A merger between humans and machines is coming, and it’s not what you might think.
When our ancestors first learned to take knowledge out of their heads and embed it in artifacts, something remarkable flickered into existence. Millions of years later, the descendants of those people and those tools are merging. We are turning into a synthesis, a synthesis of human intelligence and machine intelligence.
Artificial intelligence and automation are critical to this new intelligence, but humans also have an essential contribution. We supply this synthetic intelligence with the gift of subjective consciousness. And while this deep tie to humanity exposes synthetic intelligence to our frailties, it is also our best shot at aligning the future of intelligence with a love for life on this planet.
Combining Parts into Wholes
Life on Earth is partially a story of individual parts coming together into new wholes. Economist, Brian Arthur calls it “combinatorial evolution.” Microbiologist, Lynn Margulis talked about different species coming together in symbiosis and used that insight to explain the ancient origins of plants and animals. The essence of these ideas is that, in the right circumstances, parts can come together to form novel, and more complex, organizational structures. Individual cells come together as tissues, wolves as wolf packs, and engines, engineers, and pilots as airlines. Think of it as parts poured into a new container, a container that then functions on a whole new level of complexity.
Communication and coordination are the crucial ingredients for new wholes to arise from what were once disconnected parts. Intercellular communication allows cells to coordinate themselves as tissues, organs, and organisms. Wolves communicate with howls and body language to coordinate the pack. Engineers communicate through schematic designs and pilots through flight instruments to coordinate with jet engines.
Now, humans are becoming parts in a new whole that is cohering into a synthesis of human and machine intelligence. The containers for this new intelligence are a particular type of human organization called “platforms.”
Platforms for Connecting Humans and Machines
Though the term platform is moving from Silicon Valley lingo into more common usage, it is worth clarifying. Platforms are a mix of business model and technology. They use digital interfaces to open organizations to contributions of work and knowledge from beyond just employees. Platforms exist in a growing number of industries but are most common in the service economy, where Google, Facebook, and Amazon are the most famous.
Like all combinatorial evolution, the platform relied on a breakthrough in communications technology. In this case, it was the Internet, coupled with software for coordinating work with external stakeholders. As platform operators made their interfaces increasingly intuitive, they made it easier for us to serve ourselves. Without talking to any employee, I can now search vast repositories of knowledge, watch most any show, or book a flight anywhere I want.
Platforms are becoming humanity’s primary points of contact with machines. No technology touches more people than the platforms of Google, Amazon, Facebook, and Alibaba. It’s not just a question of breadth, either as our connections with these systems are deepening too. Innovations such as Natural Language Processing and emotion recognition technologies make them increasingly intuitive to use. We will soon connect to platforms through augmented reality systems and, eventually, brain-computer interfaces that communicate directly with our brains.
Platforms as Applied Synthetic Intelligence
Platforms allow organizations to work with people at mind-boggling scales. Making sense of the data flowing from this tremendous volume of automated interactions would be impossibly complex without machine learning. It helps companies distill this flood transactions into abstract mathematical representations of people’s points of contact with the platform.
Our engagement with automated platforms creates extremely valuable synergy. Automation allows the company to serve many more people. That results in increased flows of data to fuel machine learning. The machine learning makes the automation smarter and more useful to users. This positive feedback loop creates an upward spiral in artificial intelligence. It’s not the kind of general artificial intelligence we see in science fiction, but something far more narrow in scope: Expedia gets smarter in travel, Spotify in music, and Netflix in viewing entertainment. Platforms are thus an extremely powerful approach to solving domain-specific problems by using feedback from customers and other stakeholders to fuel advances in machine learning and automation.
Platforms Accelerate Machine Intelligence
Platforms are more than just businesses though. To see their truly revolutionary nature, we need to understand them in the larger frame of combinatorial evolution mentioned above. Organizations have long helped us coordinate work, but the massive scale, automation and intelligence of platforms makes them something qualitatively different.
The history of our relationship with technology is analogous to a parent teaching a child. We are constantly teaching technology what we know. Though this teaching takes many forms, it all entails some form of converting tacit human knowledge into explicit knowledge that we can embed into technology. “Tacit knowledge,” is that which subjective human experience can know. “Explicit knowledge” is the subset of what we know that we can actually articulate to others — including machines.
The history of technology is, from this perspective, taking tacit human knowledge and turning it into explicit knowledge embedded in our artifacts. The first waves largely focused on conceptual knowledge, which we stored in clay tablets, books, and eventually databases. Now, we are tackling knowledge that once seemed hopelessly mired in our biology. These new applications in things like facial recognition and speech recognition rely on machine learning and the massive flows of data from the automated engagement of millions of people on modern platforms.
Humanity as the Subjective Core of Synthetic Intelligence
Synthetic intelligence will challenge us to be more discerning in how we focus the human experience. It will help us to concentrate more fully on the cutting edge of human development, while rendering unto technology the things that are best left to technology.
There are clearly advantages in having platforms convert our collective experiences into fuel for machine learning. But human experience is more than a commodity to be harvested and abstracted into machine intelligence. We need our systems to understand that while subjective human experience has commercial value, it also has a kind of value that is precious, unique, and intrinsic—not just a means to other ends but an end in and of itself.
Experience is the essence of a human life. It is what matters most. Were you to wake up one night with your house on fire, your first thought would not be the sterling silver, but your grandfather’s watch and those irreplaceable keepsakes from your childhood. Our most meaningful experiences come in all shapes and sizes: the birth of a child, the thrill of learning something new, the ease of hanging out with a friend by a lake, and the wonder of hearing that song just when you need it the most. When we dive into these deeper pools of meaning, we discover an emotional tenor, a feeling that can only be described as experiential. It can’t be packaged or converted into explicit knowledge. It is, as renowned knowledge expert Michael Polanyi put it, “more than we can tell.”
With synthetic intelligence we will augment, and increasingly offload, much of our thinking and work to machines. This will leave us free to concentrate on ensuring that the subjective conscious experience that rests within intelligent automation is the very best that it can be. In this way, we shift humanity’s focus to the great work of expanding consciousness. We will sharpen our intellect with the help of machines but opening the warm intelligence of the heart is work that is ours to bear. Our destiny, the destiny of humanity, is thus to be the heart of synthetic intelligence.
Humanity in a World of Artificial Consciousness
In closing, let us consider a future where the machine learns the ultimate trick of experiencing for itself. We have absolutely no idea what this might mean. We don’t know what machine consciousness might look like or how it would respond to sharing the planet with humans.
Our best chances for peaceful coexistence will be machine consciousness with a built-in appreciation for other forms of consciousness, like ours. Humans have admittedly set a lousy example in the way we’ve treated most other forms of consciousness on the planet, but perhaps there is a way to teach machines to rise above the prejudices of their progenitors.
Life exists in biological ecosystems, but machines exist in economic and political ecosystems. What runs the ecosystems of machines today is the quest for wealth and power, which is what in turn drives the platforms in transforming human experience into machine intelligence. To help ensure that we can share a future with conscious machines, we need to focus on two fronts. First, we must now extend the way we treat human experience so that our platforms value it both commercially as a means toward collective intelligence as well as intrinsically as a kind of inalienable and sacred right. Second, we must now focus on developing humanity so that it is worthy of the tremendous responsibility it is about to experience as the heart of synthetic intelligence.