Matt Jones

SYSTEMS SHOULD SERVE PEOPLE, NOT THE OTHER WAY ROUND. “I’ve always appreciated systems-level change,” notes Matt Jones. As a child, he was enthralled by Isaac Asimov’s Foundation, a series in which a mathematician develops a statistical model that charts the collapse of a civilization, and how he takes steps to minimize the dark age to come. “I found it fascinating to think about human systems as another kind of engineering, and decided that the same subtle cleverness that makes for better engineering would be the best way to make a better world,” he says.

Matt went on to study pure math and political science at UC Berkeley, aiming after graduation for positions that fostered systemic change. Working at an activist hedge fund, he played a key role in the hostile takeover of Amylin Pharmaceuticals, drove high-return positions in a bankrupt Lehman Brothers and failing MBIA, and was one of the eight voting members on the note holder's committee driving General Motors’ bankruptcy restructuring. He then ran operations for CEAi, a catalyst fund backed by Data Collective that created novel machine learning companies in partnership with global-scale enterprise partners like MunichRe. Four new companies were created from this venture - one recently acquired by Mind Meds (NASDAQ: MNMD).

The experience of creating novel clinical trial measures using machine learning made it clear that the core problems in healthcare revolved around data usability and analysis, spurring Matt to tackle the biggest problem blocking progress in the most important arena any of us will interact with in our lives. Everybody agrees doctors should be able to share information with other doctors - but medical records are written in natural language and medical jargon, he explains. Doctors suffer with electronic systems now because those systems try to turn the full complexity of language and images into dropdown menus and checkboxes, and healthcare is held back on every front by these data bottlenecks.

So, Matt created Science, which uses the most advanced set of medical AI tools to build effortless, custom-fit applications for the world’s largest healthcare systems. For example, doctors still rely immensely on faxes to transmit information, and have to build up each patient’s file from literal scanned pictures of data. Science can ingest all of these sources into real, computer-usable data - monitoring patients for new information, creating infinitely richer research databases, and allowing healthcare paperwork to be accurately automated. Matt also points out that this reduces the stress and suffering of healthcare providers already overburdened, who are leaving the profession in droves due to burnout.

SEEING MORE FROM THE SIDELINES. "One of the things that concerns me most in current culture is being taught that LGBT identity is an obstacle, rather than an invitation to unconventional and exceptional success,” Matt says. “We’re used to being a little uncomfortable; I think growing up gay forces you to be a little more focused on the details of your environment and puts a bit of extra pressure on achieving. Being uncomfortable is a good thing. Now, being gay in the professional sphere is a bit of a superpower.”

“There are incredible people I’m very grateful for that I’ve met thanks to my identity. I think the most important thing is to not worry so much about what advantages others might have, but to be grateful for and hone your own. Some of the world’s most successful, interesting people are LGBT, and I’m thankful for having a reason to connect with and learn from them.”