How AI can help reduce food waste TOU

Computers have a bad reputation when it comes to saving the planet. Cryptocurrenciesdue to the highly inefficient technology involved, consume as much electricity as the entire country of Sweden. Elon Musk repeated several times warned about terminator-apocalypse style likely to be caused by artificial intelligence (AI). And yet, like any tool, AI has enormous potential to be good for the planet – and that future isn’t as far off as it seems.

Today, let’s look at one aspect of that potential: reducing carbon emissions from food-related systems. According to Nature, these represent a third of total emissions; them growing world population shows the increasing importance of this factor over time.

Computers are great at tracking a myriad of factors and adjusting outputs without human intervention. There are at least two tasks related to the food system for which this applies perfectly: reducing food waste and promoting the consumption of foods that are better for the environment. Let’s examine each in detail.

Reduce food waste at home

According to USDA, 21% of the food consumers take home ends up going to waste, and another 10% is thrown away at the grocery store or warehouse. Let’s look at the root causes of this waste.

An important factor is that consumers do not know what to do with the foods that caught their eye at the store. It may have been on sale; maybe part of the article was used for a recipe, and the leftovers don’t offer a good way forward. Whenever there is no plan – no recipe to make with a particular grocery item – the risk of it being wasted increases. This is especially true for items with a short shelf life, such as vegetables and proteins.

But what if the grocery paradigm shifted from focusing on individual groceries to focusing on recipes? Each item in the refrigerator would then have a “map” around it; as long as the recipes are what the family wants, the items will all be eaten.

This paradigm, combined with AI that zooms in on family food preferences and recommends recipes that every family would enjoy, has been quite powerful. Recipe-based purchases are something instagram and Amazon also embrace; there’s no reason physical grocery stores can’t too.

Additionally, instead of viewing recipes as stand-alone, food retailers should think about how consumers can reuse ingredients in recipes of the week. For example, if a recipe in the customer’s cart calls for parsley as a garnish, a complementary salad recipe can use the rest of the parsley bunch. This saves customers money and reduces the risk of unused parsley going to waste.

This task – matching complementary recipes to make the most of leftovers – is perfect for the AI.

Reduce food waste at the grocery store

A lot of waste in the grocery store and warehouse is the result of overstocking. Despite supply chain systems being fully computerized and market incentives improving, the USDA still sets retail losses at 10%. Consumer behavior is quite difficult to predict as long as the business is based on consumers walking through virtual or physical aisles and choosing the grocery items they want.

What if this pattern was reversed? What if consumers didn’t directly choose the groceries or even the recipes they want? What if they indicated their general food preferences and had an agent acting on their behalf (a human or an AI) do the shopping for them? Provided that agent does a good job representing the needs of the consumer, the agent can also be made aware of inventory levels at the retailer; they could then make substitutions that do not impact consumer satisfaction but prevent spoilage.

Besides the obvious benefit to the planet, reducing waste creates a more profitable business and allows some savings to be passed on to the consumer. When typical grocery store margins are in single digitsthese savings add up, especially in an inflationary environment.

Eat what is better for the environment

Following a low-carbon diet is a surprisingly counter-intuitive task for humans. According to Our World in Data, local food is often not better than food shipped from distant continents. Organic food often has a higher greenhouse gas footprint. Even the reduction of packaging is not the right factor to pay attention to: it is a small fraction of a food’s environmental impact and often extends its shelf life, thereby reducing waste.

It’s too hard to keep up with the latest knowledge about what’s actually good and bad, and research is changing rapidly. Therefore the cognitive charge to track is too high, even for consumers who care deeply about eating sustainably.

Wouldn’t it be great if there was an autopilot? Something like the ESG investment funds who do the work for you, but in the food sector? Something that would help you do the right thing and send you a quarterly report showing how much you’ve improved compared to the average Joe?

Unlike investing, where you can be as indifferent as you want, it doesn’t work so easily with food. In addition to worrying about the sustainability properties of your food, you care a lot about taste, allergens, macronutrient content, portion size, and many other factors. Unless you’re vegan, there are plenty of vegan meal options you wouldn’t enjoy, and plenty of low-carbon vegan, vegetarian, and omnivorous options you might like.

Understand all customer needs and adjust recommendations based on a feedback loop (using structured tools, explicit comments) is a key enabler here.

Imagine a world where there is an autopilot for healthy and sustainable food. If this autopilot knows each consumer well, it can confidently nudge some of them towards more sustainable foods – replacing a beef-based recipe with one with chicken or introducing a vegetable-based meal to someone who normally leans heavily towards meat. AI plays a central role in these nudges because each customer’s preference is unique; and because collecting feedback at scale and adjusting recommendations based on it is essential to achieving all goals.

This notion of micro nudges is highly relevant. Offer sustainable options in the shopping experience, as well as social proof, can help traditional retailers “walk the aisles” to help consumers make the right choices. For digital retailers, knowing more about each customer can help optimize relevance over sustainability. In the optimal case, these two variables need not be in competition.

AI as a force for good

As we’ve seen here, AI-based systems can help reduce greenhouse gas emissions in two profound ways: by reducing food waste and by getting consumers to eat more sustainable foods. Each of these factors can have a profound impact on the planet over the next decade.

Alex Weinstein is CDO at Hungryroot.