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Jeff Han, CEO

TownSquare, Inc

Industry: News & Media

Location: TMRW workspace

We sat down with Jeff, the founder of TownSquare, and had a conversation about the future of news and media in the era of echo chambers. Read on.

Suzanne: Tell me about Townsquare. What does it do?
Jeff: I like to call TownSquare the world’s first disagreement company. Our goal is to enable good disagreement on really divisive topics in the news. Think of us if The Economist and Facebook were merging. You’d get volumes of news but with an intelligent curation team that gives you a pro-con-neutral perspective on everything you read.

Suzanne: that sounds just like what we need right now, how does it actually work?

Jeff: It’s remarkably simple (like all good AI and ML, the hard part is in the backend) you take a 45 second survey and from there we build a personalised profile of your values and where you stand on social, economic and political issues. For every news story that comes in, we give you an article that matches your views and another that challenges them.

Suzanne: With all those news that has come out recently about Facebook and, specifically, Cambridge Analytica, this seems very timely.

Jeff: yeah I think that scandals are becoming really prevalent, and that the “social” platforms clearly brought this onto themselves; I think fueling a person to person connection is fine, but news and other forms of democratic information should not be in an echo chamber. The entire reader population is starting to realise that those practices have been going on for a number of years and no longer want to be trapped in a filter bubble. There is a need for a tool that filters the junk out and, constructively, exposes both sides of an argument.

Suzanne: Can I assume, running an app like TownSquare, that you like to disagree with your co-founder, Sean?

Jeff: “like” is a weird word, we definitely agree a lot more than we disagree. Philosophy is about learning how to structure and prioritise your thoughts; your colleagues are telling you whether or not you’re doing that in a correct way. But we do disagree and not often very well. That was some of the impetus that led to starting TownSquare. It’s very hard to disagree well when you have a supercomputer in your pocket that will display information that simply reinforces your own opinion!

Suzanne: AKA Facebook.

Jeff: Ironically,I don’t use Facebook but Google or any search engine that’s built on that kind of method of approach reacts similarly. That was our ‘wow’ moment when I realised Sean had made some very good points and I didn’t know how to rebutt ; Townsquare is our attempt to address this particular situation and convey both sides of an argument in a completely objective way using machine learning.

Suzanne: What were you doing before?

Jeff: I was a student so I just finished my undergraduate degree where I was studying philosophy theology and machine learning.

Suzanne: How did you and your co-founder Sean meet?

Jeff: We were both on a graduate programme at Oxford University studying philosophy where we became friends and we debated a lot – that’s what you do that at uni’, it’s part of developing arguments and counter-arguments. We had a very similar upbringing, both come from immigrant middle-class parents, are both Americans and there we were, both attending a really posh university; that brought us together.

Suzanne: Absolutely. What was your first impression of Sean when you meet him?

Jeff: The first time we met was at a cohort meeting in the first week at school. I’d shared a bit of my life story which involved domestic violence, not having much money growing up. He approached me after and said, “actually we have very similar backgrounds.” And so immediately I thought, here is someone who understands my background because I felt generally uncomfortable at the university. So I think that was my first impression of him and then as we went on I think we just had admiration for how the other person thought.

Suzanne: Interesting; what keeps you up at night?

Jeff: The funny thing is Sean is such a good sleeper and when we would share a dorm room he would just fall asleep even when we just started the company; I am not a good sleeper. Our team is now eleven people and my number one concern is making sure that they are well taken care of. They’re the smartest people in the world so I want to make sure that nothing gets in the way of that, and that they have all the tools they need to succeed.

Suzanne: What’s the costliest mistake you’ve made to date?

Jeff: That’s an interesting one; I’m not sure it’s costly as much as taught us a lot. Roughly 5 months in we were convinced we were ready to raise investment and so we prepared all these meetings with big investors in Silicon Valley.

We had very high profile meetings set up, all incredibly encouraging but I left being aware that we weren’t ready to take on funds.

We had the idea of what the product would look like but, from the technical side we were still working it out. We thought, let’s get the money first.

That was a week wasted and I came back with jetlag which I hate.

On the positive side, we learned the hard way: don’t raise unless you need to and you know how you’re going to allocate the funds.

Suzanne: I think it’s a common mistake many startups make. There’s just so much emphasis on raising investment and very few founders are really thinking about what investors are seeking and how they’re going to scale.

Jeff: I think businesses ultimately are reflections of the cofounders and for Sean and I, I don’t think we were comfortable raising an amount of money that we couldn’t say for certain whether or not this algorithm we had in mind would practically work. We had to do the month long math problem to work it out.

Suzanne: Have you had any lucky breaks?

Jeff: I recall the YouTuber Casey Neistat saying ‘luck is where opportunity meets preparation.’

We’ve been very lucky to have met and now have as advisors some of the top brains such as the director of Data Science and Social Science for the University of Oxford and one of the senior directors at McKinsey. Unlike most tech founders that say, “Here’s where society is going and here’s how we’re going to get ahead of that curve,” I had said “I don’t think anyone is going to do this unless we do it because it’s such a thankless job and so difficult but I think it should be done” and they functionally came on board because they believed in us.

Suzanne: Cool, have you ever failed at anything before?

Jeff: Yeah, I could write a book at this point and I’m only 23!

Suzanne: Such as…

Jeff: I think maybe one that comes to mind is I wasn’t initially going to study philosophy, theology and then the subsector of machine learning. I was really interested in English Lit and physics as a subject.

I remember trying to solve a difficult problem with another student. It was taking us three or four hours, extending over four whiteboards. A Sri Lankan guy, who had just moved to L.A. with his family, came into the classroom. He took one look at what we’d done and started crossing everything out until there were just two parts to the equation left and, with a slight adjustment, solved the problem.

I recall thinking that I wasn’t as good at Physics as I thought I was and that there are so many things that I’m not going to be good at that, that other people are better at!

Suzanne: That’s always true of everything in life though; so you’re a bit of a perfectionist then.

Jeff: I don’t know…

Suzanne: If somebody had told you how hard it would be to run a startup, would you have done it?

Jeff: I don’t want to sound arrogant but the problem is pretty vast and I really want to be the one to solve it but if there was a company that was the exact replica of ours that was well funded and had very trustworthy founders and I saw them tomorrow then I’d be tempted to quit.

Suzanne: Finally, what do you need or want?

Jeff: At this stage we now have a build of the next product that works. We’re raising a seed round of £1.5m to bring on board an engineering team as well as a human curation team that works alongside the machine learning. I like to think of them as the equivalent of NASA’s ground and flight control, amalgamating technical and human know how to propel TownSquare’s growth!

Suzanne: Good luck, Jeff and thanks for taking the time to talk to us!


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