By Ziyaad Bhorat A worker uses automated guided vehicles at Flipkart, an e-commerce firm in India, to sort items inside a fulfillment center on the outskirts of Bengaluru, India, on Sept. 23, 2021. (REUTERS/Samuel Rajkumar) Today, more than a third of the world’s population lives under authoritarian rule.
Indices ranging from the Democracy Index to V-Dem to Freedom House all concur: Democracy worldwide is backsliding. At the same time, automated technology has rapidly advanced. According to the International Federation of Robotics, the global average robot density reached a record of 126 operational industrial robots per 10 0000 workers in 2021.
The year prior, global corporate investment in artificial intelligence (AI) stood at $67. 85 billion, a 5-year increase of over 330%. Democracy is under threat, while technologies built on automation continue a breakneck pace of development.
Scholars increasingly see a link between the advance of automation and backsliding democracy, as anxiety about automation can lead to pro-authoritarian or anti-democratic beliefs/preferences even within democratic states. In 2018, for example, a team of economic researchers at Oxford University found that anxiety about automation had significantly influenced electoral voting patterns for the 2016 U. S.
presidential election, with electoral districts most impacted by automation more likely to see higher vote shares for President Trump. Political leaders are beginning to wake up to this dynamic, as evidenced by Andrew Yang’s 2020 presidential campaign built around addressing the risks posed by automation. “All you need is self-driving cars to destabilize society,” Yang warned in an interview.
“That one innovation will be enough to create riots in the street. ” Yang is right to be worried: Automation isn’t just having major economic effects, but political ones as well. Addressing the threats posed by automation requires an aggressive campaign by policymakers to make cutting-edge technology and the skills required to use it far more widely available.
This means at least two things: i) investing in new forms of automation technology ownership, design, and implementation that empower workers and citizens more generally and ii) narrowing the competency gap between a technologically skilled elite and ordinary people. The origins of automation and AI At the outset, policymakers need to understand how new technologies like AI are rooted in automation, and what that means for politics. Automation has a long history intertwined with a politics of command and control.
As David Noble’s sociological history has shown, the numerical control (N/C) form of industrial automation developed by American institutions in the 20th century—especially the military, corporations, and universities like the Massachusetts Institute of Technology—privilege a managerial command and control model of production. N/C automation formally circumvents workers by first reducing engineering blueprints to coded mathematical descriptions and instructions, and then using cards and magnetic tape (and, later, computers) to translate those codes into electrical signals for machine controls. In 1955, the United States Air Material Command, the precursor to the Air Force Logistics Command, embraced this new technology by stockpiling N/C machinery en masse.
The Soviet Union followed, placing priority on the centralized development of N/C tools for defense and productivity in its Eighth Five-Year Plan (1966 – 1970). As a military-industrial use case for machine programming, N/C automation contributed to the infrastructure on which contemporary machine-learning and AI ultimately rests. N/C automation became so successful that it laid the foundation for modern manufacturing in the postwar era.
The efficiency associated with a) bypassing workers through predetermined commands and b) controlling a precise path of action for machines, allowed for far greater optimization of industrial processes. This set the stage for the mass manufacturing and adoption of computers, which resulted in scalable computerized numerical control (CNC) of machines. Modern manufacturing factories continue to rely on CNC lathes, mills, and grinders to assemble components for automobiles, aerospace, computers, and mobile devices.
Without N/C (and CNC) technology, mass production of factory robotics would not have been possible; they also set the stage for the kind of advanced robotic systems we might find in an Amazon fulfilment center, for example. But N/C automation’s “baked in” tendency toward centralized command and control should concern us. It means that even before we can identify and address visible issues, we face a largely invisible technical infrastructure that is becoming ever more entrenched over time, and that is designed around workers’ loss of agency and control.
Automation therefore poses a growing challenge for democracy. Making automation democratic Addressing that challenge requires, first and foremost, greater investment in more democratic automation technologies. Fortunately, alternative models already exist.
In the 20th century, another form of industrial automation was developed alongside the N/C kind. The path not followed, according to Noble, was one that put the production process back into the hands of workers. Record-playback automation was so called because it recorded an individual machinist’s rhythms and movements to reproduce them in the work process.
Whereas N/C automation bypassed workers, record-playback allowed machinists to translate their individual motions onto a tape that could be used to ensure repeatability. If a machinist had a certain method of production, they could copy it on this tape and use it again. Instead of being relegated to passive users of technology, machinists became active creators in their own processes.
But entrepreneurs who favored this type of automation found a scarcity of funds and lacked the economic and political power to challenge those who preferred the more centralized, N/C automation system. According to Noble, it wasn’t cost that doomed record-playback automation, but rather elite preferences for consolidating power. Record-playback has a direct parallel for the digital age.
The low/no code automation movement aims to allow non-programmers (i. e. most of us) to develop digital software and be creative contributors to the digital world.
Low/no code automation works by enabling users to automate their workflows in an experience that relies on minimal coding. Shopify, for example, allows business users to create an e-commerce platform without coding skills. Low/no code automation has therefore been heralded as a way to transform software users in the corporate world into empowered “citizen designers/developers”—but there is no reason to limit it there.
Developing low/no code automation technologies means encouraging all digital users to become active participants in the digital world, thereby expanding the idea of a democratic digital citizenship. It is not enough, however, to rely on the private sector to drive innovations in no/low code automation. Creating a democratic digital culture requires governments to proactively invest in and incubate these technologies, as well as encourage their uptake through government acquisition.
U. S. agencies have already turned to no/low code technology in critical public services such as firefighting and grant disbursement, although not through any coordinated policy.
Estonia, or “e-Estonia” serves as a model for how a coordinated, public sector-driven investment in digitally automated technology can reap democratic dividends, and give people the ability to move beyond a passive use of digital tools towards becoming active digital creators and citizens. Estonian citizens, for example, are able to use government-issued e-IDs to vote online (“i-Voting”) in elections. Instead of going the Estonian route, many states are increasingly turning to technology to keep an insurmountable distance between ordinary people and the seats of power.
Rather than facilitating citizen participation in the development and use of new technologies like i-Voting, states like China have adopted intrusive social credit systems that punish transgressions of public “trustworthiness” with backlisting from various services and amenities. What can one individual do in the face of huge technological systems of authoritarian control? Developing more democratic forms of automation technology is necessary but not sufficient—it must occur alongside the development of technological skills and education. Digitally upskilling workers Secondly, then, democratizing automation means narrowing the competency gap between a technologically skilled elite and ordinary citizens.
In the United States, this gap is stark. A comparatively very small group of well-compensated specialists in cybersecurity, data science, and software development stand in contrast to just over 30% of Americans who have no or limited digital skills and who are, at best, able to perform basic operations like sorting through emails. This should be a wake-up call for policymakers in education to push for the explicit incorporation of digital skills into standards like the Common Core.
Here, Finland serves as a positive example for integrating digital skills like coding across early education learning, and not confining it to a discrete or standalone coding course. Moreover, digitally upskilling workers—particularly those displaced by industrial automation—is crucial. This could mean expanding the scope of worker training tax credits to incentivize corporations to upskill their workers for digital roles.
Importantly, however, this conversation cannot remain at the national level. Major supply chains are international and economic gains are distributed unevenly across developing and developed nations. This means that decisions about automation in the latter can negatively affect labor conditions, wages, inequality levels, and democratic politics in the former.
Automation in the United States, for example, can create a preference for re-shoring production and downward pressure on wages in developing markets that otherwise competitively supply offshore labor. Economic pressures can lead to political destabilization in these markets. Both domestic policy and multilateral international commitments should protect against this by strengthening international labor protections and promoting upskilling across state borders.
In this way, global labor substitution effects can be offset by increases in productivity and the development of new industry. Of course, the idea of regulating digital automation might raise concerns about U. S.
economic and technological competitiveness. But the cost of letting automation run its own course, or “laissez-automatiser”, could be democracy itself. The United States cannot afford to out-compete technologically entrenched authoritarian states by following the same illiberal path.
The proposals above will be no easy feat to accomplish. Since our earliest written history, we have imagined worlds without work and tools that could take away our toil. But if only to prevent such a world from devolving into a tech-driven dystopia, policymakers will need to forcefully champion the development of technology—and technology policies—rooted in democratic principles.
Ziyaad Bhorat is a 2022 – 2023 USC Berggruen Fellow, incoming Technology and Human Rights Fellow at Harvard’s Carr Center and a current PhD Candidate in Political Theory at UCLA. Amazon provides financial support to the Brookings Institution, a nonprofit organization devoted to rigorous, independent, in-depth public policy research. .