Curious Cook: AI and the future of food
I recently came across the World Economic Forum’s (WEF) Global Risks report, which summarises the main expected risks for our planet in 2024 as assessed by around 1,500 national leaders. Top of the list is ‘Extreme Weather’, which is the top concern of 66% of those polled.

Second on the list is ‘AI-generated Misinformation and Disinformation’ which bothered 53% of the leaders surveyed. Third and fourth on the list are ‘Societal/Political Polarisation’ and ‘Cost-of-Living Crisis’.

The column today will address some concerns about AI (Artificial Intelligence), and how much better the world may be with using AI properly, especially for ensuring a sustainable global food supply and also at home. But I will not address the AI generation of misinformation and disinformation, a uniquely human problem created by people out to pollute our minds.

Whatever anyone says, AI is very likely to be a much deeper and integral part of the fabric of human society soon. It is a matter of harnessing AI for the greater good, rather than using AI to promote greater ignorance or confusion to suit political, commercial, and/or fraudulent agendas.

Better food supply?

The current problems regarding agricultural practices are well-established. They range from destructive run-offs of pesticides, chemicals, and sewage into waterways, greenhouse gas production, overuse of water, susceptibility to drought, floods and inclement weather, overuse of antibiotics, etc.

However, AI has the potential to revolutionise the food industry, offering a wide array of benefits, applications, and solutions to challenges such as the above. From accelerating food production processes to minimising human error and improving product quality, AI is restructuring every aspect of the food ecosystem.

There is no doubt AI can and will improve/streamline human food production, but there needs to be a balanced approach to its use, as well as addressing issues such as sustainability, and meeting the evolving demands of consumers. But we should always be aware that AI can behave like a very smart kid without a conscience.

Better resource management?

AI can help manage resources better. A simple example may be moisture sensors in the ground alerting farmers only when crops need to be watered. A smart sprinkler system that waters the ground only when necessary (instead of running on a timer) can save billions of litres of water currently wasted on watering crops.

Similarly, there are AI-controlled machines that can plant crops with precision, harvest crops with minimal wastage, and also extract/destroy weeds meticulously, eliminating at least some reliance on polluting and often dangerous chemical treatments. AI can behave like a tireless and precise gardener working 24/7 tending to crops.

Smaller farmers may not be able to afford advanced AI technology compared to larger farmers or farming conglomerates. — BALAZS SIMON/Pexels

Advanced AI technology is not equally available around the world. Smaller farmers will almost certainly not be able to afford much of the advanced machinery, and in many cases, the geography and terrain would also define the limits of the use of any technology.

However, simple AI tools or apps such as calculators for the amounts of seed grains, fertilisers, water requirements, sunshine days required, planting dates, expected yield per hectare, likely market crop price, etc, can help smallholdings decide on the best crops to grow for any given year. This may be provided after a soil quality analysis to optimise the best crops to plant. Too often, small farmers simply do not rotate their annual crops enough, which eventually ruins the fertility of their lands.

During production and harvesting, pooled AI data may help small farmers organise their purchases and deliveries to the markets, possibly reducing costs and wastage.

Poorer ethics?

But AI can be a blunt tool. If AI was used simply to improve, for example, meat production, there are no inherent requirements on such systems to consider issues such as animal welfare and disposal of animal wastes. Treatments of diseases would probably be automatically targeted by more use of antibiotics, rather than better sanitation and more humane considerations for the animals, such as exercise and access to open spaces.

The volume of meat products simply becomes more important than the well-being of the livestock, a situation many humans would find unacceptable because of the implied lower quality and dietary safety of such food products.

This lack of ethics may also apply to land crops. An AI system instructed solely to improve crop yields may actually cause more fertiliser and chemical run-offs, due to overuse of crop chemicals. This can pollute and damage other areas.

Left to its own devices, AI will rarely consider the impact of agriculture on wildlife and other local fauna. The loss of such wildlife may lead to other problems for humans in the future; eg, the loss of pollinators and useful creatures such as earthworms and natural pest-killing creatures.

Human farm workers may also be exploited by AI. There may be fewer jobs in the agricultural industries as a result of following AI strategies. Also, there will always be a persistent and ever-widening gap between farmers who can afford AI solutions and poorer or smaller farmers without the technical advantage. The economies of scale of bigger farms can drive other farmers out of business, reducing competition and variety in the supply of our food.

The well-being of livestock may not be considered when AI is in use. — KAT SMITH/Pexels

A possibly lesser risk, which is ever present, is that AI solutions may be prone to cyberattacks, disrupting sensors, automated machinery, supply lines, operational processes, etc. There may be very similar issues if the AI systems fail for any reason, perhaps due to power outages or severe weather damaging the AI infrastructure.

Food processing

When produce gets from the farms to the food processing facilities, AI can be a transformative factor in modern food factories. AI-powered systems can analyse large volumes of data about the received food items from sensors and cameras, automatically routing the various types or grades of foods to the correct processing units.

AI machine learning systems then detect defects, anomalies, or contaminants, ensuring that output products consistently meet the required (or programmed) food standards. This results in improved quality control, higher efficiency, and less waste by the combined AI components acting as pitiless quality inspectors, efficiency experts, and waste reduction officers non-stop around the clock.

Heavy lifting or high-volume processes can use robotic arms and machines, programmed to perform precise movements and repetitive tasks with high accuracy, efficiency, and speed, reducing the need for manual labor. From an economic perspective, AI can be highly cost-effective simply because a well-configured, well-maintained AI system never needs a coffee break, gets ill, or takes holidays.

Consumers also benefit from the certainty of getting the expected quality of food consistently.

The downside is that many of the foods handled by AI currently are Ultra-Processed Foods (UPF), a class of foods known to cause metabolic syndrome and other diseases. Despite this, UPFs are widely consumed as these are the only foods affordable for many people.

Cooking at home

Here is a neat way of saving on food waste. Provide an AI engine with a list of ingredients and it will return with suggestions of several established recipes to follow for using the food items. Where AI is presently inadequate is the analysis of the carbohydrate, protein, and nutrient content of the suggested dishes, but this is a minor issue that may be solved one day. After all, people seldom care about the exact nutritional values of food when dining out.

AI portals and sites can help minimise wastage by generating recipes that make use of whatever ingredients you have on hand. — KATRIN BOLOVTSOVA/Pexels

Using AI is therefore an extremely useful way to use up spare food items in the fridge or at home. The recipes suggested by AI engines have led me to experiment with new dishes which often turned out to be quite delicious. I would never have thought of many of them without an AI engine to fish them out for me from the millions of recipes on the internet.

There is also a liberating aspect of using AI-picked recipes. Often, we are compelled to buy ingredients to make a selected recipe, but usually, we end up with excess food items as food is seldom provided in the portion sizes suggested by the recipe. Now it is simple to just tell an AI system what spare ingredients you have and get interesting, tasty recipe suggestions.

Sometimes it can feel like having an experienced chef helping out in the kitchen, offering useful ideas on how to cook and eat well while reducing food waste.

The views expressed here are entirely the writer’s own.
Curious Cook,Chris Chan,AI,food supply,agriculture,agricultural practises,poultry,farming,livestock
The columnist looks at the pros and cons of using AI in food production, farming, livestock management and even home cooking.