Lithium as a Social Actor

Lithium in Zimbabwe: The Social Logic of Extraction

By George Katito*

November 17,2025 

Lithium supply chains are typically discussed in resolutely technical terms: grade concentrations, extraction methods, market projections, and global demand curves. Analysts track output with mathematical precision. Yet what is rarely quantified is the social dimension—the networks of people, institutions, and histories that determine how and whether extraction endures.

In Zimbabwe, this dimension is decisive. The country’s lithium is embedded not just in rock but in relationships: between investors and communities, between the state and local authorities, between ancestry and modern governance. Treating those relationships as integral to supply resilience, rather than background noise, is arguably integral to any durable mining economy.

Rethinking Resilience

Supply-chain analyses still tend to distinguish “hard” factors—costs, infrastructure, regulation—from “soft” factors such as community sentiment or legitimacy. But social variables have hard consequences. Around the world, technically efficient projects have faltered because their models missed or minimised this human calculus.

Actor–Network Theory (ANT) underscores this point: every outcome, from ore delivery to market price, arises from interactions between people, institutions, and materials. Value chains are built not on algorithms alone but on associations built on trust, access, credibility, reciprocity. ​

History as Network Memory

Mining in Zimbabwe has always existed within such networks. Under the British South Africa Company (BSAC), geology was a tool of governance (Phimister 1988; Mlambo 2014). Modern investors still confront the spatial and social patterns that history left behind. Yet this is also a country with an ancient mineral culture attested to at Great Zimbabwe and  through artefacts of Rozvi Empire that were metallurgical hubs that transformed gold into a store of value and power (Pikirayi 2001).

When contemporary projects negotiate with local chiefs or provincial structures, they are not inventing new practices; they are engaging with deep-rooted frameworks of legitimacy. Reading these frameworks accurately is a strategic competence, not a cultural courtesy.

Modelling the Social

Today’s global lithium market has prompted a new form of analytics—one that combines numeric modelling with social insight. Traditional risk engines favour binary logic: secure or insecure, compliant or non-compliant, stable or unstable. But in real economies, especially those shaped by layered histories like Zimbabwe’s, risk behaves more like a spectrum than a switch.

Emerging computational approaches—fuzzy logic systems, hierarchical modelling, and dynamic weighting algorithms—allow complex social data to be expressed numerically without erasing its nuance. For instance:

• A fuzzy system can assign partial truth values to local support or protest sentiment rather than forcing yes/no categories.

• Hierarchical models can integrate national, provincial, and community-level indicators of confidence or legitimacy.

• Time-series social data—such as media tone or grievance reports—can inform adaptive risk coefficients, updating forecasts as relationships evolve.

The point is not to over-quantify culture, but to let numbers breathe—to model uncertainty explicitly rather than pretending it isn’t there. In modern supply-chain intelligence, this kind of social computation may soon be the differentiator between stable and brittle operations.

Concrete Cases: Social Actors in Action

Zimbabwe’s mines offer vivid illustrations. At Arcadia Lithium Mine near Harare, operated by Huayou Cobalt’s local unit, community pressure led to 14 km of tarred roads and hiring 500 local women for uniforms—moves that rebuilt trust after initial dust and job anxieties. Yet labour disputes over expatriate staffing persist, showing how unresolved social tensions can slow ramp-up.

Nearby, Bikita Minerals has faced child injuries from blasting debris, farmer displacements, and water shortages, eroding community confidence despite economic promises. These are not isolated; in Chile’s Atacama, lithium brine extraction halved local jobs and sparked protests over water, while Indonesia’s nickel sites displaced Indigenous groups, igniting land conflicts. 

Partnerships as Infrastructure

Zimbabwe’s lithium sector works through partnerships that link state institutions, Chinese investors, and local enterprises. These networks have been crucial in reconnecting Zimbabwe to global markets and national development plans. Their efficiency, however, depends on relational stability. Here, social data and economic modelling reinforce each other. Where community confidence can be tracked performance stands to benefit. Where sentiment turns, as at Bikita, costs rise. 

From Complexity to Foresight

Complex systems theory tells us that resilient networks do not eliminate volatility, they absorb it. A well-designed sociotechnical model recognises this by combining technical capacity with continuous social feedback. Quantitative forecasting that incorporates these dynamics—layering production data with “relational variables”—could anticipate not just financial shocks but social inflection points, as seen in Bikita’s unrest.

Crucially, such models help correct an old historical weakness. The colonial imagination failed not only morally but analytically: it simplified sophisticated societies into flat categories. Twenty-first-century supply-chain modelling has the tools to do better, to compute social complexity rather than reduce it to margins of error.

Conclusion

Lithium may power new technologies, but its reliability depends on old fundamentals: cooperation, legitimacy, and understanding. Zimbabwe’s example—from Arcadia’s roads to Bikita’s blasts—shows that social complexity is not an obstacle to efficiency; it is part of what resilience actually  means. The future of critical minerals arguably  belongs to those who learn to compute with both rock and relationship, precision and empathy

Selected References.

Latour, B. (2005). Reassembling the Social: An Introduction to Actor–Network Theory. Oxford University Press.

Mlambo, A. (2014). A History of Zimbabwe. Cambridge University Press.

Phimister, I. (1988). An Economic and Social History of Zimbabwe, 1890–1948. Longman.

Pikirayi, I. (2001). The Zimbabwe Culture. AltaMira Press.

*George Katito is CEO/Founder of Geostratagem