Vivienne Ming explains how she founded the Socos startup by using her AI-based deep cognitive model

Ming, Vivienne

LSE Research Online

9/20/2016An entrepreneur’s quest to build an EdTech product out ofher inventionblogs.lse.ac.uk /businessreview/2016/09/20/an-entrepreneurs-quest-to-build-an-edtech-product-out-of-her-invention/Children eating lunch at school , by USDA, under a CC-BY-2.0 licenceThe purpose of education is to produce happy, healthy, impactful lives, and let society reap the benefits.  At firstglance, this may not seem controversial, but taken to its radical extreme, this purpose statement — the core tenet ofmy company, Socos — leads to a fundamentally different approach to education, parenting, and even management.Every action by a parent or manager is selected explicitly based on its predicted impact on the life outcomes of eachchild or employee. Nothing else matters, however sacred.Don’t worry, we are not about to dive into a wonky discussion on education policy. The implications are betterunderstood as a story of innovation. (As Richard Feynman apparently never said, “If you can’t build it, you don’tunderstand it.”) For me, this story began in 2007. I had completed my PhD at Carnegie Mellon University theprevious year and was a researcher at the Redwood Center for Theoretical Neuroscience at UC Berkeley. My wifeand I had an idea for a technology to end all high-stakes testing, and we cofounded my first tech startup,Augniscient. Rather than providing structured problems to students like a standard online tutor, we developed atechnology to turn unstructured data such as online discussions directly into formative assessments. In other words,by “listening” to students talk to each other we could predict their performance in the class without ever giving thema formal test.As we saw it, teachers could then adapt their instruction for every student. Why waste time on standardized tests ifwe can predict the outcomes? Instead, focus on teaching until every student masters the required skills. My wife andI eventually published papers showing that we could predict not just grades but performance on individual finalexam questions directly from student conversations.As an EdTech startup, however, Augniscient was mostly an education for me. (For example, choose apronounceable company name.) I was a classic academic-turned-entrepreneur; I had an invention and assumedthat the world would happily do all of the hard work needed to see my “genius” brought to market. Over three years, I1/3learned that a technology is not a product, a product is not a business plan, and a business plan is not a business. Ialso learned that venture capital is not well aligned with education. If you have a truly innovative technology, there isalmost always a better business than education. To paraphrase one VC, “You can read students’ minds? Here’s $2million to do financial fraud detection.” We were quickly pushed away from education and into the then-nascent fieldof behavior analytics as one of the first companies focusing on unstructured log analysis (yes, I know…so sexy).Sick of the slow drift toward advertising, we sold the company.The path from the CIA to Carnegie Learning to Augniscient brought me part of the way to Socos. I was able to inventtechnologies which could radically transform education, but I still didn’t know what that transformation should be. Myfocus on obviating high-stakes, biased testing still assumed that the purpose of education was to learn how tofactorize a polynomial and who signed the Peace of Westphalia. I had not yet asked the simple but profoundquestion, “Why?”Perhaps unsurprisingly, the inspiration for this much more radical step didn’t come from my experiences in EdTech.Late in 2011, I was approached by a small startup called Gild. Their purpose was to take bias out of the hiringprocess. They had developed a product which mined through all open-source code repositories (e.g., GitHub andBitBucket) and surfaced the best software developers based on the quality of their code rather than traditionalcriteria, like schools or work history.Unfortunately, all of the open-source developers in the world didn’t make for a sufficiently compelling product. So, Icame on board as Chief Scientist to make the product predictive, moving from direct code analysis of 100,000 opensource developers to surfacing predictive characteristics across tens of thousands of variables applied to tens ofmillions of people. In the end, we had built a database of over 122 million people from hundreds of public sourcesacross every professional job vertical.While the story of Gild is fascinating on its own, it was my work building predictive models of work quality and careersuccess that turned education completely on its head for me. I found that most traditional characteristics used inrecruiting — grades, test scores, university — were at best only weakly predictive of quality of work. I wasn’tcompletely surprised, there was already substantial body of research findings, but I was quite surprised to discoverthat even skills and ‘knowledges’, whether claimed on a résumé and inferred from a work history, were notpredictive.Yes, you need to know how to program to be a programmer, but beyond that it told us very little about your impact.Instead, I saw the emergence of a completely different set of predictive characteristics: general cognitive ability,meta-cognition, emotion perception & regulation, creativity, and motivation. Unlike traditional hiring criteria, thesewere domain-general, as predictive for an athlete as for a programmer. While they were correlated with academicperformance, it became clear that these were the ultimate causal variables. Most importantly, these are the sameconstructs which hundreds of scientific studies have shown to predict the life outcomes of young children.Programmers aren’t successful because they know how to program in Java or Python; they are successful becauseof qualities like self-efficacy, endogenous motivation, and working memory. They are successful because they areproblem solvers. The same is true for designers, saleswomen, CEOs, and professional athletes. Of course, we don’tteach skills and ‘knowledges’ in school out of malice but we have the direction of causation wrong. A craftsmanwithout their tools is hobbled, but tools without a craftsman are pointless.With all of this in mind I launched Socos. We invented AI technology, deep cognitive models, which can analyzeimages, speech, writing, and more. We abandoned any focus on traditional skills learning or assessment andpointed our models at the causal factors leading to positive life outcomes. But that still left a big question: what thehell is our product?People need answers; they don’t need more data. Across my many startups, as a founder and advisor, I havelearned the importance making products that do the hard work rather than expecting your customers to do it for you.2/3(They won’t!) The ability to even weakly predict children’s life outcomes — health, education, income, happiness —is a frightening and profound power. For Socos it has come to mean one simple message each day: Parents, here isthe one thing you can do tonight that will have the biggest impact on your child’s life. There is no gamification, nostudy material, no dashboards. Share pictures of your child’s artwork, samples of their speech, and answers to asingle question each day, all voluntary, and we will provide a simple daily activity designed to improve that specificchild’s productivity and well-being, integrated across their life. This is Muse.Keeping Muse extremely streamlined as a product vastly expands our addressable market. Although it can run onmultiple platforms, we can deliver the entire core value via SMS. That means we can reach any family with nothingmore than a feature phone and a mobile connection. There is no assumption that a child has access to a tablet,smartphone, or even a classroom. The Muse AI lives entirely on our servers and is just “chatting” with the parents.We don’t need anything more from them than a willingness to spend 10-30 minutes playing with their kids. Anythingless than that and we simply become part of the educational arms race, businesses whose sole purpose is helpingsuccessful families pass their advantages on to their children. It’s a great business…that changes nothing.♣♣♣Notes:The post gives the views of its author, not the position of LSE Business Review or the London School ofEconomics.Before commenting, please read our Comment PolicyVivienne Ming, named one of 10 Women to Watch in Tech by Inc. Magazine, is a theoreticalneuroscientist, technologist and entrepreneur. She is the co-founder and Managing Partner ofSocos. Previously, Dr. Ming was Chief Scientist at Gild, a startup that builds better companies byunleashing human potential in their workforce using machine learning. She is a visiting scholar atUC Berkeley’s Redwood Center for Theoretical Neuroscience pursuing her research in cognitiveprosthetics. In her free time, Dr. Ming also explores augmented cognition using technology likeGoogle Glass and has been developing predictive models of diabetes and bipolar disorder. Shesits on the boards of StartOut and Our Family Coalition, and speaks on issues of LGBT inclusionand gender in technology. She lives in Berkeley with her wife and their two children. Her work and research hasreceived extensive media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and TheAtlantic.Copyright © 2015 London School of Economics3/3

An entrepreneur’s quest to build an EdTech product out of her invention

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