Previously an academic, Vivienne Ming initially regretted her decision to become an entrepreneur. Her first project combined neuroscience and artificial intelligence and education. Thinking she could change the world, she created amazing technologies, that everyone she demonstrated to loved. However, investors didn’t see the opportunity and didn’t want to work with her. Instead, they wanted to buy the entire product and appoint their own CEO’s. They assumed that because she was an academic, she couldn’t be a business leader.
Ming found it difficult to answer their brutal questions and prove her worth to potential investors.
Leading up to that, she had led an incredible career, even using artificial intelligence (AI) to help treat her son’s diabetes, prevent manic episodes in bipolar sufferers and to help children overcome brain injuries, both academically and philanthropically. However, she learnt that being a little bit different would forever distance her from these investments
Now that Ming has founded eight companies, she wanted to understand why we have such a hard time seeing human value in one another, particularly when we are a little different to each other. Around the world, people are trying to transform their homes, make change, get jobs etc and yet investors don’t always take them seriously
In response to this, Ming developed the Inclusion Impact Index which is entirely free, available at here. This enables one to see in real-time, in USA, where women are creating new jobs, where LGBT entrepreneurs and startup founders are making drug discoveries that will save peoples’ lives, and where people are getting funding and making an impact on their communities. Ming explains that they have started with a few communities and are expanding to include others.
Ming continued by explaining that the inspiration to go out and change your community is fundamentally human. The data on entrepreneurship is inhuman. It is massive and complex. For example, in Johannesburg today, there are programmes around startup hubs and incubators, and venture capitalists funding upcoming creators. But is that the same as the programmes running in Cape Town? Or further afield in Nairobi, or New York? Or Singapore?
Ming believes that we have to build artificial intelligence that can understand policies, laws and programmes.
The Inclusion Impact index, not simply a data intelligence repository. It uses using artificial intelligence to understand communities and how they can reinvent themselves. This is because people have a hard time seeing value in one another. Machines can help us understand people and help make people better be this on health or entrepreneurship. This can help us transform ourselves.
These transformations are fundamentally human. You are the one that will make the change.
Ming also believes that purpose is one of the most fundamentally human parts of our existence, explaining that purpose is not the specific thing you believe in which gives you purpose. Purpose is a broad idea, something bigger than you, that will take more than a lifetime to complete. For example: “The world gets better when old men plant trees whose shade they will never rest under”. This explains purpose so well.
Some of the most interesting communities are inside big companies. Ming has studied many of them, some with up to half a million people. She looked at behaviours that best predicted a sense of purpose within the organization and what predicts productivity inside the company.
Research has shown that a sense of purpose predicts productivity. Ming’s research has confirmed this.
“We discovered that purpose itself was the best non-traditional predictor of productivity,” said Ming. Her research also showed that making a sacrifice often indicates a great sense of purpose. “For example, in collaborative leadership, when you elevate a person in your space, this lifts up everyone around you and the whole company”.
Ming believes that people that made more sacrifices ended up with better lives. Yet, we hardly ever promote people for collaborative leadership. Companies with more people making sacrifices actually performed better.
Ming explained that she is not referring to people giving up their whole lives for a cause, but rather small moments when people chose to do what the world needs instead of what they wanted to at that moment. This was discovered this using machine learning to mine through the masses of data generated by the research in this large company
Ming’s advice:
