"Uber recently let the cat out of the bag when it admitted that it does
attempt at first degree price discrimination. Rather than charging based
on the route, or demand for drivers, Uber is using “machine learning”
to charge what it thinks individual customers are willing to pay"
Pulled from this article:
https://www.buzzfeed.com/mattstoller2/as-democracy-suffers-digital-dictators-are-seizing-power?utm_term=.gfYw8my2jY#.ub6wLy7vJK
Interesting read.
Chinese journalist Liu Hu always knew
he’d have trouble with the authorities; he had been exposing corruption
and wrongdoing for years. He was used to being hassled with regular
fines and forced apologies imposed by his authoritarian government. He
nevertheless persisted in truth-telling.
One day in 2017, Hu
logged onto a travel site, but couldn’t book a flight because the site
said he was “not qualified.” Soon he discovered he was blocked from
buying property, using the high-speed train network, or getting a loan.
And there was nothing he could do about it. His rights to essential
goods and services were now circumscribed through an algorithm designed
to discriminate against the 7.5 million people on China's “Dishonest
Persons Subject to Enforcement” list.
Welcome
to the Chinese “social credit score” system, whose goal is to rank
China’s 1.4 billion people. Conceptually, it is not that different from a
financial credit score in the US. But the social credit score includes
things like political outspokenness, shopping habits, friends, travel
habits, and anything the authorities want to encourage or discourage.
This score then fine-tunes your access to essential social goods based
on a discriminatory algorithm.
Such a nightmarish system could
never, of course, happen in the United States. Or could it? Three recent
decisions in Washington suggest it is not as far-fetched as we might
imagine, with both our courts and our government effectively endorsing
the way a handful of giant companies are centralizing control over our
society.
First, the Republican-controlled FCC abandoned rules
that prevented internet providers from discriminating between different
forms of data flowing through their networks. The result is that
interfering with the flow of information, rather than facilitating it,
will become a lucrative new business model for telecom giants like
AT&T and Comcast.
Days later, a federal judge rejected the government’s attempt
to block AT&T’s takeover of Time Warner, a giant media conglomerate
that owns TV channels like CNN and HBO. The government argued that the
combined company would be too powerful, and able to discriminate against
rivals. The judge disagreed. He essentially said Google, Facebook, and
Amazon have now become so powerful that the only way AT&T can
compete is to bulk up its own power in a marketplace of goliaths. Within
days of that decision, a bidding war between Comcast and Disney broke
out over 21st Century Fox.
The
reason these companies want to merge the pipelines of the internet with
the content that flows through them is simple: They want to build
detailed individual profiles of internet users — how they browse the
web, what they watch. If there’s any doubt that’s the reason, consider
the judge’s own words
in allowing the AT&T deal. The merger allows AT&T to imitate
“highly successful, data-driven entities” like Google, he said. To
underscore the point, this week AT&T bought yet another company,
AppNexus, which was one of the largest remaining digital advertising
marketplaces not already controlled by a Silicon Valley giant.
The hits keep on coming: On Monday, the Supreme Court, in a case involving credit cards, issued a decision that will effectively immunize tech platforms and other networked systems against antitrust scrutiny.
All
these decisions are dangerous on their own. Together they show how
centralized control of the internet could enable the possibility of
automated discrimination on the level of the individual citizen. Which
is exactly the power we are seeing deployed in China, even if the
politics are different.
To understand how frightening this power
is, it’s important to first understand the concept of “first degree”
price discrimination. First-degree price discrimination is when every
individual gets a separate price based on their unique characteristics.
We accept price discrimination all the time; going to the movies and
getting a senior discount is price discrimination. But in that case, the
decision of how to discriminate is done by class; it is publicly
posted; and everyone accepts that, in this case, seniors get a discount.
It is a public decision to discriminate.
Discriminating on an
individual level is different and allows for powerful exploitation and
manipulation of the citizen. In areas with first-degree price
discrimination, like car insurance or credit cards, there are often
gender- or race-based pricing choices. With increasing datafication of
society, we can see this increasingly organized to the level of the
individual.
An
airline could, for instance, analyze your email for the words “death in
the family” and “travel,” look at your credit limit, and then offer you
a price based on this information. Or imagine a group of companies
putting together a common list of troublemakers, perhaps negative online
reviewers or commenters or consumers who frequently return items. All
of a sudden, for no obvious reason, someone who returns an item to one
store might find that prices on a host of socially essentially goods
have done up.
Corporations generally deny they do anything like
this or even that they can. But Uber recently let the cat out of the bag
when it admitted that it does attempt at first degree price
discrimination. Rather than charging based on the route, or demand for
drivers, Uber is using “machine learning” to charge what it thinks
individual customers are willing to pay. If there’s any doubt that this
is the plan for AT&T, let’s turn to Judge Richard J. Leon’s
decision, which he said that this new entity can use “customer data to
inform their strategy and improve the customer’s experience in a number
of ways.” This is code for discrimination. And the Supreme Court just
made it clear it will be very hard to bring suits if new platform giants
use this power to dominate markets.
All of this is being driven
by the web giants — Amazon, Google, and Facebook — who use their power
over shopping, search, and social networking to discriminate in favor of
their own products and content. Amazon has built a massive
manufacturing business by privileging its own private-label products,
like Amazon batteries, over rival brands sold on its site. Google does
the same thing, using its heft over search and maps to privilege its own products and services.
What
these decisions collectively mean is becoming clearer — soon, all
information production and distribution will increasingly be created for
the profit of the web giants, or it will not be created and distributed
at all. Media executives are now saying that within a few years it is
likely that every major content company will be owned by a tech or
telecom platform.
