AI will shape the future of coffee production – but who stands to benefit?

coffee production could be left unprotected from AI
  • Studies show AI could outperform humans in 50% of tasks by 2068
  • Smart greenhouses, intelligent spraying hoses, and yield/price prediction tools are more common than ever before
  • Without further regulation, smallholder producers could face a lack of control over shaping AI in the industry

AI Is developing at an uncontrollable rate, and the coffee industry is swiftly moving into uncharted territory in which producers are left unprotected.

Artificial intelligence (AI) is not new, but machine learning tools like ChatGPT-4 are growing at a faster pace than we may understand or be able to deal with. The unchecked exponential growth of AI has massive implications for agribusiness, and that includes coffee production.

Studies show there is a 50% likelihood AI could outperform humans at all tasks within 45 years, and automate all jobs in 120 years. In agriculture, it’s changing the way we farm as tools like smart greenhouses, intelligent spraying hoses, and crop price forecast and yield prediction tools become available.

Christophe Montagnon, CEO of RD2 Vision, defines AI as “turning information into action,” highlighting that AI is different from big data in the sense that AI uses big data and suggests an action based on an input.

The automation and optimisation of various processes through AI can lead to changes in coffee production that will inevitably have an impact on farmers.

While Christophe is far from considering AI as a magic wand for smallholder farmers, he does believe that indirectly, they can benefit.

With the exception of Brazil, few coffee-growing regions are eligible for weather insurance because coffee is largely grown in areas which can fall victim to erratic weather patterns or rainfall, which in turn affect harvest yields considerably. Leveraging big data and machine learning to set up weather insurance mechanisms can improve risk assessment and make these services more accessible. 

But accessing the opportunities presented by AI isn’t that simple. “Technology isn’t inherently bad, but it is extremely political,” posits Rohan John Anthony, Research and Writing Lead at A Growing Culture. “The purpose of a technological solution is determined by those who control capital and innovation.

“Today, AI is entirely dominated by transnational corporations. Its tools are often made at the expense of workers: To replace them, to reduce their wages, to cut costs, and to boost productivity and profits.”

However, larger producers with greater access to capital could stand to benefit from AI; gaining increased efficiency, improved quality control, and better access to information and resources.

This does nothing to benefit smallholder coffee farmers, as they lack the capital that gives them control over new technologies. All the while, they will still be determinately subject to the conditions that AI creates for the whole agricultural network.

Western knowledge could be imposed on coffee production globally

Why could AI be dangerous for smallholder farmers?

The rise of smart agriculture has coincided with greater uniformity of crops and consolidation in farming, technology and big data industries.

“As they are driven into dependence on a hyper-globalised market, small farmers are increasingly vulnerable to all its failures, shocks, and crises,” says Rohan. This could reinforce dependency on already expensive inputs like fertilisers, chemicals and corporate seeds.

According to him, smallholder farmers unable to access or sustain the technological shift will struggle and lose business.

“Food prices will become increasingly volatile as they are tied to speculative markets and global shocks. Workers’ wages will decrease as they are slowly replaced or removed, and inequality and hunger will rise dramatically,” he says.

Indigenous farmer knowledge is also under threat. Locally generated solutions take into account history, climate, culture and politics. Christophe is worried that a global AI system will be based on artificial intelligence centred in the Global North, running the risk of forcing non-tailored solutions onto localised coffee production and reinforcing existing power dynamics.

AI-powered algorithms could also significantly impact the income and livelihoods of coffee farmers as they are used to predict coffee prices and optimise supply chains. In turn, this could lead to changes in the pricing and distribution of coffee.

What’s more, when producers trade their coffee on global markets, they could face issues over compliance with new EU Regulation relating to deforestation. Satellite images aren’t always clear and, when fed into a machine learning system, could quickly lead to erroneous assessments. 

Even if a case of deforestation is correctly identified, and the producer penalised for it, the reasons and ethics behind it remain unaccounted for. Motivating factors like systemic poverty, a family emergency, or threatened livelihoods, are not part of the system’s assessment mechanism. 

“If technologies are not stewarded, shaped by, and owned by the communities themselves, it can further take away farmer agency and culture, stripping them of power,” says Josh To, producer for A Growing Culture’s Peasant and Indigenous Press Program.

global coffee production will be affected by AI

How can we use AI well, and safely?

AI is a relatively new tool that has many convenient aspects, but it needs to be guided by an ethical code of conduct to protect human relationships, communities, culture, small farmers and the environment.

Reminiscent of the applications of the internet, the absence of standardised rules creates an unregulated space where “anything goes” – often predominantly affecting the most vulnerable.

A methodology that rigorously integrates social factors will be crucial. Christophe believes that for something to be called intelligence, it should incorporate ethical considerations as well.

“AI can’t take into account the life richness and complexities of a smallholder coffee farmer in Southern Ethiopia, for example,” he says. “Problems like low yield, pests and diseases require deeper solutions than simply pesticide and fertiliser application.”

Rohan suggests some guiding questions that can help assess the impact of new technology on coffee production, for example: Whether it truly adds value to farmers themselves; whether it nurtures self-sufficiency or supports dependence; and whether its access is inclusive and open source.

AI is a technology with access to big data, decision-making capabilities and global user access – it presents a huge opportunity. But it has a responsibility to be inclusive and representative, while not ignoring the needs of some of the most vulnerable actors in the coffee supply chain.