>> Narrator: From Berlin, Germany, it's theCUBE, covering DataWorks Summit Europe 2018, brought to you by Hortonworks. >> Well, hello, and welcome to the Cube. I'm James Kobielus. I'm the lead analyst for Big Data Analytics with the Wikibon team within SiliconANGLE Media. We are here at the DataWorks Summit 2018 in Berlin, Germany. And I have a special guest, we have a special guest, Bernard Marr, one of the most influential, thought leaders in the big data analytics arena. And it's not just me saying that. You look at anybody's rankings, Bernard's usually in the top two or three of influentials. He publishes a lot. He's a great consultant. He keynoted this morning on the main stage at Dataworks Summit. It was a very fascinating discussion, Bernard. And I'm a little bit star struck 'cause I assumed you were this mythical beast who just kept putting out these great books and articles and so forth. And I'm glad to have you. So, Bernard, I'd like for you to stand back, we are here in Berlin, in Europe. This is April of 2018, in five weeks time, the general data protection, feels global 'cause it sort of is. >> It is. >> The general data protection regulation will take full force, which means that companies that do business in Europe, in the EU, must under the law protect the personal data they collect on EU citizens ensuring the right to privacy, the right to be forgotten, ensuring user's, people's ability to withhold consent to process and profile and so forth. So that mandate is coming down very fast and so forth. What is your thoughts on GDPR? Is it a good thing, Bernard, is it high time? Is it a burden? Give us your thoughts on GDPR currently. >> Okay, first, let me return all the compliments. It's really great to be here. I think GDPR can be both. And for me it will come down very much to the way it gets implemented. So, in principle for me, it is a good thing because what I've always made companies do and advise them to do is to be completely transparent in the way they're collecting data and using data. I believe that the big data world can't thrive if we don't develop this trust and have this transparency. So in principle, it's a great thing. For me will come down to the implementation of all of this. I had an interesting chat just minutes ago with the event photographer saying that once GDPR kicks in he can't actually publish any photographs without getting written consent for everyone in the photograph. That's a massive challenge and he was saying he can't afford to lose 4% of his global revenue. So I think it will be very interesting to see how this will-- >> How it'll be affecting face recognition, I'm sorry go ahead. >> Bernard: Yeah maybe. >> Well maybe that's a bad thing, maybe it's a good thing. >> Maybe it is, yeah, maybe. So for me, in principle a very good thing. In practice, I'm intrigued to see how this will get implemented. >> Of the clients you consult, what percentage in the EU, without giving away names, what percentage do you think are really ready right now or at least will be by May 25th to comply with the letter of the law? Is it more than 50%? Is it more than 80%? Or will there be a lot of catching up to do in a short period of time? >> My sense is that there's a lot of catching up to do. I think people are scrambling to get ready at the moment. But the thing is nobody really knows what being ready really means. I think there are lots of different interpretations. I've been talking to a few lawyers recently. And everyone has a slightly different interpretation of how far they can push the boundaries, so, again, I'm intrigued to see what will actually happen. And I very much hope that common sense prevails and it will be seen as a good force and something that is actually good for everyone in the field of big data. >> So slightly changing track, in the introduction of you this morning, I think it was John Christ of Hortonworks said that you made a prediction about this year that AI will be used to automate more things than people realize and it'll come along fairly fast. Can you give us a sense for how automation, AI is enabling greater automation, and whether, you know, this is the hot button topic, AI will put lots of people out of work fairly quickly by automating everything that white collar workers and so forth are doing, what are your thoughts there? Is it cause for concern? >> Yes, and it's probably one of the questions I get asked the most and I wish I had a very good answer for it. If we look back at the other, I believe that we are experiencing a new industrial revolution at the moment, and if you look at what the World Economic Forums CEO and founder, Klaus Schwab, is preaching about, it is that we are experiencing this new industrial revolution that will truly transform the workplace and our lives. In history, all of the other three previous industrial revolutions have somehow made our lives better. And we have always found something to do for us. And they have changed the jobs. Again, there was a recent report that looked at some of the key AI trends and what they found is that actually AI produces more new jobs than it destroys. >> Will we all become data scientists under, as AI becomes predominant? Or what's going on here? >> No I don't, and this is, I wish I had the answer to this. For me is the advice I give my own children now is to focus on the really human element of it and probably the more strategic element. The problem is five, six years ago this was a lot easier. I could talk about emotional, intelligence, creativity, with advances in machine learning, this advice is no longer true. And lots of jobs, even some of the things I do, I write for Forbes on a regular basis. I also know that AIs write for Forbes. A lot of the analyst reports are now machine generated. >> Natural language generation, a huge use case for AI that people don't realize. >> Bernard: Absolutely. >> Yeah. >> So, for me I see it, as an optimist I see it positively. I also question whether we as human beings should be going to work eight hours a day doing lots of stuff we quite often don't enjoy. So for me, the challenge is adjusting our economic model to this new reality, and I see that there will be significant disruption over the next 20 years that with all the technology coming in and really challenging our jobs. >> Will AI put you and me out of a job. In other words, will it put the analysts and the consultants out of work and allow people to get expert advice on how to manage technology without having to go through somebody like a you or a me? >> Absolutely, and for me, my favorite example is looking at medicine. If you look at doctors, traditionally you send a doctor to medical school for seven years. You then hope that they retain 10% of what they've learned if you're lucky. Then they gain some experience. You then turn up in the practice with your conditions. Again, if you're super lucky, they might have skim read some of your previous conditions, and then diagnose you. And unless you have something that's very common, the chance that they get this right is very low. So compare this with your old stomping ground IBMs Watson, so they are able to feed all medical knowledge into that cognitive computing platform. They can update this continuously, and you think, and could then talk to Watson eight hours a day if I wanted to about my symptoms. >> But can you trust that advice? Why should you trust the advice that's coming from a bot? Yeah, that's one of the key issues. >> Absolutely, and I think at the moment maybe not quite because there's still a human element that a doctor can bring because they can read your emotions, they can understand your tone of voice. This is going to change with affective computing and the ability for machines to do more of this, too. >> Well science fiction authors run amok of course, because they imagine the end state of perfection of all the capabilities like you're describing. So we perfect robotics. We perfect emotion analytics and so forth. We use machine learning to drive conversational UIs. Clearly a lot of people imagine that the technology, all those technologies are perfected or close to it, so, you know. But clearly you and I know that it's a lot of work to do to get them-- >> And we both have been in the technology space long enough to know that there are promises and there's lots of hype, and then there's a lot of disappointment, and it usually takes longer than most people predict. So what I'm seeing is that every industry I work in, and this is what my prediction is, automation is happening across every industry I work in. More things, even things I thought five years ago couldn't be automated. But to get to a state where it really transforms our world, I think we are still a few years away from that. >> Bernard, in terms of the hype factor for AI, it's out of sight. What do you think is the most hyped technology or application under the big umbrella of AI right now in terms of the hype far exceeds the utility. I don't want to put words in your mouth. I've got some ideas. Your thoughts? >> Lots of them. I think that the two areas I write a lot about and talk to companies a lot about is deep learning, machine learning, and blockchain technology. >> James: Blockchain. >> So they are, for me, they have huge potential, some amazing use cases, at the same time the hype is far ahead of reality. >> And there's sort of an intersection between AI and blockchain right now, but it's kind of tentative. Hey, Bernard, we are at the end of this segment. It's been so great. We could just keep going on and on and on. >> I know we could just be... >> Yeah, there's a lot I've been wanting to ask you for a long time. I want to thank you for coming to theCUBE. >> Pleasure. >> This has been Bernard Marr. I'm James Kobielus on theCUBE from DataWorks Summit in Berlin, and we'll be back with another guest in just a little while. Thank you very much.