Future of Work: Digital Transformation, AI, Big Data, and business analytics ( скачать в хорошем качестве

Future of Work: Digital Transformation, AI, Big Data, and business analytics (

What are the implications of digital transformation, technology, machine learning, and new business models on the future of work? The impact of big data and business analytics with technologies such as artificial intelligence have profound implications for companies, individuals, and society. At the same time, government policy on these issue lags technology and the impact on people. On this episode, a respected futurist and well-known data scientist explore these complicated and important issues. Frank Diana leads the business solutions organization for TCS (Tata Consultancy Services) Global Consulting. and is a top futurist. Anthony Scriffignano is Chief Data Scientist at Dun and Bradstreet. Michael Krigsman is an industry analyst and host of CXOTALK. For more information, https://www.cxotalk.com/episode/futur... ------------------ Check out more CXOTALK episodes: https://cxotalk.com/episodes ------------------ From the transcript: (05:35) What are the forces shaping the future of work? Frank Diana: (05:42) So, let me kick that off and I’d love to get Anthony’s perspective on it as well. Things like the driverless car is an easy one. That one, in the last six months to a year, has really taken off, and now people don't see it as science fiction anymore, but that driverless car, as just one scenario, has brought in deep implications across every sector. And when you actually start to look at that, you appreciate just how disruptive and impactful that one scenario is. But how about things like healthy life extension? That's one of the scenarios that I'm tracking as well, as we've looked to extend our lives, and that's not just in terms of years lived, but healthy years lived. And, what does that mean to retirement? And what does that mean to insurance, and all of the things that, really, we think about? And on, and on, and on; the maker economy. The sharing access economy. These are all scenarios that I call … And again, they do intersect and intertwine. Very impactful! Anthony Scriffignano: (06:30) So, maybe I can just add a little bit to that. On the driverless car, I would expand that to this concept of autonomy. So, we have things. We have cars. We have drones. We have fill-in-the-blank. And these things have agents in them that are describing their behavior, so we give them goals. In the case of a car, it might be “drive safely and get where you’re going.” And then all of a sudden, these autonomous agents need the ability to modify their goals. Something changes in the environment, somebody runs out in front of the car, etc. And now, we are … Autonomous agents are given the power to change their behavior at our request. That’s going to change everything for us. That’s going to change the way we interact with our agents because they may not be doing what we ask them to do anymore. Kind of like children, right? And also, because those agents might be able to think faster than we can, doesn’t necessarily mean that they have the experience and the context that we do, with the emotion that we do. (07:23) So, if I could tie that to the healthy living comment, think about things like senior care. Think about things like understanding how to deal with people in the end-stages of life. Do we want autonomous agents doing that? I don't think so. So, I think at some level, this disruptive change gives us the opportunity to focus on things that human beings uniquely do better than machines, at least in the thirty-year horizon that we can see. And also, we have to pay attention to what we're giving up to those machines and make sure that that's not happening by accident. And, I would add one last thing, which is that not all of this innovation is for good. So, think about the ways that the band guys can use this disruptive innovation that's happening all around us to disrupt in ways that we don't even have words for, yet. So, there's a very high cost to doing nothing. And that high cost is that some of that innovation happens without us paying attention, and then we get disrupted in ways that are really terrifying and surprising at the same time. (23:47) And so, the question comes up: Could I write a piece of software that could write an article about an event like that that passes the Turing Test – that lets people believe that it was written by a human? And the answer is “yes,” until a hot air balloon lands in the middle of the track that was unexpected or, all of a sudden a geyser opens up. See, these unexpected things start to happen and algorithms aren’t going to be so good at that because they haven’t been taught to write about it; whereas, a reporter would jump in and say, “This is the coolest thing ever! A hot air balloon just landed in the middle of the track and I’m going to write about it first, and I’m going to get the greatest article and I’m going to get the Pulitzer Prize.”