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  • feedwordpress 15:59:20 on 2019/04/24 Permalink
    Tags: , , data, , , , , , , terms of service,   

    Mapping Data Flows: Help Us Ask the Right Questions 


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    I’ve been quiet here on Searchblog these past few months, not because I’ve nothing to say, but because two major projects have consumed my time. The first, a media platform in development, is still operating mostly under the radar. I’ll have plenty to say about that, but at a later date. It’s the second where I could use your help now, a project we’re calling Mapping Data Flows. This is the research effort I’m spearheading with graduate students from Columbia’s School for International Public Affairs (SIPA) and Graduate School of Journalism. This is the project examining what I call our “Shadow Internet Constitution” driven by corporate Terms of Service.

    Our project goal is simple: To visualize the Terms of Service and Data/Privacy Policies of the four largest companies in US consumer tech: Amazon, Apple, Facebook, and Google. We want this visualization to be interactive and compelling – when you approach it (it’ll be on the web), we hope it will help you really “see” what data, rights, and obligations both you and these companies have reserved. To do that, we’re busy turning unintelligible lines of text (hundreds of thousands of words, in aggregate) into code that can be queried, compared, and visualized. When I first imagined the project, I thought that wouldn’t be too difficult. I was wrong – but we’re making serious progress, and learning a lot along the way.

    One of the most interesting of the early insights is how vague these documents truly are. The conditional (“might,” “could,” “may” etc) seems to be their favorite verb tense. It likely comes as no surprise to dedicated readers, but despite the last two years of public outrage, tech companies can pretty much do anything they want with your data, should they care to. Another interesting takeaway: The sheet amount of information that *can* be collected is staggering. A third insight: Even if you can find the data dashboards that give you control over how your data is used, cranking them to their fullest powers often won’t limit data collection and use, but rather will limit their application in very specific use cases. It’s all about the metadata. Lastly, it’s fascinating to see how similar these documents are across the top four companies, and how Apple, for example, has pretty much exactly the same rights to use your data as, say, Facebook.

    I could go on, but what we really want to know is what *you* wish you understood about these companies’ data practices. That’s why we’ve built a very short, very subjective survey that we’re hoping you’ll take to give us input and feedback as we start to actually build our visualization.

    I’ve buried the lead, but here’s the ask: Will you please take a minute to give us your input? Here’s the link, and thanks!

     
  • feedwordpress 17:48:09 on 2019/03/12 Permalink
    Tags: , , data, , , , , ,   

    With Privacy as Its Shield, Facebook Hopes To Conquer the Entire Internet. 


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    Never mind that man behind the privacy curtain.

    I’ll never forget a meal I had with a senior executive at Facebook many years ago, back when I was just starting to question the motives of the burgeoning startup’s ambition. I asked whether the company would ever support publishers across the “rest of the web” – perhaps through an advertising system competitive with Google’s AdSense. The executive’s response was startling and immediate. Everything anyone ever needs to do – including publishing – can and should be done on Facebook. The rest of the Internet was a sideshow. It’s just easier if everything is on one platform, I was told. And Facebook’s goal was to be that platform.

    Those words still ring in my ears as we celebrate the 30th anniversary of the web today. And they certainly should inform our perspective as we continue to digest Facebook’s latest self-involved epiphany.

    Last week Mark Zuckerberg declared privacy the new black, and committed his multi-hundred-billion dollar company wholeheartedly in favor of it. Employing the now familiar trope that “people I’ve been talking to have been saying privacy’s a thing they care about,” Facebook’s monarch appeared to be pivoting his entire company around this newfound insight, and much of the press seemed to buy it.

    But this isn’t a pivot, it’s a panic born of crisis. Facebook’s core business model has plateaued, and absent new channels into which the company might stuff toxic algorithmic advertising, Zuck and crew have had to find a new cash cow. After all, those record-breaking Wall St. earnings won’t keep writing themselves – not with users leaving the service and regulators sharpening their swords for battle.

    So Facebook needs to find a new revenue source, one that’s really, really big, and ideally, one that also manages to solve its lousy image as the lusty barker at the surveillance capitalism carnival.

    The company has found its answer in the form of WhatsApp, the famously privacy-loving messaging app which Facebook paid $19 billion to acquire five years ago.

    So why WhatsApp, and why now?

    • WhatsApp was built on entirely different DNA from Facebook. It’s end to end encryption practically screams privacy. Before Zuckerberg’s come to Jesus, Facebook had attempted to turn WhatsApp into another advertising play, which drove WhatsApp’s founders to leave in a very public huff. Since then, WhatsApp has failed to become an advertising channel of any significance. Leveraging WhatsApp’s brand sheen to polish Facebook’s privacy turd is a mad genius move.
    • Going five years without figuring out monetization for a $19 billion acquisition is…embarrassing. Now Facebook can answer Wall Street’s incessant questions about WhatsApp’s contribution to the company’s bottom line.
    • Of all the tech giants, Facebook is most likely to suffer regulators ire here in the United States, including very loud calls for antitrust action. But by pivoting to privacy first and claiming WhatsApp as its new cornerstone, Facebook now has an excuse to integrate Instagram, Messenger, and Facebook, making a breakup technically and socially challenging, if not impossible.
    • Most importantly, WhatsApp has the potential to realize Facebook’s long sought dream of *becoming* the Internet for billions of customers around the world.

    But how, exactly? To answer that question, Facebook had only look to China’s Tencent, which in two short years has turned its wildly popular WeChat service into a revenue geyser, a new kind of platform where advertising represents just a fraction of the business model.

    WeChat has become an ecosystem unto itself, an essential service used by nearly two billion customers to pay for just about everything in China. It features millions of “mini programs,” essentially apps built on top of the WeChat service. Tencent is making billions on top of this new ecosystem, taking a small cut of transactions inside its internal “Tenpay” system, nudging tens of millions of users to level up inside its gaming system, and yes, by offering advertising inside its popular “Moments” feed. Tencent even built a new search engine inside WeChat, a “walled garden” version of search that should prove insanely profitable if done right. Oh, and it gets all the data.

    Put simply, WeChat is a universe unto itself, a perfect mix of app store, commerce, social, payments, and search. It’s as if the entire Internet was shrunk into one app. Exactly the kind of world Facebook would like to see happen here in the United States.

    Only…WeChat evolved in China, where the concept of individual privacy is utterly foreign, where the state has complete control over the levers of the economy, and where Facebook has been banned for years. It’s a stretch to believe that Facebook could mimic Tencent’s meteoric rise here in the US (not to mention Western Europe and the rest of the world), but if there’s any conclusion to be drawn from Zuckerberg’s latest manifesto, it’s that his company is certainly going to try.

    Once Facebook has created an integrated WeChat-like platform reaching billions, it’d be a cinch to lure app developers – perhaps by undercutting Apple and Google’s 20-30 percent take rate, for starters. And anyone in the business of selling anything would also rush to the platform, posing an existential threat to Amazon’s portal-like model of e-commerce dominance. An obvious step would be to build search to unite it all, a necessary move that would dramatically undercut Google’s control of that market as well. The only safe place to be in this scenario seems to be Apple’s hardware business – except that company is itself in the midst of a pivot to services, exactly the kind of services that a Facebook WeChat clone will challenge.

    So, to summarize: By declaring “private conversations” as its new business model, Facebook can undermine the app store model driving all of mobile, unseat Amazon as the king of e-commerce, hollow out Google’s control of search, nip Apple’s transition to services in the bud, take a vig on every transaction across its ecosystem, and insinuate itself into the private, commercial, and public lives of every citizen on the Internet. If the company pulls this off – and yes, that’s a big if – we’ll look back on the past ten years, replete with all our fears of the social media’s dominance in our lives, as positively quaint in comparison.

    Never mind that man behind that curtain, folks.


     
  • feedwordpress 17:11:23 on 2019/01/25 Permalink
    Tags: , , columbia, data, , , , governance, , , ,   

    Our Data Governance Is Broken. Let’s Reinvent It. 


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    This is an edited version of a series of talks I first gave in New York over the past week, outlining my work at Columbia. Many thanks to Reinvent, Pete Leyden, Cap Gemini, Columbia University, Cossette/Vision7, and the New York Times for hosting and helping me.

    Prelude. 

    I have spent 30-plus years in the tech and media industries, mainly as a journalist, observer, and founder of companies that either make or support journalism and storytelling. When it comes to many of the things I am going to talk about here, I am not an expert. If I am expert at anything at all, it’s asking questions of technology, and of the media and marketing platforms created by technology. In that spirit I offer the questions I am currently pursuing, in the hope of sparking a dialog with this esteemed audience to further better answers.

    Some context: Since 1986, I’ve spent my life chased one story: The impact of technology on society. For whatever reason, I did this by founding or co-founding companies. Wired was kind of a first album, as it were, and it focused on the story broadly told. The Industry Standard focused on the business of the Internet, as did my conference Web 2Federated Media was a tech and advertising platform for high quality “conversational” publishers, built with the idea that our social discourse was undergoing a fundamental shift, and that publishers and their audiences needed to be empowered to have a new kind of conversation. Sovrn, a company I still chair, has a similar mission, but with a serious data and tech focus. NewCo, my last company (well, I’ve got another one in the works, perhaps we can talk about that during Q&A) seeks to illuminate the impact of companies on society.

    It’s Broke. Let’s Fix It.

    And it is that impact that has led me to the work I am doing now, here in New York. I moved here just last Fall, seeking a change in the conversation. To be honest, the Valley was starting to feel a bit…cloistered.

    A huge story – the very same story, just expanded – is once again rising. Only it’s just … more urgent. 25 years after the launch of Wired, the wildest dreams of its pages have come true. Back in 1992 we asked ourselves: What would happen to the world when technology becomes the most fundamental driver of our society? Today, we are living in the answer. Turns out, we don’t always like the result.

    Most of my career has been spent evangelizing the power of technology to positively transform business, education, and politics. But five or so years ago, that job started to get harder. The externalities of technology’s grip on society were showing through the shiny optimism of the Wired era. Two years ago, in the aftermath of an election that I believe will prove to be the political equivalent of the Black Sox scandal, the world began to wake up to the same thing.

    So it’s time to ask ourselves a simple question: What can we do to fix this?

    Let’s start with some context. My current work is split between two projects: One has to do with data governance, the other political media. How might they be connected? I hope by the end of this talk, it’ll make sense. 

    So let’s go. In my work at Columbia, I’m currently obsessed with two things. First,

    Data.

    How much have you thought about that word in the past two years?

    Given how much it’s been in the news lately, likely quite a lot. Big data, data breaches, data mining, data science…Today, we’re all about the data.

    And second….

    Governance.

    When was the last time you thought about that word?

    Government – well for sure, I’d wager that’s increased given who’s been running the country these past two years. But Governance? Maybe not as much.

    But how often have you put the two words together?

    Data Governance.

    Likely not quite as much.

    It’s time to fix that.

    Why?

    Because we have slouched our way into an architecture of data governance that is broken, that severely retards economic and cultural innovation, and that harms society as a whole.

    Let’s unpack that and define our terms. We’ll start with Governance.

    What is governance? It’s an …

    Architecture of control

    A regulatory framework that manages how a system works. The word is most often used in relation to political governance – which we care about a lot for the purposes of this talk – but the word applies to all systems, and in particular to corporations, which is also a key point in the research we’re doing.

    Governance in corporate context is “the system of rules, practices and processes by which a firm is directed and controlled.

    But in my work, when I refer to governance, I am referring to the “the system of rules, practices and processes by which a firm controls its relationship to its community.” Who’s that community? You, me, developers and partners in the ecosystem, for the most part. More on that soon. 

    Now, what is data? I like to think of it as…

    Unrefined Information.

    I’m not in love with this phrase, but again, this is a first draft of what I hope will grow to more refined (ha) work. Data is the core commodity from which information is created, or processed. Data has many attributes, not all of which are agreed upon. But I think it’s inarguable that the difference between data and information is …

    Human meaning.

    That’s Socrates, who thought about this shit, a lot. Information is data that means something to us (and possibly the entire universe, as it relates to the second law of thermodynamics. But physics is not the focus of this talk, nor is a possible fourth law of thermodynamics….).

    As we’ve learned – the hard way – over the past decade, there are a few very large companies which have purview over a massive catalog of meaningful data, meaningful not only to us, but to society at large. And it’s this societal aspect that, until recently, we’ve actively overlooked.  We’re in the midst of a grand data renaissance, which if history remotely echoes, I fervently hope will give rise to …

    A (Data) Enlightenment

    That’s John Locke, an Enlightenment philosopher. Allow me to pull back for second and attempt to lay some context for the work I hope to advance in the next few years. It starts with the Enlightenment, a great leap forward in human history (and the subject of a robust defense by Steven Pinker last year).

    Arguably the crowning document of the Enlightenment is…

    The United States Constitution

    This declaration of the rights of humankind (well mankind for the first couple of centuries) itself took more than three centuries to emerge (and cribbed generously from the French and English, channeling Locke and Hume). Our current political and economic culture is, of course, a direct descendant of this living document. American democracy was founded upon Enlightenment principles. And the cornerstone of Enlightenment ideas is …

    The Scientific Method

    That’s Aristotle, often credited with originating the scientific method, which is based on considered thesis formation, rigorous observation, comprehensive data collection, healthy skepticism, and sharing/transparency. The scientific method is our best tool, so far, for advancing human progress and problem solving.

    And the scientific method – the pursuit of truth and progress – all that turns on the data. Prompting the question….

    Who Has the Most (and Best) Data?

    This is the question we are finally asking ourselves, the answer to which is sounding alarms.  As we all know, we are in a renaissance, a deluge, an orgy of data creation. We have invented sophisticated new data sensing organs  –  digital technologies – that have delivered us superhuman powers for the discovery, classification, and sense-making of data.

    Not surprisingly, it is technology companies, driven as they are by the raw economics of profit-seeking capital and armed with these self-fulfilling tools of digital exploration and capture – that have initially taken ownership of this emerging resource. And that is a problem, one we’ve only begun to understand and respond to as a society. Which leads to an important question:

    Who Is Governing Data?

    In the US, anyway, the truth is, we don’t have a clear answer to this question. Our light touch regulatory framework created a tech-driven frenzy of company building, but it failed to anticipate massive externalities, now that these companies have come to dominate our capital markets. Clearly, the Tech Platform Companies have the most valuable data – at least if the capital markets are to be believed. Companies like Google. Facebook. Amazon. Apple.

    All of these companies have very strong governance structures in place for the data they control. These structures are set internally, and are not subject to much (if any) government regulation. And by extension, nearly all companies that manage data, no matter their size, have similar governance models because they are all drafting off those companies’ work (and success). This has created a phenomenon in our society, one I’ve recently come to call …

    The Default Internet Constitution

    Without really thinking critically about it, the technology and finance industries have delivered us a new Constitution, a fundamental governance document controlling how information flows through the Internet. It was never ratified by anyone, never debated publicly, never published with a flourish of the pen, and it’s damn hard to read. But, it is based on a discoverable corpus. That corpus, at its core, is based on …

    Terms of Service and EULAs

    Like it or not, there is a governance model for the US Internet and the data which flows across it: Terms of Service and End User Licensing Agreements. Of course, we actively ignore them – who on earth would ever read them? One researcher did the math, and figured it’d take 76 work days for the average American to read all of the policies she clicks past (and that was six years ago!).

    Of course, ignoring begets ignorance, and we’ve ignored Terms of Service at our peril. No one understands them, but we certainly should – because if we’re going to make change, we’ll want to change these Terms of Service, dramatically. They create the architecture that determines how data, and therefore societal innovation and value, flow around the Internet.

    And let’s be clear, these terms of service have hemmed data into silos. They’re built by lawyers, based on the desires of engineers who are – for the most part – far more interested in the product they are creating than any externalities those products might create.

    And what are the lawyers concerned with? Well, they have one True North: Protect the core business model of their companies.

    And what is that business model? Engagement. Attention. And for most, data-driven personalized advertising. (Don’t get me started about Apple being different. The company is utterly dependent on those apps animating that otherwise black slate of glass they call an iPhone).

    So what insures engagement and attention? Information refined from data.

    So let’s take a look at a rough map of what this Terms of Service-driven architecture looks like:

    The Mainframe Architecture

    Does this look familiar? If you’re a student of technology industry history, it should, because this is how mainframes worked in the early days of computing. Data compute, data storage, and data transport is handled by the big processor in the sky. The “dumb terminal” lives at the edge of the system, a ‘thin client’ for data input and application output. Intelligence, control, and value exchange lives in the center. The center determines all that occurs at the edge.

    Remind you of any apps you’ve used lately?

    But it wasn’t always this way. The Internet used to look like this:

    The Internet 1.0 Architecture

    I’m one of the early true believers in the open Internet. Do you remember that world? It’s mostly gone now, but there was a time, from about 1994 to 2012, when the Internet ran on a different architecture, one based on the idea that the intelligence should reside in the nodes – the site – not at the center. Data was shared laterally between sites. Of course, back then the tech was not that great, and there was a lot of work to be done. But we all knew we’d get there….

    …Till the platforms got there first. And they got there very, very well – their stuff was both elegant and addictive.

    But could we learn from Internet 1.0, and imagine a scenario inspired by its core lessons? Technologically, the answer is “of course.” This is why so many folks are excited by blockchain, after all (well that, and ICO ponzi schemes…). 

    But it might be too late, because we’ve already ceded massive value to a broken model. The top five technology firms dominate our capital markets. We’re seriously (over)invested in the current architecture of data control. Changing it would be a massive disruption. But what if we can imagine how such change might occur?

    This is the question of my work.

    So…what is my work?

    A New Architecture

    If we’re stuck in an architecture that limits the potential of data in our society, we must envision a world under a different kind of architecture, one that pushes control, agency, and value exchange back out to the node.

    Those of us old enough to remember the heady days of Web 1.0 foolishly assumed such a world would emerge unimpeded. But as Tim Wu has pointed out, media and technology run in cycles, ultimately consolidating into a handful of companies with their hands on the Master Switch – we live in a system that rewards the Curse of Bigness. If we are going to change that system, we have to think hard about what we want in its place.

    I’ve given this some thought, and I know what I want.

    Let The Data Flow

    Imagine a scenario where you can securely share your Amazon purchase data with Walmart, and receive significant economic value for doing so (I’ve written this idea up at length here). Of course, this idea is entirely impossible today. This represents a major economic innovation blocked.

    Or imagine a free marketplace for data that allows a would-be restaurant owner to model her customer base’s preferences and unique taste? (I’ve written this idea up at length here). Of course, this is also impossible today, representing a major cultural and small business innovation is impeded.

    Neither of these kinds of ideas are even remotely possible – nor are the products of thousands of similar questions entrepreneurs might ask of the data rotting in plain sight across our poorly architected data economy.

    We all lose when the data can’t flow. We lose collectively, and we lose individually. 

    But imagine if it was possible?!

    How might such scenarios become reality?

    We’re at a key inflection point in answering that question.

    2019 is the year of data regulation. I don’t believe any meaningful regulation will pass here in the US, but it’ll be the year everyone talks about it. It started with the CA/Facebook hearings, and now every self-respecting committee chair wants a tech CEO in their hot seat. Congress and the American people have woken up to the problem, and any number of regulatory fixes are being debated. Beyond the privacy shitstorm and its associated regulatory response, which I’d love to toss around during Q&A, the most discussed regulatory relief is anti-trust – the curse of bigness is best fixed by breaking up the big guys. I understand the goal, and might even support it, but I don’t think we need to even do that. Instead, I submit for your consideration one improbable, crazy, and possibly elegant solution.

    The Token Act

    I’m calling it the Token Act.

    It requires one thing: Every data processing service at a certain scale must deliver back to its customers any co-created data in machine readable format, easily portable to any other data processing service.

    Imagine the economic value unlocked, the exponential impact on innovation such a simple rule would have. Of course we must acknowledge the negative short term impact such a policy would have on the big guys. But it also creates an unparalleled opportunity for them – the token of course can include a vig – a percentage of all future revenue associated with that data, for the value the platform helped to create. This model could drive a far bigger business in the long run, and a far healthier one for all parties concerned.

    I can’t prove it yet, but I sense this approach could 10 to 100X our economy. We’ve got some work to do on proving that, but I think we can.

    Imagine what would occur if the data was allowed to flow freely. Imagine the upleveling of how firms would have to compete. They’d have to move beyond mere data hoarding, beyond the tending of miniature walled gardens (most app makers) and massive walled agribusinesses (in the case of the platforms – and ADM and Monsanto, but that’s another chapter in the book, one of many).

    Instead, firms would have to compete on creating more valuable tokens  – more valuable units of human meaning. And they’d encourage sharing those tokens widely – with the fundamental check of user agency and control governing the entire system.

    The bit has flipped, and the intelligence would once again be driven to the nodes.

    To us!

    But the Token Act is just an exercise in envisioning a society governed by a different kind of data architecture. There are certainly better or more refined ideas.

    And to get to them, we really need to understand how we’re governed today. And now that I’ve gotten nearly to the end of my prepared remarks, I’ll tell you what I’m working on at Columbia with several super smart grad students:

    Mapping Data Flows

    If we are going to understand how to change our broken architecture of data flows, we need to deeply understand where we are today. And that means visualizing a complex mess. I’m working with a small team of researchers at Columbia, and together we are turning the Terms of Service at Amazon, Apple, Facebook and Google into a database that will drive an interactive visualization – a blueprint of sorts for how data is governed across the US internet. We’re focusing on the advertising market, for obvious reasons, but it’s my hope we might create a model that can be applied to nearly any information rich market. It’s early stages, but our goal is to have something published by the end of May.

    Finally, Advertising

    I’ve not spoken much about advertising during this talk, and that was purposeful. I’ve written at length about how we came to the place we now inhabit, and the role of programmatic advertising in getting us there.

    Truth is, I don’t see advertising as the cause of this problem, but rather an outgrowth of it. If you offer any company a deal that puts new customers on a platter, as Google did with AdWords, or Facebook has with NewsFeed, well, there’s no way those companies will refuse. Every major advertiser has embraced search and social, as have millions of smaller ones.

    Our problem is simply this: The people who run technology platforms don’t actually understand the power and limitations of their systems, and let’s be honest, nor do we. Renee Di Resta has pointed this out in recent work around Russian interference in our national dialog and elections: Any system that allows for automated processing of messages is subject to directed, sophisticated abuse. The place for regulation is not in advertising (even though that’s where it’s begun with the Honest Ads Act), it’s in how the system works architecturally.

    But advertisers must be highly aware of this transitional phase in the architecture of a system that has been a major source of revenue and business results. We must imagine what comes next, we must prepare for it, and perhaps, just perhaps, we should invent it, or at the very least play a far more active role than we’re playing currently.

    I believe that if together – industry, government, media and consumers collectively – if we unite to address the core architectural issues inherent to how we manage data, in the process giving consumers economic, creative, and personal agency over the data they co create with platforms, the question of toxic advertising will disappear faster than it arose.

    But I’ve talked (or written) long enough. Thank you so much for coming (for reading), and for being part of this conversation. Now, let’s start it.

     
  • feedwordpress 18:01:49 on 2019/01/02 Permalink
    Tags: , cannabis, , data, , , , , , , , , , , ,   

    Predictions 2019: Stay Stoney, My Friends. 


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    If predictions are like baseball, I’m bound to have a bad year in 2019, given how well things went the last time around. And given how my own interests, work life, and physical location have changed of late, I’m not entirely sure what might spring from this particular session at the keyboard.

    But as I’ve noted in previous versions of this post (all 15 of them are linked at the bottom), I do these predictions in something of a fugue state – I don’t prepare in advance. I just sit down, stare at a blank page, and start to write.

    So Happy New Year, and here we go.

    1/ Global warming gets really, really, really real. I don’t know how this isn’t the first thing on everyone’s mind already, with all the historic fires, hurricanes, floods, and other related climate catastrophes of 2018. But nature won’t relent in 2019, and we’ll endure something so devastating, right here in the US, that we won’t be able to ignore it anymore. I’m not happy about making this prediction, but it’ll likely take a super Sandy or a king-sized Katrina to slap some sense into America’s body politic. 2019 will be the year it happens.

    2/ Mark Zuckerberg resigns as Chairman of Facebook, and relinquishes his supermajority voting rights. Related, Sheryl Sandberg stays right where she is. I honestly don’t see any other way Facebook pulls out of its nosedive. I’ve written about this at length elsewhere, so I will just summarize: Facebook’s only salvation is through a new system of governance. And I mean that word liberally – new governance of how it manages data across its platform, new governance of how it works with communities, governments, and other key actors across its reach, and most fundamentally, new governance as to how it works as a corporate entity. It all starts with the Board asserting its proper role as the governors of the company. At present, the Board is fundamentally toothless.

    3/ Despite a ton of noise and smoke from DC, no significant federal legislation is signed around how data is managed in the United States. I  know I predicted just a few posts ago that 2019 will be the year the tech sector has to finally contend with Washington. And it will be…but in the end, nothing definitive will emerge, because we’ll all be utterly distracted by the Trump show (see below). Because of this, unhappily, we’ll end up governed by both GDPR and California’s homespun privacy law, neither of which actually force the kind of change we really need.

    4/ The Trump show gets cancelled. Last year, I said Trump would blow up, but not leave. This year, I’m with Fred, Trump’s in his final season. We all love watching a slow motion car wreck, but 2019 is the year most of us realize the car’s careening into a school bus full of our loved ones. Donald Trump, you’re fired.

    5/ Cannabis for the win. With Sessions gone and politicians of all stripes looking for an easy win, Congress will pass legislation legalizing cannabis. Huzzah!!!! Just in time, because…

    6/ China implodes, the world wobbles. Look, I’m utterly out of my depth here, but something just feels wrong with the whole China picture. Half the world’s experts are warning us that China’s fusion of capitalism and authoritarianism is already taking over the world, and the other half are clinging to the long-held notion that China’s approach to nation building is simply too fragile to withstand democratic capitalism’s demands for transparency. But I think there may be other reasons China’s reach will extend its grasp: It depends on global growth and optimistic debt markets. And both of those things will fail this year, exposing what is a marvelous but unsustainable experiment in managed markets. This is a long way of backing into a related prediction:

    7/ 2019 will be a terrible year for financial markets. This is the ultimate conventional wisdom amongst my colleagues in SF and NY, even though I’ve seen plenty of predictions that Wall St. will have a pretty good year. I have no particular insight as to why I feel this way, it’s mainly a gut call: Things have been too good, for too long. It’s time for a serious correction.

    8/ At least one major tech IPO is pulled, the rest disappoint as a class. Uber, Lyft, Slack, Pinterest et al are all expected this year. But it won’t be a good year to go public. Some will have no choice, but others may simply resize their businesses to focus on cash flow, so as to find a better window down the road.

    9/ New forms of journalistic media flourish. It’s well past time those of us in the media world take responsibility for the shit we make, and start to try significant new approaches to information delivery vehicles. We have been hostages to the toxic business models of engagement for engagement’s sake. We’ll continue to shake that off in various ways this year – with at least one new format taking off explosively. Will it have lasting power? That won’t be clear by year’s end. But the world is ready to embrace the new, and it’s our jobs to invest, invent, support, and experiment with how we inform ourselves through the media. Related, but not exactly the same…

    10/A new “social network” emerges by the end of the year. Likely based on messaging and encryption (a la Signal or Confide), the network will have many of the same features as the original Facebook, but will be based on a paid model. There’ll be some clever new angle – there always is – but in the end, it’s a way to manage your social life digitally. There are simply too many pissed off and guilt-ridden social media billionaires with the means to launch such a network – I mean, Insta’s Kevin Systrom, WhatsApp’s Jan and Brian, not to mention the legions of mere multi-millionaires who have bled out of Facebook’s battered body of late.

    So that’s it. On a personal note, I’ll be happily busy this year. Since moving to NY this past September, I’ve got several new projects in the works, some still under wraps, some already in process. NewCo and the Shift Forum will continue, but in reconstituted forms.  I’ll keep up with my writing as best I can; more likely than not most of it will focus the governance of data and how its effect our national dialog. Thanks, as always, for reading and for your emails, comments, and tweets. I read each of them and am inspired by all. May your 2019 bring fulfillment, peace, and gratitude.

    Previous predictions:

    Predictions 2018

    2018: How I Did

    Predictions 2017

    2017: How I Did

    Predictions 2016

    2016: How I Did

    Predictions 2015

    2015: How I Did

    Predictions 2014

    2014: How I Did

    Predictions 2013

    2013: How I Did

    Predictions 2012

    2012: How I Did

    Predictions 2011

    2011: How I Did

    Predictions 2010

    2010: How I Did

    2009 Predictions

    2009 How I Did

    2008 Predictions

    2008 How I Did

    2007 Predictions

    2007 How I Did

    2006 Predictions

    2006 How I Did

    2005 Predictions

    2005 How I Did

    2004 Predictions

    2004 How I Did

     
  • feedwordpress 17:36:20 on 2018/11/05 Permalink
    Tags: , data, , , ,   

    Lazy Ad Buying Is Killing The Open Web. 


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    But…I just *bought* a robe. I don’t want another one.

    If you’re read my rants for long enough, you know I’m fond of programmatic advertising. I’ve called it the most important artifact in human history, replacing  the Macintosh as the most significant tool ever created.

    So yes, I think programmatic advertising is a big deal. As I wrote in the aforementioned post:

    “I believe the very same technologies we’ve built to serve real time, data-driven advertising will soon be re-purposed across nearly every segment of our society. Programmatic adtech is the heir to the database of intentions – it’s that database turned real time and distributed far outside of search. And that’s a very, very big deal. (I just wish I had a cooler name for it than “adtech.”)” 

    But lately, I’m starting to wonder if perhaps adtech is failing, not for any technical reason, but because the people leveraging are complicit in what might best be called a massive failure of imagination.

    I’m about to go on a rant here, so please forgive me in advance.

    But honestly, who else out there is sick of being followed by ads so stupid a fourth grader could do a better job of targeting them?

    Case in point is the ad above. I took this screen shot from my phone this past weekend while I was reading a New York Times article. The image – of a robe Amazon wanted me to buy – was instantly annoying, because I had in fact purchased a robe on Amazon several days before. Why on earth was Amazon retargeting me for a product I just bought?!

    But wait, it gets worse! As I perused the next Times article, this ad shows up:

    That would have made sense *after I bought a robe, but…” I bought slippers two weeks ago. So WTF?

    You might think this ad makes more sense. If the dude buys a robe, makes sense to try to sell him a new pair of slippers, no? Well, sure, but only if that same dude didn’t buy a new pair of slippers two weeks ago. Which, in fact, I did just do.

    So, yeah, this ad sucks as well. Not only is it not useful or relevant, it’s downright annoying. The vast machinery of adtech has correctly identified me as a robe-and-slippers-buying customer. But it’s failed to realize *I’ve already bought the damn things.*

    Is it possible that adtech is this stupid? This poorly instrumented? I mean, are programmatic buyers simply tagging visitors who land on ecommerce pages (male robe intender?) without caring about whether those visitors actually bought anything?

    Are the human beings responsible for setting the dials of programmatic just this lazy?

    Yes.

    I’ve been a critical observer of adtech over the past ten or so years, and one consistent takeaway is this: If there’s a way for a buyer to cut corners, declare an easy win, and keep doing things they way the’ve always been done, well, they most certainly will.

    But why does it have to be this way? Digging into the examples above yields an extremely frustrating set of facts. Consider the data the adtech infrastructure either got *right* about me as a customer, or could have gotten right:

    • I am a frequent ecommerce customer, usually buying on Amazon
    • I recently purchased both a robe and some slippers
    • I am reading on the New York Times site as a logged on (IE data rich) customer of the Times‘ offerings

    These are just the obvious data points. My mobile ID and cookies, all of which are available to programmatic buyers, certainly indicate a high household income, a propensity to click on certain kinds of ads, a rich web browsing history reflecting a thickly veined lodestar of interest data, among countless other possible inputs.

    Imagine if a programmatic campaign actually paid attention to all this rich data? Start with the fact I just purchased a robe and slippers. What are products related to those two that Amazon might show me? Well, according to its own “people who bought this item also bought” algorithms, folks who bought men’s robes also bought robes for the women in their life. Now there’s a cool recommendation! I might have clicked on an ad that showed a cool robe for my wife. But no, I’m shown an ad for a product I already have.

    Why?

    I’ve got a few calls in to verify my hunch, but I suspect the ugly truth is pure laziness on the part of the folks responsible for buying ads. Consider: The average cost for a thousand views (CPM) of a targeted programmatic advertisement hovers between ten cents (yes, ten pennies) to $2.  With costs that low, the advertising community can afford to waste ad inventory.

    Let’s apply that reality to our robe example. Let’s say the robe costs $60, and yields a $20 profit for our e-commerce advertiser, not including marketing costs. That means that same advertiser is can spend upwards of $19.99 per unit on advertising (more, if a robe purchaser turns out to be a “big basket” e-commerce spender).  So what does our advertiser do? Well, they set a retargeting campaign aimed anyone who ever visited our erstwhile robe’s page.  With CPMs averaging around a buck, that robe’s going to follow nearly 20,000 folks around the internet, hoping that just one  of them converts.

    Put another way, programmatic advertising is a pure numbers game, and as long as the numbers show one penny of profit, no one is motivated to make the system any better. I’ve encountered many similar examples of ad buyers ignoring high-quality data signals, preferring instead to “waste reach” because, well, it’s just easier to set up campaigns on one or two factors. Inventory is cheap. Why not?

    This is problematic. What’s the point of having all that rich (and hard won) targeting data if buyers won’t use it, and consumers don’t benefit from it? An ecosystem that fails to encourage innovation will stagnate and lose share to walled gardens like Facebook, Google, and others. If the ads suck on the open web (and they do), then consumers will either install ad blockers (and they are), or abandon the open web altogether (and they are).

    We can do so much better. Shouldn’t we try?

     

     

     
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