Leaderless Bitcoin Struggles to Make Its Most Crucial Decision

Bitcoin’s most influential developer has proposed a controversial fix that would help it handle more transactions. 

• By Mike Orcutt on May 19, 2015/MIT Technology Review/Blogger Ref http://www.p2pfoundation.net/Transfinancial_Economics
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Why It Matters

No one person or entity controls Bitcoin’s development.

In a test of Bitcoin’s ability to adapt to its own growing popularity, the Bitcoin community is facing a dilemma: how to change Bitcoin’s core software so that the growing volume of transactions doesn’t overwhelm the network. Some fear that the network, as it’s currently designed, could become overwhelmed as early as next year.
The answer will help determine the form Bitcoin’s network takes as it matures. But the loose-knit community of Bitcoin users is not in agreement over how it should proceed, and the nature of Bitcoin, a technology neither owned nor controlled by any one person or entity, could make the impending decision-making process challenging. At the very least it represents a cloud of uncertainty hanging over Bitcoin’s long-term future.
The technical problem, which most agree is solvable, is that Bitcoin’s network now has a fixed capacity for transactions. Before he or she disappeared, Bitcoin’s mysterious creator, Satoshi Nakamoto, limited the size of a “block,” or group of transactions, to one megabyte. The technology underlying Bitcoin works because a network of thousands of computers contribute the computational power needed to confirm every transaction and record them all in a permanent, publicly accessible ledger called the blockchain (see “What Bitcoin Is and Why It Matters”). Every 10 minutes, an operator of one of those computers wins the chance to add a new block to the chain and receives freshly minted bitcoins as a reward. That process is called mining.
Under the one-megabyte-per-block limit, the network can process only about three transactions per second. If Bitcoin becomes a mainstream payment system, or even a platform for all kinds of other online business besides payments (see “Why Bitcoin Could Be Much More Than a Currency”), it’s going to have to process a lot more. Visa, by comparison, says its network can process more than 24,000 transactions per second.
The developers in charge of maintaining Bitcoin’s core software have been aware of this impending problem for a while. Gavin Andresen, who has led work on Bitcoin’s core code since Nakamoto handed him the reins in 2010, told MIT Technology Review last August that his favored solution to the problem is to increase the maximum block size (see “The Man Who Really Built Bitcoin”). Earlier this month, Andresen got more specific, proposing that the maximum block size be increased to 20 megabytes starting in March 2016, calling this the “simplest possible set of changes that will work.” In a subsequent post on his blog, Andresen called the need for the change “urgent,” noting that the network would likely become unreliable if it were allowed to reach the current limit.
Mike Hearn, a former Google software engineer who has contributed to Bitcoin’s development, has calculated that at the current rate of transaction growth, the limit will be hit sometime in 2016. “Because upgrades take time, we need to prepare for this now,” Hearn writes in his own recent post on the issue.
The problem is that a consensus is required to make a change as consequential as the one Andresen suggests, which would substantially alter the requirements for mining. And not everyone in the community of users of the Bitcoin software—which includes miners, developers, and a growing number of startups—agrees that Andresen’s proposal is the best path forward.
A popular argument against the change is that it would favor bigger, richer mining operations that could afford the increased costs that go along with processing and storing bigger blocks. That could lead to a dangerous “centralization” within the mining community, says Arvind Narayanan, a professor of computer science at Princeton University (see “Rise of Powerful Mining Pools Forces Rethink of Bitcoin’s Design”). Another, more ideological argument is that Bitcoin was never supposed to change this drastically from Nakamoto’s original design. Some even argue that the limit doesn’t need to increase at all, as long as the developers make smaller adjustments to prevent the network from buckling when it reaches it—though that could make it more expensive to get transactions confirmed without delays.

The growing commercial ecosystem around Bitcoin is at stake. If the limit remains fixed, businesses hoping to store lots of transactions on the blockchain could be out of luck. And such interest is only increasing—earlier this month, the Nasdaq stock exchange said it was testing Bitcoin’s blockchain for transactions in its private market subsidiary. If the test is successful, the exchange says, it could use the technology for all Nasdaq trades in the public market.
Will Bitcoin be able to handle that? Pieter Wuille, another of Bitcoin’s five core developers, says right now there are just too many unknowns about the consequences of increasing the block size to 20 megabytes. In addition to significantly raising the cost of validating transactions, which could force out smaller players, he says, there may be “things we don’t even know of that could break.” Wuille is in favor of increasing the block size “in general,” but says a smaller increase at first would be less risky.
For now, the debate will continue to play out on the Bitcoin development mailing list, a forum that includes the core developers as well as the many others who contribute code.
Ultimately, though, the decision-making process “really comes down to how the core developers feel about it,” says Narayanan, since they are the only ones with the power to change the code. Complicating things even further is the fact that it’s not exactly clear how they would solicit input from all the stakeholders, many of whom may prefer to remain anonymous. The core developers could eventually find it necessary to take matters into their own hands.
At least one of them thinks that would be a bad idea, though. That would set an “incredibly dangerous precedent,” says Wuille.

In Praise of Efficient Price Gouging

 

Uber’s most important innovation is the way it prices its services. But that innovation has not been unreservedly welcomed by customers. They’re wrong.

• By James Surowiecki on August 19, 2014  Blogger Ref  http://www.p2pfoundation.net/Transfinancial_Economics              

 

                     

In the four years since the car service Uber launched, it has been beset by criticism from myriad groups, including city officials annoyed by its sometimes cavalier attitude toward regulation and taxi companies annoyed by increased competition. Some of the harshest criticism, though, has come from an unlikely place: Uber’s own customers. Thanks to its reliance on what it calls “surge pricing”— meaning that during times of high demand, Uber raises its prices, often sharply—the company has been accused of profiteering and exploiting its customers. When Uber jacked up prices during a snowstorm in New York last December, for instance, there was an eruption of complaints, the general mood being summed up by a tweet calling Uber “price-gouging assholes.”

Thing reviewed
Uber's dynamic pricing model

What’s striking about the Uber backlash is that the company is hardly the first to use dynamic pricing. There have always been crude forms of price differentiation—or, as it is known in economics, price discrimination. If you go to a movie matinee, you pay less than if you go at night, and if you’re willing to wait to buy a new dress (and run the risk that it might sell out), you can often get it at a marked-down price. But dynamic pricing in a more rigorous sense was pioneered in the 1980s by Robert Crandall, CEO of American Airlines, as a way to fight off competition from discount airlines like People Express. American began by slashing prices for tickets bought well in advance, while keeping prices for tickets bought closer to takeoff (when ticket inventory was lower, and demand was less price-sensitive) as high as possible. In the decades since, this kind of yield management has become integral to the business models of airlines, hotels, and rental-car companies, and greater computing power and more sophisticated data analysis has turned pricing in these industries into an incredibly complex process. (Dynamic pricing has also allowed sites like Priceline and Hotwire to flourish, since when hotels are stuck with extra rooms, they’re often willing to drop prices rather than let a room sit empty.) More recently, as technology has made it easier to segment the market and change prices on the fly, dynamic pricing has become common in other industries, too. Many professional sports teams now use it to set ticket prices—games against high-profile teams cost more than games against cellar dwellers—while concert ticket prices wax and wane with demand.
If dynamic pricing is hardly unusual, why has Uber taken so much flak? Some of it is a matter of history: early on, Uber’s pricing was not especially transparent, so customers occasionally found themselves stuck with fares that were much higher than they expected. The fact that some of the most high-profile examples of surge pricing have been the result of big storms also matters, since it taps into people’s visceral dislike of price gouging. A 1986 study by Daniel Kahneman, Jack Knetsch, and Richard Thaler found that most people thought “raising prices in response to a shortage is unfair even when close substitutes are readily available”—a situation that almost perfectly describes Uber. Then, too, the price increases during surges are often magnitudes greater than customers are used to; during that New York snowstorm, Uber charged up to nearly eight times as much as it usually did. Thaler has suggested that people find price increases above three times normal psychologically ­intolerable.

The reality is that the times when people most want a ride are also the times when it’s most annoying and, often, most risky to drive: rush hour, New Year’s Eve, 2 a.m. on a Saturday night, snowstorms.

It’s also important that Uber’s prices only rise above the base rate and never fall below it, since customers seem to accept dynamic pricing more easily when it’s characterized as a discount. At the movies, for instance, prime-time tickets aren’t presented as a few dollars more than the normal price—rather, matinees are presented as a few dollars less. When American introduced dynamic pricing, it framed the 21-day advance-purchase requirement as a chance to buy “super-saver” fares. And happy hours at bars are, similarly, framed as a markdown from the regular price. These framing devices don’t change the underlying economics or price structure, but they can have a big impact on customer reaction. In 1999, for instance, Douglas Ivester, then the CEO of Coca-Cola, suggested that smart vending machines would allow Cokes to be more expensive on hot days, when demand was presumably higher. There was an immediate, intense backlash, and the company quickly backed down, saying Ivester’s comments were purely hypothetical. Had Ivester instead suggested that Coca-Cola could use dynamic pricing to charge less on cold days (even if it had raised the base price of a can), response would probably have been very different. Uber’s competitor Lyft seems to have recognized the power of framing: it recently introduced what it calls happy-hour pricing, offering discounts during slow business hours.
Finally, Uber also faces a challenge simply because of the industry it’s in: a business in which fares have historically been regulated (for cabs) and fixed (if you take a car service to the airport in New York, for instance, you typically pay the same price whether you leave at 6 a.m. or 5 p.m.). Uber’s pricing scheme is more complicated and harder to grasp intuitively, so that even though Uber is transparent about surge pricing, some people inevitably find it vexing. Uber’s also combating the sense that transportation is, in some sense, a public utility, and that it’s offensive to charge people so much more than they’re used to paying. This is a mysterious complaint, since there are many alternatives to using Uber. But it’s a surprisingly common one.
It’s easy to see, then, why Uber has become a flash point for criticism. But there is a deep irony here: the company arguably offers the most economically sensible, and useful, example of dynamic pricing in today’s economy.
In most cases, after all, dynamic pricing is a way for companies to maximize profits by exploiting demand—charging higher prices to people who can and will pay more. As MIT professor Yossi Sheffi has put it, it’s the “science of squeezing every possible dollar from customers.”
That’s because most industries that use dynamic pricing have a limited inventory (an airline flight has a set number of seats, a hotel a set number of rooms) and are trying to make as much money from selling that inventory as possible. Uber’s case is different. While the company also wants to make as much money as possible, it uses surge pricing not only to exploit demand but to increase supply.

The Uber app tells users how much the rate has increased during times of high demand.

When there are more would-be Uber passengers than available Uber cars, the company’s algorithm sets a price that balances supply and demand. Uber’s algorithm (which it has been refining since 2011) is the company’s greatest asset and most significant innovation, allowing it to find the price that will attract drivers—whom, as independent contractors, it can’t order onto the road—without alienating customers. The strategy works. In a recent blog post, the venture capitalist Bill Gurley, who’s an Uber board member, said that when Uber first tested dynamic pricing in Boston in 2012, it was able to “increase on-the-road supply of drivers by 70 to 80 percent.”
Plenty of us have an intuition that cab drivers would want to be on the road when there’s money to be made. But this isn’t the case: a number of studies have shown that there’s considerable variety in how they decide when to drive. Also, the reality is that the times when people most want a ride are also the times when it’s most annoying and, often, most risky to drive. Rush hour, New Year’s Eve, 2 a.m. on a Saturday night, snowstorms: generally speaking, these are exactly the times when a driver doesn’t want to be on the road. But if driving at those times pays considerably better, then they are more likely to be willing.
What this means is that in the case of Uber, surge pricing doesn’t just make rides more expensive (as is the case with airline tickets or hotel rooms at times of high demand). It also expands the number of people who are actually able to get a ride. Customers pay more, but they also get a ride that they otherwise would not have gotten. This is exactly how a market is supposed to work: higher demand induces more supply.
Of course, Uber has been making this argument for a while now, and it hasn’t stopped people from complaining. (Though it hasn’t stopped people from using the service, either: Uber is now valued at more than $17 billion.) So pundits have proffered a number of suggestions for solving the public relations problem.
The company itself should take no money during surge periods (it now takes 20 percent of every fare), so all the money goes to the drivers. Or it should cap prices to consumers but pay the higher price to drivers, essentially subsidizing people’s rides in surge periods. Or when prices rise really sharply, Uber should donate its take to charity.

 

These are all interesting ideas. But it’d be a mistake for Uber to let public relations trump economics when it comes to dynamic pricing. It makes sense that the company recently reached an agreement with New York’s attorney general that caps surge pricing during times of “emergency,” since these emergencies are rare, and the negative fallout from them can be immense. But tinkering with the basic idea of surge pricing will only reinforce the status quo and bolster people’s implicit assumption that prices should be set, in some sense, independently of supply and demand. The basic reality of Uber’s business model is that when people want a ride the most, it’s likely to be the most expensive. This will always be irritating, just as exorbitant prices for last-minute airline tickets are irritating. But over time, surge pricing will also become more familiar and less surprising.
Utilities are now starting to use dynamic pricing for electric power, which can help prevent blackouts at times of high demand and promote energy conservation more generally. A new startup called Boomerang Commerce, which is led by former Amazon engineers, has been helping online retailers set prices dynamically. Dynamic pricing is the future, even if the road to get there will be bumpy.
James Surowiecki writes “The Financial Page” for the New Yorker.

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