The story of human development is a story of disruptive – and liberating — innovation. More particularly it is a story of new tools. Early humans tamed fire, a tool that enabling them to eat cooked meat, which – according to Richard Wrangham – increased the protein density of their diet. As a result, humans grew big brains that, eventually, enabled them to develop other new tools. Over time, these tools have evolved from simple hand axes to robots – but they all share one thing in common: they enable humans to do more with less.
New tools, first and foremost, liberate our most scarce resource: time. This is implicit in many of the words we use to describe them, which relate to human functions they replace. The term “computer,” was originally applied to people who made calculations. The term “robot” was adapted, by Isaac Asimov, from the Russian word for “worker.”
The brilliant sword-swallowing Swedish physician and statistician Hans Rosling, who sadly died in February, was one of the foremost exponents of the benefits of new tools. In a highly entertaining TED talk in 2010, he made a persuasive case – aided by his own Trendlyzer software – that the humble washing machine is the most important technology to have been developed in the past 100 years. Why? Because it liberated women from the drudgery of hand washing clothes, enabling them to spend more time doing other, more productive and interesting things.
Over the course of the past fifty years, new tools have changed the way we pay and the way we invest. Payment cards, which can be traced back to the early 20th century but became a major force in the 1958 with the introduction of the American Express card and BankAmericard (which became Visa), enable consumers to make payments electronically, thereby avoiding the need to carry cash, reducing theft from consumers and merchants. Likewise, electronic trading platforms have replaced trading floors. And ETFs automatically track indices, reducing the need for human traders to buy and sell securities and thereby reducing the cost of holding a diversified portfolio.
Big brained humans have sought to identify and exploit vulnerabilities in these electronic transaction systems. Traders identify intra-day discrepancies between the price of ETFs and the value of the underlying securities, arbitraging the difference through long-short trades. And criminals have found ways to steal and use payment card information en masse.
But new tools that take advantage of advanced computational power, “artificial intelligence” (AI) programs, and vast amounts of data are addressing these vulnerabilities. Payment network operators have invested in AI-based systems to identify and stop instances of fraud and theft. Meanwhile, algorithmic trading has enabled such rapid exploitation of ETF discrepancies that prices rapidly adjust to the market clearing level.
Now, as several authors in this issue demonstrate, distributed ledger-based systems of various kinds are disrupting payments, investments and other kinds of transactions. These systems reduce the cost of authenticating transactions, liberating us from the inefficiency, ineffectiveness and bias of human-mediated transactions.
Smart contracts, which increasingly use blockchain and other distributed ledger-based systems, are beginning to replace a wide range of conventional contracts and even enable computers to contract with one another. Frustrated with your stock broker or fund manager and their high costs? An AI-powered app trading over a distributed ledger-based platform will do the job better, more securely and at lower cost.
Peruvian economist Hernando de Soto has for three decades been searching for ways enabling the poor to own the property they occupy, which represent trillions of dollars in what he calls “dead capital” (without formal rights, occupiers have been stymied in their efforts most effectively to use, develop, sell or mortgage their land). Now he and his team at the Institute for Liberty and Democracy have developed systems of standardized property registration using smart contracts that, in combination with GPS and satellite mapping, offer the ability to create at very low cost alternatives to absent or defective government property registries. Such registries may soon liberate billions of people to participate in formal economic activity from which they have been excluded.
In nearly all cases, new tools replace functions previously performed less efficiently and often with less precision by humans. And from the spinning Jenney to desk-top publishing, the tools make some human skills redundant. The new tools now being developed extend this revolution to knowledge workers, from doctors and lawyers to bankers and bureaucrats.
Some commentators have raised concerns that AI and robots will make humans redundant. In The Age of Em, economist Robin Hanson envisages a world in which multiple emulations of a small number of smart, wealthy humans do all the jobs. But while such a world is imaginable, it is neither inevitable nor is it likely to occur in the next few decades. Current AI-based systems are designed to do jobs for humans, not replace them entirely. That will enhance our prosperity.
New tools do not exist in isolation. The washing machine built upon innovations in mechanical and electrical engineering – and requires access to large amounts of electricity and running water. Likewise, the Internet is built upon innovations in information processing and transmission – and requires networks of data pipes and electricity. This cumulative nature of innovation makes it impossible to predict with precision which new tools will be developed in the future. But one thing can be said with certainty: that new tools will continue to liberate humans from drudgery, enabling us to do more with less and freeing us to do what we want, rather than what we must. And already entrepreneurs are searching for ways to enhance human abilities so that we can continue to learn, adapt and improve ourselves – and thereby take best advantage of all the new tools that emerge.
The greatest threat to human progress does not come from artificially intelligent robots eating our lunch. It comes from those who seek to use the power of the state to regulate new tools and other technologies. Many new technologies offer far superior alternatives to current systems of regulation. The algorithms and evaluation systems built into share economy apps such as Airbnb, Uber and Lyft, do a better job of providing user-relevant information about the price and quality of services being offered than regulators could ever do. Similar systems are being developed in the fintech space. Regulators simply do not have access to the granular information needed to police such transactions, so the best they can do is get out of the way.