Artificial Intelligence – for or versus the food system? (Pt. 1)

Artificial intelligence (AI) has the potential to revolutionise the agricultural industry and the food system in general. By leveraging data, machine learning algorithms, and advanced analytics, AI can help farmers and food producers optimise their operations, improve productivity, and increase sustainability. However, there are also risks associated with the use of AI in agriculture that must be addressed to ensure its benefits are realised while minimising potential negative consequences.


One of the key benefits of AI in agriculture is its ability to help farmers make more informed decisions. For example, by using sensors and drones to gather data on soil moisture levels, temperature, and other environmental factors, AI algorithms can provide farmers with real-time insights into crop health and yield potential. This information can help farmers make better decisions about when to plant, water, and fertilise their crops, which can lead to higher yields and better quality produce.

AI can also help farmers optimise their use of resources, such as water and fertiliser. By analysing data on soil type, weather patterns, and other factors, AI algorithms can recommend optimal levels of water and fertiliser to apply to crops, which can reduce waste and increase efficiency. Additionally, AI can be used to automate routine tasks, such as weed management and pest control, which can free up farmers’ time and reduce labor costs.

In the food system, AI can also play a crucial role in improving supply chain efficiency and reducing waste. By using machine learning algorithms to predict demand for certain products, food producers and retailers can better manage their inventory and reduce waste. Additionally, AI can be used to monitor food safety and quality, which can help prevent foodborne illnesses and reduce product recalls.




While AI has the potential to bring significant benefits to agriculture and the food system, there are also risks associated with its use. One of the main concerns is the potential for AI to exacerbate existing inequalities in the industry. For example, small-scale farmers may not have access to the same resources and technologies as large agribusinesses, which could widen the digital divide and lead to unequal outcomes.

Another risk is the potential for AI to reinforce existing biases in decision-making. For example, if AI algorithms are trained on historical data that reflects existing social and economic inequalities, they may perpetuate those biases in their recommendations. This could lead to decisions that are not equitable or sustainable in the long term.

There are also concerns about the impact of AI on the environment. While AI can help reduce waste and increase efficiency, it could also lead to overuse of resources if not implemented correctly. For example, if farmers rely too heavily on AI recommendations for water and fertiliser use, they may end up using more resources than necessary, which could lead to environmental degradation and soil depletion.


Overall, AI has the potential to bring significant benefits to agriculture and the food system in general. By helping farmers optimise their operations, reduce waste, and improve efficiency, AI can contribute to a more sustainable and equitable food system. However, it is important to address the risks associated with AI, including the potential for inequalities, biases, and environmental impacts. By taking a proactive and collaborative approach to AI development and implementation, we can ensure that its benefits are realised while minimising potential negative consequences.

Okay, if you have come this far it is time to note that the article has been produced by ChatGPT, which, till now, with some critical distance from itself, has analysed the topic. (Dall-E has also generated the supporting images). It is up to you to draw your own conclusions, by evaluating both the self-knowledge displayed by the AI and the intrinsic quality of the analysis. We at SuperNaturale have our own thoughts on the matter, which will counter ChatGpt’s in the second part of this article.