Five Things to Know about the Political Economy of AI

While political economy never quite disappeared from academic and policy research, the field certainly made a resurgence after the 2008 great recession, as people sought to better understand the role of economic power and hierarchies of influence in bringing about the crisis in capitalism. Now with appropriate concern about the role of AI in the future of work and labour processes, as well concern over how AI might restructure firms and the provision of government services, political economy can greatly help the public think more clearly about the powerful interactions between states, markets, classes and technological change. This will also prompt a reconsideration of its role in the broader socio-economic landscape in Africa, where the notion that AI systems are a clean break from history, politically neutral or a cure-all for growth, is dispelled. 

Through coming to fully perceive how the various statistical rules and weights of AI have political ramifications, this appraisal can help people take steps to avert another crisis of similar or greater magnitude. Customarily, political economy can be understood as a theoretical and applied framework meant to guide attention to several key areas so that the public may have a better grasp of the sum of social relations as well as what these relations mean. There are many schools of thought in the field and they have intensive, healthy intramural debate. Nevertheless, these schools tend to be unified around a concern for what existing social relations mean for the prospect of substantive social change. Typically, the key objective of a political economic analysis is to use the history of material organisation to explain relations, processes, institutions and organisations. With this agenda, let us discuss the five things to know about the political economy of AI.

First, political economy points to how economic orders are constructed by different groups within that order; how these groups negotiate, bargain and struggle against one another; and what resources they gather to defend or advance their particular projects. AI-powered products are now among those resources. Also, by being attentive to the role of wealth, how it is deployed in the market and how it is acquired, people can understand how the commoditisation of AI and the privatisation of data will mean that some groups will have dramatically more resources than others. 

Developed countries often drive technological innovation, leading to a dependency relationship where African countries may need help to keep pace with the rapid evolution of AI. AI’s data-driven nature empowers large tech companies, facilitating the accumulation of immense wealth and influence, which could intensify global inequalities. Africa, with its diverse developmental landscape, may encounter hurdles in leveraging AI for equitable economic growth. Differentials like this will, and are, begetting multidimensional social inequality. When it comes to Africa, the integration of AI into various sectors of the economy accelerates the pace at which these multidimensional inequalities unfold. The historical imbalances in access to education, skills, infrastructure, and economic opportunities are further exacerbated as AI becomes an increasingly pervasive and general-purpose technology. 

Second, the field of political economy is open and honest about the meanness of politics. Being reminded about the various positions and manoeuvering within businesses, to pick one side of politics, having winners and losers is valuable given that there is much unmoored positivity around AI automatically creating a better life for all. We are seeing governments’ strategic use of AI to control and manipulate citizens. Research has revealed instances where AI capabilities are harnessed by African governments, as seen in Ethiopia and Zimbabwe, not for the collective good but to consolidate power and intimidate citizens. AI tools, presented as potential agents of positive change, are co-opted to serve the interests of the powerful, curbing civic freedoms and reinforcing authoritarian control. 

In addition, adopting AI to automate parts of the labour process benefits some groups to the detriment of others. With so much ‘AI hype’ – whether marketing rhetoric or nationalistic proclamations – in public discourse pushing glowing one dimensional narratives, political economy provides useful empirical counterpoints that can clarify and elevate discussion by introducing new topics to public affairs.

Keeping social inequality in mind, our third point concerns the geography of AI. Like almost all other digital products, AI can overcome some geographical constraints making national regulation harder to enforce. The adoption of AI is not a singular process: there are multiple start points, it is uneven, and even differently experienced. With most colonised spaces subject to unequal exchange in the 19th and 20th centuries, and without diminishing the energies of post-independence governments to rectify that problem, unequal development remains a distinctive feature of our world system. When factoring in issues of excessively strict protections of intellectual property and overbearing data protection laws, the adoption of AI will likely be based on prospects for profit, not the upliftment of the worst off first. Notably, only Egypt, Kenya, Mauritius and Rwanda have dedicated policy documents specifically addressing AI. The lack of comprehensive regulatory frameworks in Africa underscores the nascent stage of governance and regulatory responses to AI.

Fourth, the political economy of AI can help us see which actors are deemed to have appropriate expertise. “Faced with disorienting technological change,” Seth Lazar and Alondra Nelson recently wrote, “people instinctively turn to technologists for solutions.” However they add that “the impacts of advanced AI cannot be mitigated through technical means alone; solutions that do not include broader societal insight will only compound AI’s dangers.” Due to patterns of prejudice, bigotry, and the North-South world system, some groups’ voices will not be listened to when it comes to AI dangers. Conversely, powerful shareholders are reluctant to disclose information about the inner workings of their AI products, products we already know can and do perpetuate racism. For example Kenyans were encouraged to scan their eyeballs for Worldcoin in return for cryptocurrency, which illustrates the risks associated with a lack of openness, ethical considerations and transparency in AI technologies. The consequences of adopting AI are too great to leave this matter with executives in New York and technologists in San Francisco. Due consideration and lawmaking by democratically elected representatives can channel AI enterprises to address humans’ needs.

Finally, the political economy of AI can remind people about previous experiences of profound technological change. As with other great industrial transformations which shook up whole social orders, AI will have reactionary and revolutionary components as people try to make sense and adapt to changing circumstances. Advocates of ‘the status quo but more efficient’ may not have the imaginative capacities to anticipate the potential and pitfalls that AI introduces, and could be swept aside as forces overtake them. Undoubtedly AI will lead to a “recalibration of the burdens of risk between capital and labour”, some may turn to AI to strictly enforce hierarchy, stratification and mobility, while others think about liberation. Put differently, the politics of AI will likely intensify in the coming decades as the stakes become higher.

These five ideas can help improve public deliberation around AI and inequalities, in part by avoiding common intellectual cul-de-sacs that bring about platitudes. The challenge in Africa is to realise that AI systems are not politically neutral or a panacea for growth and development; AI’s statistical rules and weights are situated judgements from those that work in Big Tech firms beholden to shareholder primacy. State commissioned transnational companies in imperial centres, like the Dutch East India Company, which carried out colonial trade were powerful. Big Tech surpasses them. AI is not a break with history, but rather its continuation. Still, the field of political economy shows how AI systems are contestable, in part because they are also social systems. This idea alone can bring energy for currently subordinated groups to pursue projects of negotiation, bargaining and struggle for a fairer political economy.

Portions of this blog post are drawn from Research ICT Africa’s new primer on the political economy of African AI. If you wish to know more about this topic, you can download the primer below.