Even Giants Started Out Small: Cooperation and the Early Days of Bitcoin

A new research paper to be released this week sheds some interesting light on Bitcoin’s first two years of existence, finding that the small group of early miners often played by the rules even when they had an opportunity to cheat.



The paper, “Cooperation among an anonymous group protected Bitcoin during failures of decentralization,” is interesting and valuable work, including the team’s discovery of a new way of tracking Bitcoin activity through a mining data stream dubbed the “extranonce.” 



But it is also highly technical and nuanced, and the topics it touches on, including Bitcoin security, privacy, and distribution, are highly contentious. This makes it quite vulnerable to misinterpretation (or misrepresentation) by nonspecialists.


The paper finds that for long stretches between January 2009 and February 2011, one miner on the nascent Bitcoin network had the opportunity to conduct a “51% attack.” 



By virtue of controlling a majority of the network’s mining power (or hashrate), that miner would have been able to double-spend coins or even take bitcoin from other users. 



But despite these lengthy windows of opportunity, no early bitcoin miners attacked the chain. “Strikingly, we find that potential attackers always chose to cooperate instead,” the researchers write.



The researchers, a large team including members from Baylor College of Medicine and Rice University, have emphasized that the paper does not make claims about Bitcoin outside of that short, early window.



The discovery that early bitcoiners cooperated even when they had a chance to cheat may seem unremarkable on its face. 



Bitcoin in its earliest years was an experiment with little or no economic value, and the various actors almost certainly had more to gain by supporting the system than attacking it.




But the research is only in a limited sense even about Bitcoin as a technical system. Its primary goal, instead, is to “study responses to a social dilemma in a group of anonymous individuals.” 



In this case, the social dilemma was how to build a system vulnerable to attack in its early stages. 



The answer – which is also apparent if you’re familiar with the real-world story of Bitcoin’s early development and growth – was some mix of trust, common cause, and enlightened self-interest.



So early Bitcoin is a useful case study of human behavior under particular game-theoretical conditions, but a better understanding of the Bitcoin system was not the researchers’ primary goal. 



“The key to the paper is the behaviors that we characterize,” team member Dr. Erez Aiden, a genomics researcher at the Baylor College of Medicine, told CoinDesk in response to emailed questions.



This helps explain why, while the team is composed largely of mathematicians and computer scientists, many of them work on research problems in genomics, biology, and medicine. 



The research is ultimately concerned less with Bitcoin itself than with the behavior of the humans who created Bitcoin – including those who, given the opportunity to steal, chose not to.



This is also why the paper concludes with a psychological experiment using a game-theoretical model to mimic early bitcoiner behavior. Participants played a game called “Centipede,” which allows anonymous players to steal from one another in a way similar to a 51% attack. 



In experimental repetitions of an eight-player Centipede game, the researchers found that players displayed “high levels of cooperation,” even when the incentive to steal was high and they were anonymous to other players.



While not directly relevant to understanding Bitcoin’s security on a technical level, these findings are at least a bit reassuring on the subject of human nature.



They do identify a new form of “data leakage” relevant to the study of on-chain Bitcoin activity. This is a piece of metadata known as the “extranonce” that is uniquely generated by individual miners. 



But the new method has fairly limited utility, and according to the researchers, isn’t a game-changer on its own even within the limited sphere of transaction graphing.

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