Are Twitter bots that disseminate fake news across the Internet comparable to metastasizing cancer cells that spread disease within a human body? Can these two seemingly disparate processes be seen as expressions of the same evolutionary dynamics?
The short answer is yes, though there are significant variations in how these processes work. Both Twitter bots and cancer cells disrupt complex cooperative societies—albeit societies of much different kinds. Fake news compromises the health of human societies by undermining our shared sense of truth. Metastatic cancer compromises the health of our bodies by undermining cooperation among our society of cells.
Both Twitter bots and cancer adopt similar strategies, using deception and misinformation to achieve their self-serving ends. In other words, they cheat.
Understanding every level of the hierarchy of life in terms of cooperative social interactions—from its origins nearly four billion years ago to our global civilization today—is a central goal of a documentary film project I’m developing with David Sloan Wilson, titled “Evolving a Major Transition in the Internet Age”. The introduction to the project at that link explains what major transitions are, how they work, and how they’ve led to life’s increase in complexity over time. Importantly, major transitions encompass both biological and cultural phenomena, such as the transition from unicellular to multicellular life and the ongoing transition from conflicted nation-states to a cooperative global society today.
This interview with Athena Aktipis, with more interviews to follow, serves as research for the documentary film. Athena is an example of how a single scientist can study diverse systems from a unified evolutionary perspective. She is a foremost authority on cancer, as she relates in her book The Cheating Cell: How Evolution Helps Us Understand and Treat Cancer. She also co-directs the Human Generosity Project at Arizona State University. This makes her ideally suited to draw connections between phenomena as seemingly diverse as cancer and fake news.
The issues at stake are not merely academic. Understanding why and how both Twitter bots and cancer cells create conflict in different kinds of cooperative social systems may help us find new strategies to bring both kinds of disruptive behavior under control. Finding new ways to cooperate at every scale of human activity is essential for solving virtually all of the social and ecological crises we face.
Following are excerpts from my extended interview with Athena. Even though I’ve been immersed in the concepts of major transitions and the evolution of multicellularity for quite a while, seeing cancer from this perspective provided much food for thought. In the interview we covered a wide range of topics. These include the evolution of cooperation, the role of information and regulatory systems at different levels in the hierarchy of life, and human behavior in times of crisis and stress.
My ongoing research has convinced me that the biological transition to multicellularity has much in common with the cultural transition to a global civilization. Not just the analogy between cancer and Twitter bots, which are situations when cooperation fails, but there must be many positive parallels as well—hints from how multicellularity evolved that might point the way to a smoother cultural evolutionary transition today.
So I looked forward to exploring these ideas from Athena’s perspective. I began the conversation by asking her to comment on a statement she makes near the beginning of her book—“that cancer is more than just a disease; it is a window into the origins of life, the challenges of large-scale cooperation, the nature of multicellularity, and the process of evolution itself.”
All of the video segments below are accompanied by written transcripts so that you can either listen or read, as you prefer.
ATHENA AKTIPIS: When I started working on cancer I realized that it was truly a matter of how bodies regulate cooperation and maintain it. And that cancer was really a failure of this large scale cooperation. So in order to understand that we have to go back all the way to the origins of multicellular life—when at first life was really just cells in a primordial broth, and they were doing things that individual cells do. They were dividing, they were consuming resources, and really operating as individuals. And then at some point those individual cells started aggregating together and operating more as a unit. And eventually that went from just groups of cells to really being these multicellular entities that were regulating their division, their resource use, and all sorts of other things as a group. And that was the origin of multicellularity, the transition from an individual way of life to a group way of life. Then they became so intensely social that they couldn’t even reproduce without each other. And so really a multicellular body is a group of cells that is cooperating at this extremely high social level in order to be viable.
Our human bodies are comprised of about 30 trillion cells that are cooperating and coordinating their behavior every millisecond to make us viable. Cancer can provide a window into understanding the origins of life and evolution and what it even means to be an organism, because cancer is a breakdown of this fundamental cooperation that was necessary to evolve in the first place.
Whenever individual entities come together to cooperate at a higher level of complexity, there is always the risk that some of the lower-level entities will continue to compete and create conflicts between levels of selection. Whatever form this conflict takes, it qualifies as an example of cheating.
Athena has a general definition of cheating that can be applied across many contexts: Cheating is breaking of shared rules, leading to a fitness advantage for the rule violator.
As explained in her book, cancer is essentially cheating by cells within a multicellular body. They become cheaters when some internal or external influence causes genetic mutations that change their behavior with respect to the larger whole. They stop cooperating, begin to proliferate wildly out of control, and may form tumors which can metastasize throughout other parts of the body and eventually cause systemic failure and death.
I first encountered Athena’s work through a scientific paper titled "Cancer Across the Tree of Life: Cooperation and Cheating in Multicellularity." In that paper, I was introduced to the five foundations of multicellularity, which I quickly came to see as the biological equivalents of the social norms, laws, regulations, and governance systems that maintain cooperation in human societies. In her book, Athena presents this set of rules under a different name—as the playbook of multicellularity.
Even though our own multicellular bodies sometimes fall prey to cancer, most of the time they maintain amazing coordination of complex cooperative processes among our 30 trillion cells. How did the regulatory processes that manage cooperation in multicellularity evolve?
ATHENA AKTIPIS: This playbook of multicellularity really evolved as multicellularity itself was evolving, because as you transition from having single cells and doing your own thing to groups of cells that need to coordinate their behavior, you actually get selection for systems to regulate that group. And one of the ways you can get that regulation, for example, is genes that regulate the cell cycle. And you needed that to really have anything that is like a multicellular body that is coherent and doesn’t just expand indefinitely. You need to have some checks on cell cycle controls.
You have the rule of don’t divide, don’t replicate unless it’s in the best interests of the whole organism. So you have that rule. And that gets instantiated through genes that regulate the cell cycle. And those genes get selected on the ‘groups of cells’ level. Because those groups of cells—hose organisms that are better able to regulate cell cycles—end up doing better in the world of being a multicellular organism than those groups of cells that don’t have genes that regulate the cell cycle.
I think that was probably one of the first ones that evolved. And also the regulation of metabolism. Those two might have actually been quite interrelated with one another. Because in free growing conditions, having enough resources is often a restriction. If you don’t have enough resources that can be a restriction on growth. So there’s some interesting examples from algae that have both unicellular and multicellular species, where the regulation of whether the cells end up being reproductive or not actually has to do with genes that also regulate metabolism. Obviously we didn’t descend from algae, that’s a different branch. But I think it’s quite likely that even at very early stages, restrictions on metabolism and restrictions on cell cycle and the signaling mechanisms underlying those were quite intertwined.
The two main dimensions of major transitions are new ways to cooperate in more complex groups and new ways to use and transmit information. These are closely interconnected, since the new information systems form the regulatory processes that govern higher levels of cooperation and complexity.
A central idea of our documentary project is that modern electronic information systems—including the Internet, machine learning, and artificial intelligence—are failing to mediate cooperation in the most optimal way. Twitter bots are only one manifestation of cheating within our electronic information networks that gets in the way of cooperating at the levels we need.
So it seems as if a useful line of investigation would be to inquire how higher levels of cooperation coevolved with new information systems in earlier major transitions. It turns out part of the answer is that for cooperation to evolve, cooperators need to associate with others who cooperate, and avoid those who don’t. That takes information of a reliable kind.
ATHENA AKTIPIS: In real life, how did these potentially coevolve? In order to get assortment, preferential interaction of cooperators with other cooperators, which is how you get the evolution of cooperation—whatever the mechanism is we’re talking about. Whether it’s through kin selection, or reciprocity, or fitness interdependence, or multilevel selection, all of these mechanisms require assortment. Cooperators preferentially interacting with other cooperators. In order to have preferential interaction, you need to have some information being processed on some level, so that cooperators are interacting with other cooperators. You could do it very simply, through like what I worked on for my dissertation, the walk-away strategy. Which is just, if you’re interacting with a defector, you leave. That’s it. So, super simple rule. It’s basically a generalization of a foraging rule. If things are good, stay, if they’re bad, leave. And you can do that for social groups. And probably early in the evolution of multicellularity, we had systems like that. Where the cells that were having bad interactions socially with the other cells leave, and maybe join other aggregations.
But as soon as you want to go from just a loose aggregation of cells to a multicellular body, that has a structure, that’s maintained over time. Then you have to solve this problem of what do you with cheating that arises within it? And so now you can’t just use a super simple foraging-like rule. Right? You have to have some systems that allow the whole organism to be monitoring for where cheating is arising, and if it arises, have some sort of response. And this is where having complex information processing abilities is essential. But we’re not talking about brains. We’re talking about decentralized information processing happening with the genomes of the cells that are in different expression states, and sharing information with each other. And even within a cell, within the genome, having information processing going on in there. Like the gene TP53, that produces a protein, P53, that’s really important in regulating the cell cycle, and it makes cells apoptose or commit cell suicide if they’re behaving inappropriately. So it’s really important in suppressing cancer. This is one great example of a system where you have a huge amount of information getting processed.
What TP53 is doing, essentially—’m going to use metaphorical language here—but it’s listening in on everything that’s happening in terms of gene expression across all of the genome. So what is the cell doing? How is it behaving? What is it paying attention to? How is it communicating with other cells? TP53 is listening in on all of that. And if something doesn’t sound right, then it initiates a process of DNA repair, and if that doesn’t work well, then it initiates the cell’s suicide, apoptosis. So that, even just within a cell, is a very intense information processing system going on, allowing the cell to regulate itself, so that it doesn’t become a threat to the multicellular body.
And that whole idea of information processing then extends to what’s going in the neighborhood of cells. They’re sharing information with each other. They’re regulating each other’s behavior. You have all of these sort of neighborhood mechanisms, where cells will stop sending survival signals to their neighbors if their neighbors are behaving inappropriately. And then you go up one more level to the whole organism, and we have the immune system, which again is processing a huge amount of information from around the body to figure out where there might be threats, and deal with those threats. So it’s a multilayer, multilevel information processing system that is really what allows us as multicellular organisms to live long and relatively cancer-free lives.
In answer to an earlier question, when Athena explained how the playbook of multicellularity evolved, she only went into detail about two of its regulatory processes—those that govern the reproduction and death of individual cells. The parallels between those rules and human social groups are limited, though some exist. I asked about those parallels, and which of the other rules of the multicellular play book might be most applicable to human cooperation.
ATHENA AKTIPIS: There certainly are a lot of parallels between the processes that happen in a human body among the cells, and processes that happen in social groups—if they’re humans, or ant colonies, or even bacteria that are interacting socially. As we look across all these different levels of organization, levels of analysis, there are parallels that are very clear. If we take, for example, the playbook of multicellularity, which I talk about in my book, there are essentially five main ways that cells cooperate with one another.
I’ve talked about how cells regulate each other’s reproduction. This is something you see in a lot of species, where individuals will actually regulate each other’s reproduction. You see control over cell death. Thankfully in humans we mostly don’t interfere with each other’s right to live. But there are some contexts where that does happen. I wouldn’t say in humans that’s necessarily something I would say is part of a suite of cooperation. But it is an aspect of interaction that you do sometimes see.
The other three are particularly meaningful though, when we think about parallels with humans. And those are regulation and restraint of resource use, and distribution of resources. That’s a clear parallel, where the cells in our body are actually sharing resources with the other cells. If you think about our digestive system, our circulatory system, all of those are part and parcel of the resource distribution system of our multicellular existence. So we have resource distribution and allocation.
Then we have division of labor. So the cells in my heart are doing something different than the cells in my liver, which are doing something different than the neurons in my brain. That division of labor allows a multicellular body to do things that an individual cell could never do. We definitely see this in human societies, where coming together and dividing labor allows us as humans to accomplish things that a single human could never accomplish on their own.
And then finally we have the regulation of the environment. The investment, in the case of a multicellular body, in the extracellular environment. We’re not just made of cells. We’re also made of a lot of stuff that’s between the cells that helps to make our bodies viable and make them function. But that requires cells to be constantly creating that environment, and keeping it clean. So you have this whole infrastructure in the body that is essentially about creating and maintaining an environment for all of the cells that is conducive to their long term existence as part of that body. That is a clear parallel with the kind of infrastructure that humans often make. We make houses and apartment buildings to live in. We have trash collection so that our environment doesn’t get too polluted for us to live in it.
I think those three examples of cooperation really work for both thinking about human cooperation and cellular cooperation. The resource use, the division of labor, and the maintenance and caretaking of that environment. Those three I think are very clear parallels.
Since the rules of the multicellular playbook rely on accurate information, I wondered if it was primarily the failure of information systems—a multicellular version of fake news—that enabled cancer cells to break the playbook’s rules, and if so, what caused those systems to fail?
She emphasized that it’s important to keep in mind that life’s information systems play two critical roles—coordination of cooperation as well as detection and suppression of cheating. Failure to fulfill either of these can cause the system to break down.
ATHENA AKTIPIS: It’s absolutely essential that the information has high fidelity so that all those aspects of cellular cooperation can happen, and also that cheating can get regulated. So there’s two levels where information is really important. One is for the coordination of cooperation. It requires a transfer of information to make sure that the division of labor is happening effectively. Even if you don’t have any threat of cheating, there’s still a challenge in making a group work together effectively to reach a collective goal. Anybody who’s been part of any group work at any point in their life knows that even when everybody has the best of intentions, you still need effective, clear communication in order to have that group work result in something that’s greater than the sum of its parts. So that is an exact parallel to a lot of what happens in the body.
But there’s also another level where information processing is essential, and that’s for the detection and effective response to cellular cheating, if it arises. In order to have the detection of cheating be something that can even happen, you need to have information being processed somewhere, and then have some sort of response system. So genes like TP53 are important in that regard, because they are processing a lot of information and then responding if it looks like a cell is in the wrong stage, or may have damaged DNA. So those are two examples where you really need to have effective information.
Now one other interesting layer on top of all of this, is that once you have information processing systems in place for detecting and responding to cellular cheating, those systems and cells can then get hijacked by the very entities that you’re trying to regulate. So oftentimes in cancer what you see is an environment that looks like a wound healing environment that just never resolves itself. Now what’s going on there? Well, what’s happening is that the cancer cells are producing signals that are simulating a wound healing environment, and in a normal body, when you have a wound healing environment it’s much more permissive for cells replicating and moving around. And so the cancer cells are basically hijacking this information processing system in order to get around some of those checks and balances that the multicellular body has in place to try to detect and control them.
The first truly multicellular organisms emerged nearly a billion years ago. Given all that time, why hasn’t multicellular life evolved regulatory systems that unfailingly detect and destroy cheating cells before they become cancerous, and inflict serious harm?
One simple answer is that cancer becomes more prevalent as we age—when we’re beyond our prime reproductive years. As far as natural selection is concerned, if cancer strikes us after we’ve already had the chance to pass on our genetic heritage, from an evolutionary standpoint our death doesn’t count.
However, it turns out that’s not the whole story. Athena explained why complete suppression of behaviors associated with cancer and cheating is not always a desirable thing.
ATHENA AKTIPIS: One of the big surprises is that suppressing cancer is not all good all the time. Now let me back up for a minute and explain what I mean. Because it seems like less cancer, that should just be better, right? Less cancer means greater survival, and survival is one of the foundations of natural selection. You need to survive. But the other piece of it is reproduction. And oftentimes some of those very same mechanisms that allow for cancer to be kept under control can also interfere with processes that can increase fitness otherwise. So for example, having too tight control over cellular proliferation can lead to a smaller final body size. And we know that in a lot of species, body size is something that’s sexually selected. So if you are too small, you might be less reproductively successful. Even though you might have a much lower chance of having cancer and dying from that. Just one example.
Another great example is wound healing. Wound healing is a sort of risky thing that organisms have to do. So if you have a wound there’s kind of a tradeoff from the perspective of your body and your fitness. Which is, should that wound close quickly, so that then you have a lower risk of infection? Or, should that wound close more slowly which might make for a larger risk of infection. But if you have a very fast wound healing physiology, then you have cells that are more poised and ready to divide quickly, to move, to cover that wound. And those are the very same phenotypes that are associated with cancer. So there are a lot of these tricky tradeoffs between being an organism that is able to accomplish all these other adaptive goals that need to happen in order to be reproductively successful, and on the other hand keeping cancer at bay long enough to actually survive to reproductive age.
So there’s a sort of tightrope walk, this balance that has to be struck between the cells having enough freedom and free rein to accomplish those goals, while not having so much freedom that they end up replicating out of control, moving in ways that they shouldn’t, consuming too many resources, and ultimately leading to cancer. So it’s a delicate balance.
The idea of maintaining a delicate balance that gives cells just enough freedom to accomplish their work in service to the multicellular whole—but not so much that they cause cancer—resonates with one of our project’s central themes. It suggests interesting parallels between the regulatory systems of multicellular bodies and the governance of human societies.
The rigid central control that would maintain a multicellular body cancer-free seems analogous to an authoritarian dictatorship. A multicellular organism with regulatory systems so lax that cancer could metastasize freely would correspond to extreme libertarianism or the chaos of complete anarchy.
In between those extremes we might find a liberal democracy that provides sufficient freedom for people to pursue their goals within the constraints of a fair system of regulation and laws. As the history of human civilization demonstrates, it’s been devilishly difficult to find and maintain that balance, even prior to the Internet Age.
Given the profound effects of information technology on so many aspects of modern society, I wondered if there were any useful parallels between the way information systems evolved in multicellular organisms and the evolution of electronic information systems today.
One critical thing certainly is having information that has high fidelity, having some way of ascertaining the validity of information, and then having trust that information is accurate. And that is something that is implicit in how a multicellular organism operates. But it’s something that we can’t assume in human life. Like when we’re on the Internet and encountering information, or on social media, or on Twitter, what do you see, is that real, is that not real?
There are a lot of tools that we might want to think about developing in order to make sure that we have ways of knowing the source of the information—because that can tell you something about its likely fidelity—and having ways of checking that information with a broader body of knowledge. Which can be a challenge if you don’t even know where to start in terms of what is true and what is not true.
So I think that it’s a huge challenge. But I think that if we look at how our body works, we have an immune system that is there to monitor for things that are going awry. Whether it’s our own cells that may be having cancerous mutations, or whether it’s viruses or bacteria that are utilizing our body for their own replication. And to the extent that we can think about creating systems for our human information processing system—humanity’s information processing system—that have elements of that, where they’re detecting things that are replicating abnormally. Or attracting attention abnormally. And flagging those. That could be useful.
Unfortunately right now there’s almost selection for those elements that replicate really effectively. Because to the extent that they take human attention, they allow these platforms to sell ads. So I think we really have to grapple with the fundamental structure of how we share and spread and amplify information, either purposely, or inadvertently, and what the consequences of that are for how we as humanity process information.
I’ll offer a speculative analogy here. Which is, if we think about each of our electronic devices…and it’s obviously an interaction between my smartphone and my brain. But if I think of my smartphone, what if every smartphone had on it some sort of a TP53-like system, which would be scanning your social media, maybe even your email, the websites that you’re going to, and flagging any information that seemed to be replicating at a rate that was too high for the kind of information that it was. And when that happens, what if that triggered a response at the level of your device, so you could then regulate your interaction with that piece of information.
But it could potentially also tie in with other devices. If multiple devices are detecting something that’s abnormal, maybe that can aggregate up and get processed by some higher-level institution that is monitoring the spread of information. I know that some sites, especially Facebook and Twitter, are starting to implement some company level processes for monitoring information that is going out and flagging things that might be fake news. And then responding to those. But we might be able to take this information processing infrastructure that the human body uses, with these multiple levels. Where you have the individual cell that’s monitoring. Our own computers could be doing some monitoring. Along with employing our own brains, and our own cognitive abilities to monitor. And then that could aggregate up to small networks, and then things that are still issues could then perhaps get pushed up to a higher level. We could think about creating some sort of a multilevel structure for monitoring the spread of fake news, or dangerous information, and keeping that regulated so that it doesn’t cause damage.
Misinformation on the Internet has played a prominent and too often a counterproductive role in our current crisis, the coronavirus pandemic. At a time when we need accurate and reliable information more than ever, we’re inundated with proliferating conspiracy theories and worse.
When I asked Athena if she had any thoughts about the pandemic and its effect on cooperation, she told me about a study she’s recently begun.
ATHENA AKTIPIS: Before the coronavirus was declared a pandemic, when it was clear to me and some of my colleagues that we were on the precipice of a serious change in how society was going to work, we put together a study to look at people’s level of cooperation, their perceived interdependence with others, their risk management and preparation behaviors, and we launched that online.
And we’ve collected data from six time points, since March 6th, over the course of the pandemic. And this is allowing us to look at how the virus has changed or hasn’t changed people’s willingness to help others, their perception of their interdependence with others, and how that relates to their engagement with preparations for the pandemic, and their willingness to help others deal with the pandemic as well.
It’s a really exciting project for us. In order to deal with crises, very often humans can’t deal by themselves. We need to rely on others. And this is something that has been the case for our whole evolutionary history. And as part of the Human Generosity project, we have been looking at cooperation across human societies. In particular in small scale societies, how do people cooperate to manage risks, especially those that come from unpredictable and unexpected events? Like natural disasters, diseases, droughts, etc.
And we’ve seen that across all these small scale societies we’ve looked at that people help each other in times of need, oftentimes without expecting anything in return. And especially when that need is arising from something unpredictable and uncontrollable. People go into this mode of what we call need-based transfers. Where they’re not keeping track of debt, they’re just like, “oh, you need help, I have what can help you”, and they give. This mode we think is a really important part of the human behavioral repertoire. When there’s a crisis, when there’s some sort of a shock, that people are much more willing to help based on need, and not expect to get paid back. So this current crisis is an opportunity to look at that in modern western society during a crisis. We’ve looked at it in more than ten small scale societies now, and this is a chance for us to look at this on a larger scale, in a modern market integrated countries.
The concept of fitness interdependence is central to the idea of major evolutionary transitions. It is what binds groups ever more tightly together once a transition starts. For me it’s compelling as a motivation for cooperation because it doesn’t necessarily rely on relatedness or reciprocity to work. All that matters is that we see our fates as being intertwined. I asked Athena to expand on that idea.
ATHENA AKTIPIS: One of the things that we’ve worked on in my lab and with several other groups that are studying cooperation is this idea of fitness interdependence. When you have organisms that are relying on one another for their survival, their reproduction, their wellbeing, then what ends up happening is they have a stake in each other’s wellbeing. And that means you don’t have to have genetic relatedness, it means you don’t need to have payback, because the fitness is interdependent. So by virtue of helping the other individual stay alive, and stay healthy, their continued wellbeing reflects on your evolutionary fitness automatically.
So to the extent that you have situations where fitness is interdependent, you can get the evolution of cooperation more readily. I think one of the things that’s really interesting, and unique about humans, is our ability to propositionally communicate about our interdependence. To say, “hey, I feel like we’re interdependent.” We use all sorts of mechanisms for that, including kin terminology. If I say, “hey, brothers and sisters, let’s accomplish this goal together.” That automatically elicits this feeling of fitness interdependence, I think.
Now of course, back to cheating, that can also be used to manipulate people. To get them to do things that might be against their interest, and for the interest of the individual that’s doing the manipulation. But regardless, it is an amazing tool that we as humans have. Not just the shared interest, but the shared understanding of our shared interest.
The concept of fitness interdependence undergirds a critical question: If we are indeed in the midst of a major transition in the Internet Age, what will bring us together to cooperate at the higher levels we so urgently need? What new form of cultural organization will evolve?
Will global-scale challenges such as climate change and ecological decline make us finally realize that our fitness is indeed interdependent and intimately intertwined? Not just our fitness as individuals, but also at the level of our families, our religions, our businesses, our cities, our nations, and the entire world. It encompasses not just the health of human civilization, but the health of Earth’s ecosystems that we depend on to survive.
There are myriad forms of cheating that cause conflict at every level, in every arena of human pursuit. We are also capable of cooperating in complex and wonderful ways, at grand scales. How can we suppress cheating, particularly as it runs wild through our electronic information systems? How can we become more broadly aware of our fitness interdependence, and make the major transition to a more cooperative global society before it’s too late?
The transition from unicellular to multicellular life offers tantalizing hints. However, as Athena points out in this final part of our interview, the challenges that confront us are unlike anything life has faced in the past. Though there is much we can learn by gaining a deeper understanding of how earlier transitions took place, evolving a major transition in the Internet Age is entirely up to us.
ATHENA AKTIPIS: I think there’s an extremely important question about how do we effectively scale up our own cooperation, as humans, to a global level. And is there anything we can learn from looking at multicellular cooperation, and how that’s regulated, in terms of ways that we might be more effective, and also pitfalls, that we might want to try to avoid. One of the issues I think that is really challenging for human large scale cooperation is that if we think of all of humanity, it is one system, that has not had the kind of evolutionary history that would allow selection to be operating on the level of the entirety of humanity.
Now if we had, say, 500 earth-like planets with human-like entities on them, and they varied in the cultural and information systems and all of that, and only a subset of them did well enough in order to start colonizing the other planets, then you could have selection among those humanities for the large scale cooperative system that is regulated in a way that allows for more growth and greater viability of that group of humans. We have this constraint that evolution hasn’t done that for us, and it’s not going to do that for us. If want to purposively create a more cooperative society we have to be very deliberate about how we’re going to create our institutions and information systems in order to leverage the things that we know help to support large scale cooperation. And keep cheating at bay within those large-scale cooperative systems.
I think that there is a vision that we can come to together and share, of a future where we are being much more effective at coordinating global cooperation. At taking care of the most vulnerable individuals because we acknowledge that there’s fundamentally interdependence of all of humanity. I think there is a vision that we can aspire to.
But I do think we have to be realistic about the challenges that we face as a global society in doing that—that it’s going to take very deliberate and very intelligent measures in order to get us there. Because we have to figure out how we can take these things we know about how cooperation is effective at lower levels of organization, and then expand that in humans to higher levels of organization.
We can’t just look at human societies for that. Because human society has never had to coordinate on the level that it has to do now. To the extent that we can draw from these other systems, that already have this massively large scale cooperation, like the human body that is made of 30 trillion cells. If we can learn from some of those systems, and actually then extract the information about how those systems are designed, and then utilize the components that make sense for human societies, we might be able to do a better job.
But we have to be really careful in all of that to also be considering the ethical dimensions of that. There are a lot of things that a multicellular body does to regulate the cells inside of it that nobody would think are ethical for humans to do to one another. Or to have an institution be regulating. So I think it is something that is a really worthwhile goal, but something that will require a lot of brains in the room that are thinking of all the different aspects of how do we properly scale up these solutions to be able to increase our global level of cooperation.