Looking ahead to the exciting future of analytics with #2023Analytics keynote Hilary Mason

Ashley Kilgore:

We’re currently in the countdown to the 2023 INFORMSs business analytics conference in Aurora, Colorado, April 16th through the 18th. And this year’s conference is particularly special to the INFORMS community as this was the site of our 2020 meeting, or it was supposed to be, but unfortunately the COVID-19 pandemic had other ideas. Now here we are three years later and we’ve come full circle and I think I speak for many in the INFORMS community when I say that I have never been more excited to attend an analytics conference.

With that in mind, I am thrilled to be joined by Hilary Mason, the INFORMS round table sponsored keynote speaker and co-founder and CEO of Hidden Door, a game technology studio using machine learning to build the future of immersive entertainment. We’re taking this opportunity to get to know Hilary a little bit, talk about her analytics journey and get a sneak peek at what she’ll be presenting at the upcoming conference. So Hilary, oh my gosh, it’s such a pleasure to speak with you.

Hilary Mason:

Thank you. I’m really excited to get to be here this morning.

Ashley Kilgore:

So as I mentioned in my opening, you are both the co-founder and CEO of Hidden Door, so you’ve been part of this machine learning based approach to immersive entertainment, which honestly sounds really cool and interesting. Since the beginning, could you share some background on how Hidden Door came to be and the kind of work you’re doing there?

Hilary Mason:

Yes, because it’s probably a little bit of a mystery why you would ask someone running an AI video game company to be here speaking about analytics, but it’s all part of the same thing. So I’ve been in analytics data science for about 20 years working in a variety of different capacities, and one of the places I’ve always been happiest is when we have some new way of understanding data and we can start to imagine the questions we can ask of that data, the products we can start to build on that data and the businesses we can start to create around those products.

So I love working in that mushy space of an emerging understanding and then some sort of new thing we can create that wasn’t really feasible or possible before. And so what we’re doing at Hidden Doors, taking any work of fiction, whether it’s a movie, a TV show, a novel, and making it a playable social game that you can play with your friends, its web based, it uses a ton of pretty cool machine learning under the hood and it lets you continue the adventures in the world in the way that you want to.

So maybe you fell in love with Bridgerton, but you want to romance in a different way in that world, or our alpha is all based on the Wizard of Oz, so maybe you have this idea for a gritty mystery in the Wizard of Oz, or maybe it’s more like a buddy comedy, and so we really allow people to create the sort of collaboration between themselves, the original authors of the creative work, and then the system to come up with something new and exciting and interesting. That’s what we’re doing at Hidden Door and underneath the hood is a ton of different data analysis techniques that we sort of bring together to create that product experience.

Ashley Kilgore:

So now in addition to that incredible work, you are also the co-founder of HackNY, a nonprofit that helps talented engineering students find their way into the startup community of creative technologists in New York City. I’d love to hear what inspired you to help create this organization and the kind of impact that it’s had.

Hilary Mason:

So HackNY is a nonprofit and it came out of this recognition. So first, I’m a lifelong New Yorker, grew up here, fifth generation, New York City kid. I left for college, graduate school and a little bit of adventuring, but eventually came back. I love the city and our city is so rich because of all of the different cultures that we have in it. And I mean that both in terms of human cultures, but also in terms of work cultures and industries and just everyone who wants to do interesting work at some point finds their way to New York or through New York or visits. It’s a really nice place for that.

But one thing we lacked, this is going back now 12 years, was a bridge between the New York area’s, incredible academic institutions and the creative technology community. So there were plenty of students, plenty of folks who were growing up as technologists, but then they would go to the Bay Area or they’d go somewhere else or they’d go work at Goldman Sachs, which is cool if that’s what you want to do, but it shouldn’t be the only thing you can do.

And so we created HackNY as this bridge organization to help introduce talented technologists to smaller, more creative organizations like startups in a variety of different places that could really use their talents. And we always made sure of a couple of things so that there was always a strong mentor at the host organizations so students would have one of those incredible experiences where they’re really learning a lot and they’re doing real work, not make work. And then it creates just this cohort of people who are going through the same thing at the same time.

So they have friends, they have a whole program of stuff outside of the job, and it’s been really great. And it’s also one of those things where New York has evolved so much where I think now the technology community here in 2023 is so strong in part because of organizations like HackNY that really sort of saw those gaps and built those bridges. And there are variety of organizations that have done that work, including things like the Queens’s Coalition, which is bringing folks into technology from other careers without charging them money to do so. Right? And so the city has been on a whole journey. The industry and the city has been on a journey. And now I think tech in New York is probably one of the… I’m very biased, but it’s a great place to be doing technology and it’s a great place to build a career.

Ashley Kilgore:

So now in addition to your work with Hidden Door and HackNY, you’ve had roles with Excel partners, fast Forward Labs and Bitly, you also serve as co-hosts of Data Gotham, are an advisor for multiple companies and even served on New York City Mayor Bloomberg’s Technology and Innovation Advisory Council. Of all of these different roles and experiences, do you have a favorite project or memory or maybe even a challenge that you overcame but still resonates with you today?

Hilary Mason:

It’s funny because what your mini biography of me is telling me is more that I just get into a lot of trouble. I tend to follow the things that are most interesting at the moment. So I’m going to try to organize these a bit in space and time in the sense of, I started as an academic, was a CS professor focusing on machine learning 20ish years ago, eventually left to work at a startup that failed and then went to work at Bitly, which you may know it for short links on the social web. And at the time I joined, my role was really one of like, okay, our product… We’ve raised some money, we have this product that lets people make short links and share them and get analytics. We don’t really know where to go next. So can you invent the future of the product and the business through the data assets we have?

This was again, starting in 2009 when, to be frank, we didn’t really understand fully the potential of social media and its impacts on society. We were really just starting as a community to lay the groundwork of analysis of that kind of data. And it was really a space of figuring out, again, this new data set requiring new techniques or adaptation of existing techniques as I’m sure your audience understands very well, in order to come to some understanding to either make a decision, potentially build a product, and that was a wild adventure. On the one hand, part of my team’s mandate was security. So dealing with the kinds of scams and things that come up around that, and I have stories about that. On the other hand, we built a real-time search engine that sort of inverted search in the sense of not I am querying for a fact, but rather what are people paying attention to right now that might be interesting to me.

So you could do queries, show me the stories people in New York City are reading about food, which is personally, a very interesting query. And so I really love playing with different ways of navigating attention as a feature for relevance and search scoring. That was super fun. And then Data Gotham was a community conference I co-hosted with some other folks in New York because again, we really wanted to strengthen the community of folks thinking about analytics, but applying it in many different ways. And what I loved about that event was we had speakers from the NFL, from the Oceanographic Institute at City University of New York, from a couple of fashion startups, from an architecture firm all doing the same math, but applying it to such different problems and then getting up one after another and saying, here’s what I’m doing and here’s the work I’m able to do with it.

And just realizing that in that room, we all had something so deeply in common and yet we had to create the space to have those conversations. And it’s something I love so much about analytics broadly is that it’s the same math, but we can do so much with it. And I would say that, I mean, you asked about challenges too. I founded Fast Forward Labs in 2014 to create a new mechanism for applied research and data science and machine learning, trying to articulate some of the emergent approaches to working with these emergent data sets and then partner with organizations so they could build analyses, products, new businesses on them. And that was, again, so many stories, so much fun with that. It was a really interesting adventure in a lot of ways. And it’s what led, frankly, directly to my current company, Hidden Door, in the sense of realizing the number of new techniques for working with unstructured data, primarily text data and language.

And at Fast Forward Labs, we did work in text generation in 2014, in summarization, both extractive and abstractive, which remains a favorite project of mine, where we actually built a product out of it to help people who were doing commodities trading essentially more quickly take advantage of news that might affect what’s in their portfolio. So it did a bunch of clustering of articles in the news and then summarizing for them the key sentences and insights extracted, the idea being that a person then would wake up in the morning, sit at their desk, and rather than trying to wade through 20 PDFs to look for those insights, it would be summarized for them to figure out where to go first.

And I have, as an aside, always been a fan of products that use data to help people make better decisions, which is what I think the core power of analytics really is. Not necessarily products that replace people or try to automate entire processes. Much more on the how do we make people better at what they do by using analytics to give them better information side of the world.

And so that that has directly informed where we ended up with Hidden Door, and I’ll say one more challenge I found there is that a lot of the projects we were able to work on at that time, again starting in 2014 where ones where we were using analytics and data science to reduce the cost of existing work inside a large organization. So finding a problem that was a scaled problem, something like even something… I think probably the most money we ever helped anyone save was in supply chain optimization. So figuring out which parts were the same as other parts from other vendors and being able to optimize everything from when orders went in size of orders across multiple business lines, really the stuff that is not, no one’s going to put their hand up and say, this is the sexiest work in the world, but it is incredibly useful.

But it’s mostly focused on taking existing cost, reducing that existing cost. I look to play in the space also of taking a new capability and now building something that you couldn’t have done before at all. So I’ll say that was one of the challenges and one of the lessons I learned from that decade of work that we just pointed out, and that one of the things I’m most excited about going forward from here is that opportunity to take some of what we’re learning today, the new techniques, the new data we have access to you, and to start to think about the kinds of experiences, the kinds of things we might understand that we don’t currently have a robust data-driven understanding for, and then what we can do with that that’s new.

Ashley Kilgore:

So at the time of this recording, we’re coming up on International Women’s Day on March 8th and INFORMS is participating in this year’s theme, embrace equity. We’ve all been taking our embrace equity selfies and have gotten oodles from our members, which has been super exciting. I’d love to hear about ways that you have both felt embraced and supported in this ORMs data science community, and likewise ways you try to help others to feel included too.

Hilary Mason:

The data science community, when you do data science, when you do analytics well, one of the greatest strengths we have is that people come to it from a variety of different academic and career backgrounds. So we have folks like operations researchers who have been doing this forever, but also actuaries who have also been doing this forever. And we have statisticians and we have computer scientists, and we have folks who are coming from a quantitative social science background. We have folks who are coming from a physics background. And one of the things I always say when people ask me how do I create the world’s greatest data team is that everyone you bring on that team should have some background and experience that is not represented already on your team. If you have a team of all machine learning CS PhDs, you have failed because you are not going to be able to take advantage of the richness of that career and work history.

And you miss out on what everyone’s personal life experience and empathy brings to the way they approach those problems. And this is an argument I’ve had with many people. I think it is incredibly naive to think that our individual empathy for a problem doesn’t affect the way we approach solving it or thinking about it analytically.

And so that means that the best data science teams, the best analytics teams are ones that have a rich variety of perspectives on them. And what that means for those of us who become leaders in that context is that we can then create the environment where everyone, no matter what their backgrounds are, can thrive. And when I assess these questions, when I look at an organization, I will ask that, are you hiring people from different perspectives, different backgrounds? Once they come join your team, are they succeeding? Are they getting promoted? Are they doing really interesting work, the best work of their careers? And this is all stuff I believe very strongly in, and I’ve been very proud to work on and lead some pretty diverse and interesting teams, and that’s the environment I want to work in. And so it’s the one I try very hard to create.

Ashley Kilgore:

So now Hilary, without giving too much away, can you give us a sneak peek at what you’ll be presenting at the 2023 INFORMS Business Analytics Conference?

Hilary Mason:

I’m very excited for this conference because it does really feel like almost a coming back and coming back with fresh eyes to think about the community we’re in, the work we’re doing. And so what I’ll be talking about is very forward-looking, sort of what are the most exciting changes in our capabilities and the kinds of data we can look at, what can we build with those things, but also with a ton of respect for what’s brought us here.

And so what I will be looking at are essentially how to build great stuff out of the data assets we have with the tools and techniques that we’ve been refining for decades. And an attempt to look ahead a little bit and think about what’s going to be really exciting in the next 10 years unless this be too optimistic. We’ll also be discussing a little bit of the ethics and challenges of doing data and analytics today in 2023, knowing what we know and having learned the lessons of particularly the last decade. So it should be a lot of fun and hopefully we’ll at least get people fired up to argue and debate, if not excitedly get on board.

Ashley Kilgore:

That really sounds super interesting and exciting. And to all our listeners out there, if you want to hear more, you’re going to have to register for the conference. Just had to slip that in there. Now, Hilary, I’d love to change gears a little bit. What’s something unique about you that others might not know? Maybe a hobby or a favorite activity?

Hilary Mason:

I love to bake. Maybe that one isn’t obvious. My mother’s a pastry chef and I feel like I learned by being her free dishwasher and prep sous chef. And so that’s one that, yeah, most people wouldn’t know that, but it’s something that I love to do. And I also have done an analysis of the optimal chocolate chip cookie recipe that was data driven. Looked at about a thousand different recipes to understand what are the average, what are the distributions, what changes in ingredients and method correlate with altitude or with chewy or with crunchy. So it’s not entirely free of my data obsession, but that’s there. Fun fact.

Ashley Kilgore:

That is super fun. Now, do you share that chocolate chip cookie recipe or is that just-

Hilary Mason:

Yes, happy to share. It’s not that novel, but the one tip I will give you is if you ever do make cookies, throw some in the freezer and then you can just bake them directly from the freezer, and that’s been my chocolate chip cookie hack because you can have them any time

Ashley Kilgore:

When you need them the most. Yes. So Hilary, if you weren’t working in the field that you are, what would you be doing today?

Hilary Mason:

That’s a really hard question. If I wasn’t working on the project I’m working on, which is one where we’re taking this emerging ability to compute around language and what is now being called generative AI to sort of do storytelling and it’s not creative. The systems aren’t creative, but the gameplay, the people around it are very creative. I feel like I would still be working in a very similar technical space. I’ve had this very long obsession with reducing cognitive drudgery through the use of technology.

In fact, I think it was in 2009, I gave a top, which you can find on YouTube called How to Replace Yourself with a Very Small Shell script, which was a summary of a bunch of my attempts to automate email, particularly as a professor where people are emailing the same questions over and over again. So it’s a little bit easier than what most of us deal with. But yeah, I’d probably be doing something like that. I really love being in that space where I get to build something that hasn’t been built before, and some of these things are tremendous failures and you build it and then you realize like, oh, there’s a reason no one ever built this. And I’ve had a bunch of those, but also some of them are really a step to something new and fun, and that’s generally where I’m happiest.

Ashley Kilgore:

So in our conversation today, we’ve covered a wide range of your roles and activities, which there are quite a few. Of all of your accomplishments, either big or small, is there one that you are particularly proud of or perhaps the most proud of?

Hilary Mason:

I mean, it’s going back to the question you asked about International Women’s Day, but it’s broader than just gender. It’s really trying to use the leverage I have to create the environment frankly, that I want to work in and where everyone can thrive because the work we do is so much more rewarding and the output of it is just so much richer and better when we allow people to be themselves and to really be challenged to do amazing work, to have the support of a team. And so maybe I’ve grown up, I think my ambition is not to build a rocket ship, it’s really to build that kind of organization and to normalize it so it becomes everybody’s idea, this sort of inclusive, supportive organization of what working should be like. And there are a lot of challenges to doing this of course, and doing it remotely is a whole new thing now or semi remote for some folks, but it’s one that I think about a lot.

Ashley Kilgore:

So Hilary, I’d love to hear what’s next for you. What big goal do you still hope to conquer in the future?

Hilary Mason:

I mean, what we’re doing at Hidden Doorway are creating a new kind of entertainment experience. And it feels to me like the inevitable future of fandom that when you love something, you want to bring it home with you. You want to live inside of it, you want to tell your own stories in it. And that is the thing that I just can’t get out of my head. It’s going to be a lot of fun.

Ashley Kilgore:

So Hilary, thank you so much again for taking time to chat with me, and I, for one, cannot wait to see you in Colorado in just a few weeks at this point.

Hilary Mason:

Thank you so much. I’m really looking forward to it.

Ashley Kilgore:

Want to learn more? Visit resoundinglyhuman.com for additional information on this week’s episode and guest. The podcast is also available for download or streaming from Apple Podcasts, Google Play, Stitcher, and Spotify. Wherever you listen, if you enjoy Resoundingly Human, please be sure to leave a review to help spread the word about the podcast. Until next time, I’m Ashley Kilgore and this is Resoundingly Human.