cause the two major parties to take note of their ideas, and court lost voters by moderating their policy positions. In effect, a strong Green party is a conscience-check on the Democrats (and the Libertarians in some respects serve the same role to the Republicans).

Failing that, simply telling people that these options exist is enough to trigger debate on some of their ideas, and debate is crucial to a democratic society. Debate of those ideas can also be had in respect to the major party conventions and their platforms. That is why I mention them here. A candidate need not win an election to have a lasting impact on public policy, and with the two major parties standing for war and bigotry on behalf of corporate overlords, 2016 may be a better time than ever to register one’s dissatisfaction.

Interstate 495 - Massachusetts

I want to tell a story about how a frustrating 15-minute struggle to procure a burrito tells me something about the design of so-called “digital assistants”. This happened in late 2014, and I intended to write about it back then, but somehow it fell by the wayside until Dag Kittlaus unveiled Viv at the TechCrunch Disrupt NY conference.

If you have no idea who Dag Kittlaus is, he was one of the co-creators of Siri, which we all know as the digital assistant software inside iPhones. Apple is far from alone in this space: Google has its Google Now platform as part of Android and, soon, other physical devices. Even Amazon is getting in on the act, with its Echo speaker. No doubt they imagine a future where we’re standing in our kitchen, and have emptied our box of corn flakes into a bowl, and are able to say right then and there “Amazon, add a box of corn flakes to my weekly delivery on Friday.”

That’s all well and good, but for anyone who has actually used Siri, its limitations are laid bare pretty quickly. From the outside, I would wager that the hardest part about developing Siri was decoding naturally spoken language, first and foremost, enough to glean the user’s intent. Once they managed that, Siri appears to be essentially a database lookup service with some functionality tacked on (for example integration with an API to make restaurant reservations). So you can say: “What’s the score in the Blue Jays game?” and it talks to the MLB or whomever and fires the result back to you. This kind of thing is helpful, particularly in an environment where being hands-free is important, like driving a car, or while holding a baby in one arm and a package of diapers in the other.

Unfortunately, our needs can’t always be expressed in one sentence like that, because sometimes elements in the world create a context that limits or adds additional complexity to the actions we can perform. It would be helpful if digital assistants understood some of these real-world limitations and automatically worked within them.

Which brings me back to what turned into the seemingly sisyphian task of getting my grubby paws on a burrito.

Above is a map of central Massachusetts, in the USA, just to the northeast of Worcester. After handling some business south of Worcester, I had driven north through Worcester, east across 290, and had just merged onto 495 north, about where the town of Hudson appears in this map.

You’ll notice there are some Chipotle Mexican Grills highlighted. That is not a coincidence; we are on a burrito quest, after all. Since I was driving, and didn’t relish the idea of my head smashing violently into the windshield as my car careened into a tree after I lost control because of staring at my phone instead of the road, I opted to ask Siri “where’s the nearest Chipotle?”. She dutifully responded “I found a Chipotle nearby” and showed me that it was in Marlborough. I’m somewhat familiar with this area; I’ve noticed on previous drives that there’s a mall around there. On the map above, that location is the one directly south of Hudson, on route 20. It is indeed the closest Chipotle, and I had just driven past it.

I’m traveling on 495 north, more like next to the “H” in Hudson on the map. I don’t particularly want to get off the highway, do a U-turn, head south until route 20, and then turn onto that and drive a mile+, all before circling back north to eventually be where I already am. I try another approach: “Where is the second nearest Chipotle?” Siri spins her wheels and says “I found a Chipotle nearby”, and shows me the same one again. I try a few other queries, like “Is there a Chipotle between here and Lowell?” (a city just off the northeast corner of this map that I would be driving through). She spins her wheels and says “I found a Chipotle nearby”. The point is, no matter what I did, it feels like Siri works for the Marlborough branch’s franchisee. Siri really, really wants me to go to that Chipotle. As a developer, this tells me is that basically Siri pays attention to the word “Chipotle” and does a geo-search on my location, and spits out the #1 response.

For those hanging on every suspenseful thread of this riveting tale, yes, I did eventually get my burrito, up there north of Littleton. I sat outside on a beautiful sunny day and ate it while I talked to my girlfriend, who was on the other side of the world. Technology can be great. How did I find the Chipotle near Littleton? By pulling off the highway, launching Google Maps and typing in a search query. So technology, still great (a map in our pocket!), but unfortunately in this instance it made me temporarily cease my northward progress to fiddle with it. This experience can be better.

When you’re in a car, the world is structured according to roads, and some of those roads (like 495) are limited access highways, so our ability to make a quick u-turn is limited or inconvenient. I have a destination to the north, and I would like to get there at a reasonable time. The iPhone has a wealth of information about me in that moment (scarily so, actually). It knows that it is traveling at a reasonable rate of speed. It knows that it is traveling along a particular highway. It knows the direction of the car along the road.

So hopefully developers could create a virtual assistant that gives us not just one option, but a couple. It would be great if she could say “There’s a Chipotle about ten minutes to the south, but there’s also one twenty-five minutes away in the direction you’re going. Would you like one of those, or another option?” Further to that, these assistants should allow us to restrict the search ourselves from the get-go: “Siri, is there a Chipotle near 495 to the north of here?”

There are other situations where these assistants could benefit from knowing about the constraints the real world places on its users. Imagine you’re in Hong Kong International Airport. Siri says there’s a Starbucks here. Great! But…is the Starbucks outside of security, or inside, beyond the security checkpoint? If I’m just here at the airport picking up a friend, I’m not permitted to go to the Starbucks beyond security. Conversely, if I’ve ventured beyond security already, boarding pass in hand, then I’m probably not going to want to exit through immigration and customs and so on just to get a latte. Another example: If it can tell from elevation, speed and location that I’m in the Seoul subway riding on Line 4, rather than telling me about the Tous Les Jours locations closest to my location, it should tell me about Tous Les Jours shops that are close to subway stops along this line in the direction I’m going. You get the point.

All of this brings the discussion back to Viv. It’s clear that the team wants to build a ubiquitous, platform agnostic virtual assistant (so that they can have a bajillion users to monetize), and it’s also clear that they have expended time on handling more complex use cases. In the talk below, Kittlaus describes how Viv is able to decode natural language, and then compose a short program dynamically to represent logic it believes existent in the instruction. Maybe then we could have queries like “Viv, show me some Mexican places around here, but only if they have at least four star ratings.” Would it have helped me do a more fuzzy search for Chipotle while heading north? I am not sure yet, but if these assistants are to be worthwhile beyond simple queries, we’re going to need to imbue them with data that guides search algorithms with an understanding that the real world isn’t as flexible as the virtual one.

West Midlands Police Forensic Scene Investigators Lab

How should crime labs be paid for their work? The question has particular resonance now in light of the recent FBI admission that there were flaws in their hair analysis (or to put it less charitably, there is good reason to believe a lot of forensic “science” is bullshit to begin with).

The fact that CSI was a show about bullshit may be a tough pill for us to swallow. We would all like to believe that if wrongly named a suspect in an investigation, the system would be able to prove us innocent. But the cracks (more like, gaping holes) in the foundation of forensics which show that not to be the case, are surprisingly only part of the problem.

If you don’t think about it too much, it seems like a good idea to pay people based on some quantifiable measure of the results of their efforts. But in implementing any such plan, it’s important to be thoughtful about distorting the incentives in the system. State crime labs, through various kickbacks and incentives, are at least partially paid not for the work that they do, but for the number of convictions they help cement. Think about that for a second.

Even an armchair student of game theory immediately realizes this dis-incentivizes crime lab employees from becoming better scientists (at least insofar as you can consider forensics a science to begin with), and instead encourages them to interpret their findings in a way that will result in favorable outcomes for prosecutors. In a nutshell: rather than objectively processing data, the crime lab employees have reason to make the data fit a prescribed outcome, all of which invalidates the very nature of their existence to begin with.

This is a serious systemic failure: people’s lives are at stake. Taking away someone’s freedom is a very real, and very serious, thing. The process by which you strip someone of their rights is one that should be handled with diligence and care. If you were ever fingered for a crime you didn’t commit, you’d want law enforcement and its crime lab to look for the truth, not look for a way to build a case against you to boost its prosecutorial success rate.

Luckily, the solution to this particular hole in the process is simple: pay crime labs an hourly rate for their work.

testing brain-computer interface

There are people who are dedicated to their vision, and then there are people like Phil Kennedy. Wired has a feature about the man, and it’s pretty fascinating. In a nutshell, Mr, Kennedy is a neurologist who has been working on brain-computer interfaces since the 1990s, and put himself under the knife in order to test some equipment.

To put it in blunt terms, he paid someone $30,000 to slice open his scalp, and shove wires into his brain, as well as implant some electrodes. He then went home and recorded his own brain activity while speaking, in an attempt to refine his idea of having an interface that would allow someone to communicate speech with their thoughts (to be used by, for example, people with injuries or other issues that prevented them from communicating verbally).

The idea, generally speaking, is nothing new. We’ve known since the 1800s that there is electrical activity in the brain, and where there is electrical activity, there theoretically should be the ability to read or manipulate it.  When computers came along in the 1950s and 1960s, there were, almost as quickly, efforts at using the brain as a control interface.

Let’s think about a use case. As a programmer, it’s easy to see why such a device would hold appeal. How do we have to code, today? We have to sit somewhere, and type into a keyboard.  This is actually a fairly easy process, and one that we can do almost as quickly as speech. But I know from experience that typing moves nowhere near as fast as my brain, and it is also fraught with problems.

Our body does this stuff fast enough that we don’t think about it much in everyday life, and also, we’re just used to our limitations. For us, “it is what it is”, but think about what’s actually happening here: first, we programmers conceive, in our brain, what abstract structure we think will work in our code. We have to translate the ideas into whatever language we’re using (not unlike the process of translating your thoughts to be used in French vs. Spanish, or whatever). We then need to fire electronic pulses from our brain down the arms and into the fingers for each component of each programmatic structure (the smallest unit of which is a letter or number). At the same time, we have to follow along and try to process the output (did our fingers fully strike the keys?) and be on the lookout for typos, errors, etc.

Oh, and errors? There are many. It’s anecdotal, but I am certain that more than 50% of coding is fixing errors (and I suspect the number to be much higher). Sometimes, these errors are conceptual, meaning we can’t blame them on the mechanical process of translating thoughts into finger movements. Part of programming is that it is a process of trial and error, so errors in judgment or strategy are to be expected. But there are another class of mistakes entirely, insidious ones that can result from simple mechanical miscues. Either you inadvertently type the wrong key (or forget to type a key), or, because your brain is moving more quickly than your fingers, you proceed quickly to get the idea out before it flutters away and are left with issues in the code which you have to go back over and double check. Sometimes these errors can be so minute that they don’t become apparent until the code is actually run.

So, as a coder, it is frustrating that the latter class of errors exist at all. If we could eliminate the physical and mechanical roundtrip of data from brain to extremities, we could reduce or eliminate much of the minor errors in our code. This is one reason why a brain-computer interface would be a boon for programmers (not to mention writers and so on). If it could (hopefully) perfectly capture your intent (in ways your fingers can’t), then at the least you would only be left with conceptual errors, which are the more interesting ones to think about, test and examine, and the ones which are more impactful to the quality of the end result. We could spend more time optimizing structures for performance instead of hunting and rooting out syntactical errors.

There would be other advantages. As it is today, programmers have to park their asses on a chair somewhere to work. This is another aspect of coding that would be improved with an accurate brain-computer interface. Not only is it a drag to have to put yourself in a particular location to work, but sitting is generally bad for your health, no matter whether you are working or watching TV.

Besides programming, another activity I engage in is running. At the moment, I am training for a marathon, and therefore an awful lot of my time is wasted. You could argue spending time getting fit isn’t a waste (although extreme running like marathoning is probably not good for you). When you are fit you generally have more energy to work or be productive in other ways. Still, the actual time spent during running is not productive in terms of getting things done.

When I’m in that zone, legs relentlessly moving, there’s little to do but think, and it’s often then that I can work out issues with my work. What if I could actually be coding during this time (or even just doing something simpler like chatting with a friend)? There are other similar moments, like when you’re out at a bar having a few pints with friends, and suddenly an elegant solution for some nagging structural problem pops into your head…it would be great to be able to save it, without even leaving the bar.

So a well-functioning brain-computer interface would be a boon to all sorts of people. Probably most of us don’t want someone jamming wires into our brains (indeed, most current efforts are centered around external devices). But, intrepid souls like Phil Kennedy are needed along the route to progress. Even if their efforts alone don’t crack the nut, they add to the body of knowledge that will allow someone else to finally make the pieces fit together.

guys playing go

Finally, software has beaten humans at Go.

It’s been a long time since IBM’s Deep Blue beat Garry Kasparov in a chess match. In the 18 years since, chess playing software has gotten better and better, to the point top human champions rarely win. In 2009, a program running on a fairly weak HTC mobile phone (by today’s standards) was able to play at a grandmaster level.

Chess, though, isn’t a particularly complex game, mathematically speaking.

It is another, older, game which has proven to be a tougher nut to crack with AI. The game, of course, is Go (围棋), which is believed to have originated in China 2,500 years ago. Go is an elegant game, in that the rules are simpler than Chess, and yet the number of possible positions is orders of magnitude more.

This is why, until recently, Go masters have not lost to their computer counterparts, and it is why excelling at the game has been seen as a significant hurdle for AI.

That hurdle has finally been surmounted. Google’s DeepMind division in the UK have revealed that in October of last year, their software AlphaGo beat the European champion, Fan Hui.

When you start playing Chess, at first it seems like a game of strategy. But, for practiced players, Chess becomes a game of pattern matching, because the commonly used variations of play are few enough that people can recall game positions and methods of counterattack. For these reasons, chess simulators work pretty much by searching a tree and looking for patterns, and chess simulators can beat humans essentially because they can scan more trees faster than our brains can.

Because Go is more mathematically complex, it remains a game of strategy for the human brain. That means nothing special except that there are simply too many board combinations for us to remember and act upon. We simply can’t take all the variables into account, and so at some point we have to play by guessing the best move. In other words, “strategizing”.

But even though computers can scan trees more efficiently, the number of mathematical possibilities is great enough that the number of nodes to scan is still too large to happen reasonably in real-time. (Maybe it would be possible to build a computer that could win at Go by simply scanning trees, but it would need to be a supercomputer, and would probably take days, weeks or months to make a single move, which isn’t practical.)

So the DeepMind team had to find a way other than brute force, and they settled on a neural network that was fed data from past games by Go champions, and was then left to play against itself, essentially “learning” optimal strategies. (This is essentially how I improved myself at Scrabble as a kid. Ahh, the things you do when you are an only child.)

The end result was that the neural network was able to predict the move a player would make 57 per cent of the time. The next step will be a match in March with the top Go player in the world, Lee Sedol.

Winning at Chess may have been important for PR and for bringing the concept of AI into the public consciousness, but conquering Go may have more impact on future AI, simply because the strategies employed are more general purpose, and therefore suited to other AI efforts.

As an amusing addendum to this story, Facebook also has a Go program of its own, and has recently placed third in an AI competition. That’s laudable. Facebook tried to steal the show with an announcement of its own successes, but it didn’t work out as well as they had hoped.


An admittedly rather limited study claims that drummers’ human error actually has some mathematical basis: namely, that it creates a fractal pattern, like those seen throughout nature. The team studied drummer Jeff Porcaro’s work on Michael McDonald’s “I Keep Forgettin'”, and found a fractal pattern in short snippets as well as the whole track.

When thinking about software to generate algorithmic music, it may serve coders well to create algorithms that aren’t too “perfect”, if in fact humans are wired to appreciate the imperfection in nature. My own opinion is that we may want future AI involved in any creative endeavor to be able to make mistakes (either organically, or through intentional coding), because it is often in the mistakes where the real beauty or appeal lies.

Perhaps this is more succinctly said by Prince, as quoted in a review of his first intimate “Piano and a Microphone” solo show:

“The space between the notes — that’s the good part. How long the space is — that’s how funky it is or how funky it ain’t.”

Indeed. Listen to the space in the bass, the drums, and the guitar on this live performance of “Do Me, Baby” from 1982.

CarPlay interface

Why will Apple make a car? Free time.

The new worst kept secret in tech is that Apple is working on a car. It’s probably pretty much impossible to launch an effort as big as a new car, and keep it all a secret. The news and rumors have people asking, “Why would Apple make a car in the first place?”

For that matter, why is Tesla making a car? They’re certainly not making any money off it. Google is sinking serious energy into their car project as well.  If this is a highly competitive market, with so many ways to fail, why are all these companies blowing R&D dollars to get into it?

The answer, in a nutshell: it’s not about the car.

If the future of cars were the same as today, meaning combustion engines, and gears and levers and stick shifts, I do not believe Apple would make a car. It’s not a particularly high margin business, it’s incredibly competitive, and there are numerous legal and governmental hurdles to surpass.

Jean-Louis Gassée broke down many of the logistical challenges Apple will face in order to launch a fledgling car business. He notes, for example, that Apple is a much larger company, with higher profits and margins than Toyota, which is the current worldwide market leader. It seems an awful lot of work to go through just to at best build a business that’s smaller than their current phone business. (Apple has enough buying power, incidentally, that it could buy Toyota at its current market cap – roughly $200B – with cash. A smaller boutique company like BMW would be a cinch for Apple to acquire. If the car itself were the endgame, that would be a much simpler route to the finish line than launching a massive internal skunkworks project.)

Ultimately, Apple might not need Toyota or BMW, because they don’t necessarily need their expertise. That might seem counterintuitive, at first. Let car industry veteran Bob Lutz explain why he thinks so:

When it comes to actually making cars there is no reason to assume that Apple, with no experience, will suddenly do a better job than General Motors, Ford, Volkswagen, Toyota, or Hyundai. So I think this is going to be a gigantic money pit …

Bob Lutz is right, but only within the confines of his lack of imagination. Sure, if Apple had to build a combustion engine car, as we currently think about them, with a bajillion parts and so on, obviously they’re not going to do anything better than GM, Ford, Toyota and so on. The thing is, Apple is not going to build that kind of car. They’re going to build a car powered by a battery, or fuel cell, with far fewer moving parts. It’s going to have less of a focus on performance and optimization and more focus on customer experience. It’s going to be a different beast.

Google’s car effort will give you the answer to the question of why tech companies are getting into the car business: the endgame isn’t gears and levers, it’s autonomous cars powered by software.

Google and Apple are the companies best suited to tackle the software problem. Microsoft might be in with a chance here, and has announced a deal with Volvo to develop autonomous cars. Tesla’s cars already have autonomous capabilities, though their track record as a software company is more unproven. I’d go out on a limb and say that those companies are quite possibly the only ones who could realistically pull off a mass-market autonomous vehicle, at least within the next several years. Current car makers have less software experience, and this is why I think Bob Lutz’s comments are shortsighted.

When you think about the car as software, instead of hardware, this is when it quickly becomes clear why these companies are angling for a place. Toyota can keep cranking out hardware at its paltry 2% margin, but the software companies perhaps see an opportunity to license software at higher margins (in Apple’s case, they may well follow their own ethos of controlling the whole widget, but that remains to be seen). So, the public will probably focus on the hardware, as they do with iPhones and the like, but the software is what has value.

That’s not all, though. There’s something else that happens when cars become autonomous. Think about driving, today. What are you not doing when you’re driving?

  • Watching movies and TV
  • Shopping
  • Chatting, Facebooking, Instagramming (unless you don’t care about safety)
  • Playing video games
  • Working

This, I believe, is where Apple and Google see the real opportunity. If people no longer have to drive, they become more like urban commuters, except in their own semi-private space. Which is to say, they have free time, and they are essentially held captive for the duration of their journey. Or, to look at it in a more basic way: you are sitting in a semi-private moving room with its own screen.

Imagine you’ve told the car’s computer to drive you from Boston to New York with a stop at a Chipotle near Hartford for some lunch. It knows you have 4-5 hours of idle time. So why not recommend a movie? Why not send in that burrito order automatically (and charge you for it with ApplePay) ten minutes before arriving so it’s ready when you arrive? If the car knows you have a conference call scheduled along the way, it can remind you 20 minutes ahead and recommend a stop for a bathroom break now. If you have some time to kill, or are in unfamiliar territory on vacation, how about telling the car to take you on the most scenic route, let you know when there are good spots to take photos and automatically recommend a restaurant people have rated highly along the way? (Or if delivery drones become a reality, maybe that Chipotle burrito order can be delivered straight to a scenic rest stop on the side of the road, so you can enjoy a piping hot picnic lunch with a view.)

Traveling by car therefore becomes a very different experience. You, as the rider, are a captive consumer the whole time, with little to do but keep giving Apple your money. Instead of driving, you’re video chatting with Mom, working on your novel, browsing for new clothes, videoconferencing with colleagues, binge-watching the last season of Game of Thrones, or playing games against your friends. Once live TV is worked into Apple’s ecosystem, you can watch the beginning of the Superbowl even though you’re late on the way to your friend’s Superbowl party. Started a movie in the car but arrive home before the movie ends? No problem, pick up where you left off on the TV in your living room.

Apple, having positioned itself as a distributor of all that media, would stand to receive micropayments for any or all of those interactions. So even if they only make a few percent margin on the cars themselves, ancillary services will quickly compound those margins into something significant, and allow them to have more control of consumers’ total entertainment consumption time, regardless of location, further locking them into their product ecosystem.

So, maybe someday, you’ll be sitting in the front seat of your Apple car, driving. Only, you won’t be driving the car, you’ll be driving in a racing game on your iPad, while the car drives itself, and Apple collects profits all along the way.