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  • feedwordpress 15:59:20 on 2019/04/24 Permalink
    Tags: , , , data policy, , , , , , 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 17:11:23 on 2019/01/25 Permalink
    Tags: , , columbia, , data policy, , , 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 20:07:01 on 2018/10/31 Permalink
    Tags: , , data policy, , , food, , , , , , small business   

    After the Token Act: A New Data Economy Driven By Small Business Entrepreneurship 


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    Gramercy Tavern in New York City

    If Walmart can leverage data tokens to lure Amazon’s best customers away, what else is possible in a world of enabled by my fictional Token Act?

    Well, Walmart vs. Amazon is all about big business – a platform giant (Amazon) disrupting an OldBigCo (Walmart and its kin). Over the past two decades, Amazon bumped Walmart out of the race to a trillion-dollar market cap, and the OldCo from Bentonville had to reset and play the role of the upstart. The Token Act levels the playing field, forcing both to win where it really matters: In service to the customer.

    But while BigCos are sexy and well known, it’s the small and medium-sized business ecosystem that determines whether or not we have an economy of mass flourishing.  So let’s explore the Token Act from the point of view of a small business startup, in this case, a new neighborhood restaurant. I briefly touched upon this idea in my set up post, Don’t Break Up The Tech Oligarchs. Force Them To Share Instead.  (If you haven’t already, you might want to read that post before this one, as I lay out the framework in which this scenario would play out.) What I envision below assumes the Token Act has passed, and we’re at least a year or two into its adoption by most major data players. Here we go…

    ***

    Fresh off her $2,700 win from Walmart, Michelle decides she’s ready to lean into a lifelong dream: Starting a restaurant in her newly adopted neighborhood of Chelsea in New York City. Since moving to the area from California, she’s noticed two puzzling trends: First, a dearth of interesting mid- to high-end dinner spots walking distance from her new place, and second, what appears to be higher-than-average vacancy rates for the retail storefronts in the same general area. It appears to be a buyer’s market for retail restaurant space in Chelsea. So why aren’t new places launching? She read the Times’ piece on vacancies a few years ago (before the Token Act passed) and was left just as puzzled as before – seems like there’s no rhyme or reason to the market.

    Michelle wants to start a high end American gastro pub – the kind of place she loved back when she lived in Northern California (she’s fond of Danny Meyers’ Gramercy Tavern, pictured above, but it’s a bit too far away from her new place). She has a strong hunch that such a place would be a hit in her new neighborhood, but she’s not sure her new neighbors will agree.

    Now starting a restaurant requires a certain breed of insanity – they say the best way to make a small fortune in the business is to start with a large one. The truth is, launching restaurants has historically been a crap shoot – you might find the best talent, the best designer, and the best location – but if for some reason you don’t bring the je ne sai quois, the place will fail within months, leaving you and your partners millions of dollar poorer.

    It’s that  je ne sai quois that Michelle is determined to reveal.  The tools she will leverage? The newly liberated resources of data tokens.

    Before we continue, allow me to draw your attention back to the rise of search, indeed, the very era which begat Searchblog in the early 2000s. Google Adwords launched in 2000, and within a few years, the media world had been turned upside down by what I termed The Database of Intentions.  As if by magic, people everywhere could suddenly ask new kinds of questions, finding themselves both surprised and delighted by the answers they received.

    Gates-Line compliant ecosystem quickly developed on top of this new platform, driven by an emerging industry of search engine marketing and optimization. SEO/SEM sprung into existence to help small and medium sized businesses take advantage of the Google platform – by 2006 the industry stood at nearly $10 billion in spend, growing more than 60 percent year on year. Adwords grew from zero to millions of advertisers by connecting to a long tail of small businesses that took advantage of an entirely new class of revealed information: The intents, desires, and needs of tens of millions of consumers, who relentlessly poured their queries into Google’s placid and unblinking search box.

    Were you a limo service in the Bronx looking for new customers? It paid huge dividends to purchase Adwords like “car service bronx” and “best limo manhattan.” Were you a dry cleaner in West LA hoping to expand? Best be first in line when customers typed in “best cleaners Beverly Hills.” Selling heavy machinery to construction services in the midwest? If you don’t own keywords like “caterpillar dealer des moines” you’d lose, and quick, to whoever did optimize to phrases like that.

    My point is simply this: Adwords was a freaking revolution, but it ain’t nothing compared to what will happen if we unleash data tokens on the world.

    ***

    Ok, back to Michelle and her new restaurant. Of course Michelle will leverage Adwords, and Facebook, and any other advertising service to help her new business grow. But none of those services can help her figure out her je ne sai quois – for that, she needs something entirely novel. She needs a new question machine. And the ecosystem that develops around data tokens will offer it.

    Thanks to her Walmart experience, Michelle has become aware of the power of personal data. She’s also read up on the Token Act, the new law requiring all data players at scale to allow individuals to create machine-readable data tokens that can be exchanged for value as directed by the consumer. After doing a bit of research, she stumbles across a startup called OfferExchange, which manages “Token Offers” on behalf of anyone who might want to query TokenLand. OfferExchange is a spinout from ProtocolLabs, a pioneer in secure blockchain software platforms like Filecoin. It’s still early in TokenLand, so an at-scale Google of the space hasn’t emerged. OfferExchange works more like a bespoke yet platform-based research outfit – the firm has a sophisticated website and impressive client list. It uses Facebook, Twitter, LiveRamp, and Instagram to identify potential token-creating consumers, then solicits those individuals with offers of cash or other value in exchange for said tokens.

    Michelle does a Crunchbase search for OfferExchange and sees it’s backed by Union Square Ventures and Benchmark, which gives her some comfort – those firms don’t fund fly-by-night hucksters. And OfferExchange site is impressive – in less than five minutes, it guides her through the construction of an elegant query. Here’s how the process works:

    First, the site asks Michelle what her goal is. “Starting a restaurant in New York City,” she responds. The site reconstructs around her answer, showing suggested data repositories she might mine. “Restaurants, New York City,” reads the top layer of a directory-like page. Underneath are several categories, each populated with familiar company names:

    • Restaurant Reservation and Review Services
      • OpenTable Google Resy Yelp Eat24 Facebook (more)
    • Food Delivery Services
      • GrubHub Uber Eats PostMates InstaCart (more)
    • Transportation Services
      • Uber Lyft Juno Via (more)
    • Real Estate Services (Commercial)
      •  LoopNet DocuSign CompStak (more)
    • Location Services 
      • Foursquare Uber Lyft Google NinthDecimal (more)
    • Financial Services
      • American Express Visa Mastercard Apple Pay Diners Club (more)

    And so on – if she wished, Michelle could dig into dozens of categories related to her initial “restaurant New York City” search.

    Michelle’s imagination sparks – the kinds of queries she could ask of these services is mind blowing. She could  limit her query to people who live within walking distance of her neighborhood, asking her *actual neighbors* for tokens that tell her what restaurants they eat at, when they eat there, the size of their checks, related reviews, abandoned reservations, the works. She might discover that folks like Indian takeout on Mondays, that they rarely spend more than $100 on a meal on Tuesdays, but that they splurge on the weekends. She could discover the percentage of diners in Chelsea who travel more than two miles by car service to eat out at a place similar to the one she has in mind, and what the size of the check might be when they do. She can also check historical average rents for restaurants in her zip code, over time, which will certainly help with negotiating her lease. The possibilities are endless.

    Put another way, with OfferExchange’s services, Michelle can litigate the merde out of her je ne sai quois.

    *** 

    This post is getting long, so I’ll stop here and pull back for a spot of Thinking Out Loud. I could continue the story, imagining the process of the token offer Michelle would put out through OfferExchange’s platform, but suffice to say, she’d be willing to pay upwards of $5-20 per potential customer for their data. The marketing benefit alone – alerting potential customers in the neighborhood that she’s exploring a new restaurant in the area – is worth tens of thousands already. And of course, OfferExchange can connect anyone who offers their tokens to Michelle’s new project a discount on their first meal at the restaurant, should it actually launch. Cool!

    But let’s stop there and consider what happens when local entrepreneurs have access to the information currently silo’d across thousands of walled garden services like Uber, LoopNet, Resy, and of course Facebook and Google. While better data won’t insure that Michelle’s restaurant will succeed, it certainly increases the odds that it won’t fail. And it will give both Michelle and her investors – local banks, savvy friends and family members – much more conviction that her new enterprise is viable. Take this local restaurant example and apply it to all manner of small business – dry cleaners, hardware stores, bike shops – and this newly liberated class of information enables an explosion of efficiency, investment, and, well, flourishing in what has become, over the past four decades, a stagnant SMB environment.

    Is this Money Ball for SMB? Perhaps. And yes, I can imagine any number of downsides to this new data economy. But I also believe the benefits would far outweigh the downsides. Under the Token Act as I envision it, co-creators of the data – the services like Uber, OpenTable, or Facebook – have the right to charge a vig for the data being monetized. Sure, it’d be possible for an entrepreneur to steal customers via tokens, but I’m going to guess the economic value of allowing your customers to discover new use cases for their data will dwarf the downside of possibly losing those customers to a new competitor. Plus, this new competitive force will drive everyone to play at a higher level, focusing not on moats built on data silos, but instead on what really matters: A highly satisfied customer. That’s certainly Michelle’s goal, and the goal of every successful local business. Why shouldn’t it also be the goal of the data giants?

     
  • feedwordpress 03:26:39 on 2018/09/20 Permalink
    Tags: , data policy, , , philosophy, , , software   

    If Software Is Eating the World, What Will Come Out the Other End? 


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    So far, it’s mostly shit.

    Seven or so years ago, a famous VC penned a manifesto of sorts. Writing at a time the world was still skeptical of the dominance to which his industry has now ascended (to think, such a time existed, and so few years ago!), Marc Andreessen had a message for the doubters, the naysayers, and the Wall St. analysts who were (credibly!) claiming that his investments amounted to not much more than a bubble:

    Software, he claimed, was eating the world.

    Seven years later, no one can dispute Andreessen’s prescience. The man was right: If you had purchased a basket of his favorite stocks back then – he name-checked Apple, Amazon, and Facebook directly – you’d be up at least 10X, if not more. Software, it seems, has indeed eaten the world, and those smart (and rich) enough to put money into technology, as Andreessen has been, have done very, very well for themselves.

    Of course, not many people have in fact been that smart. As of last year, ten percent of investors own 84 percent of the stock market, and that ratio only gets worse as time goes by. Most of our society simply isn’t benefiting from this trend of software eating the world.  In fact, most of them live in the very world that software ate.

    ***

    We – us, all of us – have turned the world to data. Some of us – the founders of software companies, the funders of those founders, the cheerleaders who run the capital markets – took that data and used it to change the world. Along the way, the world didn’t disappear like some unfortunate animal distending a python’s midsection. No, the world remains.

    Who are we now that we’ve been eaten? What have we become?

    These are questions, it turns out, that almost none of technology’s leadership have deeply pondered. It certainly never came up in Andreessen’s manifesto. And it’s manifestly evident in the behavior of our most treasured technology founders. They are puzzled by these newfound demands from United States senators and European socialists. Don’t they understand that regulation is damage to be routed around?

    ***

    But the world is not just software. The world is physics, it’s crying babies and shit on the sidewalk, it’s opioids and ecstasy, it’s car crashes and Senate hearings, lovers and philosophers, lost opportunities and spinning planets around untold stars. The world is still real. Software hasn’t eaten it as much as bound it in a spell, temporarily I hope, while we figure out what comes next.

    Software – data, code, algorithms, processing – software has dressed the world in new infrastructure. But this is a conversation, not a process of digestion. It is a conversation between the physical and the digital, a synthesis we must master if we are to avoid terrible fates, and continue to embrace fantastic ones.

     

     
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