Automation and labor: insights from the American Economic Association meetings last week

As briefly mentioned in my previous post, the American Economic Association held its annual meetings last week in Philadelphia. While the panel on gender bias was not webcast, several other lectures and discussions are available online. Another session that caught my eye was on automation and the future of labor, seeking to answer: what are the projected effects of automation, artificial intelligence, and robotics on labor share, wages, and the nature of work?

Daron Acemoglu presented a theoretical paper, co-authored with Pascual Restrepo, that provided a framework for understanding the relationship between artificial intelligence and labor share. He breaks down the impact of artificial intelligence into two countervailing effects: a displacement effect and a productivity effect. The displacement effect is the inevitable displacement of the labor force that takes place when firms substitute machines to complete specific tasks previously done by labor. The reason there is a displacement effect at all is that the capital is cost-saving for firms. One result of this cost-saving displacement is that there may be an increase in productivity associated with the firm's output. This productivity effect will lead to a demand for new skills and new job creation. But the question posed by Acemoglu and Restrepo is how large is that increase in productivity associated with employing machines instead of labor and will it lead to large enough job creation that it will balance out the displacement effect?

An example provided in the paper of these two effects comes from Bessen's (2016) analysis of the introduction of ATM machines. The paper found that the introduction and wide dispersal of ATM machines, a technology that took over many of the existing tasks of bank tellers (notably many existing tasks that were performed more expensively by bank tellers), allowed banks to cut costs. This cost saving allowed them to open more branches, which in turn led to an increased demand for bank tellers who could then focus on more specialized skills that the ATMs did not have. I don't review that paper here, but I note that it is contentious in its isolation of the causal effect of ATM machines on the banks' decisions to open new branches. The example, however, illustrates the mechanism by which the displacement and productivity effects work according to the paper (some bank tellers in existing branches displaced and bank tellers in new branches added).

The model in Acemoglu and Restrepo indicates that the effect of automation on labor share is unambiguous (labor share will decrease with the displacement effect holding productivity constant) but if the productivity effect leads to new job creation (demand for new skills leads to new job creation) then it has the ability to lessen the inevitable job displacement associated with AI. The productivity effect from employing ATM machines arguably led to an increase in the number of bank branches employed and the number of bank tellers employed who then needed to have new skills in the tasks that the ATM could not complete. I don't think that the "new skills" required in the bank teller positions are necessarily a good example of the demand for new skills modeled by Acemoglu and Restrepo since the new jobs created are effectively the same as the old jobs being displaced at existing branches but it's possible they may require improving on some existing skills in order to better advise the client on the different transaction opportunities available to them or bringing in new clients.

There are a couple of takeaways I think are important here:

• Will jobs be created at all?: 
• The paper highlights the case in which firms adopt technologies that are only marginally more efficient than labor at performing the same task ("so-so technologies"). The adoption of these technologies leads to few productivity gains and as a result lesser job growth through new skills. But the displacement effect will still be resounding and Acemoglu and Restrepo argue that it is these marginally more efficient technologies that will be the most harmful to the labor force since they don't lead to productivity gains. 
• In the case of the bank tellers, what if instead of investing in new physical branches (requiring employment of bank tellers), banks invested in improving their mobile and online infrastructure to better serve clientele online? Firms' productivity may be growing but the productivity gains do not necessarily translate into job creation at the same rate (creates jobs for those tasked with updating and maintaining the online infrastructure but would this be comparable to creating jobs for a new set of tellers at new locations?).
• Address inequality implications: This leads to the next point. It is clear that the jobs that are created through the demand for new skills will not employ the same skills as the jobs that are displaced (see the example of investing in new physical branches versus investing in a better online infrastructure and the skills needed to maintain each of those). Which raises the question of whether income and wealth inequality will be exacerbated by rising automation if the jobs that are displaced disproportionately impact those at the lower quintiles and the jobs that are created disproportionately require skills that those at the lower quintiles do not possess or cannot reasonably acquire. Perhaps anticipating the impacts on those at the lowest quintiles of the income ladder several prominent tech executives, including Elon Musk, have advocated for a universal basic income that they claim will be the only way to address the widespread job loss associated with automation. 
• Identify type of jobs created: The response from Ben Jones in the discussion directly following Acemoglu's presentation raised an important point: the model appears to assume that all of the new tasks that are created based on the productivity effect are essential, i.e. there would be no output if the task were not completed. How likely is it that the new jobs created in the aftermath of technology adoption would be essential jobs (essential to production)?
• If, as Jones hints at, the new jobs are non-essential, it is also likely that they may be of lower quality. Quality of employment is particularly important given the rise of the gig economy and trend towards temporary and part-time employment that offers fewer benefits and protections to workers. 
• Prepare for "new skills": In order to preempt the potentially negative implications on labor share and inequality the key would be to identify the kinds of new skills that will be most valuable in a future with automation and how governments, policymakers, and educators can effectively plan for such a future by preparing students for those skills. Furthermore, they would want to be able to prepare those outside of formal education (those who are not in schools, universities, or training programs) for retraining and lifelong learning so that they can better adapt to changing conditions in the labor market. 
• Identify market failures contributing to "excessive" automation: In their paper, Acemoglu and Restrepo outlined the phenomenon of "excessive" automation that is only marginally more cost effective than labor and that leads to few productivity gains and little job creation. They provided a few reasons for the "excessive" automation, one being that capital is potentially over-subsidized through the tax system which in turn encourages firms to automate.

Women in economics: Elinor Ostrom's work and its lasting impact on fishing communities in the Gulf of California

Researcher Erin Hengel's recent paper "Publishing while female" (2017) was chronicled in a brief article in the Economist last week profiling the differences in readability standards posed to publications authored by male versus female academics in economics. I don't do a thorough review of that piece here, but Hengel's results indicate that: (i) female-authored articles are better written in terms of readability than similar papers by men, controlling for year, journal, editor, topic, institution, and English language ability; (ii) the gap widens during peer review; (iii) female economists' readability improves over the course of their careers whereas male economists' does not presumably due to the higher standards they face. These findings, if true, add to an existing body of evidence that suggests that female academics are held to higher standards than their male counterparts and often receive less credit than their male counterparts for their accomplishments.

Yet, despite the biases that persist, progress is being made in that we have the data to identify and analyze them now more than ever. The New York Times reported on a panel at the American Economic Association's annual meeting of the minds held this week which presented the research of several academics on systemic gender bias within the field.

My reading on the gender bias in economics led me to write on the first and to-date only woman to win the Nobel Prize in Economic Sciences, Dr. Elinor Ostrom, and on the contributions that she made to the fields of economics and governance through her writings on collective action. While the lack of female prize winners reflects a gender bias in economics in the 1960s, 1970s, and 1980s more so than biases that exist today (the prize rewards contributions that were made more than several decades ago) it is still striking that economics only has one winner where other fields do better on this dimension.

Existence of collective action outside of the public and private sectors

The prevailing notion of collective action during Ostrom's time was posited by Mancur Olson (1965) in the Logic of Collective Action. To provide a brief summary of Olson's thesis: 

• Olson posited that individuals in groups would choose to free-ride to reap the communal benefits from public goods without incurring any individual costs to procure or maintain said goods. After all, public goods are non-excludable and individuals would obtain the benefits whether or not they incurred the costs (so long as others paid the price). 
• He argued that individuals would not act collectively in their common interest unless selective incentives were provided or force used to induce them to participate. 
• Furthermore, large groups faced greater costs of collective action than smaller ones: not only larger selective incentive costs but larger monitoring costs, and the total benefits from participation would be spread more thinly across the members of the group. Which leads to, as he put it, "surprising tendency for the exploitation of the great by the small" (smaller groups with more concentrated incentives are more effective at organizing than larger ones). 

Ostrom's work was designed to bridge the gap between the predictions made in the theory of collective action and the empirical evidence that often evidenced widespread, voluntary cooperative behavior. She theorized the existence of norm-using players in addition to the rational egoist actors traditionally employed in game theory: the norm-using players value social norms including reciprocity, fairness, and being trustworthy. Certain norm-using players are willing to initiate cooperate action when they believe others will reciprocate and will continue to do so as long as a significant number of others reciprocate; others are willing to punish free-riders either verbally or through sanctions. The existence of these actors, and equally or even more importantly, the existence of strong social norms within a community, makes voluntary collective action feasible in a way that Olson did not theorize. 

She posited that cooperative behavior especially where communication is involved "can work as well or nearly as well as externally imposed set of rules and monitoring and sanctioning in order to generate cooperative behavior" and furthermore claimed it is more effective in settings where external authorities impose rules but can only achieve weak monitoring or sanctioning (Ostrom, 2000). She proposed eight design principles critical to the survival of voluntary cooperative behavior, including local rules that restrict the amount, timing, and technology of harvesting the resource in question and access to rapid and low-cost methods to resolve conflict among users.

Local resource governance

Ostrom's work was directly relevant to the governance of common-pool resources, or "natural or humanly created systems that generate a finite flow of benefits where it is costly to exclude beneficiaries and one person's consumption detracts from the amount of benefits available to others" (Ostrom, 2000). Common-pool resources are distinct from public goods: in the case of public goods one person's consumption does not subtract from the pool of resources available to others but in the case of common-pool resources it does. Examples of common-pool resources are fisheries, irrigation systems, and water. 

Indeed the implications of her work are even more relevant today, as these and other environmental resources continue to be depleted at high rates and long-term benefits of sustainable use of said resources are foregone in favor of short-term gains. Not to mention her theoretical and empirical evidence for the viable existence of self-organized resource regimes, distinct from any government or private entities, is hopeful especially in environments where there is a lack of political will, public sector leadership, or public sector capability in the realm of environmental conservation. 

"Your margin is my opportunity" 2.0

An article this week in the Wall Street Journal makes a bold statement on Amazon's growth prospects: it argues that Jeff Bezos' well known mantra ("Your margin is my opportunity") is a double-edged sword that will limit Amazon from achieving the world domination that everyone fears. A section entitled "What Amazon Can't Do" discusses Amazon's inability to compete in high-margin industries, citing Amazon's Fire Phone and Amazon Studios as products that are far behind the premium iPhone and HBO of their respective markets. The article claims that these high-margin industries are where the profits lie (in some form evoking Benjamin Graham's cautionary advice, "Obvious prospects for physical growth in a business do not translate into obvious profits for investors").

But I wouldn't be too quick to write-off Amazon's ability to compete in these high-margin markets. In my opinion the article misses a few key points:

• Amazon is and has been constructing an infrastructure that allows it to enter new markets much more easily than the average firm. This infrastructure includes (1) its seemingly infinite access to capital: investors that are willing to endure Amazon's losses quarter on quarter in pursuit of long term results and its own diversified set of businesses, as well as (2) its access to high quality data on consumer preferences through its dominance of the e-commerce retail market.
• It already does have at least one high(er)-margin business: Whole Foods. With average grocery store margins hovering around 1 percent, Whole Foods profit margins at 4 percent are high even if the market is not a glamorous one. More telling in my opinion is the way that Amazon obtained this business: through M&A. I wouldn't underestimate Amazon's ability to use M&A strategically in the future to merge other high-margin businesses to capitalize on its strong fundamentals in physical logistics and e-commerce to compete and compete effectively.

Though "your margin is my opportunity" may originally have applied to Amazon's strategy for the basics (your Amazon Basics, Amazon tablets, and AWS) and not high-margin businesses, having a foothold in those low-margin businesses will allow Amazon to obtain an advantage with high-margin businesses in the future if it so chooses.