Should-Read: Dan Costa: Fast Forward: Scientist, AI Expert, Entrepreneur Vivienne Ming

Should-Read: Dan Costa: Fast Forward: Scientist, AI Expert, Entrepreneur Vivienne Ming: “If you are doing the same job you were doing a year ago, Vivienne Ming is going to replace you with an AI… https://www.pcmag.com/article/351278/fast-forward-scientist-ai-expert-entrepreneur-vivienne-mi

…Vivienne Ming: “Alexa is not AI. Siri is not AI. They are just voice interfaces for database search. There’s some neat stuff behind the scenes, but it’s automation. It’s great automation, I’m not knocking it.

AI to me, the most basic and tangible would be the face recognition and images that Facebook and Google can do. AI is some aspects of self-driving cars. Not everyone, but a lot of them…. Andrew Ng who is the Chief Scientist at Baidu, put it really well. AI is anything that feels uniquely human, but we can do in maybe in a second to five seconds. Now we can build… deep neural networks that can do anything you and I can do that kind of cognitive scale. If I can, for example, look at a resumé and think after about five seconds ‘ah, maybe I won’t hire this person.’ I can build an AI to do that different and better. Real AI is made up of things like face recognition, self-driving cars….

Again, think about a complex judgment. Do I know this person? Are they happy, are they sad? Should I hire them? At least those snap judgments. We can really automate that sort of thing nowadays. There are some implications about that, but that’s what I’m getting at with AI. What’s interesting is just as hard as it can be for me to tell you why I recognize you, why I would hire this person, it turns out we needed these deep neural networks that are almost just as complicated to understand to solve those problems….

I don’t think people should be bent over in fields picking strawberries. I don’t think [miners] should have to go a mile under the ground to mine coal. We can build systems to do that. I don’t mean I can imagine. People are building those technologies right now. They can be deployed and they are better, more efficient, and less costly than a human solution. Then we got to think, what am I going to do with all of those people?…

I build it, I have built systems for diabetes and for bipolar disorder, for finding jobs, for education. I’m truly hooked, I am part of the problem. Did I believe in its potential, does it make the other problems go away? We tend to work under this very optimistic assumption that yes, people are going to lose jobs and they’re going to be financial analysts and farm workers and doctors and long-haul truckers…. We aren’t building people to be creative problem solvers, to be adaptive. We’re building them to pull levers, sometimes very complex, cognitive levers, but still it’s lever pulling. Those people are not going to be ready for an AI-enabled job….

We need craftsmen, we don’t need tools with just legs carrying them around. We need adaptive, creative problem solvers that can then take these amazing technologies and do something amazingly creative with them…. we need to do is move education away from the tool side of the equation. Tools being all the skills and knowledge that I can give you a test and say do you know how to do this…. We need to stop with the focus on tools and think how do we build people that have strong cognitive skills, strong problem solving, metacognition, social and emotional intelligence. These are the things that are actually valuable. Then it turns out once I have those, once I’ve got a bunch of craftsmen I can actually teach you all sorts of tools and then augment it by AIs that can quickly and adaptively change.