DAOs are collaborative networks which are likely to have a unique role in the future. To determine this role, you need to be able to look beyond what is happening today. Like a toddler taking its first steps, the DAOs of today are immature, unsteady and likely to stumble.
While it can be tempting to write them off, especially in ‘serious’ innovation domains, their structure gives them unique capabilities as vehicles for discovery. We’ll take a short walk through their structure, and finish on the following point:
DAOs are novelty search engines which can more efficiently explore a search space by enabling many cooperating teams to collect and integrate stepping stones.
Imagine yourself at the shore of a lake. You intend to reach the other side, and must do so by hopping across stepping stones on the surface. However, the lake is shrouded in a dense fog, which obscures all but the stepping stones closest to you. As you walk across the stepping stones, the shore dissolves from sight behind you.
Eventually, you find yourself at a fork; a decision to be made. Which way is best? The fog ensures that you can’t see where either path leads. Still, you must make a choice.
Stanley & Lehman (2015) draw this analogy in relation to discovery. The lake represents the abstract space of all possibilities, and the stepping stones represent strategies for navigation. Your journey is a process of searching through the space of all possibilities. The question is, how do you navigate when you don’t know the nature of the territory?
We can reframe this by thinking of the space of all possibilities as a room. Now imagine yourself an artist, searching through the room to discover the next Monet. Conceived as a search space, we see that this rare diamond is already there. Your purpose is merely to find it among the plethora of meaningless dead-ends.
As you paint, you search through the room. What you paint will be influenced by the parts of the room you have already visited. If you’ve spent time working with modernism, you’re likely to be influenced by it. Without having visited the watercolour corner, you are unlikely to invent them. The problem of the lake arises here again. How do we reach the Monets? What stepping stones lead us there?
We can think of all complex domains in this way. We know there are new discoveries to be made, if only we knew how to get there. Unfortunately, we can rarely see beyond the most immediate stepping stones.
Consider vacuum tubes. It was obvious to nobody that they would enable the first computers. This only became clear after vacuum tubes and associated computing discoveries had been made, so that someone could make the connection. If you had set out to build a computer in the 1800s (as Charles Babbage did), it’s unlikely that you would have drawn this insight.
We are biased to believe that the interim steps resemble the final goal, and use objectives to reach stepping stones that appear to lead to the final destination. However, without knowing the nature of the territory, those objectives may well lead us to get stuck.
It’s perfectly possible that moving closer to the goal actually does not increase the value of the objective function, even if the move brings us closer to the objective.
Why Greatness Cannot Be Planned - Stanley & Lehman (2015)
Consider education. We measure improvement in education based on test scores, on the assumption that better test scores mean we’re getting smarter. “But the Math scores are up! That’s good, right?” Wrong. Optimising for Math scores through assessment forces us to invest in things which improve short term scores, while preventing the exploration of the larger search space.
So what’s the alternative? Well, novelty search is a form of non-objective search. Instead of following the stepping stones that appear to lead to the objective, simply collect stepping stones that lead in interesting directions. Focus on newness, regardless of where it leads.
Because eventually you have to acquire some kind of knowledge to continue to produce novelty, it means that novelty search is a kind of information accumulator about the world in which it takes place. The longer the search progresses, the more information about the world it ends up accumulating.
Why Greatness Cannot Be Planned - Stanley & Lehman (2015)
Each stepping stone you collect opens up new possibilities. New ideas tend to arise from the combination of existing ideas; from combining stepping stones together. Every now and then, you land on a combination that lifts you into an entirely new context.
The more stepping stones you collect, the more interesting combinations you can create. You can’t predict where they’ll take you, but keep doing it, and you can predict you’ll end up somewhere interesting.
Companies and DAOs both exist on spectrums that can’t be painted with a single brush. However, their core structures have different organisational characteristics that optimise them for different roles in the future of innovation.
Great ideas tend to arise from a single mind that has collected and synthesised an unusual series of stepping stones.
Companies are hierarchies that are led by a single person who is ultimately responsible for decision-making. For ideas that require many people to materialise, companies are an ideal structure for making them real, since leaders are empowered to optimise their resources in pursuit of their vision.
This is a feature (not a bug), and is both what makes companies strong and simultaneously brittle. A strong leader with a strong vision can guide a company to achieve incredible things. A weak leader with a weak vision can't achieve much, and may in fact cause harm.
In either case, the point of a company is to align everyone to achieve something specific; to converge everyone's work on a centralised axis. This is "strong alignment", in the sense that everyone must work together to achieve a convergent outcome.
A consequence of strong alignment is the need for objectives. Leaders use objectives to distil their vision into something that can be easily understood, and enable each individual to put their work into the context of the whole. Without them, it risks dilution of a strong vision into a mosaic of interpretation.
The strength of the hierarchical model is the ability to pursue singular visions arising from a leader, by aligning the work of many individuals towards a convergent outcome. To do so, companies must carefully define the problem they want to solve and maintain a strong focus by measuring their progress against interstitial objectives.
However, this prevents companies from exploring the adjacent possible via stepping stones that do not resemble their objective. In turn, it causes them to lose out on their combinatorial possibilities.
DAOs are networks that are defined by nodes and links, corresponding to people and relationships.
Networks have a flexible topology that can re-organise in response to change, adopting new shapes that evolve over time. Leadership is distributed contextually and individuals are empowered to make decisions that meaningfully change the structure of the organisation, without requiring permission or consensus. We can call this ability self-organisation.
Consider a large network arrangement like a democratic nation state. A nation is composed of many individuals and organisations all contributing to its growth and change. However, the complexity of a nation ensures that no single entity can appreciate it as a whole, not even a President.
Instead, each is embedded in a context, like a local community, a business, or a social circle, and interprets the nation in its own way to make decisions that affect that context. As they make decisions, like starting a business, voting on governments, or forming new relationships, the structure of the network meaningfully changes in response.
This makes it challenging for nations to pursue a specific, unified agenda. Instead, they more successfully focus on highly interpretable goals like increasing GDP and improving the quality of life.
Similarly, in a mature DAO, individuals will be able to understand a part of the network (local context), but they will not be able to appreciate it as a whole (global context). Individuals will interpret the DAO in their own way, and explore directions that affect their local context without having to consider the context of the whole. As they make decisions, the structure of the network will self-organise in response.
Through this mechanism, networks have an information advantage. Individuals know more about themselves than anyone else, and decide for themselves how they are best able to contribute.
…it is intuitive that specification and pricing of all aspects of individual effort—talent, motivation, workload, and focus as they change in small increments over the span of an individual’s full day, let alone months—is impossible.
…hierarchical organization is a lossy medium. All the information that could have been relevant to the decision regarding each factor of production, but that was not introduced in a form or at a location that entitled it to “count” towards an agent’s decision…is lost.
Coase’s Penguin - Yochai Benkler (2002)
Networks are also able to allocate people more efficiently, since anyone can take on any role and the network can benefit from the best combinations.
…different people will be more or less productive with any given set of resources and collaborators for any given set of projects, and that this variability is large.
Peer production has an advantage over firms and markets because it allows larger groups of individuals to scour larger groups of resources in search of materials, projects, collaborations, and combinations…
Coase’s Penguin - Yochai Benkler (2002)
Tokens, meanwhile, create a mechanism for “weak alignment“, in which everyone in the network has a shared incentive to increase its value. However, the way in which that value is achieved is open to interpretation.
The consequence is that DAOs are not suited to pursuing one vision. They are optimised for exploring many divergent visions simultaneously, emerging from individuals making decisions based on their local context. This is a feature (not a bug), and will be the source of strength for the networks to come.
This is an uncomfortable thought for some. “There’s nobody steering the ship!”. “There’s no roadmap!”. No - and that’s the point. They are autonomous. Autonomy derives not just from smart contract logic, but from a continuous process of distributed self-organisation.
DAOs and companies have different organisational characteristics arising from their core structures. However, this does not mean to say that they are mutually exclusive - quite the contrary. Instead, DAOs can be conceived as containers for many weakly-aligned hierarchies.
Great ideas tend to come from a single mind and leadership is a requirement for effective human collaboration. Hierarchies are well-optimised to enable strong leaders to achieve strong outcomes. DAOs do not get around this fact. Hierarchies work because they enable leaders to synthesise the contributions of a group.
Leaders with differing ideas naturally surface in groups of people, and it is equally natural for people to follow leaders and causes they believe in. Rather than replacing hierarchies, DAOs create a mechanism through which a single organisation can allow many hierarchical teams to explore different directions simultaneously.
Problems tend to arise in hierarchies due to groupthink: a progressive inability to consider alternative points of view.
Homogeneous groups are great at doing what they do well, but they become progressively less able to investigate alternatives.
The Wisdom of Crowds - James Surowiecki
In a network arrangement, each team interprets its own direction based on local context, and contributes what they believe will increase its value, without having to align to a singular vision or narrative. There is no need for consensus or compromise, because each group is empowered to self-organise.
…the best collective decisions are the product of disagreement and contest, not consensus or compromise.
The Wisdom of Crowds - James Surowiecki
In this way, a single DAO can be seen as a multi-organisational network. In times past, these structures have struggled to exist due to lack of the technologies required to coordinate. Now, weak alignment with a programmable token gives each team an incentive to cooperate and share information, while open blockchains make information increasingly easy to share.
Its key principle is heterarchic (or, to offer another term, “panarchic”) collaboration among members who may be dispersed among multiple, often small organizations, or parts of organizations. Network designs have existed throughout history, but multiorganizational designs are now able to gain strength and mature because the new communications technologies let small, scattered, autonomous groups to consult, coordinate, and act jointly across greater distances and across more issue areas than ever before.
Tribes, Institutions, Markets and Networks - David Ronfeldt (1996)
DAOs of the future will benefit from the best of both worlds. Strong, unified hierarchies to achieve convergent outcomes in a local context, exploring many divergent directions while cooperating with one another to improve the state of the whole.
Let’s return to our search for a Monet. We know it’s out there somewhere, we just need to find it.
As we identified, objectives aren’t much use when we don’t know the nature of the territory. Instead, we should collect stepping stones that lead in interesting directions, without knowing exactly where we’ll end up.
Companies help us hop between single stepping stones by using a hierarchy to pursue a singular vision. However, they rarely move beyond this because this same mechanism prevents the exploration of the wider search space.
The magic of DAOs is to embrace complexity by enabling many cooperating teams to collect divergent stepping stones. Those stepping stones can be shared, reused and combined in new contexts, leading in new directions.
DAOs are a generating system for discovery, with people and information as its parts.
A generating system… is a kit of parts, with rules about the way these parts may be combined. Almost every ‘system as a whole’ is generated by a ‘generating system’. If we wish to make things which function as ‘wholes’ we shall have to invent generating systems to create them.
Systems Generating Systems - Christopher Alexander (1968)
As such, DAOs are a mechanism for open-ended evolution. Or rather, evolved open-endedness: a way to not only generate solutions to directions, but to progressively generate entirely new directions.
…instead of thinking of the open-endedness as existing conditions or properties of the evolutionary system, we consider them as the outcome of evolution itself.
Evolved open-endedness, not open-ended evolution - Pattee & Sayama (2019)
And so we arrive at the crux of the argument. DAOs are novelty search engines which can more efficiently explore a search space by enabling many cooperating teams to collect and integrate stepping stones.
This capability suggests a unique and interesting role in the future of innovation. Where we end up is unpredictable, but predictably interesting.
*Taken from Self-organisation in communicating groups (Heylighen, 2015).