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Many of us intuitively think about intelligence as an individual trait. As a society, we have a tendency to praise individual game-changers for accomplishments that would not be possible without their teams, often tens of thousands of people that work behind the scenes to make extraordinary things happen.
Matt Ridley, best-selling author of multiple books, including The Rational Optimist: How Prosperity Evolves, challenges this view. He argues that human achievement and intelligence are entirely “networking phenomena.” In other words, intelligence is collective and emergent as opposed to individual.
When asked what scientific concept would improve everybody’s cognitive toolkit, Ridley highlights collective intelligence: “It is by putting brains together through the division of labor— through trade and specialization—that human society stumbled upon a way to raise the living standards, carrying capacity, technological virtuosity, and knowledge base of the species.”
Ridley has spent a lifetime exploring human prosperity and the factors that contribute to it. In a conversation with Singularity Hub, he redefined how we perceive intelligence and human progress.
Raya Bidshahri: The common perspective seems to be that competition is what drives innovation and, consequently, human progress. Why do you think collaboration trumps competition when it comes to human progress?
Matt Ridley: There is a tendency to think that competition is an animal instinct that is natural and collaboration is a human instinct we have to learn. I think there is no evidence for that. Both are deeply rooted in us as a species. The evidence from evolutionary biology tells us that collaboration is just as important as competition. Yet, at the end, the Darwinian perspective is quite correct: it’s usually cooperation for the purpose of competition, wherein a given group tries to achieve something more effectively than another group. But the point is that the capacity to co-operate is very deep in our psyche.
RB: You write that “human achievement is entirely a networking phenomenon,” and we need to stop thinking about intelligence as an individual trait, and that instead we should look at what you refer to as collective intelligence. Why is that?
MR: The best way to think about it is that IQ doesn’t matter, because a hundred stupid people who are talking to each other will accomplish more than a hundred intelligent people who aren’t. It’s absolutely vital to see that everything from the manufacturing of a pencil to the manufacturing of a nuclear power station can’t be done by an individual human brain. You can’t possibly hold in your head all the knowledge you need to do these things. For the last 200,000 years we’ve been exchanging and specializing, which enables us to achieve much greater intelligence than we can as individuals.
RB: We often think of achievement and intelligence on individual terms. Why do you think it’s so counter-intuitive for us to think about collective intelligence?
MR: People are surprisingly myopic to the extent they understand the nature of intelligence. I think it goes back to a pre-human tendency to think in terms of individual stories and actors. For example, we love to read about the famous inventor or scientist who invented or discovered something. We never tell these stories as network stories. We tell them as individual hero stories.
“It’s absolutely vital to see that everything from the manufacturing of a pencil to the manufacturing of a nuclear power station can’t be done by an individual human brain.”
This idea of a brilliant hero who saves the world in the face of every obstacle seems to speak to tribal hunter-gatherer societies, where the alpha male leads and wins. But it doesn’t resonate with how human beings have structured modern society in the last 100,000 years or so. We modern-day humans haven’t internalized a way of thinking that incorporates this definition of distributed and collective intelligence.
RB: One of the books you’re best known for is The Rational Optimist. What does it mean to be a rational optimist?
MR: My optimism is rational because it’s not based on a feeling, it’s based on evidence. If you look at the data on human living standards over the last 200 years and compare it with the way that most people actually perceive our progress during that time, you’ll see an extraordinary gap. On the whole, people seem to think that things are getting worse, but things are actually getting better.
We’ve seen the most astonishing improvements in human living standards: we’ve brought the number of people living in extreme poverty to 9 percent from about 70 percent when I was born. The human lifespan is expanding by five hours a day, child mortality has gone down by two thirds in half a century, and much more. These feats dwarf the things that are going wrong. Yet most people are quite pessimistic about the future despite the things we’ve achieved in the past.
RB: Where does this idea of collective intelligence fit in rational optimism?
MR: Underlying the idea of rational optimism was understanding what prosperity is, and why it happens to us and not to rabbits or rocks. Why are we the only species in the world that has concepts like a GDP, growth rate, or living standard? My answer is that it comes back to this phenomena of collective intelligence. The reason for a rise in living standards is innovation, and the cause of that innovation is our ability to collaborate.
The grand theme of human history is exchange of ideas, collaborating through specialization and the division of labor. Throughout history, it’s in places where there is a lot of open exchange and trade where you get a lot of innovation. And indeed, there are some extraordinary episodes in human history when societies get cut off from exchange and their innovation slows down and they start moving backwards. One example of this is Tasmania, which was isolated and lost a lot of the technologies it started off with.
RB: Lots of people like to point out that just because the world has been getting better doesn’t guarantee it will continue to do so. How do you respond to that line of argumentation?
MR: There is a quote by Thomas Babington Macaulay from 1830, where he was fed up with the pessimists of the time saying things will only get worse. He says, “On what principle is it that with nothing but improvement behind us, we are to expect nothing but deterioration before us?” And this was back in the 1830s, where in Britain and a few other parts of the world, we were only seeing the beginning of the rise of living standards. It’s perverse to argue that because things were getting better in the past, now they are about to get worse.
“I think it’s worth remembering that good news tends to be gradual, and bad news tends to be sudden. Hence, the good stuff is rarely going to make the news.”
Another thing to point out is that people have always said this. Every generation thought they were at the peak looking downhill. If you think about the opportunities technology is about to give us, whether it’s through blockchain, gene editing, or artificial intelligence, there is every reason to believe that 2017 is going to look like a time of absolute misery compared to what our children and grandchildren are going to experience.
RB: There seems to be a fair amount of mayhem in today’s world, and lots of valid problems to pay attention to in the news. What would you say to empower our readers that we will push through it and continue to grow and improve as a species?
MR: I think it’s worth remembering that good news tends to be gradual, and bad news tends to be sudden. Hence, the good stuff is rarely going to make the news. It’s happening in an inexorable way, as a result of ordinary people exchanging, specializing, collaborating, and innovating, and it’s surprisingly hard to stop it.
Even if you look back to the 1940s, at the end of a world war, there was still a lot of innovation happening. In some ways it feels like we are going through a bad period now. I do worry a lot about the anti-enlightenment values that I see spreading in various parts of the world. But then I remind myself that people are working on innovative projects in the background, and these things are going to come through and push us forward.
Image Credit: Sahacha Nilkumhang / Shutterstock.com
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Malthus had a fever dream in the 1790s. While the world was marveling in the first manifestations of modern science and technology and the industrial revolution that was just beginning, he was concerned. He saw the exponential growth in the human population as a terrible problem for the species—an existential threat. He was afraid the human population would overshoot the availability of resources, and then things would really hit the fan.
“Famine seems to be the last, the most dreadful resource of nature. The power of population is so superior to the power of the earth to produce subsistence for man, that premature death must in some shape or other visit the human race. The vices of mankind are active and able ministers of depopulation.”
So Malthus wrote in his famous text, an essay on the principles of population.
But Malthus was wrong. Not just in his proposed solution, which was to stop giving aid and food to the poor so that they wouldn’t explode in population. His prediction was also wrong: there was no great, overwhelming famine that caused the population to stay at the levels of the 1790s. Instead, the world population—with a few dips—has continued to grow exponentially ever since. And it’s still growing.
There have concurrently been developments in agriculture and medicine and, in the 20th century, the Green Revolution, in which Norman Borlaug ensured that countries adopted high-yield varieties of crops—the first precursors to modern ideas of genetically engineering food to produce better crops and more growth. The world was able to produce an astonishing amount of food—enough, in the modern era, for ten billion people. It is only a grave injustice in the way that food is distributed that means 12 percent of the world goes hungry, and we still have starvation. But, aside from that, we were saved by the majesty of another kind of exponential growth; the population grew, but the ability to produce food grew faster.
In so much of the world around us today, there’s the same old story. Take exploitation of fossil fuels: here, there is another exponential race. The exponential growth of our ability to mine coal, extract natural gas, refine oil from ever more complex hydrocarbons: this is pitted against our growing appetite. The stock market is built on exponential growth; you cannot provide compound interest unless the economy grows by a certain percentage a year.
“This relentless and ruthless expectation—that technology will continue to improve in ways we can’t foresee—is not just baked into share prices, but into the very survival of our species.”
When the economy fails to grow exponentially, it’s considered a crisis: a financial catastrophe. This expectation penetrates down to individual investors. In the cryptocurrency markets—hardly immune from bubbles, the bull-and-bear cycle of economics—the traders’ saying is “Buy the hype, sell the news.” Before an announcement is made, the expectation of growth, of a boost—the psychological shift—is almost invariably worth more than whatever the major announcement turns out to be. The idea of growth is baked into the share price, to the extent that even good news can often cause the price to dip when it’s delivered.
In the same way, this relentless and ruthless expectation—that technology will continue to improve in ways we can’t foresee—is not just baked into share prices, but into the very survival of our species. A third of Earth’s soil has been acutely degraded due to agriculture; we are looming on the brink of a topsoil crisis. In less relentless times, we may have tried to solve the problem by letting the fields lie fallow for a few years. But that’s no longer an option: if we do so, people will starve. Instead, we look to a second Green Revolution—genetically modified crops, or hydroponics—to save us.
Climate change is considered by many to be an existential threat. The Intergovernmental Panel on Climate Change has already put their faith in the exponential growth of technology. Many of the scenarios where they can successfully imagine the human race dealing with the climate crisis involve the development and widespread deployment of carbon capture and storage technology. Our hope for the future already has built-in expectations of exponential growth in our technology in this field. Alongside this, to reduce carbon emissions to zero on the timescales we need to, we will surely require new technologies in renewable energy, energy efficiency, and electrification of the transport system.
Without exponential growth in technology continuing, then, we are doomed. Humanity finds itself on a treadmill that’s rapidly accelerating, with the risk of plunging into the abyss if we can’t keep up the pace. Yet this very acceleration could also pose an existential threat. As our global system becomes more interconnected and complex, chaos theory takes over: the economics of a town in Macedonia can influence a US presidential election; critical infrastructure can be brought down by cybercriminals.
New threats, such as biotechnology, nanotechnology, or a generalized artificial intelligence, could put incredible power—power over the entire species—into the hands of a small number of people. We are faced with a paradox: the continued existence of our system depends on the exponential growth of our capacities outpacing the exponential growth of our needs and desires. Yet this very growth will create threats that are unimaginably larger than any humans have faced before in history.
“It is necessary that we understand the consequences and prospects for exponential growth: that we understand the nature of the race that we’re in.”
Neo-Luddites may find satisfaction in rejecting the ill-effects of technology, but they will still live in a society where technology is the lifeblood that keeps the whole system pumping. Now, more than ever, it is necessary that we understand the consequences and prospects for exponential growth: that we understand the nature of the race that we’re in.
If we decide that limitless exponential growth on a finite planet is unsustainable, we need to plan for the transition to a new way of living before our ability to accelerate runs out. If we require new technologies or fields of study to enable this growth to continue, we must focus our efforts on these before anything else. If we want to survive the 21st century without major catastrophe, we don’t have a choice but to understand it. Almost by default, we’re all accelerationists now.
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These are just part of a much wider societal problem of information overload. There is so much data stored—exabytes of it, as much stored as has ever been spoken by people in all of human history—that it’s humanly impossible to read and interpret everything. Often, we narrow down our pool of information by choosing particular topics or issues to pay attention to. But it’s important to actually know the meaning and contents of the legal documents that govern how our data is stored and who can see it.
As computer science researchers, we are working on ways artificial intelligence algorithms could digest these massive texts and extract their meaning, presenting it in terms regular people can understand.
Can computers understand text?
Computers store data as 0s and 1s—data that cannot be directly understood by humans. They interpret these data as instructions for displaying text, sound, images, or videos that are meaningful to people. But can computers actually understand the language, not only presenting the words but also their meaning?
What if a computerized assistant could digest all that legal jargon in a few seconds and highlight key points? Perhaps a user could even tell the automated assistant to pay particular attention to certain issues, like when an email address is shared, or whether search engines can index personal posts. Companies could use this capability, too, to analyze contracts or other lengthy documents.
To do this sort of work, we need to combine a range of AI technologies, including machine learning algorithms that take in large amounts of data and independently identify connections among them; knowledge representation techniques to express and interpret facts and rules about the world; speech recognition systems to convert spoken language to text; and human language comprehension programs that process the text and its context to determine what the user is telling the system to do.
Examining privacy policies
A modern internet-enabled life today more or less requires trusting for-profit companies with private information (like physical and email addresses, credit card numbers and bank account details) and personal data (photos and videos, email messages and location information).
These companies’ cloud-based systems typically keep multiple copies of users’ data as part of backup plans to prevent service outages. That means there are more potential targets—each data center must be securely protected both physically and electronically. Of course, internet companies recognize customers’ concerns and employ security teams to protect users’ data. But the specific and detailed legal obligations they undertake to do that are found in their impenetrable privacy policies. No regular human—and perhaps even no single attorney—can truly understand them.
In our study, we ask computers to summarize the terms and conditions regular users say they agree to when they click “Accept” or “Agree” buttons for online services. We downloaded the publicly available privacy policies of various internet companies, including Amazon AWS, Facebook, Google, HP, Oracle, PayPal, Salesforce, Snapchat, Twitter, and WhatsApp.
Our software examines the text and uses information extraction techniques to identify key information specifying the legal rights, obligations and prohibitions identified in the document. It also uses linguistic analysis to identify whether each rule applies to the service provider, the user or a third-party entity, such as advertisers and marketing companies. Then it presents that information in clear, direct, human-readable statements.
We also found, with the help of the summarizing system, that privacy policies often include rules for third parties—companies that aren’t the service provider or the user—that people might not even know are involved in data storage and retrieval.
The largest number of rules in privacy policies—43 percent—apply to the company providing the service. Just under a quarter of the rules—24 percent—create obligations for users and customers. The rest of the rules govern behavior by third-party services or corporate partners, or could not be categorized by our system.
The next time you click the “I Agree” button, be aware that you may be agreeing to share your data with other hidden companies who will be analyzing it.
This article was originally published on The Conversation. Read the original article. Continue reading
This week we’ve rolled out our first major round of improvements to Singularity Hub since our ground-up redesign last December. If we did it right, you’ll find that discovering the technological goodies you come here for is much easier, and so too are other Singularity University offerings you might be interested in.
The first and most major change is in the way Hub’s navigation is structured.
The previous categories in our header (Tech, Future, Health, Science) have been replaced by a single page, Topics, which profiles the most popular tech topics across our site. The featured topics in this menu will be updated regularly based on article performance, so you can keep up with what’s trending in AI, biotech, neuroscience, robotics, or whatever is making the biggest splash most recently.
Rolling our hottest topic category tags into one header dropdown allowed us to create greater focus on some of our newest and best offerings.
Our header now prominently features In Focus, which includes articles on how leaders can make the most of today’s accelerating pace of change by learning to think like futurists, innovators, technologists, and humanitarians. We’ve always been technological optimists, and we want to to make it easy for leaders to find the stories that help make hopeful problem-solvers of us all.
We’ve added a section for Experts, which features leaders in the Singularity University community and showcases their thought leadership including interviews and books. In Events, we highlight Singularity University’s global library of local happenings and summits.
Lastly, we’re excited that our growing original video efforts—from our Ray Kurzweil series to our weekly tech news roundup posts—now live under a central Videos section on Hub. This also gives us a place to highlight our favorite video posts from around the web, including the sci-fi shorts we love so much.
Cruising through the rest of Hub, particularly our homepage, you’ll find a much greater variety of content options, including new stories, top stories, event coverage, and videos. In short, it’s everything a homepage should be. On posts, we’ve tried to keep things as clean as possible, and we put a lot of hours into laboriously streamlining our content tagging structure, making it much easier for you to click through category tags into other stories you might like.
Here’s what @singularityhub looked like 2 years ago, 2 weeks ago, & today. Check it out: https://t.co/7cmlTJwc7d pic.twitter.com/jDayIEIFNv
— Singularity Hub (@singularityhub) July 13, 2017
You’ll also see greater visibility into Singularity University events, along with clearer ways to keep up with Hub and SU both, from simple email newsletter signups to callouts for the SingularityU Hub iOS app and events like SU’s Experts on Air series.
We hope you enjoy the ever-evolving, ever-improving Singularity Hub, and we’d love to hear your feedback. Feel free to tweet us, and let us know your thoughts. You can also pitch us or email us. And as always, thank you for your support. Continue reading