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区块链国际资讯

区块链不仅是一种技术,更是一个全新的经济体系

区块链国际资讯

区块链不仅是一种技术,更是一个全新的经济体系

区块链是现在主流加密货币的一种底层技术,但是它不应该仅仅被视为一种投资赌注,而更应该被看作一种全新的经济体系。

就像任何经济体一样,区块链要求其设计者定义货币政策(通货膨胀)、财政政策(区块大小)、税收(收费)、投票(治理/升级)并提供共同防御(保护网络)。然而,与传统经济不同的是,区块链提供了更大的自由度和透明度的可能性,因为这种技术避免了过度中心化的问题。

然而,随之而来的风险也比传统经济模式要高。

区块链发展受到人为因素影响

区块链创建者在开发这些新经济体时会面临另一大风险:准确预测人们的行为。

制定经济规则是一回事,而用软件对其进行编码则是另一回事。因为这些规则的基础是对人们在经济中行为方式的预测。而那些预测很难得到正确的结果。

从日常生活来看,我们可能会投票支持违背我们自己的经济利益的政策,我们也可能做出与我们的身体健康不符的食物选择。所以说,我们的很多行为都是不明确的,也不存在什么编码逻辑。

实际上,已经有不少人开始针对人类行为展开研究,其中就包括诺贝尔奖获得者Daniel Kahneman和Cass Sunstein。

这时候,我们就需要建立一些必要的激励机制,鼓励人们以理想的方式行事,从而使区块链网络优势得以肯定并发展。

区块链领域的激励措施以数字代币的形式出现。这些代币是网络的内部货币。它们的感知价值对于使矿工积极保护网络的行为非常重要以及帮助个人用户评估他们从网络获得的收益。

获得激励措施是正确的网络发展的基础,反映在增加的代币流通的采用,产生积极的网络效应。这个飞轮一旦启动,它就成为未来发展的持续筹资机制。没有它,网络就无法实现自我维持。社区和代币的价值在于激励新成员加入。如果这个价值是难以察觉或是负值的,新的人不会加入,整个系统网络也将走向终结。

还有很多方面需要研究和改进

精通加密代币经济学对于构建强大、可持续的区块链经济至关重要。因为这个过程会涉及机制设计、博弈论、行为经济学、公共政策、宏观经济学和对分散技术的正确理解等多个方面。未来,也许高等研究机构中会出现专门的加密货币经济领域的博士。但是至少现在来看,具有丰富加密货币经济经验的专家人数还并不多。

如果不能真正地理解一个项目的加密经济学意义,那么投资者、开发商和潜在的网络贡献者就无法评估这种分散网络的长期潜力。与团队、技术、管理和社区等几个方面一样,这种区块链“代币”也是衡量项目成功与否的“T3CG框架的一部分。

而Gnosis,Numeraire等这样依赖人类及其理性行为倾向的区块链,将面临如比特币等更少经济类规则的区块链更大的挑战。

未来,区块链技术和系统可能会得到极大的发展。而2017年和2018年的区块链系统或许智能成为加密代币经济学学习如何避免系统设计不足的一个案例而已。

 

Forget for a moment about the value of the cryptocurrencies that you may or may not own. Instead of thinking of blockchains as investment bets or just cool technology, think of them as entirely new, and previously impossible, economic systems. Because that’s what they are.

Just like any economy, a blockchain requires that its designers define monetary policy* (inflation), fiscal policy (block size), taxation (fees), voting (governance/upgrades), and provide for the common defense (securing the network). Yet, unlike traditional economies, they offer the possibility of greater freedom and transparency because they avoid the problems of centralization and concentration of power.

That’s the good news. The bad news is that these new economies comes with extremely high risk.

Then there are … the people

As if designing a system without flaws weren’t enough pressure, blockchain creators face another big risk when developing these new economies: accurately predicting people’s behavior.

It is one thing to lay down the rules for an economy and encode them in software (i.e. “code is law”). But those rules are based on predictions of how people will behave in the economy — the value they will place on a currency or the level of incentive that will drive them to participate in the ecosystem, for example. And those predictions are notoriously hard to get right.

Just look at some of the decisions each of us make on a daily basis. We may vote for policies that go against our own economic interests. We make food selections that are at odds with our physical health. There’s no clear, codeable logic in much of our behavior.

In fact, an entire field of people study this very phenomenon, including Nobel laureates Daniel Kahneman and Amos Twersky as well as University of Chicago professor and former Clinton advisor Cass Sunstein (author of Nudge). It was Sunstein who discovered that changing the default setting from “opt-in” to “opt-out” on things such as organ donation on a driver’s license and 401k contributions at work could dramatically improve uptake.

Of course, once Sunstein discovered this, he only had to share the findings with a few, key central authorities who were able to institute the decision across the entire network. They did not need to poll every citizen in a state to get approval to change the Driver’s License registration process. The “fork” of the protocol, in this case, was relatively painless.

Blockchain system designers face greater challenges than Sunstein in implementing changes. This makes the accurate prediction of how individuals will behave in a given situation an absolutely critical, non-negotiable, component to crypto-economic system design. In fact, creating sustainable peer-to-peer value transfer systems at scale is simply unlikely to happen otherwise.

And this is where incentives come in. Properly designed, they can encourage people (like Sunstein did) to behave in desirable ways that benefit and grow the network.

Incentives, in blockchain land, come in the form of digital tokens. These tokens are the internal currency of the network. Their perceived value is important in keeping miners active in securing the network (what amount of block reward at what frequency and with what difficulty is enough to motivate them?) as well as in helping individual users assess the benefits they get from the network compared to alternative networks.

Getting incentives right is fundamental to network growth, reflected in increased token adoption that yields positive network effects. Once this flywheel gets started, it serves as the ongoing funding mechanism for future development. Without it, the network cannot achieve self-sustainability. The value of the community and the token is what incentivizes new members to join. If that value is off, new people don’t join and a death spiral begins.

You can see why getting those incentives just right it is so fraught with risk.

There’s still a lot to learn

A mastery of crypto-token economics is critical to the design of robust, sustainable blockchain economies. It involves multi-disciplinary skills, including mechanism design, game theory, behavioral economics, public policy, macro-economics, and a decent understanding of decentralized technology. The day will come when we have Ph.Ds emerging from top universities in the field of crypto-token economics. Today, however, there are only a handful of experienced practitioners in the entire world. As Aleksandr Bulkin wrote over a year ago– “Cryptoeconomics is hard.” No joke.

Without understanding the token economics of a project, investors, developers, and potential network contributors have no way to assess the long-term potential of a decentralized network. Along with team, technology, governance, and community, “token” forms part of the critical “T3CG Framework” I use to assess the likelihood of project success.

As excited as I am about the potential of blockchain systems, I am humbled by the realization that we have only just scratched the surface on how to build this systems properly. Blockchains that depend a lot on humans and their propensity to behave rationally — such as Augur, Gnosis, Steem, and Numeraire, for example — will face bigger challenges than blockchains with less complex economic rules, such as Bitcoin.

It may end up being the case that the super-hyped, human-powered blockchain systems of 2017 and 2018 are merely the case studies that future students of crypto-token economics will study to avoid flaws in system design.


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