Artificial intelligence, food waste, and computer vision

There’s a lot of hype in AI right now.

It’s hard (especially for me) to distinguish what’s a real-world, legitimate application, vs what’s just pure fantasy – at least right now.

One area I’ve been looking into lately is an interesting application of computer vision within artificial intelligence: using cameras and machine learning to monitor discarded food, with food waste reduction being the end-goal.

For context, about one-fifth of the trash in our landfills is wasted food, and up to one-third of the world’s food supply ends up in the trash.

There’s a couple startups doing interesting work here (Winnow and Zero Foodwaste), and I wanted to talk through some stuff they’re working on.

 

Actually taking action

First, what I like about these startups is they are actually doing something about a societal problem – or at least trying.

In the age of peak slacktivism (10k likes = 1 cancer cure), it’s way more common for us to just hope our retweet is sufficient for addressing the world’s problems.  Raising awareness!

The problem is…if everyone’s ‘raising awareness,’ and no one’s actually doing the work – nothing would get done.  But, I guess at least everyone would feel better about themselves.

When you cofound a startup, you’re taking huge personal risk – both mentally, socially, and professionally.  These guys are putting themselves out there and actually going for it.

 

What do they actually do?

Winnow and Zero Foodwaste use computer vision and essentially weight scales (‘smart meters’) to identify different food types put into waste bins.

This image recognition and weight data is processed by their AI and then reported back to the kitchen manager – to give them a much more specific idea of exactly what type of food (and how much) they’re wasting.

 

A more realistic philosophy for being sustainable

A lot of startups within the impact and sustainability category don’t really make fundamental economic sense – many of them are floating along on the vague notion that “we’ll help some bigger profitable company hit their ESG goals.”

With these startups, it’s not like that.  For example, with Winnow, they are focused on putting actual dollar-amount food waste numbers in front of hotel kitchen managers.

When you start showing business owners the black-and-white dollars they’re losing due to food waste, it becomes less about “am I feeling responsible today” and more about “I want to stop throwing away money.”

 

A concrete, real-world application example that people can easily relate to

Kind of contrary to my ‘AI is all hype’ sentiment from earlier, I do think that it’s pretty important to get people excited about the cool things AI can do – especially when it’s for something that will benefit society in general, as opposed to just a few investors/CEOs.

When people hear stuff like ‘autonomous trucks’ or ‘AI chatbots,’ I think the usual initial reaction is not “hey that’s pretty cool.”  I think it’s more, uh wouldn’t that be dangerous (trucks), that’s kind of creepy (chatbots).

However – using AI computer vision to monitor and reduce food waste – I think that’s an application that everyone can get behind.

It’s an example of AI that many people can more unambiguously appreciate, since we all know what it’s like to throw away perfectly good food – it’s not just some abstract concept.

 

Conclusion

As a former cofounder of a socially-conscious/impact startup, I appreciate the effort of these startups.  It’s really, really hard to do an impact startup – and even more difficult to propose something that actually could be economically viable.

I have no idea if these guys will be successful, but I applaud the effort (slacktivism!).

 

The views expressed on this site are my own and do not represent the views of any current or former employer or client. 

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