In this post we argue that behavioral factors and psychology are not given enough consideration in cryptoeconomics. We think it imperative that experts in actual human economic behavior, such as public policy experts, behavioral economists and social scientists, be included in the teams designing cryptoeconomic systems, in order to ensure their long-term utility, viability and success.
Crucially, Bitcoin’s security does not depend on any “Homo Economicus” assumption that humans are ruthless optimizers and ultra-rational. Rather, even if people are lazy, and even if some malicious coalitions are formed, the system would still be secure. Compared to modern assumptions like those of Steemit or Augur, the assumptions of Bitcoin are much more realistic and uncontroversial.
The “automatibility’ axis describes how much manual work is needed by the (human) stakeholders to follow the incentives. In a nutshell: In Bitcoin, computers make decisions, while in Steemit, humans make decisions. In detail: Bitcoin miners can follow incentives without lifting a finger, just by letting the computer mine honestly. Augur and Steemit, on the other hand, rely on humans to manually make predictions, write posts, and to get rewarded for it. In the middle, Polkadot and Proof-of-Stake systems require humans to stake entities that they trust to not act against the system.
The “size of action space” axis describes how many possible actions must be explored in order to maximize reward. In Steemit the possible actions are as wide as the number of possible good posts, while in Bitcoin the effective action space consists of just one action: “mine and validate honestly”. In Numerai, a human is asked to design a good algorithm, and gets rewarded according to its performance.
m0t0k1ch1.icon 縦軸（size of action space）は「報酬を最大化するためにできる行動がどれだけあるか」
This points to an absence of expertise in the multidisciplinary skills needed for practical incentive design. These skills include mechanism design, cryptography and engineering, but also behavioral economics and the humanities: an understanding of the complex, nuanced, illogical ways in which humans actually behave. Blockchain incentive design needs the public policy experts as well as the scientists.
The difficulty is that humans are not rational actors. In reality, humans diverge from optimal behaviors very often. A classic example is the Ultimatum Game: person A is given $100 and asked to offer some amount of it to person B. Person B then has to “accept”, or to “reject”. If B “rejects”, both players go aways with nothing. If B “accepts”, B gets what was offered, and A gets the remaining part. Game theory tells us that the rational strategy for player B is to always accept, even if player A offers 0.01$. However, in reality, people typically reject offers of less than $30. Furthermore, people playing as A usually offer at least $20–30. So we see that in empirical settings both players adopt strategies that are wildly suboptimal (in the game-theoretic sense). We might well expect such this effect to replicate in the intricate settings of cryptoeconomic systems such as Steemit.
The less automatible an incentive system is, the harder it is to design, and the more it is exposed to human irrationalities such as confirmation bias, sunk cost fallacies, and various types of Groupthink.
The larger the action space, the harder it is to optimize and make the right choice. Computers can often search large spaces, but the cost of this might be prohibitive. With humans the situation is much worse. Humans hate having to choose, so the larger the search space, the higher the Cognitive Deliberation Cost, and the worse the results.
m0t0k1ch1.icon action space が大きいと、最適化や正しい選択が難しくなる
We thus see that in systems outside the “less-risky space” (the pink region in the chart), the actors themselves have a hard time figuring out which actions maximize their profits. And the challenge of the system designers is much harder: as it becomes harder for players to decide on actions, it becomes exponentially harder for the designer to design a stable, predictable, system.
m0t0k1ch1.icon 上図における less-risky space の外側は、参加者が利益を最大化するのが難しいし、システムの設計も難しい
So far, we have established that the design of complex cryptoeconomic systems is a difficult and not-yet-understood task. Thus cryptoeconomic systems will mostly start out broken, and have to undergo repeated iterations of improvements. But what’s wrong with that? Isn’t that the way technical systems have always worked? From the invention of fire and writing, through state-building and the space race, and onto computing, software and the internet — all of these start out deeply flawed, and become better over time.
In summary: good incentive systems are notoriously difficult to create under the best of circumstances. Under Blockchain systems — where code is law, etched in stone, and deployed to a wide community of pseudonymous stakeholders — good incentive systems are all the harder to get right. The success of Bitcoin should not make us complacent and optimistic: our incentive design paradigms needs to be scrupulous, slow growing, with a framework of checks and balances. If we design our new economies badly, then like in the last financial crisis, as the system begins to falter, it will trigger cascading effects that lengthen and deepen the fall. It is sobering to think that blockchain economies could meet the same fate as the very systems they were meant to replace: emboldened by exponential growth and short-term profits, we turn a blind eye to the long-term unsustainability of the model. Historically this led to external interventions in the market (though a taxpayer bailout may not be as feasible given blockchain’s stateless nature.)
The oracles and prophets of this brave new world would be well advised to heed caution when trying to build an economy from scratch. There are mounds of past examples and historical data to learn from among the rubble of fallen economic systems. Blockchain systems hold unprecedented potential to solve some of the world’s most radical problems: by aligning incentives and disrupting entrenched interests we can reshape society for the better. Let’s not squander this opportunity.