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Where Warren’s Wrong Follow-up, Amazon’s Price Parity Provision, The Amazon Marketplace Question

Senator Elizabeth Warren deserves credit: I have been writing about antitrust, particularly in the context of Aggregation Theory, for years, but the most concrete proposal I have put forward is that social networks should not be allowed to acquire other social networks.

To do that, we need to stop this generation of big tech companies from throwing around their political power to shape the rules in their favor and throwing around their economic power to snuff out or buy up every potential competitor.

Unfortunately, Senator Warren’s proposal helps highlight why I have not gone further with my own: hers would create massive new problems, have significant unintended consequences, and worst of all, not even address the issues Senator Warren is concerned about (with one possible exception I will get to in a moment).

Worst, it would do so by running roughshod over the idea of judicial independence, invite endless lawsuits and bureaucratic meddling around subjective definitions, and effectively punish consumers for choosing the best option for them.

In the 1990s, Microsoft  —  the tech giant of its time  — was trying to parlay its dominance in computer operating systems into dominance in the new area of web browsing.

The story demonstrates why promoting competition is so important: it allows new, groundbreaking companies to grow and thrive — which pushes everyone in the marketplace to offer better products and services.

What is more striking is that, in retrospect, the core piece of the government’s case doesn’t make any sense: of course a browser should be bundled with an operating system;

Moreover, Apple, not without merit, argues that restricting rendering engines to the one that ships with the OS (all browsers on iOS have no choice but to use the built-in rendering engine) has significant security benefits;

it was fabulously profitable, and as history shows again and again, being fabulously profitable with an existing value chain is the best way to not only fail to recognize a new market opportunity (Microsoft didn’t even have a web crawler until after Google’s IPO!), but to in fact be at a massive disadvantage when you finally do so.

the opportunity — Windows Mobile came out back in 2000 — it was just stuck in a PC mindset when it came to product development, attached to its Windows licensing model when it came to monetization, and institutionally incapable of producing superior end user experiences thanks to the company’s traditional focus on platforms and compatibility.

if anything the real question is whether or not Google’s emergence shows that the Microsoft lawsuit was a waste of time and money.1 Senator Warren’s second mistake is a misstating of why large tech companies are dominant.

Each of them leveraged technology to solve a unique user needs, acquired users, then leveraged those users to attract suppliers onto their platforms by choice, which attracted more users, creating a virtuous cycle that I have christened Aggregation Theory.

Specifically: Aggregation Theory is the reason why all of these companies have escaped antitrust scrutiny to date in the U.S.: here antitrust law rests on the consumer welfare standard, and the entire reason why these companies succeed is because they deliver consumer benefit.

Consider the Google Shopping case: Google was found guilty of antitrust violations in a case brought by a shopping comparison site called Foundem, which complained about their site being buried when consumers were searching for items to buy.

at a fundamental level, though, any sort of antitrust proposal that does not seriously grapple with the reality that the power of these companies flows from controlling demand — that is, consumer choice, willingly made — not from controlling supply, like monopolies of old, is going to be fundamentally flawed.

Back when the railroads were dominant, and you had to get steel or wheat onto the railroad, there was a period of time when the railroads figured out that they could make money not only by selling tickets on the railroad, but also by buying the steel company and then cutting the price of transporting steel for their own company and raising the price of transporting steel for any competitors.

This is pretty explicitly taking Senator Warren’s critique of Amazon in particular and applying it to Apple, and to be fair, it is not completely without merit: Apple has quite clearly leveraged the fact it owns the platform to compete with Spotify, for example, and has definitely suppressed competition when it comes to built-in apps like Mail and the aforementioned Safari.

What is even more striking, though, is that the App Store does have a massive antitrust problem: it is not Apple unfairly competing with app developers, it is Apple unfairly imposing massive complexity and extracting 30% of revenue with its contractual requirement, enforced by App Review, that developers use Apple’s payment mechanism.

There is a big benefit to suppliers (app developers) as well: the app market on PCs died in large part due to security concerns, which Apple obviated with the App Store to the tremendous benefit of every participant in the ecosystem.

They all have different value chains and different ways of impacting competition, both fairly and unfairly, and to fail to appreciate just how different they are is a great way to make bad laws that not only fail to fix problems but also create entirely new ones.

To my mind there are three major issues that deserve antitrust attention: Senator Warren expresses concern in her article about kill zones when it comes to new startups:

Venture capitalists are now hesitant to fund new startups to compete with these big tech companies because it’s so easy for the big companies to either snap up growing competitors or drive them out of business.

The number of tech startups has slumped, there are fewer high-growth young firms typical of the tech industry, and first financing rounds for tech startups have declined 22% since 2012.

Facebook quite clearly isn’t an industrial site (although it operates multiple data centers with lots of buildings and machinery), but it most certainly processes data from its raw form to something uniquely valuable both to Facebook’s products (and by extension its users and content suppliers) and also advertisers (and again, all of this analysis applies to Google as well):

And then, in exchange for these benefits that derive from data, Facebook sucks in data from all three entities: The end result is that Facebook and Google are far more valuable to advertisers than anyone else: they offer the most efficient spend when it comes to a return on advertising, and thanks to their ability to reach practically everyone, combined with the infinite nature of digital content, require the lowest investment.

The single most important feature when it comes to building a large user base and a leverage-able network effect is that the product be free-to-use, which means the only viable business model is advertising.

The fundamental problem facing Snapchat is that it wasn’t enough for the company to have higher usage or deeper engagement with teens and young adults, demographic groups advertisers are desperate to reach.

To that end, what makes the most sense from a management perspective is leveraging the tremendous amounts of cash thrown off by their core businesses to acquire and invest in companies competing in different value chains.

There are significant problems with this, to be sure, particularly when it comes to the incentives for new company creation (most successful exits are acquisitions, not IPOs), but at least this is a remedy that is somewhat approaching the problem.

This is an area ripe for enhanced antitrust enforcement: these large tech companies have enough advantages, most of them earned through delivering what customers want, and abetted by the fundamental nature of zero marginal costs.

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But they now dominate their respective markets for e-commerce and online ads, which gives them too much power, not only over ordinary users (just try to go a week without using Google!), but also companies that rely on their platforms to reach customers.

Consumers benefit when Google serves tailored ads based on search results, while companies benefit when Amazon can use its insight into what customers want in order to connect them with the right sellers at good prices.

The EU has already passed some of the world's toughest privacy rules and recently adopted a new law to curb conflicts of interest by big internet platforms.

European anti-trust supremo Margrethe Vestager has recently backed away from the idea of breaking up tech companies, saying it should only be a 'last resort' and pointing to more surgical enforcement of anti-trust rules as the way forward.

Calls to break up Silicon Valley giants would likely be fiercely opposed by business-friendly Republicans in Congress – and probably some Democrats who are cozy with the tech sector , or others who just think her policies would be bad for innovation.

Inside the Pentagon's Big Plans to Develop Trustworthy Artificial Intelligence

As federal agencies ramp up efforts to advance artificial intelligence under the White House’s national AI strategy, the Pentagon’s research shop is already working to push the tech to new limits.

Last year, the Defense Advanced Research Projects Agency kicked off the AI Next campaign, a $2 billion effort to build artificial intelligence tools capable of human-like communication and logical reasoning that far surpass the abilities of today’s most advanced tech.

Included in the agency’s portfolio are efforts to automate the scientific process, create computers with common sense, study the tech implications of insect brains and link military systems to the human body.

There's a certain ability to recognize new situations, behave appropriately in new situations, [and] recognize when maybe you don't have enough experience or training to actually function in a predictable or appropriate way for new situations.

Machine learning-enabled AI does certain tasks quite well—image classification, voice recognition, natural language processing, statistical pattern recognition—but we also know AI can fail quite spectacularly in unexpected ways.

In image classification, a machine will see a picture of a panda and recognize it as a panda, but you just make a few minor changes to pixels that the human eye wouldn't even recognize, and it's classified as a gibbon or something.

We need AI systems that do have some ability for introspection, so when given a task they could communicate to their partner 'based on my training and my experience, you should have confidence in me that I could do this' or ‘I’ve not encountered this situation before and I can't ...

[For this program], the time from posting a topic announcement to actually getting people doing work is 90 days or less, and that's fairly unprecedented in government contracting.

AI Exploration allows us to go after some of the more high-risk, uncertain spaces quickly to find out whether they're on the critical path toward reaching our ultimate vision.

There are clear challenges in making sure we have the manpower and the human capital to make sure that we're applying the right STEM approaches and that we are protecting that technological edge while not stifling innovation.

Should We Trust Artificial Intelligence Regulation by Congress If Facebook Supports It?

Photo illustration: Soohee Cho/The Intercept, Getty ImagesTry to imagine for a moment a declaration from Congress to the effect that safeguarding the environment is important, that the effects of pollution on the environment ought to be monitored, and that special care should be taken to protect particularly vulnerable and marginalized communities from toxic waste.

The real cause for concern is not that a resolution expresses a desire to rein in artificial intelligence, but that it does so with endorsements from Facebook and IBM — two fantastic examples of why such reining in is crucial. It’s hard to square the track records of either company with many of the values listed in the resolution.

According to a confidential Facebook document obtained and reported on last year by The Intercept, the company is courting corporate partners with a new machine learning ability that makes explicit the goal of all marketing: to predict the future choices of consumers and invisibly change their decision without any forewarning.

Using a technology called FBLearner Flow, the company boasts of its ability to “predict future behavior”; this allows it offer corporations the ability to target advertisements at users who are “at risk” of making choices that are considered unfavorable to such and such brand, ideally changing users’ decision before they even know they are going to make it.

victories, was found last year to have “often spit out erroneous cancer treatment advice,” according to a report in Stat. Last year, The Intercept revealed that the New York Police Department was sharing troves of surveillance camera footage with IBM to develop software that would allow other police departments to search for people by hair color, facial hair, and skin tone.

Another 2018 Intercept report revealed that IBM was one of several tech firms lining up for a crack at aiding the Trump administration’s algorithmic “extreme vetting” program for immigrants — perhaps unsurprising, given that IBM CEO Ginni Rometty personally offered the company’s services to Trump following his election and later sat on a private-sector advisory board supporting the White House.

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