I started and stopped this post four times as I tried to find the right way to open. Eventually I got tired of searching and figured it was easiest to just jump off the note I wrote to myself in Google Keep after the idea popped into my head:
That might not make so much sense (yet), but like any good note it captured enough of the concept that I remembered what I was thinking when I wrote it. I jotted it down as I was prepping for a webinar I did last week offering up some predictions for marketing in 2019. I was getting worked up (as I’m wont to do) about how much it bugs me when everyone in marketing talks about AI as if they have any idea what it really means or the implications.1 Someone asked why it bothered me so much and my answer, which kind of just poured out, was that once everyone starts agreeing about something (and saying it endlessly) it becomes less and less meaningful. This is not just some soft definition of the word meaning, though, it literally has less information.
Literally how?
A few months ago I wrote about Claude Shannon and information theory. Shannon wrote a seminal paper in 1948 called “A Mathematical Theory of Communication“. In it he defined the measure of information as, effectively, its unexpectedness (he called it entropy). The more random, the more information. This is precisely what bits measure (you can think of it as the number of yes/no questions it would take to get to the answer). What happens when you compress a photo? You take away the randomness. That’s why otherwise complex surfaces like sky or skin might come to look a bit pixelated: The compression algorithm is constraining the number of hues available in order to bring down the entropy (and therefore the file size) of the whole photo.
What does that mean for marketing buzzwords?
Well, as everyone starts to say the same thing and continue to offer little behind it, it becomes more and more expected and, therefore, starts to carry less and less information. When people layer on top of those buzzwords with real examples or alternative ideas, they return some randomness (and therefore information) to the concept. At their best, marketing contrarians are attempting to breathe some life into words and ideas that have otherwise lost their information content.
I don’t really like to think of myself as a contrarian because I think that often carries with it some notion of being different for the sake of being different (and trolling). Rather, I think if everyone is following one strategy or idea, the value of being the next person to jump on board is incrementally less (especially when that idea is poorly defined/understood). In a way it’s like an anti-network effect.
Back to Hinkie’s letter. It was leaked and provided an amazing view into the psyche of someone who was willing to be a pariah. In it he paints an interesting picture of the connection between contrarianism and traditionalism.
Here he is on contrarianism:
To develop truly contrarian views will require a never-ending thirst for better, more diverse inputs. What player do you think is most undervalued? Get him for your team. What basketball axiom is most likely to be untrue? Take it on and do the opposite. What is the biggest, least valuable time sink for the organization? Stop doing it. Otherwise, it’s a big game of pitty pat, and you’re stuck just hoping for good things to happen, rather than developing a strategy for how to make them happen.
And on traditionalism:
While contrarian views are absolutely necessary to truly deliver, conventional wisdom is still wise. It is generally accepted as the conventional view because it is considered the best we have. Get back on defense. Share the ball. Box out. Run the lanes. Contest a shot. These things are real and have been measured, precisely or not, by thousands of men over decades of trial and error. Hank Iba. Dean Smith. Red Auerbach. Gregg Popovich. The single best place to start is often wherever they left off.
Let’s bring it back to buzzwords.
So basically Hinkie’s argument is that the most appropriate way to be a contrarian is to also be a traditionalist: To be a respectful student of the underlying principles while also constantly probing and questioning whether they still make sense. One of the things that surprises me about the marketing industry is how often people miss this tradeoff. In an attempt to play the contrarian they shun traditional wisdom, but at the same time they repeat empty phrases and approaches at every conference that will let them on stage.
I actually think one of the reasons Byron Sharp’s book How Brands Grow has picked up as much steam as it has is because it strikes a good balance between these things. It’s a contrarian take (loyalty shouldn’t be a goal because it’s an outcome) but at the same time it’s deeply rooted in some traditional marketing ideas (marketshare, reach, and creativity to name three). This is a tough balance to strike, but when someone hits the spot is has the opportunity to really resonate.
Unfortunately, most of the time the industry misses the market by a lot. What we end up with a bunch of anti-historical/anti-intellectual slogans that get repeated ad-infinitum. It’s lots of words and little information.
Footnotes:
Here’s the notes I had for the question: “Let me start by saying that I predict in 2019 marketers will continue to talk about AI and ML interchangeably with no idea what the words mean. (I’m particularly salty about this.) I would broadly see we will continue to see ML become more available as different kinds of wrappers are made available that enables folks to use it in more of their everyday work. This seems to be some of what Microsoft and Google are doing with smart integrations into their work suites. In general, my take on AI/ML is it’s a classic case of Amara’s law, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” In the short term, these things aren’t going to be writing copy and, anyway, that’s not that big a deal. In the long term, the promise of ML is data modeling and coding written by computers, not people. That’s definitely not a 2019 prediction, but it’s the road we’re going down.”↑
I recognize that the word/idea transformation belongs in the buzzword bucket, but if you read about Hinkie and what he did I think it’s a fair use of the word with real meaning. He was a heretic who questioned the most fundamental law of professional sports (“you play every game to win”) and rewrote the path to building a championship contender.↑
It’s been awhile since I did a Remainders posts so I figured I’d throw one together. In theory it’s all the other stuff I didn’t get a chance to blog about. In reality, it’s pretty much everything I’ve been reading that isn’t about mental models/frameworks (and even some of that). You can find previous versions filed under Remainders and, as always, if you enjoy the writing, please subscribe by email and pass around.
Let’s start with some books. Here’s what I’ve read in the last three months (in order of when they were read):
Judas: How a Sister’s Testimony Brought Down a Criminal Mastermind (Astrid Holleeder): Inspired by the New Yorker story by Patrick Radden Keefe about a Dutch woman who eventually testified about her mobster brother, I decided to dig into the English translation. It was a lot more difficult to read than I expected. The New Yorker story, because of length, isn’t able to go into the extensive psychological abuse Holleeder’s brother put his family through. I found it emotionally exhausting about two-thirds into the book.
Countdown to Zero Day(Kim Zetter): As far as I know this is the definitive book on Stuxnet, the digital weapon that targeted the Iranian nuclear facility at Natanz.
Complexity: A Guided Tour (Melanie Mitchell): Easily one of my favorite books of the year. I’ve read lots about complexity theory, but nothing that pulled all the various strings together so well. (This also helped send me down a deep physics rabbit hole that I’ve yet to emerge from.)
My Holiday in North Korea: The Funniest/Worst Place on Earth(Wendy Simmons): I really loved the graphic novel Pyongyang and thought I’d give this travelogue a try when I saw it sitting on a shelf at the bookstore. It was a fine book to read alongside some of the heavier stuff I’ve been reading lately.
Remote: Office Not Required (Jason Fried): This book sucked, but at least the Audible narration was slow enough that I could crank it up to 2x speed.
Einstein 1905: The Standard of Genius(John S. Rigden): Like I said, I’ve been falling deeper into a physics rabbit hole, and as part of that I’ve been watching a bunch of physics and math lectures on YouTube. One of the ones I watched was Douglas Hofstadter essentially trying to recreate a talk he once saw the John Rigden, the author of this book, give in 2005. The book, and the talk, are about the ideas behind Einstein’s five papers of 1905 (four of which are considered foundational in physics).
Hit Refresh: The Quest to Rediscover Microsoft’s Soul and Imagine a Better Future for Everyone (Satya Nadella): Like just about everyone, I’m super impressed with everything Microsoft has done since promoting Nadella to CEO. Although this book promises to be about how it’s all happening, it’s about 75% a commercial for Microsoft’s vision for the future (which although it could be right, is not particularly interesting or original).
A Brief History of Time (Stephen Hawking): If you find yourself in a physics rabbit hole, this seems like something worth reading …
Dreamtigers (Jorge Luis Borges): I read about this in the Borges interview book. He basically explained that his publisher asked for a book and so he collected a bunch of poems and stories that were sitting around his house and hadn’t been published and stuck it together.
Okay, onto some other reading, etc. …
This Wired piece about the possibility of a coming “AI cold war” has two particularly interesting strings in it: One is a fundamental question about the nature of technology and its relationship with democracy (put simply: is the internet better structured to support or defeat democratic ideals) and the other is about how China (and the US) will use 5G as a power play (“If you are a poor country that lacks the capacity to build your own data network, you’re going to feel loyalty to whoever helps lay the pipes at low cost. It will all seem uncomfortably close to the arms and security pacts that defined the Cold War.”)
We’ve been having lots of trouble convincing our three-year-old to wear a coat in the cold. Turns out its pretty normal.
The Chronicle of Higher Education asked a bunch of academics for their most influential academic book of the last twenty years. Lots of interesting things to read here.
Benoît Mandelbrot (of fractal fame) is apparently responsible (at least in part) for the introduction of passwords at IBM. From When Einstein Walked with Gödel (which I’m reading now), “When his son’s high school teacher sought help for a computer class, Mandelbrot obliged, only to find that soon students all over Westchester County were tapping into IBM’s computers by using his name. ‘At that point, the computing center staff had to assign passwords,’ he says. ‘So I can boast-if that’s the right term-of having been at the origin of the police intrusion that this change represented.'”
Also from the same book, the low numerals are meant to be representative of the number of things they are. Since that makes no sense, here’s the quote from the book: “Even Arabic numerals follow this logic: 1 is a single vertical bar; 2 and 3 began as two and three horizontal bars tied together for ease of writing.”
A Rochester garbage plate “is your choice of cheeseburger, hamburger, Italian sausages, steak, chicken, white or red hots*, served on top of any combination of home fries, french fries, baked beans, and/or macaroni salad.”
Rahimi believes contemporary machine learning models’ successes — which are mostly based on empirical methods — are plagued with the same issues as alchemy. The inner mechanisms of machine learning models are so complex and opaque that researchers often don’t understand why a machine learning model can output a particular response from a set of data inputs, aka the black box problem. Rahimi believes the lack of theoretical understanding or technical interpretability of machine learning models is cause for concern, especially if AI takes responsibility for critical decision-making.
Uber’s business plan, like that of so many other digital unicorns, is based on extracting all the value from the markets it enters. This ultimately means squeezing employees, customers, and suppliers alike in the name of continued growth. When people eventually become too poor to continue working as drivers or paying for rides, UBI supplies the required cash infusion for the business to keep operating.
So far this is all just NBA news you either don’t care about or already know. So why write about it? Because I can’t deal with the “this guy shouldn’t complain, he is making almost $30 million a year” conversation. Of course there were variations, but the gist is that because you’re an athlete and you (deservedly) get paid lots of money you a) shouldn’t have, or b) shouldn’t voice, regular human feelings (this is, in case you haven’t noticed, a stance also shared by our president).
Since I read Alan Jacob’s book How to Think, I’ve had his answer to this question (or a version of it at least) rattling around in my head:
But that’s because Gladwell [in his Revisionist History podcast episode asking why Wilt Chamberlain didn’t shoot underhand free throws], like many of us, seems to have unwittingly internalized the idea that when professional athletes do the thing they’re paid to do, they’re not acting according to the workaday necessity (like the rest of us) but rather are expressing with grace and energy their inmost competitive instincts, and doing so in a way that gives them delight. We need to believe that because much of our delight in watching them derives from our belief in their delight. (In much the same way we enjoy watching the flight of birds, especially big birds of prey, associating such flying with freedom even though birds actually fly from necessity: they need to eat. And yet we have no interest in watching members of our own species drive to McDonald’s.)
That’s nearly perfectly expressed. We need to believe in their delight because of our delight and we can’t stand to think we care more about winning or losing than they do. Or, as my friend Jeff at DaBearsBlog put it, “fans think it should be honor to play pro sports because they all wish they could.” The thing here is it’s still just a job. If we zoom ourselves out for a minute and replace athlete with employee and professional sports league with desk job, we start to see things more clearly. If you hold a senior role at a company there are many in the organization who feel the same way about you as you feel about athletes: That you have it easy and if they could just be in your position everything would be right in the world. Of course you don’t and it wouldn’t.
What’s more, while some of us may have found a way to practice our passion at work (I feel pretty lucky in that regard much of the time), it’s only natural to have moments where we don’t feel like doing the things required of us or can’t find the excitement we know is there somewhere. It’s a normal part of doing the same thing everyday, which is what it means to be a professional at anything. (An interesting analog is the surprising number of startup founders I’ve met who are completely clinical about the industry in which they start their companies. They don’t need to care about the space as long as it offers the right market conditions.)
Getting back to the start, there are two main things people say about professional athletes that get under my skin: They’re rich so they should get over it and they should have known when they signed a contract. Let’s take these one at a time.
They’re rich so they should get over. While it’s true they make an unbelievable amount of money, that can create a whole new set of things to deal with that many of us can’t imagine. There’s lots of documentation that suggests after a certain point money stops making you happier. What’s more, they surely will eventually get over it, but sometimes that takes some time (try to remember back to how effective it was when someone told you “you’d get over it” after what felt like a momentous breakup). DeMarcus Cousins, a superstar NBA player who has earned around $80 million in his career but was forced to take a low-money short-term contract this season after getting hurt put this perfectly recently. When asked whether he was nervous through the free agency process, Cousins answered, “Have you ever been unemployed? Were you nervous then? Alright, that answers the question.”
They should have known when then they signed a contract. Here, again, it’s easy to turn back to all of our regular job experience. Most of us in America are at-will employees, meaning we can be fired at any time for essentially any reason. Despite the fact that we all sign an at-will employment agreement, people are frequently shocked when they’re fired, whether there is good reason or not. Do we wonder why they’re so surprised? Of course not. Sure DeRozan wasn’t fired, but he can still be surprised and sad and frustrated that it happened.
Last, but not least, there’s a much bigger story here about professional sports, money, power, and race. The NBA is a very progressive league, but even there you can’t get away from fan loyalty sitting with teams instead of players. And I’m not advocating it should, that’s the fun of watching sports: You live and die with your squad (there’s a famous Seinfeld joke about rooting for laundry). However, we can enjoy the game and our teams while not questioning the humanity of the athletes who make the whole thing possible. The NBA has made huge strides in becoming a player-centric league, but fan conversations are still lagging behind.
Annnnnd here’s my 10th blog post of the month. Hit my goal. (Might even make it to 11 if I have a burst of inspiration.) Thanks again for reading and encouragement. I’m going for 10 again in May. As usual, feedback welcome and you can subscribe by email here (for those of you reading this via email, thanks and sorry about the wasted words, it just emails exactly what I put on the web).
It’s time for another Remainders. This is my chance to share all the stuff I didn’t get a chance to blog about this week. As for me, I’ve been back and forth from San Francisco again. I wrote one long pieces this week on satisficing and the two strategies of marketing. On the reading front I finished up Artemis, which was easy, but nowhere near as good as The Martian. New book is the Master Algorithm, which is all about the different approaches to machine learning. It’s a bit painful at times, but I’m almost to the other side. If you’re interested in machine learning I’d highly recommend this post from Andrej Karpathy on Recurrent Neural Networks.
Black infants in America are now more than twice as likely to die as white infants — 11.3 per 1,000 black babies, compared with 4.9 per 1,000 white babies, according to the most recent government data — a racial disparity that is actually wider than in 1850, 15 years before the end of slavery, when most black women were considered chattel. In one year, that racial gap adds up to more than 4,000 lost black babies. Education and income offer little protection. In fact, a black woman with an advanced degree is more likely to lose her baby than a white woman with less than an eighth-grade education.
By rendering a not-too-distant future, Kubrick set himself up for a test: thirty-three years later, his audiences would still be around to grade his predictions. Part of his genius was that he understood how to rig the results. Many elements from his set designs were contributions from major brands—Whirlpool, Macy’s, DuPont, Parker Pens, Nikon—which quickly cashed in on their big-screen exposure. If 2001 the year looked like “2001” the movie, it was partly because the film’s imaginary design trends were made real.
The show offers a clever finger trap for critics. Call a hit dangerous and you imply that it’s really quite sexy. And, in fact, the seventh episode, which I won’t spoil, pulls a daring switcheroo, one that may offer a new lens through which to interpret Roseanne’s behavior. It’s not enough. The reboot nods at complexity without delivering—there are good people on many sides, on many sides. If you squint, you might see the show’s true hero as Darlene (Sara Gilbert), a broke single mom forced to move in with that charismatic bully Roseanne. But, if that were so, we might understand Darlene’s politics, too. We’d more fully feel her pain and also that of her two kids, transplanted to a place they find foreign and unwelcoming.
Tsudonku: “Acquiring reading materials but letting them pile up in one’s home without reading them.”
Genchi Genbutsu: “This is a Japanese phrase meaning ‘go and see for yourself’, which is a central pillar of the Toyota Way, the famous management system adopted by the Japanese car company.”
This is where the promise of artificial intelligence breaks down. At its heart is an assumption that historical patterns can reliably predict future norms. But the past—even the very recent past—is full of words and ideas that many of us now find repugnant. No system is deft enough to respond to the rapidly changing varieties of cultural expression in a single language, let alone a hundred. Slang is fleeting yet powerful; irony is hard enough for some people to read. If we rely on A.I. to write our rules of conduct, we risk favoring those rules over our own creativity. What’s more, we hand the policing of our discourse over to the people who set the system in motion in the first place, with all their biases and blind spots embedded in the code. Questions about what sorts of expressions are harmful to ourselves or others are difficult. We should not pretend that they will get easier.
I liked this definition of speed versus velocity from Farnam Street: “Speed doesn’t care if you are moving toward your goals or not. Velocity, on the other hand, measures displacement over time. To have velocity, you need to be moving toward your goal.”
On the other end of the sporting spectrum, the Times got a hold of tapes from a meeting between players and owners and I can’t imagine it making the NFL look worse. Here’s a small example from Buffalo Bills owner Terry Pegula: “For years we’ve watched the National Rifle Association use Charlton Heston as a figurehead … We need a spokesman.” These guys are such bad news.
I've been working with HTML for about 20 years and just today I realized that Radio Buttons refer to actual radio buttons, where only one can be pressed at a time. pic.twitter.com/QtUAVaBIpM
Yesterday I was reading an article about the first female assistant coach in the NBA in the latest issue of the New Yorker. The piece was moderately interesting and not particularly worth sharing here, except for one paragraph, and really just one sentence within it (emphasis mine):
Because of their success, the Spurs have not been eligible for the highest picks in the draft. Instead of relying on college superstars, they have built their team through some crafty trades and by pushing their young players to the limit. They scout top international players—like Parker, from France, and Manu Ginóbili, from Argentina—and sign N.B.A. veterans like Pau Gasol, from Spain, who is thirty-seven but can anchor a defense and move in a way that creates space on the floor; they also, as in the case of Leonard, hone the raw athletic talent of less experienced players. When the Spurs are at their best, the ball moves fluidly and freely. Duncan, who retired in 2016 and was perhaps the least flashy major star in the N.B.A., was emblematic of the team’s unselfish style. On a given night, almost anyone on the roster can be the leading scorer.
Now obviously this is one tiny point in a giant article. But it happens to be an article about a subject I’m kind of obsessed with (the NBA) and that’s pretty rare for a magazine that covers a huge diversity of topics.
Which brings me to the title of this post: The Gell-Mann Amnesia Effect.
Named after famous physicist Murray Gell-Mann, the Amnesia Effect was coined by Jurassic Park author Michael Crichton to describe the act of feeling skeptical as you read a magazine or newspaper article about an area in which you have expertise and then completely forgetting that skepticism as you turn the page and read about something you know less about. If they could get it so wrong for one, why don’t we assume they could get it so wrong for all?
Briefly stated, the Gell-Mann Amnesia effect is as follows. You open the newspaper to an article on some subject you know well. In Murray’s case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward — reversing cause and effect. I call these the “wet streets cause rain” stories. Paper’s full of them.
In any case, you read with exasperation or amusement the multiple errors in a story, and then turn the page to national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page, and forget what you know.
The Gasol slip up put me in a funny state with my favorite magazine: What misportrayals, however small, do I take for granted when I read about topics like Catholicism or pharmaceuticals? What bothers me even more is that I feel some guilt even writing this. In this moment of conversations about fake news, questioning a publication that is unquestionably a beacon of extraordinary journalism (and fact-checking!) feels like adding fuel to a fire that’s trying to burn down my house.
But reading with skepticism is something we should all do, not because we don’t trust the publication, but because it’s our responsibility to be media literate and develop our own points of view. The biggest problem I have with the conversation around fake news is that it makes it more difficult to legitimately critique the media, something we should all be doing more often.
In the meantime, I’m going to hope the New Yorker stays away from basketball …
1 Because I can’t go through this without making it clear: The Gasol thing is an opinion and not fact and some might argue that the act of being a center makes you a defensive anchor. I spoke to a friend who is a Spurs fanatic and reinforced my raised eyebrow reaction with a “Umm hell no” to the label applied to Gasol.
