Sylvain Charlebois: AI can make our food system more efficient, but if we’re not careful, also more expensive

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Technology has been changing food production for years. Precision agriculture can help farmers target irrigation, fertilizer and crop protection more accurately. AI can strengthen those decisions by identifying patterns and anticipating needs. In distribution, forecasting and automation can improve inventory management, delivery schedules and the movement of perishables.

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Much of this work happens beyond the consumer’s view. A more efficient warehouse rarely attracts the attention that a price change does. That is where the debate becomes more difficult.

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Location pricing, dynamic pricing and surveillance pricing are different practices. Restaurants and stores have long charged different prices at their various locations due to differences in rents, labour costs and competition. Dynamic pricing changes prices over time. Surveillance pricing uses personal information to tailor the price offered to a particular shopper.

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Finding a different price for the same meal at two restaurants does not, by itself, prove that either restaurant is using AI or profiling customers.

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But using someone’s browsing history, purchasing habits or inferred income to charge more for food raises a fundamentally different concern. Imagine two people buying the same basket of goods at the same moment, with one paying more because an algorithm believes that person can afford it — or has fewer alternatives.

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That should trouble anyone concerned about food security.

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Maryland has already enacted legislation restricting surveillance pricing in groceries. Canadian policymakers should establish clear prohibitions against using personal data to impose higher food prices.

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Those protections should preserve useful practices, including transparent promotions and markdowns that help sell food before it spoils. An electronic shelf label can reduce administrative work and make discounts easier to offer. The concern lies in how a pricing system treats people.

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We tolerate fluctuating prices for flights and hotel rooms, but food carries a different social obligation. Households can postpone a holiday. They cannot postpone eating indefinitely.

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AI could help make our food system more productive. Better forecasts can reduce waste. More efficient operations can ease cost pressures. Yet efficiency does not automatically translate into lower prices. Competition will help determine how much of the benefit reaches consumers.

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Consumers, meanwhile, will have tools of their own. AI could make it easier to compare prices, identify worthwhile promotions, plan meals and avoid purchases that offer poor value. A retailer may become better at predicting what a shopper will buy, while that shopper becomes better at finding another place to buy it.

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That contest will create opportunities and expose weaknesses. Businesses that ignore AI risk losing ground. Businesses that use it carelessly risk losing trust.

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Food companies should pursue innovation with a clear understanding that consumer confidence is an economic asset. Once damaged, it is expensive to rebuild.

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AI should help the food industry produce more, waste less and serve people better. Using private information to determine how much extra a household can be made to pay for dinner crosses a line.

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Our food system needs greater intelligence. Consumers deserve fair treatment at the checkout.

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National Post

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Sylvain Charlebois is director of the Agri-Food Analytics Lab at Dalhousie University, co-host of the Food Professor Podcast and visiting scholar at McGill University.

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