Two Brains

Imagine a civilization of creatures living on a rock in space, trying to design a future for themselves in the vast unknowable universe. For reasons no one understands, these creatures evolved in a peculiar way: They all have two brains—one super-smart and transcendent, the other primitive and murderous— that struggle against each other in their heads. One of the brains predominates in all individuals. But everyone is capable of savagery, everyone can have brilliant thoughts. The results of this endless conflict are apparent in the civilization they’ve created: Every tribe has a long history of ingenious art and science, paralleled by the most outrageous brutality and self-inflicted suffering.

If we get enough altitude above these creatures, we can see their history over time:

The ones most dominated by their rapturous, transcendent brains gave instructions to the others who then went out to spread the good word—with swords and slaughter.

They figured out how to make great sailing boats to travel to strange new countries where they raped and murdered the strangers who lived there and stole their land and possessions. They figured out how to split the atom. We know what happened with that.

The creatures’ most recent double-edged sword is made of data. Just like building sailing ships and exploring the insides of atoms, collecting data from the world with sensors and turning it into intelligence is their next great accomplishment. It can be a tool of great liberation and social growth. It can also be a tool of slavery whereby the controlling social powers can derive their data from surveillance of members of the population and use it to build virtual cages for them.

What will they choose to do with it?

Open Technologies

The late Buckminster Fuller used to say that all significant inventions eventually become the common property of humanity, regardless of their proprietary origins. There was, for example, a moment when the technology of the ballpoint pen was brand-new and belonged to its inventor (whoever that was). At that point in time, a ballpoint pen was a precious thing. Over time, the concepts and techniques for creating ballpoint pens became common knowledge, and the once-amazing writing implement became cheap and commonly available—an unremarkable fact of everyday life.

Fuller was also fond of pointing out that if you were stranded on a desert island and your life depended upon creating a ballpoint pen, you were in big trouble, even though in the midst of humanity you could get one for pennies. In other words, the benefits of shared information are incalculable, good for everyone, and vital for our evolution as a species.

A couple of decades after Fuller’s death, the open source software movement came into its own. Fuller had nothing to do with it, but he would have liked it. The open source philosophy holds that digital technology is among the most significant of human inventions, and its core manifestations should be the common property of humanity, too—not “eventually,” but now, as they are being created.

Think Like a Child

What’s the first thing kids are taught? Maybe you have children in pre-school or kindergarten, or you can remember your own early years in school. When we look back, what sticks out most are lessons in sharing. “We share because we care” was the slogan our teacher used, and she made it concrete. We couldn’t eat a piece of candy unless we’d brought enough for the entire class. It would be wrong for Johnny to enjoy a chocolate bar in front of classmates who had nothing. Every child learned this.

Many of the biggest truths in life go back to the simplest things. “Think like a child” people say when they want you to see things in a fresh way. Some of the most truly innovative thinking has come from perceiving the painfully obvious—once the perceiver saw past her learned preconceptions. Albert Einstein boarded a train and for one crucial moment he didn’t know whether it was his train that was moving or the train alongside him. That simple experience led to the Theory of Relativity and changed our understanding of reality.

“We share because we care” could easily be a foundational principal of data policy in the 21^st century: We share data because we care about the welfare of our society.

We’re not necessarily talking about sharing “for free,” though much data, like that gathered with public funds, will continue to be shared without a fee because it’s already been paid for with our taxes. But whether we pay in advance or in arrears, whether the data is privately held or held in the commons, our point remains the same. Innovation should make life better for all humans, not just for some.

To do that in this century means sharing data to further develop AI and machine learning, and to facilitate the lifelong learning that humans need to do to continue developing themselves alongside their machine servants.

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Creative Contention – Web3 or What?

Many industry observers have written recently about Web 3.0 technology developments being the “ultimate” answer to the many challenges we are writing about.  We think not. At least not entirely.

First, we all need to acknowledge that there is no single or stable definition for Web3 technically or otherwise. Many people have identified Web3 with the “semantic web,” which focused on the ability of machines to read and interact with content in a manner similar to humans.  More recent definitions of Web3 have focused on decentralized or distributed systems and new enabling technologies, such as blockchain with its ability to authenticate and decentralize information and enable trust.

We applaud the early idealism, optimism and vision of Web3 but we have been here before. We have all gone through several cycles of decentralization and recentralization. The personal computer decentralized computing by providing a standard PC architecture that anyone could build and that no one controlled. But Microsoft figured out how to recentralize the industry around a proprietary operating system. Open source software, the Internet, and the World Wide Web broke the stranglehold of proprietary software with free software and open protocols, but within a few decades, Google, Amazon, and others had built huge new monopolies founded on data analytics and surveillance.

If the original thinking was to return the power of the large platform players like Google and Facebook to individuals, the result we have all witnessed quickly defaulted into a Web3 vision based on blockchain and crypto. The advertised decentralization of power has, in fact, been a re-centralization of power into fewer hands. Roughly 10% of the Ethereum blockchain accounts hold approximately 80% of its nearly $200 billion market value. This is the practice of “whitelisting,” which keeps the bulk of NFT profits within a tight circle of insiders. Approximately 2-3% of Bitcoin accounts control more than 90% of the $500 billion supply of Bitcoin. Crypto technology players are a lot like all techno-optimists — they never criticize each other about their noble missions to save the world.

Web3 advocates claim decentralized autonomous organizations are superior to traditionally organized corporations. However, even if the digital world is shifting dramatically from centralized to decentralized to enable large scale frictionless interactions and collaboration, it does require some degree of “centralization.”  The extensible, technology-neutral nature of the Internet allowed it to scale dramatically and gracefully with minimal central administration, but it still needed oversight and management.

None of this is the technology’s fault. Distributed organization structures create the potential to streamline communications, improve relationships and achieve more transparent corporate governance. There are many indicators that companies will continue to become more structurally distributed and drive new modes of innovation that reduce bloat and slow decision making. However, like most innovations that are aggressively promoted when they first appear in the marketplace, their evolution is less dramatic and often takes longer to mature.

SOLVE THIS RIDDLE

Here’s a riddle for you: How is the global rise of nationalism like the widespread failure of digital transformation in business?

The result of the English and Brexit reminds us that the EU is a far more significant experiment in cross-country cooperation than most people realize, and cooperation of that type is hard work. Beleaguered by the complexities of living in a modern ecosystem, the English elected to return to the simpler world of the past. They chose to regain “control” of their money and borders at the price of isolating themselves. Presumably they will now “make England great again.”

Similarly, our ability to take advantage of digital technology’s true promise remains close to nil. The Internet began as a great experiment in collaboration and decentralization; in a mere 20 years we’ve siloed it into Facebook and Google and Amazon. We were offered the opportunity to craft organic global ecosystems; instead, we pedaled backwards as fast as we could, crafting not utopias but dystopias of surveillance capitalism and government-operated facial recognition.

What commonality do isolationist nationalism and digital-transformation failure share? Human fear and the need to maintain control, however insane those things may actually be.

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THE LIMITS TO GROWTH WAS ACCURATE

Fifty years ago, an international team of researchers based at MIT conducted a study of the sustainability of human activity on Earth. The non-technical report of their findings, published in 1972 by the Club of Rome under the title The Limits of Growth, was conclusive: The Earth’s interlocking resources—the global system of nature in which we all live—cannot support present rates of economic and population growth much beyond the year 2100, if even that long.

Although the conclusions of The Limits to Growth were taken seriously by enlightened thinkers in the 1970s, they were widely ridiculed by the political and corporate establishment of the time. But recent scientific reviews of The Limits to Growth confirm that humanity is on track to play them out almost exactly as predicted.

In fact, the 33^rd Report to the Club of Rome, published in 2014, draws on the work of the world’s leading mineral experts and forecasts that “industrial civilization’s extraction of critical minerals and fossil fuel resources is reaching the limits of economic feasibility and could lead to a collapse of key infrastructures unless new ways to manage resources are implemented.”

The planetary systems that human beings radically disrupted took millions of years for nature to create. Often referred to as “circular economies,” they are paragons of efficiency, using everything they contain to minimize or even eliminate waste. In a human-built world that is quickly revealing itself to be unsustainable, they are the natural models we ignore at our peril.

However, if you watch mass media you might think the real story is about which billionaire will take the first ride in space to the Moon, or beat his (they’re all men, of course) competitors to Mars.

THE BLIND LEADING THE VISION IMPAIRED

This evolution reminds us of a story by H. G. Wells, The Country of the Blind. The story concerns a group of people living in total isolation in a valley of the Andes Mountains. For an unknown reason, the inhabitants of the valley have been congenitally blind for two or three generations.

The people in the valley have re-evaluated much of the information handed down through oral tradition. New impressions have been forged based on subjective experience. For example, they have decided there is no difference between angels and birds. The people have reasoned that they can hear both birds and angels sing, and they can feel the wings of both brush their faces—so there must be no difference.

The story depicts a group of people who, as long as they remain in isolation, can rationalize any type of behavior—no matter how absurd the behavior appears to an outsider. Isolation and blindness lead the inhabitants further and further away from the truth.

In our opinion, existing schemas, institutions and approaches for collaboration and sharing are, for the most part, broken. In this age of digital innovation, the complexity of the interdependent relationships required to solve really big societal problems only compounds the challenges. In this environment, collaboration depends on interacting in new and creative ways. Linking “strange bedfellows” by breaking down the barriers to communication is the first step, but it can’t stop there. The key is trust.

IN BOTS WE TRUST

Apparently, the bots are coming, so it follows that humans are rapidly moving into a world where we interact with artificial intelligence and bots on a daily basis. AI is enabling a whole new realm of cognitive services but in a very different way than our brains and neurological system does. If that’s the case, then how do we build relationships with bots and how do we know if we should trust them?

Computers are destroying pre-existing communication modes. We can now use innovations like voice recognition, natural language processing, computer vision, affect detection, synthesized voice, and 3D-modeled character animation to filter input and output channels for computer-human interactions.

An everyday occurrence like waving and saying, “Hello, Friend!” used to be a coordinated multi-modal set of analog signals. The words, sounds and image all happened at once. Digital technology can now filter those signals, separating them into discrete modes. Computers segregate natural language into words that are separate from voice and distill sounds, phrases, gestures, and more, channeling each mode into different segments for processing, filtering, and analysis. Computing is great for all of this AI stuff.

When meeting a person, we don’t know we exchange conscious and unconscious social cues. The right combination of social cues, symbols, and signs instills trust in the participants of the exchange. These modes of interaction help both parties predict and understand the other person’s thoughts and actions. It’s been shown that you’re more likely to trust someone that looks like you.

But what does any of this have to do with bots? Can you look up the professional qualifications of a bot, or get a sense of their personal interests? How would you test if a bot is going to act in your own interests? It’s becoming crucial to understand whether accepted evidence for human-human reciprocity holds true for human-bot interactions. The notion of trust underpins so much of society, whether we realize it or not.

In order for bots to realize a return on their technology investments, they must obtain users’ trust. Trust is largely founded in repetition; without repetition and predictability it’s almost impossible to build trust, especially when interacting with a system. Just like people create trust through authentication, repetition and exchange of information, bots need to do the same things humans do to earn your trust.

Without rich, multi-modal communication, you don’t have empathy, and without empathy you don’t have trust, and without trust, society breaks down. Bots will need to become multi-modal. It’s not about them. It’s about us.

STUCK IN A SILOED WORLD

Our civilization is built on knowledge, innovation and collaboration. Our progress is predicated on growth – increasing knowledge leading to vitality, expansion of life, and the well-being of humankind.

There are only three sources of growth: people and population growth, natural resource utilization, and technology. Developed societies are shrinking and depopulating across cultures all over the world and natural resources have finite limits, both real and political. The only perpetual source of growth is technology – new ideas, new tools and innovation.

Innovation is Darwinian and driven by the natural selection of ideas. The best and most productive ideas win and are combined and generate even better ideas. Those ideas materialize in the real world as technologically-enabled goods and services that never would have emerged on their own.

Ray Kurzweil defined his Law of Accelerating Returns: technological advances tend to feed on themselves, increasing the rate of further advancement. Brian Arthur defined Combinatorial Evolution: radically novel technologies do not come into existence by the cumulation of small changes in earlier technologies, they spring from combining or integrating earlier technologies.

As we continue to evolve, many of our biggest challenges in society and business still originate directly from our inability to creatively collaborate and solve big cross-border problems (pandemics, climate change, and more). New knowledge, new tools, and innovation are the feedstock of growth, but not without collaboration.

Human beings started out living in nature as part of an ecosystem. Then we self-elected out of the ecosystem and started destroying it. We continue to live in silos of our own making, despite digital technologies and global networking that offer more opportunities to cooperate than we’ve ever seen before. Optimization of any resource illustrates the value of shared systems and collaboration, but do we really understand what it will take to leverage knowledge and new tools for collective good? ◆