Using AI to automate political fact-checking

In an age where we can’t even agree on what facts are anymore, it can seem like a lost cause to even attempt political fact-checking.

And to be fair, right now things don’t look great.  However – and this is a topic that I have a history with – I think it’s a cause absolutely worth supporting.

Back in the day, I was a cofounder of a startup called fuseGap.  It was a political/educational social app with the goal to make it cool to be informed about politically-relevant facts.  So instead of who can bring the spiciest political opinions…it would be more about who could bring the best facts.

Given that I’m here writing this…yeah it didn’t work out.  We learned a lot, but ultimately it’s really, really hard to get people motivated to learn facts in a golden age of the political hot take.

Lesson learned: people are way more interested in providing and consuming opinions than in actually looking to see if those opinions have any basis in reality.  Of course, few people would admit that they feel this way personally…but I’m pretty sure it’s true.

Anyways, all that doesn’t mean that it’s not important to have the general population informed about political matters – if anything, it’s more important than ever.

Which brings me to a cool startup I’ve been looking into: Full Fact.  They’re a startup based in the UK, and they’re using AI to automate political fact checking.


Why does it matter?

Given that most news today is more about ‘engagement’ and basically getting the viewers riled up (as opposed to…reporting on reality) – it seems that fact-checking is unfortunately becoming a relic of the past.

This has been going on for a while now: flashback to the 2012 presidential campaign, when Mitt Romney’s campaign hit us with the “We’re not going to let our campaign be dictated by fact-checkers.”  Fun times.

Things haven’t gotten much better since then.  Depending on who you ask, some might say that the UK and USA are starting to get torn apart by rampant polarization.

When many media outlets are more interested in making you think your fellow citizens are the enemy, vs actually reporting the facts…I’m not sure that will end well.  But hey, at least the audience will be ‘engaged!’

So getting back to Full Fact.  While most politicians are out there throwing hot takes left and right, it’d be nice to have someone checking whether their spiciest statements have any basis in reality.

The problem is, fact-checking is hard.  While also being not exactly the most fun activity, and not the most profitable either.

And with more and more people getting politically outraged and outspoken about all sorts of things, there are more and more impactful hot takes to sift through.  It’s becoming more of a scalability problem…

…which sounds like a great use case for artificial intelligence!


Full Fact’s automated fact-checking project: some traction, momentum

Full Fact has some decent momentum, along with some big-name players supporting them in a few different ways.

In 2016 they announced a partnership with Google’s Digital News Initiative, and their automated AI fact-checking approach has been featured on BBC.  They’ve also been covered by TechCrunch, Wired, The Guardian, among others.

More recently, in May 2019 they were co-winners of the Google AI Impact Challenge.

Again, fact-checking is hard.  It’s generally a thankless endeavor, and pretty much no one gets passionate about supporting the fact-checkers.  It’s only when the facts happen to support someone’s opinion that people will generally even acknowledge the effort.



I think it’s cool to see people using AI to attack very impactful, very immediate real-world problems.

I do have some longer-term questions about how well Full Fact’s approach can handle the complexities and subtleties of fact-checking, but so far they certainly are off to a good start.

Now if only we could get people to care more about facts instead of opinions…


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

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.



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.