I love Nassim Nicholas Taleb’s work. I think I’d love it even more if he understood (or knew about) TRIZ. Or at least the concept of contradictions and our ability – should we give ourselves permission– to ‘solve’ and eliminate them.

I’ve been busy absorbing his latest epic, Skin In The Game, after I picked up my copy at his lektchur in London last month. As expected, it’s full of great insight and even fuller of (highly deserved) jibes at the Intellectual-Yet-Idiot (IYI) sector of society. By which he means economists, most academics, journalists, CEOs and all those other parts of society who make pronouncements about ‘the way things should be’ without having any skin in the game. Because they don’t have skin in the game, Taleb argues, they really don’t care whether their pronouncements are valid or not. In many situations, they win irrespective of whether they’re right or wrong with those pronouncements. Meanwhile, the rest of us who act on the pronouncements only to discover they were inappropriate, suffer asymmetrically. A classic example being former US Treasury Secretary, Rob Rubin. Rubin became a highly rewarded director and ‘senior adviser’ at Citigroup as it over-reached itself in the 2000s. When the bank became insolvent, Rubin didn’t write any check, but rather invoked (Black Swan) uncertainty as an excuse. Taleb comments, ‘nobody on this planet represents more vividly the scam of the banking industry. He made $120 million from Citibank. And now we, the taxpayers, are paying for it.”

As Taleb describes it in the book, there are two kinds of people, IYIs like Rob Rubin and people with ‘skin in the game’. Or, put another way, people who sound and look convincing yet talk nonsense, and people who talk sense but don’t sound or look the part. Skin In The Game describes the example of two surgeons to illustrate the point. One surgeon looks very smart, has all the right certificates on the office-wall and talks with great confidence to the patient. The other surgeon looks unkempt, has no certificates on the wall, probably doesn’t have an office and mumbles when they speak to you. Which one should you choose to operate on you? Taleb’s answer is that the in detelligent decision would be to choose the second surgeon. His compelling rationale being that the unkempt, mumbling surgeon has had to work harder to maintain their position than the smartly dressed surgeon. The unkempt surgeon has more likely spent their time devoted to being the best surgeon they can be, while the other surgeon has spent their time devoted to looking like the best surgeon.

We can express the two-kinds-people-story on a simple 2×2 matrix. Something like this:

The horizontal dimension of the matrix considers whether a person understands reality or not. The vertical dimension considers whether the person looks and sounds like they know what they’re talking about. Taleb’s IYI class of people form the top left quadrant of the picture, and people with ‘skin in the game’ – people, in other words, who survive by knowing how the real world works – are contained in the bottom right quadrant.

Drawn as a 2×2 matrix, however, we see there to be not two but four kinds of people. The bottom left quadrant are people that don’t know what they’re talking about and don’t look the part either. I think this is about 95% of people on the planet. The more I look at what people write and say on social media the more I’m convinced this number is probably on the low side. And is probably getting lower.

But then there’s the top right-hand quadrant of the matrix. These are people that Taleb’s worldview doesn’t seem to acknowledge. These are people that know reality (and, by association, have skin in the game) and look and sound convincing. In TRIZ terms, these would be the people who successfully resolved the contradiction. In TRIZ terms life is specifically concerned with not accepting either/or dilemmas, and instead looking towards people who successfully switched to a both/and frame of mind.

I’m pretty certain Taleb doesn’t acknowledge such a both/and possibility. When I saw him lektchuring in London I’d have to say it was one of the worst presentations I’ve ever witnessed. It looked to me like he hadn’t spent more than ten minutes preparing what he was going to say, he mumbled, his most frequent word seemed to be an uncomfortable clicking ‘err’ noise, and he spent half the time fiddling with the copy of his newly published book, trying to find pages to read from, not finding them, and then moving on to another point, leaving everyone hanging halfway through his previous point. It was toe-curlingly bad. Part of me believes that Taleb has convinced himself that it’s not only okay for him to lektchur ‘badly’ (e.g. he now actively uses the self-depracating term ‘lektchur’), but that, like the mumbling-surgeon, its actively necessary for him to be bad in order to avoid falling in to the IYI category.

But this is surely a dumb assumption on his part. It is perfectly possible to solve the contradiction. He could have spent some time preparing his lecture. He could have bookmarked pages in the book that he wanted to refer to. He could have constructed some coherent anecdotes. But yet he chose not to do any of these things.

There are people who have solved the contradiction. Not many of them admittedly (inevitably since 95% of people are in the bottom-left quadrant of the picture), but we only have to think of people like Churchill, Rommel, Schwarzkopf, Napoleon (early part of career at least), King, Norton, Carson, Ghandi and Lincoln: people who knew that it was possible to solve the contradiction, solved it, and went on to deliver the best of both worlds.

Having skin in the game is really important. I totally get that. But that doesn’t mean I have to turn up to lectures ill-prepared. Taleb, I think, needs to understand contradiction solving far better than current evidence suggests he does. If he did, not only would Skin In The Game have been a better book, but he’d also begin to understand that ‘Black Swan’ events are merely revealed or resolved contradictions. And once he understands that, he’ll also come to realise that there are no such things as Black Swans. Only contradictions that society hasn’t solved yet. Or – more likely – didn’t have the foresight to go look for.

Last year, brambles had the measure of me. For every bramble I lopped from its roots and pulled up, another three grew in its place. And three times faster than the previous one. It was like bramble-Hydra. Now its February 2018 and, looking out into the garden, it felt like a new season of bramble-based torture was already in full swing. Pretty much nothing is growing except brambles. The 3x20m mound that I distinctly remember clearing in October, was already choked with new growth bramble.

Something was going to have to change. Time for desperate measures. TRIZ-based desperate measures. Time to solve the bramble contradiction. I want to make it easier to remove them, but every time I try and pull out a branch, all of the barbs do their best to impede the removal. Here’s how the I mapped the problem on to the Contradiction Matrix:

Principles 1 and 24, it seemed, were already part of my bramble-removal armoury: one branch at a time, using clippers and wearing gloves. Principles 5, Merging; 25, Self-Service and 17 Another Dimension, on the other hand, appeared to offer up more intriguing strategy alternatives.

Self-service particularly so. If the brambles refuse to be parted from one another, why not use their self-sticking nature as a resource? Merging seemed to be a complementary idea: don’t try and take one at a time, take them all together. ‘Another Dimension’ took a bit more experimentation, but ultimately made the final solution into a small piece of magic. Instead of pulling-up, I tried pushing everything to the side: push the brambles sideways to expose the next bit of root, clip those roots, then move the pile further sideways. Repeat.

And hey presto, ten minutes later, 60 square metres of bramble were all self-bundled at the end of my mound.

You know, there might yet turn out to be something in this TRIZ lark.

I’ve long been a fan of Joseph Campbell’s Hero’s Journey model as a means of explaining the dynamics of discontinuous change. We typically use the model in an innovation context, but we’ve also had some of the best opportunities to quiz people about it when we’ve been using it to help explain and explore some of the difficulties of organisational change. ‘Where do we think we are on the story?’ is the typical starter question. The answers are many and varied, but in the last couple of years a couple of recurrent themes have begun to appear.  Two quite literally recurrent themes. Teams getting stuck in seemingly never-ending loops.

The first one is what I’ve come to think of as the ‘Big Five Consulting Company Dream Cycle’. The dream being their dream of perpetual fees without having to do any meaningful work. As opposed to the client’s dream of meaningful change without expensive bullshit artists watching them do it. This loop – labelled ‘1’ on the Hero’s Journey centres around the ‘Refusal Of The Call’ and ‘Meeting The Mentor’ stages before the Hero crosses the threshold (i.e. jumps off their current S-Curve) into the Campbell’s ‘Special World’. Crossing The Threshold is always a daunting cliff-jump into the unknown. The job of the Mentor is to tell the Hero that it will be all right because they, the Mentor, has already been there, and that the Special World is the only sensible way forward. The job of the Big Five Mentor, on the other hand, is to stop the Hero from crossing the threshold. Partly because the Big Five Mentor has probably never crossed the threshold (unless you count inviting themselves, vampire-like into your ordinary world) before and would quickly reveal they don’t know what they’re doing. And partly because they’ve learned that they can help make the Hero feel better – at least in the short term – by explaining in comforting and convincing ways why it’s not necessary to jump off any cliffs any time soon. What the Hero will see instead are a whole series of seemingly very do-able tiny steps. Do this little thing over here. Stop doing that little thing over there. Get rid of this position. Take three people out of this department. Put them into this new department over here. In so many words, its called tampering. The Big Five Mentor knows how to do it for years if you let them. All the time helping the Hero to Refuse the ever-louder Call. Usually – in the ideal Big Five Mentor world – for as long as it takes for a change in the client’s Senior Leadership Team. Someone brought in to do some crisis management because the Big-Five Band-Aid clearly isn’t working any more. Now everyone in the business is going to cross the threshold. No doubt waving bye-bye to the hanky-waving Mentor, still stood firmly on solid Big Five Consulting Company ground.

The second seemingly perpetual loop occurs later in the Journey. I call this one the Perpetual Design Thinking Procrastination Cycle. It’s the place a lot of Design Thinking teams get themselves stuck. They think they know what the right design (‘The Reward’) is from their Special World (i.e. lab/studio) perspective, but when they try and take the Road Back into the Ordinary World of the customer, they are continually able to find something else to tinker with. Maybe, too there’s an element of knowledge that there’s going to be a Death & Resurrection, and, if they’re not careful, the thing that will die will be the Design Thinking team. Either way, the new thing that’s being designed seemingly never gets to have its opportunity to get past a Tipping Point to become the new ‘Elixir’.

If the first loop is all about not wanting to enter the Special World, this second loop is all about not wanting to leave it. Designers ‘know’ they need to test their solutions in the (Ordinary World) of their intended customers, but they also know the Ordinary World can be quite boring. And, worse still, demanding of some tough commercial decisions. So any opportunity to return to the comparatively safe waters of their Special World is adopted with gleeful arms.

They say awareness is half way to a solution. Having watched the Big Five consulting companies operate for over three decades now, I’m pretty certain they’re confident its not. As for the Design Thinkers and their rather newer perpetual loop, I suspect a lot of them – the growing army of Design Thinking Authors – are desperately learning as fast as they can from the Big Five consulting companies how to ensure their own trains remain full of gravy.

Good job I’m not cynical about these things.

On 9 September 2014, the band U2 gave away their new album ‘Songs Of Innocence’ free to 500 million iTunes subscribers. No doubt sponsored by Apple, the gesture rapidly backfired on the band and, within a month, singer Bono was forced to organise a press conference to apologise for the incident. Listening to him speak, it was still pretty evident that he didn’t know what the band had done wrong. It was an apology of sorts, but then again any apology containing the word ‘if’ isn’t really.

In Bono and clearly Apple’s mind, the gesture was a no-brainer success story. What customer wouldn’t want a free album? From one of the most popular bands on the planet no less.

But the gesture disobeyed two and likely three of the First Principle foundations of human behaviour. People make decisions for good reasons and real reasons. The ‘real’ reasons are the ones that come from our emotional brain. That part of our thinking focuses around four Principles: we want Autonomy, we want Belonging, we want to feel like we’re Competent and we want to do things that have Meaning. ABC-M.

The innovation rule is that all four – ABC-M – all need to be moved in an improving direction.

If U2 had been aware of this rule, they would quickly have seen that:

a)    By installing the album onto customer’s iPhones without permission, they demonstrated that they, the band, were in Control and the customer was not.

b)    U2 is a very polarising band. Lots of people love them. Even more feel the opposite. If you love U2 and they give you their new album, your sense of allegiance and Belonging to the U2-tribe is likely to go up. If, on the other hand, you really don’t like U2 and they force their new album on your phone, it comes across like they’ve tried to force you to Belong to a tribe you’ve already decided you want no part of. Forcing tribal solutions on non-tribe members will only ever have one effect: it will unite the non-tribe members against you even more.

c)    Then, if getting the A and B wrong, as if to twist the knife they’d stuck in everyone’s stomach, when the majority of the 500 million tried to delete the album from their accounts they quickly noticed it wasn’t easy. Now hundreds of millions of customers also felt incompetent.

Three years later, the band are still taking stick for their Song of Naivety. Or was it Songs of Meglamania?

ABC-M all need to get better. It’s not rocket science.

Il faut souffrir. Supporting any football club involves an emotional rollercoaster ride. With some clubs the highs are higher. With others the lows are lower. Sometimes, as in the case of my team tangibly so. Sometimes the lows are just dumb frustrations. Like the fact that, this season, my team is beating all the top clubs and losing to all the bottom ones. To the point where, because we were scheduled to play a relegation-zone team today, I was 100% confident that we would lose.

Part of that confidence, these days comes from running our PanSensic software. Every week, our manager gives a press conference, and I’ve started to put the narrative into the software. This is what it told me this week:

The important thing to look out for is the high ‘Innocence’ score in the Archetypes dial. This score is only high during the press conferences prior to playing opponents at the bottom of the league. When we’re about to play the top clubs ‘Innocence’ is almost zero and the ‘Pilgrim’ and ‘Warrior’ scores go off the end of the scale.

Against the big clubs, the manager seems to know its going to be a tough day. When we’re about to play one of the bottom clubs the message usually involves phrases like ‘no complacency’ and – this week’s humdinger, ‘we are not naïve enough to think it will be that simple’.

I don’t think anyone from the Club is ever likely to read my insignificant nonsense, but I kind of wish they would. Maybe then the manager would realise that the human brain doesn’t process words like ‘no’ and ‘not’. When we tell someone not to think of pink elephants, so says the cliché, its almost impossible to avoid thinking about pink elephants. We’re not wired to process negatives. So, ‘no complacency’ is heard (by the team as well as everyone else) as ‘complacency’. Likewise, ‘not naïve’ is heard as ‘naïve’.

Then there’s the killer word ‘that’. It’s the word that reveals the manager also isn’t processing the negative. He’s trying to tell everyone not to be complacent and to not think the game will be simple, but he’s already convinced himself that its okay to be complacent and that the game will be simple. Put simply, we lost today because of what he said on Thursday.

During the eighties and nineties it was rare to visit a client where there weren’t Dilbert cartoons all over the walls. The joke was funny then. Today I see less of them on the walls. I don’t know whether that’s because management have banned them, or because Baby-Boomer and Generation X workers don’t like being reminded that they’re still living in the same Kafka-esque nightmare today that they were thirty years ago. Either way, you sometimes still have to love a Dilbert cartoon.

This one is a particular favourite. I’m in the contradiction business, so I guess I have to love it. Even better, this strip describes a great trilemma. A lot like the ‘cost, quality, schedule’ problem and the ‘which two would you like?’ question, Alice’s response to the Communication, Integrity and Teamwork triad defined by management is a classic ‘two out of three’ solution.

If Alice had used TRIZ, she might have re-framed the problem to look something like this:

The Contradiction ‘Bubble Map’ is in effect a way of drawing trilemmas. The physical contradiction – ‘I should be honest and I should not be honest’ – being the part of the trilemma Alice was unable to solve.

If we map the problem onto the Contradiction Matrix we ought to be able to tap into the solutions used by others to solve the whole problem. When we do this, the ‘three-out-of-three’ solution to the Communication, Integrity and Teamwork trilemma is likely to make use of these Inventive Principles:

   7 – Nested Doll

 13 – The Other Way Around

   2 – Taking Out

 17 – Another Dimension

All of which, suggests that Dilbert and Wally in this case – rarely – are the ones that hold the key to the ultimate solution. Damn, Scott Adams is good.

According to our research last year’s US election was pretty much won on the basis of nine syllables. Whatever your politics and whatever you think about the morality of spending money to influence how people vote, I think its fair to say that a certain level of genius had been at play.

The nine syllables came in the form of three three-syllable phrases that Donald Trump managed to use in nearly all of his campaign speeches. In many they were turned into crowd-chants.

Drain The Swamp. Build The Wall. Lock Her Up.

They say a picture speaks a thousand words. Here were nine words that each spoke a thousand pictures. Ah, sweet Resonance.

Whoever was responsible for the genius, clearly doesn’t seem to be in place any more.

The person that came up with Rocket Man got the three syllables part right but, right from the get-go it sounded more like a pretty cool compliment than the belittling jibe it was intended to be. Recognising the mistake, some bureaucrat quickly tried to modify the phrase to ‘Little Rocket Man’. This didn’t help. Ten more minutes of thinking and they might just have come up with ‘Rocket Boy’. That would have done the intended job far more effectively. Albeit at the possible risk of nuclear Armageddon.

Things didn’t go much better this week, when Drain The Swamp got down-rated to ‘Spread the Swamp’. When the bureaucrats realised those words didn’t work, they switched to ‘Move The Swamp’. That was vaguely less clumsy, but still utterly missed the killer instinct of the original. And the ultimate election winning aphorism was now turned into an embarrassing climb-down.

Amazing how smart people can work out the DNA of election success and then ten minutes later completely screw things up.

Single syllable words. Three word phrases. Emotive verb. Thousand-pictures object. Simple.

I can feel a new SI mission statement coming on…

One of Facebook’s earliest executives has said the social network is “destroying how society works” and that he feels “tremendous guilt” about his work. Chamath Palihapitiya, who joined Facebook in 2007, accused it of “programming” its users and said he no longer uses the website or allows his children to access it. “It literally is at a point now where I think we have created tools that are ripping apart the social fabric of how society works,” he told an audience at Stanford University. “We are in a really bad state of affairs right now in my opinion, it is eroding the core foundations of how people behave by and between each other.”

Daily Telegraph, front page, 12 December 2017

Society makes progress when contradictions get identified and solved. The bigger the contradiction, the greater the progress potential. In this context, when two goliaths of the modern business world find themselves embroiled in a very public argument we perhaps get to see a really big contradiction.

Zuckerberg says that Artificial Intelligence is good; Musk says it is bad. Who’s right and who’s wrong? Or are they both right? Or both wrong?

What we do know for certain is their argument centres around a contradiction: we want AI and we don’t want AI. AI will eventually help society to solve an awful lot of its current problems; AI today is probably doing more harm than good. And therein lies a clue. Two clues. Eventually and today.

Once we understand what we’re doing, then we open up the possibility for AI to be our best friend rather than our worst enemy. We solve the contradiction, in other words, in time (eventually…) and on condition (…once we know what we’re doing).

What Elon Musk seems to understand that Mark Zuckerberg clearly doesn’t is that the vast majority of today’s AI solutions – and especially those being deployed by Facebook – have not been coded with an understanding of complex systems. Once we accept that a system is complex, the only sensible hope of affecting it in a positive manner is to understand behaviours within the system at a First Principles level. Elon Musk represents the epitome of First Principles thinking. Mark Zuckerberg is, as far as I can tell, the precise opposite. He naively believes that by connecting everyone you create one big happy family. The reality is that when people are motivated by Autonomy, Belonging, Competence and Meaning (the First Principles of human behaviour), any attempt to connect everyone ends up connecting no-one. For every tribe we connect to become a member of, a dozen other tribes that oppose what we think appear.

Zuckerberg, in other words, might be right about AI in the long term, but right now, Musk knows that Zuckerberg is the very person preventing AI from going beyond its current manifest dysfunctions.

There aren’t too many advantages to being an aerodynamicist, but one of them is not having to sweep up fallen leaves in the Autumn. Even when we had a garden the size of a postage stamp, it was a pain. Now we have two-acres and look after a dozen or so hundred-and-fifty-year-old trees, the task has, in previous years, been, how shall I put it, onerous.

Last Autumn, I figured it was time to apply a little TRIZ to the problem: how could I get the leaves to collect themselves?

It didn’t seem too likely, but on the other hand a quick search for free resources highlighted a couple of big ones. Firstly, the prevailing wind direction served to blow all the leaves off the trees and towards the house. Secondly, the shape of the house lends itself to creating an aerodynamic vortex that I could use to coax the leaves into a ‘trap’:

I’d noticed some kind of naturally propensity for leaves to find themselves entering the vortex in previous Autumns, the problem was it didn’t happen as fast as I’d like and when it did happen, the leaves tended to accumulate in front of the door. Which in turn meant that when the door was opened, the leaves tended to migrate into the house.

So what to do? How to increase the vortex flow rate? And how to subtly re-direct the leaves so they entered the vortex but stayed away from the door?

Another search for resources…

Realisation number one: changing the places the cars are parked changes the vortex entry. Park the cars differently and the vortex trap works better.

Realisation number two: outdoor plants. Judicious placing of plant pots lowest pressure point of the vortex and the leaves accumulate around the pots rather than the door.

Add a couple of days of experimental adjustment of car and pot placement and hey presto, we have self-collecting leaves.

Now all I need to do is wait a couple of days for the new mountain to appear, rake them into the wheelbarrow and take them down to the compost bin, then wait another couple of days.

A multiple hour chore now becomes a 20-minute game. Autumn? My new favourite season.

It feels like a long time ago when I wrote the Systematic (Software) Innovation book. One of the main, albeit inadvertent, themes of the book was to highlight a dichotomy that, now we all live in the first stirrings of a Big Data tsunami, seems to be getting worse rather than better: software engineers and architects, the book described, are simultaneously the people most likely to determine how society evolves in the coming decades, and also the people least well qualified to take on such responsibilities.

Last week I came across an online article bearing the ominous title, ‘Machine Learning Is Racist Because The Internet is Racist’. If I ever needed a way to exemplify the dichotomy, I think this might just make it into my Top Five.

The article represents the sort of complete abdication of responsibility now becoming quite typical of the ICT industry. An industry that still – two months after it hit the media – hasn’t done anything to tackle the problem that recommendation algorithms now teach people how to make bombs. ‘People who bought this product also bought…’ and hey presto, everyone knows how to make their very own explosive device. This the same industry that – they tell the media – can’t be blamed for providing a conduit for terrorist communications.

At the crux of the issue here is Artificial Intelligence. Plenty of the former, not so much of the latter it seems. There’s perhaps a telling irony in the fact that the software geeks effectively try to tell us all that their AI algorithms can’t be blamed for mimicking the content of what they find on the internet. The irony being that if they are able to declare a significant enough amount of internet content is ‘racist’, how come they weren’t able to create a racist-comment-detecting algorithm and thus exclude such trash from the data they use to train their algorithms?

Sure, the Internet might be ‘racist’ right now. But in no way does that give AI professionals a ‘get out of jail free’ card excuse for creating racist AI. It’s not rocket science.

Or maybe it is. Not in the offending blame-dodging article under examination here, but I’ve heard from other ICT ‘thought leaders’ that any racism (or any other kind of ‘ism) detection algorithm cannot be their responsibility, because who are they to decide what is and what is not racist? Only the politicians can tell us what the rules are, they claim. My confidence that our politicians can help solve the problem is frankly quite low. Not so much because the problem requires any rocket-science per se, but rather that it requires someone to come at the problem with a contradiction-solving mindset.

I suspect every person on the planet is guilty of at least half a dozen ‘ism-crimes’ during any given day. I can be confident of this because spending a couple of hours watching any trending ‘controversial’ topic on Twitter quickly reveals the rapid appearance of a quite staggeringly broad spectrum of responses. Every single respondent sits somewhere along an -ism spectrum. From one day to the next, their position might shift, as might those of every other person wanting to join the conversation. The fact this spectrum exists and that it might be dynamic, however, does not mean the job of the AI algorithms (or their programmers) is to define ‘the’ point along the spectrum at which ‘on average’ the boundary between racist and not-racist sits. Making decisions based on any kind of average is a pretty dumb thing to do in any kind of complex environment.

The only meaningful design response in this kind of dynamic spectrum situation is to solve the contradiction between the two ends of the spectrum: make people at each extreme ‘happy’ and everyone in the middle is also happy. If every person on the planet draws the racist/not-racist boundary somewhere different, the AI needs to take into account that personal boundary when delivering content to that individual.

Solve one contradiction, of course, and the next one inherently appears in its wake. Every person on the planet is entitled to hold their own opinion about where the racist/non-racist (or sexist/non-sexist, etc) boundary exists for them personally, but by the same token they are absolutely not entitled to hold their own truths. Truth-wise, then, the new problem becomes whether it is ever possible to objectively determine what racism is and is not? This too would appear to require a dynamic way of thinking. I’ve heard several comedians making jokes around the phrases ‘different times’. What was apparently ‘acceptable’ in the 1970s, clearly appears not to be today. Whether that makes it appropriate to judge historical ‘misdemeanors’ according to today’s norms is yet another contradiction to be solved.

But again, it is ‘merely’ a contradiction. Systematic (Software) Innovation was intended to help software engineers – the future rulers of society, right? – to identify and resolve such conflicts. If any of them was in any way smart, they’d be writing AI algorithms that automatically identified society’s conflicts and conundrums. If they were smarter still, they’d be writing self-evolving code that also helped solved these conflicts and then automatically identified the next contradictions. More fool them if they haven’t started the journey yet. The slower they are to the game, the further ahead PanSensic gets. AI gets intelligent by asking intelligent questions, and intelligent questions start by measuring what’s important rather than what’s easy to measure. It’s very easy to measure racism. Or sexism. Or any other kind of ism. (We know because we do it every day.) Real intelligence is knowing why we’re measuring it. And what contradictions we’re intending to solve when we do find it. Perhaps our next PanSensic lens should be one for detecting software engineers abdicating their moral and ethical responsibility to think before they code. I don’t think that’s rocket science either.