What differentiates modern economies such as those of present-day Europe and North America from their primitive ancestors of 500 years ago? People living today have at their disposal a range of inventions and amenities, from electricity and running water to the aeroplane and the washing machine, which together make life vastly easier, healthier and more productive than it was for our forebears.
But technical inventions and innovations give only a partial account of the contrast. Indeed, when life was nasty, brutish and short, revolving around the procurement of basic essentials and rarely anything more, the imperative was to devise production methods that would assure enough could be produced to survive.
As mechanization expanded production, the increasing complexity of economic activity raised the importance of what economists call “transaction costs.” These are the costs of searching, bargaining, and enforcing agreements. They are, most saliently, the costs to firms of finding, hiring and monitoring employees; the costs to customers of searching, sorting and negotiating with suppliers; the costs to sellers of obtaining payment; and the costs to companies of discovering consumer preferences and identifying the most efficient production and distribution methods.
Transaction costs may appear to be a subsidiary component of economic activity, until we realize just how much of the available resources in modern society are dedicated to facilitating transactions. Consider the prominent role of – to name a few – auditing firms, management consultants, investment banks and fund managers, retail banks, search engines, financial advisors, retail platforms and, importantly, educational institutions, whose role is partly to indicate to firms which individuals they should hire. A famous paper by Nobel Prize winner Douglass North and John Wallis1 estimated that economic activity related to reducing transaction costs accounted for 41 per cent of U.S. GNP in 1970, up from 18 per cent in 1870.
Until recently at least, transaction costs likely continued their upward trend. Increasing automation, together with globalization, has made production ever cheaper and reduced the labor requirements of both agriculture and manufacturing. Since demand for food and manufactured products is income-inelastic – we will not normally double the calories we ingest, nor the number of cars we drive, every time our income doubles – resources are increasingly dedicated to creating more diverse and technologically sophisticated products at lower cost, with the result that more people are able to obtain higher standards of living. But the costs of searching, bargaining and enforcing agreements were not subject to the same downward cost pressures – and as a proportion of total costs they continued to rise.
The Internet changed all that. Uber and Airbnb are but two examples of industries spawned by a desire to reduce transaction costs – and the means to do so. The welfare gains from technology-enabled disintermediation are not negligible: a sophisticated recent study by economists at the University of Chicago put the consumer surplus of Uber users at $6.8bn per year in the U.S. alone.2 These gains have arisen in no small part because Uber (like Lyft and other ridesharing services) has been able to lower the transaction costs associated with connecting drivers to passengers so that services may be supplied and consideration exchanged with speed and confidence.
A key element in the success of many of the new transaction cost reducing services, from Google to Uber, is trust. Indeed, economic progress in modern commercial society largely revolves around ensuring trust. The income gap between New Zealand, one of the world’s freest and most advanced economies, and relatively backward Russia is more readily explained by the greater abundance of trust in the former than by any knowledge gap in production methods: Russian engineers are no less alert to the latest technical improvements than their Kiwi counterparts. As another Nobelist, Kenneth Arrow, wrote in 1972, “It can be plausibly argued that much of the economic backwardness in the world can be explained by the lack of mutual confidence.”
The relationship between trust and economic development is unambiguous. Countries with more robust rule-of-law protections, property rights, contract enforcement, and an independent judiciary tend to have average incomes far in excess of those in countries where the legal system is weak.
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Trust facilitates investment and exchange, which make societies wealthier. But trust assurance is expensive. Consider just the function of lawyers, whose job is to negotiate, draft and help to enforce the contracts central to most large-scale economic activity. The legal services market in the U.S. alone, as measured by law-firm revenue and the budgets of corporate legal departments, is worth $437 billion, or 2.4 per cent of American GDP. Lawyers are among the more highly remunerated professions, with a median wage of $81,300 in comparison to median U.S. personal income of $50,500.
Legal practitioners are doubtless productive, since few business dealings could today be conducted in their absence. The flip-side is that legal costs are a considerable portion of company expenses, which makes the legal sector increasingly vulnerable to technological disruption.
Industry incumbents are being challenged on a number of different fronts. First, there are platforms such as Lawyers on Demand (LOD), which match freelance lawyers with clients, thus giving the former flexibility they would not have if employed by a traditional law firm, whilst sparing the latter the expense of a sprawling internal legal department. Interestingly, these self-described New Law providers seem to place as much emphasis on the benefits they offer participants on the supply side (lawyers) as those to be derived by clients. And the business model appears to be taking hold: a third of top 20 law firms now offer similarly flexible work arrangements.
Then there is the application of machine learning to legal services. There already exist large specialized search engines, such as LexisNexis, where lawyers can find relevant case information. Precisely because legal services involve the processing of vast amounts of text, the sector lends itself to the application of software that will sift through and classify content according to given parameters. Through experience, it can be taught how to respond to particular findings, thus helping with case preparation. Not only can machines process large volumes of data faster and more cheaply than humans, but they are also less prone to error. In that sense, the law is analogous to the medical profession, where diagnostics stands to be dramatically improved thanks to artificial intelligence.
It might be surmised that AI applications to the law will doom the legal assistant, but that has not necessarily been the historical experience in other sectors. When ATMs were first introduced, it was predicted that the profession of bank teller would quickly become obsolete. In fact, the number of bank tellers has steadily increased3 with the widespread deployment of ATMs, and they have each become more productive as automation allowed them to graduate from administrative work into higher-value-added sales and marketing roles.
Perhaps the greatest change to the legal profession will be wrought by what The Economist has dubbed “a machine for creating trust”: blockchain. Indeed, as early as 1997 cryptographer Nick Szabo posited the use of online protocols to design, agree and enforce contracts at low cost. Szabo argued that automatic processes constituted the ultimate neutral arbiter. Furthermore, because data on distributed ledgers such as blockchain is instantly replicated and shared, verifiability is also ensured. This is why bitcoin has become popular in countries with mismanaged fiat currencies, and why development luminary Hernando de Soto has high hopes for the blockchain’s application to land-title registrations in poor countries. No longer will ordinary citizens be held to ransom by kleptocratic elites and local strongmen.
But the use of distributed ledger technologies may pose an existential threat to much of the legal profession. After all, the latter’s value proposition (often buttressed by government-sanctioned monopoly) has historically come from their role as intermediaries in negotiation, contracting and dispute settlement. If a peer-to-peer network can perform all of those functions in an equally or more reliable way, then what is left for lawyers to do?
This is why we should expect a backlash as more economic activity moves to the blockchain. If licensed taxis have been able to block peer-to-peer apps from entering many local transport markets around the world, then there is no doubt that lawyers, who know the letter of existing statutes better than anyone else and are overrepresented in lobby groups and national parliaments, will similarly fight and delay the widespread adoption of labor-saving technologies.
The impact will likely be distinct in common-law as compared to civil-law countries. The latter in particular would seem vulnerable to automation because their prescriptive approach means much of the application of the law leaves little room for creativity and interpretation, at which humans (so far) have a comparative advantage. There will of course still be room for lawyers and judges in a disintermediated world, but machines may well reduce the rents legal professionals have been able to fetch for centuries. If Amazon long ago pulled the rug from under traditional booksellers, then one can be sure that the unfolding trust revolution will in turn upend the incumbent suppliers of trust.