Tag: google

don’t be evil

~ ginsu ~ Leave a comment
B42

“Don’t Be Evil.” 

If you recognize this as Google’s former corporate motto, you probably regard it as a broken promise. But arriving too quickly at this judgment misses the lesson of the journey. It may be true that we now live in a tech dystopia created at least in part by those who once proclaimed, “Don’t Be Evil.” But in the beginning, that motto contained a magnetic True North that once meant something, that still means something, something that is awaiting our rediscovery. 

So before memorializing “Don’t Be Evil” as a broken promise, we must remember what it once meant.

We have to remember the time before the first widespread criticism of this mantra, before the semantic noodlers complained that it is impossible to define what “evil” means. See, the thing is, before this criticism was widely shared, it wasn’t relevant. It wasn’t relevant because the real audience for “Don’t Be Evil” already knew what the phrase was supposed to mean.

The real audience was undoubtedly the employees of Google at the turn of the millennium, when either Buchheit or Patel (depending on the storyteller) first proposed this as the company’s motto. Google had fewer than 250 employees at the time. “Don’t Be Evil” was a phrase that was easily understood by not only those 250 employees, but also by all of the company’s potential employee base. Yep, I’m claiming that every person who had the qualifications to be hireable by Google at that time (1999-2001) would easily understand the basic meaning of Don’t Be Evil.

See, if you knew enough about computing in those days to be employable at Google, then you grew up in technology watching IBM lose to Microsoft, then watching Microsoft crush Apple, and then watching the government strangle Microsoft. And then you got to enjoy watching Google beat the crap out of Microsoft. It’s just human nature to watch all this and make it into a morality play, with extremely domain-specific notions of “good” and “evil.”

When the government hampered Microsoft in the ’90s, that was a fair comeuppance for an abusive player, just as had happened to IBM in the ’80s when Microsoft was coming up. Small new companies innovate into the spaces left by the decrepitude of large old companies. The cycle of life applies to all of us, businesses too. In business, as in life, that cycle plays out in predictable patterns. And as humans, we love telling ourselves a story about our patterns. And to be compelling, our stories must have good guys and bad guys, good and evil. “Don’t Be Evil” is a morality play, and it is just a fiction, but still, these notions of good and evil move us – especially when we’re deciding where to work and how to win competitive battles.

So IBM vs Microsoft, Microsoft vs Apple, Microsoft vs Google – that was the drama that played out in information technology at the time, and our notions of “good” and “evil” were aligned with the prevailing morality play that everyone knew as orthodoxy, even if they disagreed with it: Microsoft was the bad guy, Apple was awesome and cool before MSFT used monopolistic advantages to crush them (this was before the Second Coming of Jobs). Microsoft was Evil. Google was Good.

So in this morality play, “evil” means, basically: using “business techniques” instead of superior technology to win. Don’t Be Evil simply means: win with technology, not with business techniques. 

“Business techniques” include perfectly legitimate and absolutely necessary decisions and deals around pricing, packaging, and distribution. But that’s just the bare minimum. The expanded world of business techniques gets pretty gray pretty fast, and eventually you end up where we are today: dark patterns that manipulate users, platform rent-seeking, externalization of business costs into the community, lobbying and other political manipulation. I don’t really like calling these things “evil,” but it’s fair to say that these are the tactics and methods of mature businesses, and they are not what successful startups do.

I worry that the tech world has been so dominated by the usual BigTech suspects for so long now that entrepreneurs have forgotten the difference between Good and Evil. But no matter: the world doesn’t need to remember because the truth will out: for the first time in a long time, nearly all the BigTech companies are grappling with disruptive technologies that they do not understand. When there is this much disruption in the air, fancy business techniques become less valuable, and a True North for product development becomes far more valuable. For the first time in a long time, opportunity is everywhere, all incumbents are vulnerable, and all startups have this one incontestable upper hand: Don’t Be Evil is a winning strategy, not an empty corporate motto.

The Morality of Ads and The End of Zuck

~ ginsu ~ 1 Comment

The “An Open Letter To …” format has always struck me as inescapably self-aggrandizing in a particularly duplicitous way. The explicit presumption is that the addressee will actually read the letter and care about the advice and admonitions within, when in fact the entire exercise is so transparently a cri de coeur that serves only the writer’s need for attention.

Nevertheless, I have to admit that I’m writing this post for one person, and one person only. If I could send this to him directly and be sure that he would take it seriously, I would simply send it to him. If there were no chance of him ever reading this, I wouldn’t bother writing it. However, Facebook tells me that my social distance to Mark Zuckerberg is quite short, so it’s possible that someone that Mark takes seriously will send this to him. I feel compelled to write this silly letter in this annoying format, because the future of the free world is at stake.

Dear Mark,

At this point, I hope you are past the point of denying that you are in fact The Leader of the Free World. This honorary title has traditionally (in our myopic nation) gone to the President of the United States, but the current occupant of the White House explicitly denies this “globalist” worldview, and implicitly disqualifies himself with his statements and actions. If there is such a thing as a leader of the free world, you’re it. Sorry.

Surely you already know what I’m going to write about here, but you don’t know why you should listen to me, so let me start with that. I am the only person in the entire world who (a) has faced a problem of the kind and magnitude of the one you face today, (b) has hands-on experience in implementing solutions to this problem, and (c) is willing to tell you all about it.

In 2010, I was hired to lead Product Management for Ads Policy at Google. This was an odd role: Policy isn’t thought of as a Product problem; it seems more like something that might be addressed by legal or operational or PR functions. But Google recognized that they had a serious problem, and felt that a product approach to this problem was required, in addition to all the other approaches.

By the way, the existence of this problem at Google was partially albeit indirectly your fault. Google had historically implemented Ads Policy through sales ops, which was led by Sheryl. You lured her away at a critical time, when Google was reaching yet another level of scale and impact, and the leadership vacuum in sales ops resulted in many small cracks in an implicit system of rivers and dams of policy issues. It was inevitable that one of these cracks would burst a dam somewhere, which is a pleasingly vague way of glossing over the numerous ads policy problems that led to the DOJ imposing a $500 million fine on Google. As you might imagine, a half-billion dollar fine tends to sharpen one’s attention.

So I had a Facebook-scale problem … but bigger. Facebook is arguably more important now, but Google still has more of everything: more users, more data, more dollars, more decisions. Billions of users, trillions of ads, the tiniest fractions of a second to make decisions: how do you decide what ads NOT to show? The clueless commentariat think it’s easy, but I know what it really takes.

I also know there is almost no margin for error. You can get it right 99.999% of the time, but for every billion results per day, that means you got ten thousand wrong that day. Not a lot of businesses can survive getting ten thousand decisions wrong every day. Each one of those errors is not only potentially ruinous, but each one can seem almost impossible to debug. When something gets through all of your best efforts, how do you know what went wrong?

So yeah, I think I understand your problem. Here’s my advice …

Question Your Attitude

Obviously, I don’t know what your attitude is, I can only make assumptions from your public statements, and I understand that there are many legitimate reasons why we must make public statements that don’t reveal our true attitudes.

So at the risk of making obnoxious assumptions, your attitude towards this problem can be summed up as: “Well, it’s very hard. I’m uncomfortable making these decisions.”

Having had the same problem, I can say that it wasn’t any harder than other hard problems. I mean, of course it was a challenge, but I’m not sure it was any more challenging than dozens of other initiatives at Google. I don’t mean that we solved it perfectly, clearly there are still challenges, but addressing these problems is just another part of the business, not some special, impossible area.

I understand why you dream of a dynamic system that reflects different values for different communities, but that is an abdication of responsibility. I also understand the enormous business advantage in claiming that Facebook is just a “neutral platform.” I happen to think that it’s high time that all tech companies stop advancing the fictions that allow them to continue to benefit from the legal sacred cow that feeds tech, but it’s not necessary for you to admit that publicly or privately. You just have to understand that you really have a business problem and you have address it with a straightforward business attitude.

Your business is ads. The funny thing is, lots of people hate ads, and ad businesses justify ads to users by saying that ads fund the great experiences that users get for free. But it’s so much more than that: Ads are the conduit for the only morality that exists when we cling to the idea that we run neutral platforms.

You can blame “the algorithm” for a lot of things that you claim weren’t the result of human judgment. The Algorithm – the holy algorithm, the all-powerful, the unknowable – sure, you’ll fool the people who don’t actually understand computing. But even if you continue this claim into the ads business, you cannot escape the pressures that ultimately impose a kind of morality through the ads business.

Ads have advertisers, and the truly important advertisers care about their reputations. They have limited tolerance for being on a platform that hurts those reputations. That tolerance is limited by the fact that their customers are actual people, and almost all of those people have some sense of morality. So even though we may have amoral (i.e. “neutral”) algorithms, even if advertisers themselves might be amoral, ultimately the common morality of people flows up through the advertisers, and through our ads systems, and finally imposes a sense of morality on the people who run the most powerful ads businesses. It is this slow flow of morality that has finally become a deluge upon you.

It’s not that hard to understand the downstream impacts of your business, and get ahead of the trickle of backwash before it becomes a deluge. The problem here isn’t about being a neutral platform, it’s not about avoiding the content business with its obligations and regulatory attention. It’s about understanding the cycle of users, advertisers and apps in the world’s most powerful ads business – that’s you now, apologies to my Google friends – and protecting each properly so that you are limiting the appearance and impact of bad ads.

I realize that the unwashed masses think that ads are evil. Only people who don’t understand business and don’t understand ads think that a powerful platform would knowingly sacrifice user interests for short-term revenue gains. Advertisers flee platforms that treat their users poorly. “Focus on the user and all else will follow” is a business mantra, not a moral mantra.

You struggle publicly like this is some kind of impossible problem. For that struggle, I can only play you the world’s smallest violin. You have a business problem, and it’s your business and therefore your problem.

Invest In People First

I had a medium size team at Google. Eight product managers working with over a hundred engineers, closely partnered with several hundred internal operations people and several thousand contract operations people. Yeah, I understand that most of the world looks at that and says “This is medium??” But as you know, that’s merely a sub-team when you’re talking about a critical function in a (then) $40 billion business.

How big is the policy team at Facebook, Mark?

All those people worked together to produce thoughtful policies, powerful computing systems, and vigilant human operations, working closely in a virtuous cycle. I could detail all of what we did, but you are better off just giving your own people in this area many more people.

Yes, I know AI can make this a lot more efficient than it was in Ye Olde 2010. I still don’t believe that AI is sufficiently advanced enough to get where you need to be without many many humans, though I’m no expert in AI. More importantly, I don’t think that the type of expert who can make that assessment is the type of person who should be deciding how many humans to put on this problem.

Here’s the part that will look like bragging, but I’ll take that risk. I want you to know what it takes to manage ads policy products, so I have to talk about myself. I studied political philosophy and law, under the great conservative theorist Robert P. George as well as the liberal giant Ronald Dworkin. I learned economics from Alan Blinder. I started my career in high finance law, working on leveraged buyouts for Mitt Romney, before I chased Silicon Valley dreams, first coming to Craig Johnson‘s firm, then going into venture capital and eventually working for “the Willy Wonka of virtual reality,” Philip Rosedale.

My point isn’t that I’m so great. I’ve done a lot of things, but I was mediocre or worse at many of them – a C grade in macroeconomics! My point is that this isn’t a job for just programmers, or philosophers, or economists – it’s highly multidisciplinary. Now that you know the template, it will take you less than a second to find the thousands of people who are basically just like me (except with higher grades). It’s not hard to put together a team to go after this particular kind of problem, but you have to know what you’re looking for.

Deep in the well of self-aggrandizement already, I’ll risk some more name dropping in order to move onto the next point. (I comfort myself by thinking it’s not name dropping when the person you’re talking to already has all these connections in his database.)

You need to truly empower the people working on this problem. I wasn’t particularly powerful by title. And yet, when I told Dennis Woodside that he was letting me down, he stepped up. When I told Nikesh Arora he was getting in my way, he pulled back. When I told Philipp Schindler he had to give up sales, he gave it up. When I showed Kent Walker we had a fire, he brought the fire trucks. When I told Claire Johnson I needed her help, she became my greatest ally. None of this was because I was great or powerful – I doubt any of these highly distinguished people remember my name. And yet they always cooperated with me, because they knew that when I got in their faces, they weren’t talking to me; they were talking to the leadership behind me. And there was never any question that my leadership would back me.

I wonder if policy leaders at Facebook feel that way? I wonder if they can go around to literally anyone at the company, insist on doing what is good and what is right for the business, and act with complete confidence that everyone will cooperate, all the way to the very top?

Assess Your Leadership

Let’s take the gloves off, shall we? You have built a company that has played a great part in letting a foreign influence endanger the integrity of our democracy. Have you even yet truly internalized the failure of leadership for which you bear complete responsibility? I mean to ask this clinically, not as an attack on your ego, character or capabilities. Do you have a complete grasp of how you have failed as a leader, and do you truly want to institute the change in yourself and in your company that would be required to make amends?

It’s really not a terrible thing if you understand the challenge and don’t think it’s yours at this point. Lots of people believe that you could be the actual President, not just the holder of the mythical “Leader of the Free World” title. Maybe you should make your impact on the world from the White House rather than Menlo Park. Given the current state of affairs, I would happily vote for a Sandberg/Zuckerberg ticket. Maybe it’s time to elevate yourself to the board Chair at Facebook, and focus on preparing for your campaign.

You’d have almost any option in the world to take on the CEO role at Facebook. I certainly don’t know everyone, but I can tell you who I know is great, because they were great with exactly the same problem at Google. Oh, I guess that this part of the open letter is addressed to them –

Nick, Susan, Sridhar: you guys don’t get enough credit for handling Google’s problems way before they could turn into the problems that Facebook has now. You would be the first to admit that of course Google still has problems, but we know they would be a lot worse without your leadership. 

– back to Mark, in closing – You probably can’t get Susan or Sridhar out of there. Why would they want the headache? You could probably get Nick, if you were serious about giving him true leadership authority to fix your problem.

If you still intend to fix Facebook yourself, I sincerely wish you luck. You’re going to have to change: the “Zuck” who created Facebook is not the person who can fix it. I haven’t seen you doing the things that I know would work, and it truly worries me. The future of the free world depends on your success.

the force awakens

~ ginsu ~ Leave a comment

Yep, it’s an end-of-the-year technology prediction post …

We’re at a special place in the consumer technology cycle. I’ve seen this movie before. Consumer technology trends are often described as waves, but I like a movie metaphor better, because it captures the notion that I actually saw these events when they were first released in the theater, and that we keep seeing the same plot points, themes and character types. I’ve lived through three really big waves of consumer technology. The third wave – the third movie – is finally coming to an end, which is a relief, because it kinda sucked. I’m really looking forward to the next show.

I’m a fan of the franchise generally, despite the repetitive plots. Each movie starts with the introduction of products that clearly show the possibility of what’s to come, although these are not the products that actually survive the revolution. Those products depend on a crucial underlying technology trend, which is not itself the consumer-facing technology. There is a spectacular platform war that decides the big winners and losers. The story ends, until next time, when the business patterns in the field have matured, and outsized returns for investing in those businesses have therefore disappeared.

The Origin Story: Personal Computers

pirates-of-silicon-valley

Like the first movie in a series, this one defined many of the patterns, tropes and heroic character types of the sequels to come. In a digital desert, a lone gunslinger appeared on the horizon, known only by the mysterious name Altair. The story really picks up when the Commodore PET, the TRS-80, and the Apple II appear on the scene. That trio of bandits opened up the Wild West, only to be dominated by the strongman IBM PC. But IBM only won a hollow victory, as it turned out that they’d unwittingly given the keys to the kingdom to Microsoft, the ambitious vassal that became the overlord. The story of the rise of the PC is the classic foundation of everything that came after in consumer technology.

But it would be a mistake to only pay attention to the foreground. In the backstory, the silicon chip is the key enabling technology that’s powering the other players. Moore’s Law is the inexorable force of progress, and Intel was the master who kept on top of the industry despite laudable challenges by AMD, Motorola, Texas Instruments, and a host of international competitors. This global tale of intrigue and ambition is a worthy accompaniment to the marquee narrative. In fact, the invention of Silicon Valley can be considered the prequel to this series.

The Worthy Sequel: World Wide Web

the-matrix

Many people say The Empire Strikes Back was a better movie than Star Wars. The Godfather was in many ways outclassed by Part II. The explosive success of the World Wide Web was at the very least a worthy sequel to the PC story. A knight in shining armor, Tim Berners-Lee, led a devoted band of heroes on a worthy quest to unite all of the world’s information. Early services like Prodigy and CompuServe leapt on the ensuing opportunity, but latecomer AOL won the day by sending a CD to every mailbox it could find. That was only the first act, as Netscape and Yahoo emerged as the real heroes … until the third act, when eBay and Amazon and Google trampled the field.

It’s usually not worth the effort to make a distinction between the Web and the Internet, but it makes sense to do so here because “World Wide Web” is the story with a beginning and an ending, while the technologies of the Internet are the more enduring enablers of that story. As protocols, the details of TCP/IP, DNS, HTTP and the like are not exactly gripping narrative. But like silicon chips powered the PC revolution, and could be considered the more enduring story, the Internet will live on long after the Web sinks into irrelevance.

The Failed Trilogy: Smartphones

phone-booth

Return Of The Jedi was a very successful movie. And it did have some awesome special effects for the time. But it was all of the same characters, and pretty much the same plot, soiled by dominant commercial motives and treacly pandering to a younger audience. By which I mean, fuck Ewoks. And Godfather Part III? The less said about that, the better.

The story of the last dozen years or so has been the move of personal computing and the Internet to smartphones. There’s some compelling pathos in the storyline of the death of the Web, overrun by mobile apps. But it was mostly dull to watch the Treo and Blackberry reprise the role played in prior movies by the Altair, Prodigy and CompuServe. I’ll admit it was great fan service to see the Apple character repurposed, and maybe there hasn’t been a more colorful personality than Steve Jobs, so that part of the story was pretty entertaining. You could say that the return of Jobs was as momentous as finding out about Luke’s father.

Let’s face it, it just wasn’t that exciting to watch Google and Amazon continue to grow. Facebook is a great new character as a flawed hero, and that whole subplot with Twitter and the rest of social media was a very strong B story. Other new characters like Uber and AirBnB have their minuses and pluses, but I don’t believe they’re going to be big characters in the next movie. (“Uber for X” companies are the goddamn Ewoks.) The overall experience has been like coming in to watch a huge blockbuster mega-sequel: you can really see the dollars up there on the screen, and there’s a certain amount of entertainment value that comes through, but the whole exercise just lacks the originality, joy and passion of the earlier entries.

Not a bad backstory though, and as in the other movies, this one will continue to be meaningful in all future sequels. Cloud computing, software as a service, the evolution to microservices – these things fundamentally changed the way that new businesses start and grow. They reduced the capital costs in starting a new information technology company by orders of magnitudes, letting in many more characters. Unfortunately, most of those new characters are Ewoks.

The Force Awakens

So what’s the next movie going to be about? Will it reinvigorate the franchise? Or will it be a terrible prequel (or worse, prequel trilogy) that we’ll all have to agree to pretend never happened?

I think we don’t know all of the elements, but we do know some of them. Let’s first recap what we saw in the first three installments:tfa-chart

And here’s what I think we know about the chart today:

tfa-chart-f

Main Story: There is a flood of products that don’t have an agreed category name yet – Siri, Google Assistant, Amazon Alexa, Microsoft Cortana, chatbots, chatbots and more chatbots. Some industry terms that are cropping up are intelligent personal assistants, virtual assistants, conversational search. Or chatbots, fer chrissake.

The point is, you will have things in your house (your car, your pocket, etc) that you talk with, and these things will talk back to you in a way that makes sense. You’ll regard your interaction as a conversation rather than button punching or screen swiping. Until people converge on another name for all of these things, I’ll call them “conversational devices” – this captures that you have a productive back-and-forth with a physical object. Yes, you can already do something like this on your smartphone, but those implementations are only a hint of where this will go.

As early as it is, there are plenty of curmudgeons who don’t see the point. Smarter people have said we’ll never need more than five computers, no one wants a computer in their home, the Internet is a fad, the iPhone is going to be a flop. Predictions are hard. But screw it, here’s mine: within 3 years, it will be apparent that the adoption curve of conversational devices is in the same category as PCs, the Web, and smartphones.

Conversational devices will be the story of the next decade in consumer technology. Not that there won’t be other stories, it’s just that this one will be the lens by which we understand the era. I still love virtual reality, but it’s still not time yet. The blockchain isn’t consumer-facing, and  I don’t believe in Bitcoin. Not Internet of Things, not 3D printing, not self-driving cars, not wearable devices (unless they are also conversational devices) – some of these will be big stories, but not the biggest story of the next dozen years.

Backstory: Conversational devices rely on this chain of technologies: Machine Learning -> Natural Language Processing -> Speech Synthesis. These technologies are complex and interrelated, and rather than explain why this is their moment (the foregoing links give that explanation), I’ll just skip to the punchline: People will be able to speak to machines, machines will understand and speak back. Most people already have experience with primitive versions of these technologies, and find those experiences frustrating and unsatisfying. (“Press 9 to go back to the main menu.”) But the rate of improvement here is at an inflection point, and this is about to become undeniably apparent on a mass consumer level.

Platform War: The most successful conversational devices will be on a common platform of delivery. Amazon Echo and Google Home are devices that sit in your home and listen to everything you say, and respond back to help you. Facebook Messenger has bots that will have a conversation with you. Each of these is currently displaying only the limited strengths available in their existing businesses (Amazon:Shopping, Google:Search, Facebook:Brands), but they are all trying to expand to become a delivery platform for third-party conversational devices. Amazon and Facebook already offer developer platforms, Google is focusing on partnerships.

This platform war will have elements of past wars, in hardware vs software, apps vs operating system, open vs closed. That complexity makes it very interesting, but remember, this is theme rather than story. The platform war is the Empire vs the Rebellion, the Mob vs America, it’s the thematic texture that gives the story meaning. You shouldn’t mistake it for the main narrative though. In Mac vs PC, Microsoft won, not Apple or IBM. In open vs closed web, Google won, not Tim Berners-Lee or AOL. Ok, the winners in iOS vs Android were also the platform owners, but that’s yet another reason that movie sucked, maybe it’s the fundamental reason that movie sucked. I hope everyone involved is smart enough not to let that happen again.

Pioneers and Winners: We are far enough into the story that we can guess at pioneers, but we can’t be sure until the extinction event happens: in all previous movies, the early pioneers proved the market, and then died, crushed by an onslaught that included the eventual winners. I’m convinced that this plot point will repeat in the new movie. Look in the chatbot space for potential pioneers – it’s certain than one of these will become historically important. And then it will die.

I’m hoping the platform war victors aren’t also the heroic winners of the main story, as happened in the smartphone movie, because it’s boring and tends to result in Ewoks. Facebook is the pivotal character to watch, as it has a platform opportunity with Messenger, but has huge weaknesses relative to Google, Amazon, Apple and even Microsoft in hardware production and delivery, and hardware will be key to platform ownership. So it will be interesting to watch whether Facebook dives into hardware, or partners with one or more of the other platform players, in the hopes that there’s a bigger opportunity in the main story than the theme.

Well, that’s all I have to say about that. Enjoy the show!

WWGD?

~ ginsu ~ 1 Comment

Six months ago, I said that Trump would win the election in part because the rise of new media destroyed the historic function of the media as our Fourth Estate. I was upset that product managers at our most important Internet companies seem to refuse to own the problem that is so clearly theirs.

Now that the chickens have come home to roost in a big orange nest of hair, others are saying that the election was, in a sense, rigged by Facebook. They say fake news has defeated Facebook. Facebook denies responsibility, while people are literally begging them to address the problem.

Product managers at Facebook are surely listening now. If any happen to be listening here, let me say: I’m sorry I called you cowards. I realize that today’s state was hard to foresee, and that the connection to your product even still seems tenuous. I am awed at the great product you’ve built, and I understand that no one knows the data better than you do, and that it is tough to take criticism that comes from sources completely ignorant of your key metrics. It’s not easy to regard something so successful as having deep flaws that are hurting many people. I think it is a very human choice to ignore the criticism, and continue to develop the product on the same principles that you have in the past, with the same goals.

I have faith that you are taking at least some of the criticism to heart. I imagine that you know that you can apply machine learning to identify more truthful content. I am sure that you will experiment with labels that identify fact-checked content, as Google News is doing. Once you reliably separate facts from fiction, I’m sure you’ll do great things with it.

I’m still concerned that facts aren’t enough. I think we’re in a post-fact politics, where people no longer (if they ever did) make their political choices based on facts. I have read many analyses of the election results, many theories about why people voted as they did. There are many fingers pointing blame at the DNC and the Electoral College; at racism, sexism, bigotry; at high finance, globalism, neoliberalism; at wealth inequality, the hollowing out of the middle class, the desperation that comes with loss of privilege. I am not convinced that giving people more correct facts actually will address any of this.

The most incisive theory that I’ve seen about today’s voters says that the divide in our country isn’t about racism or class alone, but about a more comprehensive tribalism, for which facts are irrelevant:

There is definitely some misinformation, some misunderstandings. But we all do that thing of encountering information and interpreting it in a way that supports our own predispositions. Recent studies in political science have shown that it’s actually those of us who think of ourselves as the most politically sophisticated, the most educated, who do it more than others.

So I really resist this characterization of Trump supporters as ignorant.

There’s just more and more of a recognition that politics for people is not — and this is going to sound awful, but — it’s not about facts and policies. It’s so much about identities, people forming ideas about the kind of person they are and the kind of people others are. Who am I for, and who am I against?

Policy is part of that, but policy is not the driver of these judgments. There are assessments of, is this someone like me? Is this someone who gets someone like me?

Under this theory, what is needed isn’t more facts, but more empathy. I have no doubt that Facebook can spread more facts, but I don’t think it will help. The great question for Facebook product managers is, Can this product spread more empathy?

The rest of this might be a little abstruse, but here I’m speaking directly to product managers of Facebook News Feed, who know exactly what I mean. You have an amazing opportunity to apply deep learning to this question. There is a problem that the feedback loop is long, so it will be difficult to retrain the production model to identify the best models for empathetic behavior, but I think you can still try to do something. There is some interesting academic research about short-term empathy training that can provide some food for thought.

I am convinced that you, and only you, have the data to tackle this problem. It is beyond certainty that there are Facebook users that have become more empathetic during the last five years. It is likely that you can develop a model of these users, and from there you can recreate the signals that they experienced, and see if those signals foster empathy in other users. I don’t think I need to lay it out for you, but the process looks something like this:

  1. Interview 1000 5-year Facebook users to identify which ones have gained in empathy over the last five years, which have reduced their empathy, and which are unchanged.
  2. Provide those three user cohorts to your machine learning system to develop three models of user behavior, Empathy Gaining, Empathy Losing, Empathy Neutral.
  3. Use each of those 3 models to identify 1000 more users in each of those categories. Interview those 3000 people, feed their profiles back into the system as training data.
  4. See if the models have improved by again using them to identify 1000 more users in each category.

At this point (or maybe a few more cycles), you will know whether Facebook has a model of Empathy Gaining user behavior. If it turns out that you do have a successful model, of course the next thing to do would be to expose Empathy Losing and Empathy Neutral users to the common elements in the Empathy Gaining cohort that were not in the other two cohorts.

But now at this point you are in a place where the regression cycle is very long. Is it too long? Only you will know. How amazing would it be to find out that there’s a model of short-term empathy training that is only a week or two long? People use Facebook for hours a day, way more than they would ever attend empathy training classes. This seems to me to be an amazing opportunity. Why wouldn’t you try to find out whether there’s something to this theory?

One reason might be a risk to revenue models. Here I’d encourage you too see what Matt Cutts said to Tim O’Reilly about Google’s decision to reduce the prominence of content farms in search results, even though that meant losing revenue:

Google took a big enough revenue hit via some partners that Google actually needed to disclose Panda as a material impact on an earnings call. But I believe it was the right decision to launch Panda, both for the long-term trust of our users and for a better ecosystem for publishers.

I understand this mindset personally because I was there too. At the same time Matt was dealing with Google’s organic search results, I was dealing with bad actors in Google’s ads systems. So I was even more directly in the business of losing revenue – every time we found bad ads, Google lost money. Nevertheless, we had the support of the entire organization in reducing bad ads, because we knew that allowing our system to be a toxic cesspool was bad for business in the long run, even if there were short-term benefits. In fact, we knew that killing bad ads would be great for business in the longer run.

News Feed product managers, I’m not writing this from a position of blaming you. I was in a situation very much like yours and I know it’s hard. I can also tell you, it feels really really good to solve this type of problem. I am convinced that an empathy-fostering Facebook would create enormous business opportunities far exceeding your current path. It is also entirely consistent with the company mission of making the world more open and connected. You can make a great product, advance your company’s mission, and do great good in the world all at the same time. You are so fortunate to be in the position you’re in, and I hope you make the best of it.

dear prudence

~ ginsu ~ 2 Comments

When I joined Google in December 2010, my friends didn’t think I’d last six months. I’d been working in startups for over a decade, and my experience and predilections had given me an enormous appetite for chaos, joyful appreciation of uncertainty, and incorrigible disdain for authority. Joining the world’s largest Internet company didn’t seem like a long-term move.

I lasted five years. It’s still a bit of a wonder to me how I stayed so long, but the attractions are undeniable. Google is routinely ranked as the best place to work, and it’s all true: market-leading products, smart colleagues, admirable leaders, outstanding perks and outsized pay. The list of reasons to work at Google is long and enviable.

Usually “great culture” is on that list, but it’s not on mine because no culture is great for every person. Only insane zealots would seek to impose a monoculture on the world, and to claim there’s just one way to have a great workplace culture is similarly indefensible. If chaos makes you hungry, if uncertainty brings you joy, if authority makes you want to punch up – you probably don’t want to work in a culture of extremely refined processes, luxurious reaction times, and deference to position. None of these are bad qualities in the abstract; it’s not inherently disadvantageous to be wild or deliberate, only the context makes it so. The context can vary from company to company, and even within companies.

I was in the right context, even at Google, for the first couple of years. Then I spent three years learning valuable things that nevertheless weren’t skills I wanted to have. Despite all the benefits, I feared becoming dependent on the enormous generosity of the leviathan, reduced to a remora suctioned to a whale for so long that it forgets how to swim. Unfortunately, I’m constitutionally incapable of adopting the prudence required to enjoy stability and luxury. I don’t think I’m irrational, I just value the parts of my personality that strain against these bounds. Prudence is expensive, unbearably dear, when it comes at the cost of your hunger, your joy, even the double-edged sword of your pride.

So finally, I’m out of the longest and most comfortable work relationship I’ve ever had, finally a fish without a host in the ocean, flapping the atrophy out of my fins. The water is deep and wide, filled with fearsome predators and cold currents, and the friendly coves are as yet hidden to me, but still it feels like home.

real time

~ ginsu ~ 4 Comments

At Second Life, we occasionally debated the merits of virtual reality vs augmented reality. In caricature:

Virtual reality was the core dream of SL, same as the core proposition of Snow Crash, the Holodeck, the Matrix – the idea that a computer simulated world could have all of the sensory and intellectual stimulus, all of the emotion and vitality, all of the commerce and society, of the “real” world (quotations necessary because virtual reality would be so real that non-simulated reality has no better claim on the term).

Augmented reality said that the virtual realists dropped too much acid in their youth. A fully simulated environment might be escapist pleasure for the overcommitted few, but computers would show their real power by adding a layer to our existing lives, not creating entirely new ones. Computers would sink themselves into our phones, our clothes, eventually our fingers and eyeballs and brains, not in the service of making another world, but enhancing the world we live in.

If that debate sounded ridiculously theoretical to you, then I hope that was yesterday because today it’s as real as it gets.

Google Glass is the vanguard of augmented reality, and obviously important to the company.* Google’s mission has always been to organize the world’s information – not to create a fantasy world but to organize our world.

Second Life had its heyday after Google established itself as the new tech titan, but before any serious challenger had risen up behind it. We spent a lot of time trying to convince people that SL could be the next big thing … trying to explain that people wanted to have an online identity, instantiations of themselves that would interact with other online personalities, creating tiny bits of content that might not have individual value, but would have enormous value as a whole fabric of an online world where people would go and interact every day …

I was laughed out of a lot of buildings after explaining SL. Who wants to live online? Who wants friends that they see only in a computer? Who wants to spend their leisure hours pecking away at a keyboard and looking at the cascades of dreck that other non-professional users create?

Second Life missed the mark for a lot of reasons, but not because we were wrong about online life. Facebook came along, and gave us all of the virtual life that the Web could really handle – only 2D, status updates instead of atomic 3D content, kitten pictures instead of furries – but Facebook succeeded in creating a virtual world.

And now they’ve acquired Oculus VR. If it wasn’t clear before – and perhaps it wasn’t clear even to them – they have now taken a side in that old debate, the same side that they’ve been on since the beginning. Facebook is going to go more and more towards virtual reality, while Google expands further and further into augmented reality.

 

*I don’t work on Glass, have no special knowledge of the product or strategy, and actually have never even tried it.

Facebook and the end of the Web

~ ginsu ~ 1 Comment

This week Facebook released a barrage of announcements that reveal a stunning level of ambition.  You have to ask, are they really the next Google, but with evil?

I can’t speak to the question of evil, but I do have a mental benchmark for the next Google, and it isn’t simply about being the next giant tech company.  The next Google would have to create an entire sector of economic activity, keeping a dominant position worth many billions of dollars while also creating many billions of dollars of value for other companies.

Before Google, the commercial Web was motley mix of emerging media, with some interesting economic opportunities in portals, ecommerce and auction.  Google created and dominated search advertising, but the utility that search brought to the Web was a major driver in the overall economic growth of all advertising on the Web, including display advertising.  Today the entire commercial Web runs on advertising, and Google helped create many more billions of dollars than it captured for itself.

If Facebook merely becomes the world’s best ad network, they would not be the next Google.  They would simply be the biggest winner in the economy that Google helped create.  They could even suck all the oxygen out of Google’s room and thereby kill Google, but that wouldn’t make them the next Google any more than John Wilkes Booth was the next Abraham Lincoln.

I think Facebook’s ambitions go far beyond advertising.  I’ve got no crystal ball showing the future, but the analogue from the past that seems relevant to me is television.  TV was once a wondrous new technology, giving rise to a new world of entertainment and news media.  Businesses quickly hooked the economic engine of advertising to the media of television, and decades of fantastic growth followed.  It once seemed a given that television would hold a central place in our media lives forever, and that it would always be free.

And then cable TV came along.  You might not remember this personally, but cable TV was initially a terrible affront to consumers.  People had become accustomed to getting a huge amount of media for free, and now these horrible new companies wanted outrageous fees every month for the same kind of media.  This could be very painful for a consumer with devotion to a particular kind of content, for example a sports fan seeing important sporting events disappear into the hole of paid TV.

Could the same thing happen to the Web?  An entire generation has become accustomed to Web media as free media, and assumes that will be true forever.  But cracks in that assumption have appeared recently.  We’re seeing a new wave of paid content efforts on the Web.  More importantly, we’re seeing platform owners make good money from Web-like content, like Amazon with Kindle and Apple with iPhone/iPad.

Amazon and Apple have shown that you can make money from digital content if you own all the important parts of the value chain, from digital content rights to an ecommerce store to a payment service to a physical device.  Facebook could be about to find out whether you really need the last link of that chain.  They might not need control over the physical device, because they have something even better in the social graph and identity management.

Facebook knows who you are and knows who your friends are, and they own that information in a way that no one ever has before.  Add in the right content relationships, a payment system, and a universal interest indicator, and that becomes a complete enough platform to enable more paid content on the Web.  A hidden key may be that their payment system is a prepaid credit system, which allows small transactions that would otherwise have burdensome costs and usability barriers.

That may sound a little abstract, so I’ll offer up this fanciful example:  I go to visit Pandora for music, and Facebook and Pandora immediately know it’s me.  They know what kind of music I like, and they know what kind of music my friends like, so they are able to recommend some really great music for me.  Right there I have already participated in a content transaction:  I have offered my valuable tastes and contact information to Facebook, who handed that info over to Pandora – you have to think that Facebook gets paid for that.

And Pandora was glad to pay, because I really like that music they recommended.  In fact, I liked it so much that now I’m going to sign up for a Pandora subscription.  I’m about to reach for my credit card when I realize, hey, I can pay for this with Facebook credits!  Oh, I see I’m a few credits short.  No problem, I’m going to go this this Facebook game, SheepWorld, and rack up the extra FB credits I need – then back to Pandora to pay.

A bunch of little transactions happened in that scenario, and none of them actually involved me pulling out my wallet.  In fact, it seemed like fun, it didn’t seem like I was paying at all.  I was able to participate in a new economy because I’m a Facebook user, and now I’m getting used to paying for premium content.  And when the New York Times puts up its paywall, I’m not going to care so much because I’ll be paying with Facebook, which separates the media consumption experience from the payment experience.

Sound a little farfetched?  Could be.  But there was a time when I couldn’t imagine paying for TV.  Both free broadcast and paid cable television still bring in a lot of money, but cable is a much better business.  If Facebook enables new revenue opportunities on the Web for content creators, they will enrich themselves and enrich others even more.  I won’t like it, just as I didn’t like it when I started paying for TV.  It would be the end of the Web as we know it.

google killer

~ ginsu ~ 3 Comments

By my own admission, I’ve become a complete hack, for using the term [blank]-killer.  A lot of people are asking whether News Corp would really block its content from Google’s index, and make a deal with Microsoft for exclusive search access.  And if they did, and others followed, would this represent a serious threat to Google?

The tech-über-alles crowd would have you believe that “de-indexing” from Google would be suicide for any publisher.  The assertion there is that Google drives the majority of web traffic, so if you’re not findable through Google, you might as well not be on the Internet.

But that assertion flies in the face of another observation from the technoscenti – social media like Facebook and Twitter are becoming increasingly important as traffic drivers (though this importance may be overhyped).  We may be heading towards a future where the links are shared through social media are more valuable than search links.

More importantly, and against the prevailing wisdom in some circles, content still matters.  People use media services because of the content on it.  Other factors are important too:  the features must be complete, the UI has to be easy, the price has to be right, yadda yadda yadda.  But would any of those other factors make up for terrible content?  No, content is, if no longer king, still the jewel in the crown.

If Bing is able to be the exclusive search partner for the right content, Google is dead.  Of course, what’s “right” can vary quite a lot from person to person.  For me, it’s as simple as two publications:  If the New York Times and Wikipedia are de-indexed from Google, I’m going to stop using Google in favor of the search engine that has those two.  I might think it’s unfair, I might think it’s a triumph of soulless MBAs over tech heroes, I might think it’s the desperate grasping of dying empires.  But I want the content I want, and those principles aren’t enough to prevent me from switching.

Bing doesn’t have to make deals with every content provider, just a dozen or so critical ones that will cause another 40% market share gain (they’re at 10% now).  Sure it’ll be expensive to acquire the best content, but Microsoft’s got more cash than Google.  Once it’s 50/50, it’s anybody’s ballgame but the advantage goes to the one who has the content.

I’m pretty sure that Google is not going to sit back and smugly assume that Murdoch’s gambit will fail.  They’re going to get involved, they’re going to try to start locking down their own partnerships.  If I were them, I’d start with Wikipedia, one of the most important search result destinations on the web – it’s in the top five results of just about any search you do.  Sure, they’re a non-profit, but non-profits need money too.

advertising in 3 E-Z slides

~ ginsu ~ Leave a comment

Has the Internet ushered in a revolution in advertising, or is web advertising destined to fail?

I couldn’t begin to have an opinion without some basic context about advertising, so I gave myself a crash course.  Here’s the 3 most important things I learned:

1.  Advertising has multidimensional sectors.

Two of the fundamental axes in advertising are the lines between brand and direct response marketing, and between online and offline ads.

ad status

I can’t do the differences justice here, but essentially brand marketing is intended to make you feel a certain way about a product, while direct response is intended to make you take an immediate action regarding a product.

The concepts seem simple, but whenever new media arises, it can be quite tricky to determine what kind of advertising is suited to the media.  When the Web first burst into mass acceptance, some advertisers treated this new medium as a branding opportunity, plastering their logos and flashy campaigns wherever they could.  Google was among the first to realize that direct response principles fit the Web much better than branding – deliver ads against search results and you have a natural audience to act upon that hyperlink.

But the Web continues to evolve, giving continued opportunities to make the wrong choices about ads.  When social networks like Facebook reached mass popularity, many advertisers tried to deliver targeted direct response advertising to demographics discovered through the social graph.  But “banner blindness” and the very social intent of these sites combined to make pure direct response ads ineffective.  The better strategy for advertisers in social networks is to build a community and create engaging viral media to enhance the brand.

So the lesson here is that advertisers have to make very savvy choices between brand and direct response advertising as the evolution from offline to online continues.

2.  Online and offline ad spending patterns are currently inverted.

In the excitement about the growth of online advertising, it’s easy to forget that offline is still much bigger, with online making up roughly $23 billion of a $137 billion U.S. ad market.  These numbers are even more interesting when examined along the divide between brand and direct response.

 

According to one estimate, around 75% of offline ad dollars are spent in brand marketing, while 80% of online ad dollars are spent in direct response.  Because offline is so much bigger than online, that means that direct response offline (a.k.a. “junk mail”), makes up around $28 billion.  Yep, junk mail is bigger than the entire Internet ad industry.

Now here’s a point that’s a little more abstruse, but I hope it’s worth the time to understand it:  the advertiser’s spending pattern is inverted in online vs offline.

Offline brand advertising is expensive to create, but reaches a mass audience, so the spend per viewer is low.  Take a Super Bowl ad:  a 30-second commercial can cost $4 million (for air time and a lavish production cost), but with 95 million viewers, that’s only 4 cents per viewer.  Let’s call this low cost per viewer a mass spending pattern.

Offline direct response advertising total cost is lower, but higher per person reached.  For example, it can cost $50K to produce and mail a catalog to 10K recipients.  At $5 per person, that’s 125 times more expensive per person than a Super Bowl ad!  But it works because of the targeting – those 10K people have been identified by the advertiser as being likely to be interested in the product.  This low threshold, high cost per viewer is a targeted spending pattern.

The patterns are rewired online.  Search advertising and email campaigns are direct response in that there is a clear desired action (usually a click).  Though the cost of the keyword or email campaign can be relatively low, the distribution is very broad, so the cost per viewer is extremely low –  this is a mass spending pattern.

Conversely, doing effective brand advertising on a social network requires really identifying the target demographic and crafting a creative campaign to get that ballyhooed viral explosion.  That means relatively high creation cost and a specific audience, resulting in a high cost per viewer – this is targeted spending.

So offline, brand advertising is mass spending while direct response is targeted spending.  And online, brand advertising is targeted spending while direct response is mass spending. Or at least, that’s the way it is today . . .

3.  Successful advertising tactics will seek equilibrium.

Pundits are always rushing to declare failure, or any new method the death of all old ones.  But offline advertising feeds online, and online direct response may morph into “brand response.”  Advertising, like nature, restlessly searches for equilibrium.  The story above is heading towards a more stable balance so the value of the spending better matches the returns.

ad future

It’s not controversial to suggest that offline ad dollars will move online – that’s more an observation than a suggestion at this point.  And it’s also been an observable trend that offline direct response marketing is declining at an even faster rate than offline brand marketing, because Internet direct response has rapidly become effective for larger audiences.  But I’m adding two conjectures that aren’t easily observable today.

First, online brand marketing will grow at a faster rate than online direct response.  This means that social media like Facebook and Twitter (like them, not necessarily those two) will grow revenues faster than Google.

Second, online brand spending will revert back to the offline spending pattern of mass rather than targeted, and online direct response will similarly go to targeted spending rather than mass.  I believe that dominant social media sites and practices will arise that allow brand advertisers to reach a large audience at a low cost per viewer.  At the same time, increasingly effective data collection on Internet consumers will allow data holders to sell highly targeted direct response ads at premium prices per consumer.

What does it take to get from here to equilibrium?  In monetary terms, holding the total ad industry constant at $140 billion (not a safe assumption):

  • $50 billion will move from offline to online
  • $15 billion will move from offline direct response to online direct response
  • Online direct response will grow by $20 billion, while the revenue per viewer seeks a relatively high number
  • Online brand marketing will grow by $30 billion, while the revenue per viewer seeks a relatively low number

That is a lot of money sloshing around, in a lot of different directions.  I think it’ll happen within 5 years.

love the machine

~ ginsu ~ Leave a comment

The Wall Street Journal reported that Google is working on an algorithm to predict which of its employees is likely to leave. Putting aside for the moment whether there is some creepy aspect to the machine anticipating personal career choices, there are two aspects to this that I find interesting.

First, exactly how and why did this make it into the news? I’m not questioning whether it’s newsworthy (it is), I’m wondering about the exact path that this took from fact to front page. Was this program broadly announced at Google, and a random employee alerted the media? That would be one typical path. Was it an unannounced program, and someone in the HR department leaked it to the press? Or perhaps the HR folks proactively fed this to the press. If one of the latter two, what’s the motivation? Does it make Google look smart as a company? Does it comfort employees to know that Big Brother is watching and cares whether or not you leave? I don’t think any answer to any of these questions is necessarily a bad thing, I’m just wondering what the answers are.

Second – and more answerish this time than questioney – it’s really interesting to consider the reported inputs to the algorithm. According to the WSJ, “data from employee reviews and promotion and pay histories” comprise the formula. At first glance, this might seem logical: you would hope that reviews and compensation have some correlation to job performance and satisfaction.

Ah but then – you’ve been hoping that all your life, haven’t you? And haven’t you found that the content of employee reviews is often radically disconnected from actual performance, that the “wrong” person often gets promoted, that compensation has at best a tenuous connection to performance and satisfaction?

So the data set might not be as logical as it first seems; fortunately the magic of the sample size means that this isn’t a logic problem, but simply a correlation exercise. There is certainly some correlation between the content of that data and the incidences of employee departure, or Google wouldn’t be trying this.

But I’d bet that the correlation is much weaker than you’d think, and much weaker than Google would like. Any manager knows that reviews and compensation are blunt tools, and these are likely to be trailing indicators rather than the leading indicators of dissatisfaction that you want for real predictive power.

I worked at a company that somewhat famously had a “Love Machine” – a simple tool for employees to express appreciation for each other. Basically, as an employee, if a colleague did something that you appreciated, you could send them a point of Love, along with a one-line comment as reason for the gift. It was just a neat little way to say Thank You, and people really appreciated both giving and getting Love. And as very minor benefit, periodically the accrued Love points would be paid out to employees as a cash bonus.  (Distribute that on a Friday and watch people really spread the love around.)

When this was reported externally, some people misunderstood the corporate purpose of the Love Machine. Which is to say, some people thought it had no purpose at all, except as some gross hippy dippy vibe. Those people not only misunderstood the effect on morale, but also vastly underappreciated the value of the data from the Love Machine.

Think about it: as a manager, is it valuable to know which of your employees is appreciated, and which is not? The Love Machine is certainly not the sole source of information on this, but the data gives at least some general information on both specific and aggregate cases. You can see not only who is appreciated, but who gives appreciation. You can see which departments are praised and which toil without recognition. You can see who works across departmental boundaries and who only interacts upwards or downwards in their own reporting silos.

All this is phenomenally powerful data that gives factual indication of matters that you might otherwise pay significant amounts to guess about through expensive organizational consultants. I was convinced back then and I still am today that if HR departments and managers understood the power of this data, every company would have a Love Machine. Most would call it something else, but that part is just internal marketing.

Back to Google: as far as I know, they don’t have a Love Machine. But that doesn’t mean that they are feeding the best data they have into their Who’s Leaving? algorithm. Nearly every company has somewhat similar data in their email traffic, and certainly in a big data set, email traffic would work quite well. Now, I’m not saying that the email content should be analyzed – even though many companies actually do that, I find it unacceptably creepy. I just mean the fact of communication. Every manager knows that communication is a powerful indicator (and motivator) of job satisfaction.

Who’s talking to who? Who’s on how many email lists? What is the response rate and timing and length? Is communication cross-functional, up and down and across reporting levels, inside and outside the company?  All of that information is available in company email – I guess you could call it the email graph.

I would bet almost anything that this kind of data from email traffic provides a more powerful indicator of who’s leaving the company than the data from reviews and compensation. In fact, I’d bet that the email graph has better correlation to actual job performance than performance reviews!

Of course, the combination of those data sets could be even more powerful, and it’s entirely possible that Google is already doing this, though that wasn’t reported in the Journal piece.