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Alter Everything Podcast

A podcast about data science and analytics culture.
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In this special episode of Alter Everything, Melissa Burroughs, Senior Product Marketing Manager at Alteryx, hosts Dr. Michio Kaku, one of the most globally recognized figures in science today. Melissa sat down with Dr. Kaku while at our Inspire conference in London, for a chat about the future of data and analytics, and what lies ahead for data scientists.

 

Dr. Michio Kaku is one of the most widely recognized figures in science in the world today. He is an internationally recognized authority in two areas. The first is Einstein’s unified field theory, which Dr. Kaku is attempting to complete. The other is to predict trends affecting business, medicine, finance, and our way of life, based on the latest research in science. He has written four NY Times Best Sellers. His latest is the Future of Humanity, which projects the future of the space program decades to centuries into the future. His previous best seller, The Future of the Mind, hit #1 on the NY Times, Amazon, and Barnes and Noble Best Sellers List, making it the #1 hardcover, non-fiction book in the country. He appears regular on national and international TV, and hosts numerous science TV and radio programs.

We’ve also announced a competition to create the theme music to be featured on an episode of Alter Everything in 2020! To enter, send us your name, along with a 60 second .mp3 file to podcast@alteryx.com by December 3, 2019. We’re looking for an original piece, with no vocals, that really captures the spirit of Alter Everything. Download a .pdf of the full contest rules below.

 

 

 


Panelists:


Topics:


 

Transcript:

Spoiler

Melissa: [00:00:04] This is Alter Everything. A podcast about data science and analytics culture. I'm Melissa Burroughs, Senior Product Marketing Manager at Alteryx, and I'll be your host. In today's episode, I had the chance to interview Dr. Michio Kaku, one of the most globally recognized figures in science today.

If you like futurism, you've heard of Kaku. He's written four New York Times bestselling books, prognosticating what lies ahead for all of us. Getting to speak to Dr. Kaku meant a lot to me. I've been aware of his theoretical physics work since I was a kid, when my father used to try to read Dr. Kaku’s string field theory books to me. Suffice to say, I didn't understand M-theory then, and I hardly understand it any better now despite having pursued a physics education myself.

And that's why I was so excited to get to have a discussion with Dr. Kaku about the future of data and analytics while at our Inspire conference in London this fall. Let's get started.


Photographer and producers:
[00:01:19] Start start.


So we're recording now.


Okay. Good. I didn't want to interfere with your recording. Do you want to just pretend for 30 seconds and I'll get the shots and then I won't bother you too much?


Melissa:
[00:01:30] We get to do a fake interview before we do a real interview, which is nice. But I've got, I've got my notes here. I hope you don't find it disrespectful if I consult my notes because I want to make sure that I've got excellent...


Dr. Michio Kaku:
[00:01:43] No, whatever it takes.


Melissa:
[00:01:47] Should we do more things for the camera?


Dr. Michio Kaku:
[00:01:48] So what kind of topics do you want to cover? We can cover almost anything.


Melissa:
[00:01:52] So I am really excited to hook into one of the topics that you touched on during your keynote, and that has to do with the future of the career of many of our users, which are analysts. So you talk about - and I feel like I'm jumping into the interview – do you want me to do that? Or can I do...


Dr. Michio Kaku:
[00:02:05] Mm hmm…


Melissa:
[00:02:09] Great. I'm just going to pull up my notes...

So you discussed how analytics are going to affect all aspects of society in the near future from medicine to architecture, consumerism, and beyond. What do you think it's going to mean to be a data scientist or a data analyst in the future?


Dr. Michio Kaku:
[00:02:29] Okay, so we could start with that. As I mentioned, oil was to the industrial age as data is going to be for the information age. So data will be the source of wealth, value, progress, all contained within data, and it's going to affect the job market.

Many people think that, wow, there's a lot of unemployment out there. Jobs are fleeing. It's the opposite. There are jobs begging to be filled in computer science. But there's not enough qualified people to fill these jobs. And so we have to train people to the point where they can then apply for these jobs that are just begging for people to fill them. These firms go to Congress, begging Congress to ease up on immigration on, on different kinds of hiring practices so that they can fill these slots. So data is the lifeblood of society. And data analysts are going to be at the forefront of the job market.


Melissa:
[00:03:37] I love hearing that. So if you, if you think ahead into the practice of being a data analyst or a data scientist in the future, what kind of toolkit would you imagine would be at their disposal considering the advances in computing that we also expect?


Dr. Michio Kaku:
[00:03:54] Well, any field of human endeavor is going to generate mountains of data. And to analyze it, you need several things. First of all, you have to have the mathematics and the mathematical training of analytics so you can begin the process of, of grinding and processing this data. Just like oil, crude oil has to been made into refined oil. Same thing with data, and then you need artificial intelligence to help make sense of this. What does it mean? What does it mean for the bottom line? Artificial intelligence is great because it gets better at every iteration. Deep learning allows you to actually learn from the past mistakes so that the data can be processed more efficiently, better into the future.


And then virtual reality allows you to then put this in visual form so you can actually walk through the data, walk through what you are looking at. So we have all these tools, big data. Algorithms, artificial intelligence to process this mountain of data, which is going to be generated by every corporation.


Melissa:
[00:05:08] Excellent. So based upon your perspective on the kind of jobs that are going to be not automatable in the future, one of your comments was those individuals who need to communicate with humans will never be automated away. Certain human to human interactions are just not expected to be replicable by robots.

So as you yourself - a very popular popularizer of data science - do you have any advice for our data science and analytics professionals and community regarding how we can more effectively communicate analytics to the rest of our business and the broader world?


Dr. Michio Kaku:
[00:05:53] The jobs in the future will be those jobs which cannot be done by robots, everything else will be done by robots. So then the question is what robots cannot do. That's going to be where the jobs of the future are. And as I mentioned, the three basic areas:


First is semi-skilled, manual labor, because robots, believe it or not, had no manual dexterity. They're very bad at pattern recognition in the real world, not in a controlled environment, but in the real world. And so this means that plumbers, gardeners, construction workers, sanitation workers will all have jobs because robots cannot pick up garbage.


But the second category is human to human interaction. Robots, for example, do not understand common sense. Robots do not know that water is wet. Why can't water be dry? Well, you touched water, but robots have never touched water. Mothers are older than their daughters. Well, we know that mothers are older than their daughters, but robots don't know that. According to Einstein, you can be the reverse. And strings can pull. Strings cannot push. Or sticks can push, but sticks cannot pull. Now how do we know that? How did we know those strings can pull, but cannot push? We've seen string. Any child has seen string, but robots have not. Therefore, when you talk to a robot, you're talking to a child basically, that has never experienced reality. That's one aspect. 

The other thing is emotions and interacting with what humans want. When you talk to people, the first thing you understand is well what does that person want? Does that person want information that I can give them? Does that person want life stories? Does that person want gossip? Robots don't know any of these things. What do humans want? They don't know. So this means that lawyers, counselors, professors, human resource people, people that interact with other humans on a level requiring human understanding of common sense and what people want. Those jobs are going to flourish in the future. And analytics, of course, is very complicated and you have to explain it to other people, plus explain it to the public. And that's where you need human skills to do that.


And then the third category is intellectual capital. Things that the mind can do that a robot cannot. For example, this means planning, innovating, strategizing, creativity, gossip, experience. Robots don't have any of those things. Robots are adding machines. We forget that. They are very sophisticated adding machines, or Turing machines. They add very well, much faster than us. But that's all they are. Now, you may say to yourself, well can't robots play chess? Well, yeah, but that's all they can do. They're one trick ponies. We marvel at what robots can do so far, but we realize that they're just one trick ponies. They can play checkers, they can play chess, but that's about it. Or they can add faster than you. But that's about it. So we have a long way to go before robots can begin to replace humans.


But those are the three categories of jobs that are going to be wide open for humans.


Melissa:
[00:09:20] So would you agree that analytics professionals, if they develop their skills and things that you've mentioned such as identifying and connecting to their listeners' emotions, storytelling with data, and planning for the cadence of the absorption of change, do you think these are the kinds of skills that today's analysts will need in the future, or do you see that development differently?


Dr. Michio Kaku:
[00:09:42] Oh, no, those are the basics. And take any field, any field: energy medicine, teaching. It generates data and data has to be analyzed by artificial intelligence, by humans in order to extract usable information.


So this is going to be a constant for all of society, no matter what business you're in. As I mentioned, even things that at first you think there's no connection at all, there's a connection. For example, look at genomics. We're now beginning to understand the genes that control aging to a degree. In the future we'll have billions and billions of people's genomes analyzed on young people, old people. And we'll subtract. We'll find out where the damage takes place and we'll fix those damaged genes and we'll live forever. So the fountain of youth that drove human society for so many thousands of years is analytics. That's the fountain of youth. Think about that.

The earliest story ever told is the tale of Gilgamesh. The Bible is based on many of the stories found in the tale of Gilgamesh. What was Gilgamesh looking for? The fountain of youth. So this is one of the oldest searches in humanity, and analytics will point the way.


Melissa:
[00:11:07] Wow, that is inspiring. So would you say that in your opinion, that's the greatest contribution that we as analytics professionals could make to humanity?


Dr. Michio Kaku:
[00:11:19] I think across the board it's going to make life cheaper, more efficient, less bottlenecks, less aggravation. Basically the friction of life. Think of all the choke points, bottlenecks that you have, the frustrations, and we'll be able to digitize all of that. And analytics will tell us where these bottlenecks are and what is the best way to eliminate these bottlenecks.

So one of the contributions of this will be that life will be easier, life will be cheaper. You'll have infinite information at your fingertips, and that's because all this data was processed to make a seamless, frictionless, personalized society possible. Frictionless because we remove all the bottlenecks. Personalized - it'll be just for you, not generic. It will be digitized, and it'll be fun.


Melissa:
[00:12:16] That's amazing. So analytics could pave the way to an entirely new and better reality.


Dr. Michio Kaku:
[00:12:22] I call that perfect capitalism because capitalism has a lot of inefficiencies, bottlenecks, middlemen. That's why things cost so much. A lot of inconveniences, but that's what it's headed toward. It's headed towards cheaper products, infinite knowledge of what you're dealing with, and it means that we'll have a liberation of capitalism rather than a confining of capitalism.


Melissa:
[00:12:48] So it sounds like upside is almost unlimited, and analytics is an incredibly powerful force.

Now, I know that you've spoken out in the past about the pitfalls of the misuse of powerful things like science, nuclear weaponry, as an example. Now, for those of us who are exploring advanced analytics and data science, do you believe there are any moral imperatives that come with those studies?

In other words, with this great analytic power to shape the future, do you believe there's a concomitant great responsibility as well?


Dr. Michio Kaku:
[00:13:22] Yes. First of all, I disagree with some of my colleagues who say that science has no moral direction. That science is like a hammer. It can be used for you or against you, like a sword, a double edge sword. I don't quite agree with that. First of all, what does the internet do? The internet spreads information. And analytics allows you to understand, digest this information. And what does this information do? It empowers you. It educates you. It makes you aware of what's possible in other societies.


So people are saying, "gee, I don't want to live under this dictatorship. I don't want to live under this oppressive government." Because other countries, they don't have oppressive government, they have democracy. And that means that the internet spreads democracy and democracies do not war with other democracies.

I'm a scientist. Let's do an experiment. Write down every single war you had to learn since you were a child. Every single war, they've always been between kings, queens, emperors, and dictators. Never between two major democracies. Democracies do not war with other democracies, and so I think we'll always have wars in the future because of territorial disputes and things like that.


But in the future  it's going to be more democratic and more peaceful. When I was a child, we learned something called ‘dictator for life.’ If you were a puppet of the Soviet Union or the United States, you were dictator for life. Nobody could get rid of you because you had the United States and the Soviet Union backing you.


Today, we laugh. We laugh at the concept of dictator for life because of the fact that people are empowered. They can take their destiny in their hands now. They can organize, they can liberate themselves because of the internet. And what makes the internet possible is the fact that data can be analyzed through analytics.


Melissa:
[00:15:24] That is immense. So data and analytics is a channel to shaping the future and evolving additional, more powerful technologies is something that we all have to take seriously, whether or not we're professionals in the field, but especially if we are. So in your opinion, how might we ensure that emergent technologies like artificial intelligence, that I know you've weighed in on, how do we ensure that they're used for good and not for nefarious purposes?


Dr. Michio Kaku:
[00:15:53] Well, that's difficult because the internet magnifies human behavior. It doesn't change or alter human behavior - it just magnifies it. And there are criminals. And so it means that we have to be one step ahead of them, one step ahead of criminals, so we can protect privacy, we can make sure that people don't use the internet to hurt other people and to steal their money and things like that.


And also people wonder, well, one day will the machines take over? That is the ultimate fear. I don't think so anytime soon. Our most advanced robot today is ASIMO. You've seen him on television and ASIMO can walk upstairs, run, dance. He dances better than me. I've been on many science specials with ASIMO. So I interviewed for BBC television, the creator of ASIMO, and I asked him how smart is this so-called world's smartest robot? And he was very honest. He said that ASIMO has the intelligence of a bug. A bug! Even a bug is smarter than ASIMO. You put ASIMO in a forest and a bug in a forest. A bug runs around, finds food, finds mates, finds shelter, hides. You put ASIMO in the forest, and what does he do? Fall over, get lost.


But one day these robots will be as smart as a mouse. Then as smart as a rat. Then as smart as a rabbit. Finally, maybe by the end of the century as smart as a dog or a cat and maybe a monkey. Now at that point, they're potentially dangerous. Monkeys know they're monkeys. Monkeys have self-awareness. They know they're not human. Now dogs, dogs are confused. Dogs think that we are a dog. We're the top dog. They're the underdog. And so if you take a puppy and raise them from birth, they think you're a dog. They think you're the number one top dog. That's why they obey you. But monkeys know they are not human. So when robots become as smart as a monkey, perhaps late in this century, I think we should put a chip in their brain to shut them off if they have murderous thoughts - fail safe systems, because let's face it, it's possible.


Melissa:
[00:18:25] Let's face it. It is possible. Although he recognizes that analytics like most technologies can be a double edge sword. Dr Kaku clearly feels that the future for analytics is promising.


Data has grown to be the lifeblood of society, and analytics will need to point humanity in the right direction to solve the problems that affect all of us. There's huge opportunity ahead of us to leverage our ever-growing data corpus with advanced techniques, machine learning, artificial intelligence, robotics, virtual reality, and more. The tools of the future will afford analytics professionals the power to change the world. And we have to consider how we want to use that power. And that's why we can't wait to see what happens next.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).

Madeline Johannsen
Alter Everything Podcast Producer

Hey there! I'm Maddie, the Producer for our Alter Everything Podcast on our lovely Community team. I'm skilled and experienced at connecting people, and work to foster an encouraging analytics culture for learning and collaboration to help grow the Alteryx Community. Drop me a line to say hello and listen to Alter Everything on your favorite podcast app!

Hey there! I'm Maddie, the Producer for our Alter Everything Podcast on our lovely Community team. I'm skilled and experienced at connecting people, and work to foster an encouraging analytics culture for learning and collaboration to help grow the Alteryx Community. Drop me a line to say hello and listen to Alter Everything on your favorite podcast app!

Comments
ACE Emeritus
ACE Emeritus

Always loved Dr. Kaku, since reading some of his early books in the mid-90's or so.  I would argue with his stance of dismissing the double-edged sword of data, though. I'm not overly worried about super-smart robots at all: they are no more worrisome than nukes have already been for the last 70+ years.

 

But when a large agency or conglomerate can spread disinformation in sufficient volume to sway public opinion, I become concerned. The power of information is great, but so is the power of disinformation. Consider the climate change debate: we understand that most climate scientists believe this or that, but even they are starting to recognize their responsibility to argue more clearly:

And... on the up side, we're starting to see some reproducible research becoming available...

The real problem then is the claim that data is falsified. (just google: falsification of climate data, and see what turns up), which opens a whole new can of worms.  Seems there's always room to argue.  Anyway... don't mean to turn it into a climate change discussion, by any means: it just servers as a good and for-the-time-being relatively benign example of information at play on a global scale.  (More insidious examples include the world of politics and various counter-cultures; information warfare via memes, bots, etc...)

 

Great podcast - made me think. Thanks!