Never Too Much AI: Upwork's Andrew Rabinovich

**Sam Ransbotham** (0:00)
Stay tuned after today's episode, as Shervin and I talk about the changing role of the CIO.

**Shervin Khodabandeh** (0:08)
With AI infused products and services advancing so rapidly, what one component is holding developments back? Find out on today's episode.

**Andrew Rabinovich** (0:20)
I'm Andrew Rabinovich from Upwork, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:26)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy guest editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:45)
And I'm Shervin Khodabandeh, senior partner with BCG, and one of the leaders of our AI business. Together, MIT SMR and BCG have been researching and publishing on AI since 2017, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.

**Sam Ransbotham** (1:11)
Today, Shervin and I are talking with Andrew Rabinovich, Vice President and Head of AI and Machine Learning at Upwork. Andrew, thanks for talking with us.

**Andrew Rabinovich** (1:20)
Thank you. Good morning. My pleasure to be here.

**Sam Ransbotham** (1:23)
So, Andrew, I've long been interested in online labor platforms, and Upwork in particular, both as a user, I admit, and as a researcher. In case any listeners are looking for some light bedtime reading, I've recently published an academic paper using online platforms. And what's fascinating is that these IT improvements are shrinking transaction costs. And that's changing the structure of firms. I don't know that the economist from 1937 would recognize firms these days. But before I digress too much, let's step back. Andrew, road me in. Tell people what Upwork is and what the platform does.

**Andrew Rabinovich** (1:58)
Sure. So Upwork is a world's largest bidirectional marketplace, which is an important distinction that we can dive into later, where clients can look for talent across a variety of categories to help them work. And freelancers from around the world can look for work opportunities in online software, any kind of development that allows them to leverage their skills without necessarily being physically close to where the action is.

**Sam Ransbotham** (2:33)
That makes sense. And you're the vice president and head of AI machine learning. Tell us about what that role means.

**Andrew Rabinovich** (2:38)
Upwork is a company that is a result of a merger of two large marketplaces, ODesk and Elance, started in early 2000s and in 2015 merged to become Upwork. And for the longest time, the platform has offered a matching service between clients and freelancers, as I had mentioned. However, in the evolution of technology that you referred to, we are on the path to transform Upwork, where the goal is to distance ourselves away from matching client to talent. But rather than doing that, offer an outcome-driven business, where clients come onto the platform and describe the problem that they want to solve, rather than looking for folks to help them solve the particular problem. And in order to facilitate that experience, there's a tremendous amount of AI and machine learning involved to create an effective and pleasant experience.

**Shervin Khodabandeh** (3:49)
So explain that more. I'm a client, I show up, and I say, I have this technical problem. I'd like to develop a forecasting model for my supply chain.

**Sam Ransbotham** (4:03)
Podcast listeners.

**Shervin Khodabandeh** (4:04)
Yeah. For my podcast listeners, actually. That's a better one, right?

**Andrew Rabinovich** (4:07)
That's a great example. Traditionally, say you come onto the platform and you say, I am looking for a financial analyst to help me improve traction of my podcast. And then you would have to write super technical specifications of the type of a person you're looking for. And then Upwork's match engine would find you a list of highly skilled candidates that you can pick from.
And then Upwork steps away, and then you transact with that individual, whichever.

**Shervin Khodabandeh** (4:41)
We're all familiar with that model, right? So the new one is...

**Andrew Rabinovich** (4:45)
There's two problems with this original approach. And they're not really problems, they are more limitations. First of all, you have to know what kind of a person you need, or a group of people you need to solve the particular task. You have to be able to describe it in very technical terms, such that the search engine on Upwork is able to provide you with the right matches. Now, suppose you are doing a podcast on travel, or mycology, or design, and you really aren't a technical person, and you're like, I have some traction, people listen to my podcasts, but I want it to like explode so I can become an influencer, make a million dollars, whatever. And that's your level of technical expertise. This is as far as you can explain it. You're like super experienced in your domain, but when it comes to unit economics of podcasting, you have no clue. So essentially Upwork is useless to you because the barrier to entry into this platform is so high that you can't use it.