Sociobiologist Edward O. Wilson once said that the real problem of humanity is [that] we have paleolithic emotions, medieval institutions, and God-like technology. A positive exponential future will depend on how effectively that trio handles society.

Wilson’s is an insightful yet frightening framing. But, as I will argue, there is reason for optimism as long as we move beyond our fixation with our own individual brains as the center of the action — because they are clearly no match for the challenge at hand. Instead, we can and should deliberately enlist the power of digitally augmented collective-intelligence entities: superminds.

Think about it. Various forms of technology have triggered momentous changes in networks since time immemorial. Think of the emergence of the most powerful societies in history, from the Roman and British empires to the United States and modern China: they are closely intertwined with the evolution of networks and their technology such as roads, language, and media.

One could even intuit a more general power of very simple primitives of collective intelligence. For instance, nodes that are connected and fed simply but not randomly, are able to store information curated through some form of active inference. They may then predict future events and can help organize lots of things. From tree roots and fungi to our brains, to industrial ecosystems, and perhaps even some form of planetary Gaia system, network-based intelligence drives successful evolution through new organizing structures.

In this essay though, we will focus on something closer to home: organizational, economic, and civil-society networks, and how we can deliberately and effectively design and engineer them to fight climate change, build a future of work that works, improve our democratic governance mechanisms — and more.

Superminds, originally conceptualized by Prof. Thomas Malone (founder of MIT’s Center for Collective Intelligence), are not Kurzweil’s Singularity things, or a philosophical or religious concept — at least, they don’t need to be. They simply represent a valuable framing for organizational design in an exponential world.

I describe future superminds as the result of the interplay of networks of people and intelligent machines, thus generating emergent, superior (and possibly exponential) cognitive properties.

Superminds are all around us already. From social media networks to blockchain and modern financial trading markets, from Wikipedia to Google Search to PatientsLikeMe, from Linux to Gitcoin and Bellingcat, from Taiwan’s use of Pol.is to Citizen Assemblies and OpenStreetMap, from drone swarms to Ukraine’s decentralized defense networks, from manufacturing giant Haier to hedge-fund Bridgewater to enterprises using Microsoft Viva Topics, bits of superminds are being harnessed already. (A few hundred examples of them and their components, big and small, here.)

The network is the mind — and it can be hijacked

Network effects underlying collective intelligence have changed the world’s competitive dynamics. Seven of the ten most valuable companies as of 2021 end rely on them extensively: Apple, Microsoft, Alphabet / Google, Amazon, Meta / Facebook, Tesla, and Tencent, use some form of supermind, as they harness communities and markets as part of their operating model. As Exponential View regulars among you will know, founders and investors already use network effects — a precursor to collective intelligence. I highly recommend listening to his conversations with James Currier of NfX, a16z’s Andrew Chen, and NumerAI Richard Craib.

Much of these companies’ strengths comes from their use of the cognitive power of billions. Web 2.0 has largely been about concentrating that power into the hands of the few, who could increasingly use AI to monetize its power — often for some sort of commercial recommendation system. In so doing, they’re steering the output of the supermind they’ve summoned in a very specific direction. The upshot is obvious and might make the difference between sharing facts and propagating disinformation (which human networks tend to like), or between following democratic processes and sleepwalking into civil strife or autocracy. And just maybe, a hijacked supermind could be the endgame of AI gone rogue, which makes Nick Bostrom’s superintelligence nightmare come true. (Oh, if one thinks that good ol’ institutions and their circuit-breaking censorship can do better, remember how China’s social-media signal suppression slowed down a global response to Covid-19.)

Like all powerful technology-based practices, digitally-augmented collective intelligence can be used for good and for bad — and/or incompetently.

And some are using them, with often insufficient scrutiny and regulatory boundaries, as the raging debate on social media content moderation attests. The cat is out of the bag.

Tomorrow’s problems, solved with tomorrow’s intelligence

There’s a lot that we can do with intentionally engineered superminds.

Think about using them for fighting climate change, and specifically to hasten the adoption of relevant technologies. The cycle historically takes decades but for climate change, we just don’t have that time. I believe we can do better today than we ever did in previous technology-propagation waves. Hyperspecialized collective-intelligence “utilities” could accelerate the spread of high-momentum/low-signal content (both granular practical enablement and broader learning materials), and support the identification and engagement of relevant people (experts and practitioners). The upshot would be that the new granular, practically implementable knowledge could be quickly matched with the early majority of mainstream users to cross, in the words of Geoffrey Moore, the innovation chasm.

Decentralised-science superminds could benefit from a potential revolution in collaboration (think knowledge graphs and AI transformers) and incentives (think tokenization).

The Future of Work agenda can also benefit from, for instance, a better understanding of the drivers of the Great Resignation by using a network lens; or by rekindling the serendipitous connections between “weak-tie colleagues” that are often severed when working from home, and yet are so important for innovation and culture.

Where do we go from here?

One of the hardest skills to find in innovators is the ability to think in systems — superminds are systems-design for organizations, and I believe they can be learned by extending current innovation practices. My MIT colleagues and I call this “supermind design”. My money is on the prediction that our children, and some of us, will have jobs such as supermind designer, supermind engineer, and supermind operations lead. I am open to (maybe crypto-denominated) bets on this.

(There’s a lot more to it. ​​For more detailed guidance, take a look at my open source book.)

Our society has created huge challenges through the interplay between our paleolithic brains, our archaic institutions, and our technology. But we can take the logical next step to build superminds that overcome them, and withstand the thrust of an exponential world.

This article was originally shared as a newsletter in Exponential View, Azeem Azhar’s highly recommended analysis and curation of technology and society trends.