Vivienne Ming is a theoretical neuroscientist, entrepreneur, and author. Named one of 10 "women to watch in technology" by Inc. Magazine, she is the co-founder and managing partner of educational technology company Socos, which focuses on using machine learning and neuroscience to improve educational outcomes and workplace development. She was previously a visiting scholar at the Redwood Center for Theoretical Neuroscience at UC Berkeley, and sits on the board for companies and nonprofits like StartOut, the Palm Center, and Cornerstone Capital.
We had the opportunity to speak with Ming as part of our AI Trailblazers series. We discussed artificial intelligence, workforce development, and how purpose drives performance before she delivered a fascinating Dreamtalk on AI and augmented intelligence at Dreamforce in early November.
You’ve spoken previously about your mission to leverage AI to maximize human potential. In our own research, we’ve found that 59% of marketers and 80% of sales executives believe that AI will have a major or moderate impact on their productivity.
How do you see AI helping employees — and the companies that hire them — maximize their potential in the workplace?
When I was the Chief Scientist at Gild, I worked on predicting who will be a company’s best employees, such that recruiting teams could bring in employees most likely to be successful.
Our main finding was that it wasn’t someone’s specific skills and experiences — whether they knew how to program in a certain language, or whether they went to the right university — that predicted success.
Instead, the predictive elements are things like emotional intelligence, social skills, level of creativity, or strategic thinking.
We already know that AI will be able to replace specific skills. If there's enough data on a process or task, someone like me can build an AI tool to do discrete tasks faster, cheaper, and better than a person.
But AI is unlikely to replace emotional intelligence or creativity as easily. That’s why the future of work will be defined by people that you can give an open task to, without a lot of direction, and trust that they'll make progress on it themselves. These creative, strategic thinkers I call the explorers. They have the skills that we’ll become desperately hungry for in an AI-powered future.
My work focuses on how we use AI to identify those sorts of people. And more than that, how we can take people already within a company’s workforce, and actually build and develop those abilities into them over time.
Let's take the best of what machines can do and stop wasting human beings’ time doing those things. Then let’s work to lift people up, and let them explore. Let's massively extend the creative class.
I can see how identifying individuals with these key skills — creativity, strategic thinking, emotional intelligence — is important, and that AI can help you identify those people. I’m less clear on how a company can go about encouraging the development of these characteristics in an existing employee base. Can you go into a little bit more detail as to how that happens?
Before AI, if you wanted to understand an employee base in any detail, you needed to conduct interviews, or have them fill in forms, or submit to annual 360-degree reviews. What’s exciting about AI is you don’t need to do any of that. Instead, let the employee keep doing what they are doing, and have AI observe and track their activity and learn from them.
AI listens to the sorts of thing you're working on, and the challenges you have. From those inputs, it’s able to figure out a number of things about you, and recommend changes.
For instance, we know that for employees, motivators that are exogenous (or external) to the self are a major negative predictor of long-term productivity. Employees who are motivated in large part by other people’s perceptions of their work are less likely to be happy or productive.
So instead of constantly thinking of their work in terms of "What is my boss going to think? What are my fellow employees going to think?” we encourage people to focus on questions like "What do I think is the right thing to do?"
An AI algorithm can start to spot if an employee is too focused on exogenous motivators, and it can send targeted messages to that employee to switch their focus. This is very much in the employer's best interest in terms of both employee happiness and productivity.
If employees are more effectively motivated by internal, rather than external motivators, how can companies go about motivating and encouraging them? What’s more, how can companies find the balance between appealing to an individual’s own value set, and leading by a defined company-wide set of values?
I'm collaborating with several academic and industry groups about just this topic. How do you balance an individual’s endogenous motivation and your organization’s big mission statement?
Essentially, the answer is that companies should not expect to align all their employees with one static purpose that attempts to define every employee across their company. You’re forcing people to align with one single set of values that perhaps don’t reflect their own priorities.
It’s far better for companies to understand an individual’s values, and then highlight the overlap with the company’s values.
As such, companies have got to do a better job of understanding their employees’ individual motivators, and why they’re doing what they're doing. It’s only with that knowledge that you can begin to target messages that speak to both the company’s goals, and the motivations of the individual employee.
For example, I worked on a project with a number of data scientists at a big bank. The bank had a terrible problem with attrition. The entire team would turn over every two years and they couldn't work out how to make them stay.
I didn’t need to deploy any AI algorithms to work out what was going wrong there; after a few one-on-one interviews, it became clear. These employees were working at the bank to learn, and to expand their resumes. This was a stepping stone to bigger and better things.
We encouraged the bank to set aside its ego and attempt to align its employees’ motivation with the bank’s own goals. That simple step increased retention rates by 50%. Employees stayed an average of three years instead of two.
That cost essentially nothing. We simply worked to strengthen and reinforce the idea that the bank was a place where employees could learn and improve their long-term careers. That simple change, clarifying how the bank could help them achieve what they cared about, totally changed how employees saw their jobs.
The power of AI is it gives companies the ability to understand their employees’ motivations at a greater scale than ever before. Then AI can personalize the messages and direction given to each individual employee.
Vivienne Ming, Co-Founder of Socos and Chair at StartOut, spoke at Dreamforce 2017, alongside other AI luminaries like Peter Norvig of Google, Suchi Saria of Johns Hopkins University, Paul Daugherty of Accenture, and Salesforce’s Richard Socher. For more information on Dreamforce, please visit dreamforce.com.