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.
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. Cross posted from Searchblog.
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 chasing one story: The impact of technology on society. For whatever reason, I did this by founding or co-founding companies. Wiredwas kind of a first album, as it were, and it focused on the story broadly told. The Industry Standardfocused on the business of the Internet, as did my conference Web 2. Federated 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.
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 relationshipto 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.
Social conversations about difficult and complex topics have arcs – they tend to start scattered, with many threads and potential paths, then resolve over time toward consensus. This consensus differs based on groups within society – Fox News aficionados will cluster one way, NPR devotees another. Regardless of the group, such consensus then becomes presumption – and once a group of people presume, they fail to explore potentially difficult or presumably impossible alternative solutions.
This is often a good thing – an efficient way to get to an answer. But it can also mean we fail to imagine a better solution, because our own biases are obstructing a more elegant path forward.
This is my sense of the current conversation around the impact of what Professor Scott Galloway has named “The Four” – the largest and most powerful American companies in technology (they are Apple, Amazon, Google, and Facebook, for those just returning from a ten-year nap). Over the past year or so, the conversation around technology has become one of “something must be done.” Tech was too powerful, it consumed too much of our data and too much of our economic growth. Europe passed GDPR, Congress held ineffectual hearings, Facebook kept screwing up, Google failed to show up…it was all of a piece.
The conversation evolved into a debate about various remedies, and recently, it’s resolved into a pretty consistent consensus, at least amongst a certain class of tech observers: These companies need to be broken up. Antitrust, many now claim, is the best remedy for the market dominance these companies have amassed.
It’s a seductive response, with seductive historical precedent. In the 1970s and 80s, antitrust broke up AT&T, ultimately paving the way for the Internet to flourish. In the 90s, antitrust provided the framework for the government’s case against Microsoft, opening the door for new companies like Google and Facebook to dominate the next version of the Internet. Why wouldn’t antitrust regulation usher in #Internet3? Imagine a world where YouTube, Instagram, and Amazon Web Services are all separate companies. Would not that world be better?
Perhaps. I’m not well read enough in antitrust law to argue one way or the other, but I know that antitrust turns on the idea of consumer harm (usually measured in terms of price), and there’s a strong argument to be made that a free service like Google or Facebook can’t possibly cause consumer harm. Then again, there are many who argue that data is in fact currency, and The Four have essentially monopolized a class of that currency.
But even as I stare at the antitrust remedy, another solution keeps poking at me, one that on its face seems quite elegant and rather unexplored.
The idea is simply this: Require all companies who’ve reached a certain scale to build machine-readable data portability into their platforms. The right to data portability is explicit in the EU’s newly enacted GDPR framework, but so far the impact has been slight: There’s enough wiggle room in the verbiage to hamper technical implementation and scope. Plus, let’s be honest: Europe has never really been a hotbed of open innovation in the first place.
But what if we had a similar statute here? And I don’t mean all of GDPR – that’s certainly a non starter. But that one rule, that one requirement: That every data service at scale had to stand up an API that allowed consumers to access their co-created data, download a copy of it (which I am calling a token), and make that copy available to any service they deemed worthy?
Imagine what might come of that in the United States?
I’m not a policy expert, and the devil’s always in the details. So let me be clear in what I mean when I say “machine-readable data portability”: The right to take, via an API, what is essentially a “token” containing all (or a portion of) the data you’ve co created in one service, and offer it, with various protections, permission, and revocability, to another service. In my Senate testimony, I gave the example of a token that has all your Amazon purchases, which you then give to Walmart so it can do a historical price comparison and tell you how much money you would save if you shopped at its online service. Walmart would have a powerful incentive to get consumers to create and share that token – the most difficult problem in nearly all of business is getting a customer to switch to a similar service. That would be quite a valuable token, I’d wager*.
Should be simple to do, no? I mean, don’t we at least co-own the information about what we bought at Amazon?
Well, no. Not really. Between confusing terms of service, hard to find dashboards, and confounding data reporting standards, The Four can both claim we “own our own data” while at the same time ensuring there’ll never be a true market for the information they have about us.
So yes, my idea is easily dismissed. The initial response I’ve had to it is always some variation of: “There’s no way The Four would let this happen.” That’s exactly the kind of biases I refer to above – we assume that The Four control the dialog, that they either will thwart this idea through intensive lobbying, clever terms of service, and soft power, or that the idea is practically impossible because of technical or market limitations. To that I ask….Why?
Why is it impossible for me to tokenize all of my Lyft ride data, and give for free it to an academic project that is mapping the impact of ride sharing on congestion in major cities? Why is it impossible for a small business owner to create an RFP for all OpenTable, Resy, and other dining data, so she can determine the best kind of restaurant to open in her neighborhood? I’m pretty certain she’d pay a few bucks a head for that kind of data – so why can’t I sell that information to her (with a vig back to OpenTable and Resy) if the value exchange is there to be monetized? Why can’t I tokenize and sell my Twitter interactions to a brand (or more likely, an agency or research company) interested in understanding the mind of a father who lives in Manhattan? Why can’t I tokenize and trade my Spotify history for better recommendations on live shows to see, or movies to watch, or books to read? Or, simply give it to a free service that’s sprung up to give me suggestions about new music to check out?
Why can’t an ecosystem of agents, startups, and data brokers emerge, a new industry of information processing not seen since the rise of search optimization in the early aughts, leveraging and arbitraging consumer information to create entirely new kinds of businesses driven by insights currently buried in today’s data monopolies?
Such a world would be fascinating, exciting, sometimes sketchy, and a hell of a lot of fun. It’d be driven by the individual choices of millions of consumers – choosing which agents to trust, which tokens to create, which trades felt fair. There’s be fails, there’d be fraud, there’d be bad actors. But over time, the good would win over the bad, because the decision making is distributed across the entire population of Internet users. In short, we’d push the decision making to the node – to us. Sure, we’d do stupid things. And sure, the hucksters and the hustlers would make short term killings. But I’ll take an open system like this over a closed one any day of the week, especially if the open system is governed by an architecture empowering the individual to make their own decisions.
It’s be a lot like the Internet was once imagined to be.
I’ve been noodling on such an ecosystem, and I’m convinced it could dwarf our current Internet in terms of overall value created (and credit where credit is due, The Four have created a lot of value). It’d run laps around The Four when it comes to innovation – tens of thousands of new companies would form, all of them feeding off the newly liberated oxygen of high quality, structured, machine readable data. Trusted independent platforms for value exchange would arise. Independent third party agents would munge tokens from competing services, verifying claims and earning the trust of consumers (will Walmart really save you a thousand bucks a year?! We can prove it, or not!). Huge platforms would develop for the processing, securitization, permissioning, and validation of our data. Man, it’d feel like…well, like the recumbent, boring old Internet was finally exciting again.
There’s no technical reason why this world doesn’t exist. The progenitors of the Web have already imagined it, heck, Tim Berners Lee recently announced he’s working pretty much full time on creating a system devoted to the foundational elements needed for it to blossom.
But until we as a society write machine-readable data portability into law, such efforts will be relegated to interesting side shows. And more likely than not, we’ll spend the next few years arguing about breaking up The Four, and let’s be honest, that’s an argument The Four want us to have, because they’re going to win it (more money, better lawyers, etc. etc.). Instead, we should just require them – and all other data services of scale – to free the data they’ve so far managed to imprison. One simple new law could change all of that. Shouldn’t we consider it?
*In another post, I’ll explore this example in detail. It’s really, really fascinating.
Apple dropped a bomb at their global developer conference: It’s stepping in to curb phone addiction. This is a big blow to the ad-driven platforms that have hijacked our phones and our attention.
Right before Craig Federighi, Apple’s head of software, demonstrated the latest advancements in emojis, including tongue detection, he announced the release of “a comprehensive set of built in features to help you limit distraction.” This is a big deal, because until now, we have been fending for ourselves — and we’re totally outgunned in the war for attention.
Attention is the oxygen of advertising.
There’s a reason why phones are so addictive: ad money. You paid for your phone, but most of the things you do on it are powered by advertising. Google, Facebook, Instagram and Twitter all make their money from advertising.
Those companies compete with each other for your attention — fighting to have you on their properties a little longer. With your attention, they have opportunities, without it, they have nothing.
In bowing to China, Apple forces us to contemplate the true role of business in society
“China is likely to emerge in the next few years as the world’s largest supplier of capital.” — Brookings Institute, Jan. 2017
A clash of fundamentally competing economic philosophies broke into the mainstream news this weekend, with the fate of democratic capitalism hanging in the balance. And while it’s likely too early to call a winner, the trends are certainly not looking good for democracy as we understand it in the west.*
First, the news. Bowing to Chinese law, Apple will be storing the keys to its Chinese customers’ data inside China — subjecting that information to Chinese legal oversight, a system which, as Yonatan Zunger points out, is markedly distinct from that of the United States, where Apple had heretofore protected its Chinese customers.
Apple has agreed that the encryption keys for iCloud user accounts for Chinese persons will be stored in China, as Reuters reported today.
If you aren’t familiar with Chinese law and the situation around this, this may seem relatively innocuous: a company is doing business in a country, and complying with that country’s local laws. What’s significant about this is that it represents a major change in how legal process works.
Under most countries’ laws, people have some kind of rights around their own information. The government has the right to demand such information subject to things like subpoenas and warrants; those have to be signed by judges, and the recipient of one of them can immediately go to the judge and contest them, as well as contest the use of any evidence derived later based on evidence collected illegally. That is, there’s legal process between governments and people’s data — and companies which deal in user data fight this process aggressively, because their users’ trust ultimately depends on it.
Houston’s tragedy is still unfolding, but its lessons can already be drawn. When an area the size of fifteen Manhattans floods, there’s plenty of blame to throw around. But in the end, it all comes down to money, in particular, the kind of money one can make by encouraging short term thinking.
Many are claiming Hurricane Harvey’s wrath proves climate change is real — and that our current administration’s steadfast ignorance of that fact should be called out. It’s hard to disagree, but also hard to believe anything will change. After all, we already knew Houston had a major weather problem: Journalists and academics had pointed that fact out repeatedly, and repeatedly, society has ignored that fact. Why?
In the end, Harvey’s destruction has as much to do with intentional ignorance — essentially, economic collusion between local business and local politics — as with anything else. Over the past four decades, Houston’s native ecosystem of bayous and flood plains have become a sea of impermeable concrete: hundreds of square miles of strip malls, office parks, housing developments, and roadways. When you pave your lungs with asphalt, flooding is your inevitable cancer. Along the way, untold legions of local developers and small businessmen got rich. But now that the floods have come, it will be the US taxpayer left with the bill, a bill that will be many times higher than the economic cost of a more fact-based and proactive approach to growth.
Apple is sitting on an unimaginably huge pile of spare cash —roughly $250 billion. This corporate wealth reserve will only grow if and when the Trump administration makes good on its desire to help tech giants repatriate profits that they have stashed overseas to evade U.S. taxes.
What should Apple do with all that money? There are only so many perfect doorknobs a company can buy, after all. In Quartz, David Mattin proposes a suitably grand goal for the company: Fund a giant pilot-test of a universal basic income scheme.
Shareholders wouldn’t be happy, he admits, and at first the idea might seem a little far afield for a company whose specialty has been computing and gadgetry. But right now Apple is stuck sitting on its laurels and its cash. It’s having a hard time following up on the iPhone, and it has lost its sense of purpose. It needs a new big mission, and, Mattin suggests, “reinventing capitalism” might be a great one.
Apple’s secrecy is a legendary and defining corporate trait. Like the quasi-government the company is increasingly becoming, it has an extensive program to fight leaks. We know that because, well, somebody leaked a recording of an hour-long presentation on Apple’s campaign (William Turton in The Outline). It turns out Apple employs a global team of leak-stoppers that includes former employees of the NSA, the FBI, the Secret Service, and branches of the U.S. military.
The purpose of all this secrecy, Apple execs insist, is “surprise and delight” among customers when they finally learn of some new Apple product or feature at the time of the company’s choosing. That kind of choreographed product launch has long been an Apple trademark, to be sure. But the company’s insistence on secrecy, like the inward-turning design of its gigantic new headquarters, underscores the increasingly insular nature of Apple’s culture.
“We don’t have a Big Brother culture,” an Apple exec says on the recording. Nonetheless, as The Outline puts it, “The presentation makes working for Apple sound like working for the CIA.”
