This is FiveMinuteFriday, the History of Data Science, Part 5.
Welcome back to the SuperDataScience Podcast everybody. Super excited to have you back here on the show. In today’s episode we’re going to wrap up the history of data science. And if you remember from the previous four episodes of this mini-series, we’ve already spoken about the history of data science before the year 2000, then between 2000 to 2010, 2010 to 2015, and 2015 to 2020. So we’ve covered up all of the history of data science. Technically, what is left to talk about?
Well, today we’re going to talk about the future of data science. The future of this industry. In fact, the whole world that we’re moving into because data is becoming more and more ubiquitous. And what are we going to do is… It’s of course hard to talk about the future because it hasn’t happened yet. There’s an interesting interpretation of that, that we cannot remember the future because entropy never decreases. Our universe is just such that entropy either stays the same in a closed system or continuously grows and that is the reason, or that asymmetrical feature of entropy is the reason behind why we can’t remember the future. There’s a really cool movie about this called Mr. Nobody with Jared Leto, highly recommend checking it out if you haven’t.
Anyway, we can’t talk about the future cause we can’t remember it, but we can hypothesize and make some predictions about the future. And what are we going to do for this episode is we’re going to look at the predictions by some or specifically five of the most influential people in the space of artificial intelligence, technology and data science, and see what they have to say. Let’s have a quick look at that.
The first person we’re going to talk about is a famous futurist named Ray Kurzweil. If you haven’t heard of Ray Kurzweil, there’s a quick sidestep into the background of Ray Kurzweil’s array. Kurzweil, he was an inventor, futurist. He actually invented the first synthesizer that accurately replicates real musical instruments. So his was the first synthesizer where real piano experts couldn’t detect the difference between a sound played on a synthesizer and a sound played on a real piano. In addition to that, he makes a lot of interesting predictions about the future. Back in around 1999 and 2000, he predicted… In his whole life, in his old career as a futurist, he’s made about 108 predictions and 89 of them have come true and that is about 82% accuracy rate. And he’s predicted things. This is back in the 2000. Early like 1999 to 2000, he predicted things that like the cloud, cloud computing, cloud storage, Google Glass, portable computers, wireless internet, Fitbits and other embedded computers. And many more things that we use today, he’s been able to predict. So definitely he’s got a lot of credibility around this space.
What Ray believes, is that he believes that by 2029, we will have developed artificial intelligence as smart as humans. That’s nine years away from now. And that prediction based on his track record, has an 82% accuracy. You can say that with about 80% accuracy, we can believe that by 2029 AI will be as smart as humans. Quite a long shot, but let’s see how we go. Such as the nature of exponential technologies, it’s really hard for humans to predict with our linear thinking into the future, you really need to like apply different prediction methods. And this is one of the results that Ray is looking towards. 2029 is when we will have AI as smart as humans.
And from there the rate of technological progress will accelerate even further and AI will continue improving itself. That means that we’ll get to technological singularity or it’s also described as the moment when the rate of scientific progress will be so fast that it appears instantaneous to humans. Some people say we will have Nobel Prize level discoveries happening every second. Not even every day, every second. Though according to Ray, that’ll happen somewhere around the year 2045. That’s the outlook from Ray Kurzweil. Let’s look at another person now.
Bill Gates, everybody knows Bill Gates, Founder of Microsoft, a huge philanthropist. Well, he believes that AI will create huge leaps in productivity and he’s very optimistic about what are the consequences of artificial intelligence progressing so fast. Well, he’s saying that people who will be displaced from the current roles will be able to fill other very important roles in society such as elder care, teaching, support for those with special needs. Overall, his view is that a rise in productivity brings a rise in prosperity for everybody. Because we will need to work less, we can spend more time learning and developing and bringing further opportunities and continuing the cycle of growth.
On the other hand, we’ve got another influential person in this space, Yuval Noah Harari. You may know him from his book Sapiens, or his second book, Homo Deus, and now he’s got a third book, which I highly recommend reading. Mitja and I, when we were traveling to Yosemite we listen to it in the car. It’s got a great audio book version. It’s called 21 Lessons for the 21st Century. And he actually has a less optimistic view. He warns that re-educating people into new fields isn’t as easy as it’s sometimes made out to be. For instance, a customer service agent can probably be retrained to program customer support AI, but what about the millions of manual laborers in underdeveloped nations? Will a rapid automation of almost every imaginable job turn all or at least a large majority of us into a useless, jobless, aimless, and ultimately powerless mob?
If machines can do everything better than humans, what is the point of working? Is there a point of working at all? And if the power to control all these powerful machines is concentrated in a small group of people, won’t those people become dictators against whom a new revolution is virtually impossible.
In his book, he actually talks a lot… Not a lot, but he warns about the danger of dictators states that now with technology they’re able to process all the data and we could be heading or in some place in the world, a dystopian future like what was portrayed by George Orwell in 1984, can actually be now possible, something that could actually happen. So there you have two different opinions on this. One from Bill Gates, one from Yuval Noah Harari.
And here’s another one from Dr. Ben Goertzel. I listened to a podcast or Hadelin and I actually listened to a podcast with him almost a year ago. Fantastic podcast, highly recommend. He was on the London Real Show. Dr. Ben Goertzel, he’s the Founder and CEO of SingularityNET and Chief Science Advisor for Hanson Robotics. Dr. Ben Goertzel actually refuses to take sides on this discussion.
He argues that the future after the technological singularity is a period of irreducible uncertainty. When superintelligence is free to grow, change and develop, it will surpass our ability to comprehend it. Like we cannot predict what will happen in the age of superintelligence or super artificial intelligence or general artificial intelligence. If it’s something that surpasses us in intelligence, we cannot predict how it will behave or what it will do and what the future will look like. So whatever we try, whatever predictions we try to make… I love this phrase, is an irreducible uncertainty around what will happen. With our level of intellect, with our level of understanding of the world, there’s just no way we can reduce that uncertainty. So we just have to wait and see.
On the other hand, there’s no way of stopping technological progress if one country bans it, or even if a group of country ban technological progress, the rest of the countries are going to go ahead. So it’s just not going to happen. So we just have to wait and see and there’s no point in making predictions because there’s that uncertainty that’s irreducible.
And also Dr. Ben Goertzel believes that AI is dangerous, but he emphasizes the point that the value system or mind-state of the initial superintelligence will be influenced by the values of earlier AI and in essence the values that we are putting into artificial intelligence. He talks that right now what are the most important purposes that we use artificial intelligence for? They’re selling, gambling, spying and killing. That’s pretty much all we’re using artificial intelligence. Selling in terms of marketing, AB testing, putting ads in places. Gambling it’s used on exchanges on the stock exchange, on the foreign exchange. It’s used to make profits. Spying, surveillance systems. Killing with drones and robotics and so on. So that’s all we’re using artificial intelligence for. And if we give that example to a general AI that we create, that’s exactly what it’s going to learn. That’s exactly what is going to focus on, it’s going to do. It’ll see that those are our morals and if our morals are low, then AI will have low morals.
What he would like to see, he would like to see a shift in the world towards more worthy causes like education, childcare, scientific research and government support. And hopefully, such renewed focus on developing a more moral and ethical artificial intelligence will smooth the transition period and lead superintelligence towards being a benevolent force that works in cooperation with humanity, not against humanity. And the promises of such an AI are actually incredible. Rapid development in all aspects and life without pain or scarcity where humans can either connect into our global mind matrix or remain individual, each according to their own desire.
That is a future where basically Ben is saying, “Don’t try to look into the future and predict will happen. Focus on now and use AI data science for benevolent things now in order for the artificial intelligence that’s coming to learn good from us, for us to show it that we’re leading by example.”
And so what role does data science play in all of this? Well, a few days ago I interviewed DJ Patil who is the person behind the term data scientist, coined the term data scientist and who has had massive influence on the industry. By the way, this podcast will come out live in three weeks, so highly recommend checking out. I was very inspired talking to DJ.
One thing that he mentioned is that it would be ashamed to have a data science career that just benefits the data scientists themselves. Like if you’re doing data science for the purpose of having a massive salary or for just progressing in the career ladder and not even considering the impact it has on the world, that would be a shame, that would be a waste of a career. So he says, really consider what you’re doing data science for. Don’t waste your time. Don’t waste your time just on selfish reasons, but think of what impact can you have, what impact does your work have, what’s cause are you supporting? What are the ethics behind this?
We even went into talking about topics such as what are the questions you should ask when you come to an interview. One of the things you should bring up is how ethical is your organization? How do you make sure that data science is used in an ethical manner? What kind of safe guard mechanisms does your organization have to prevent any bias or racism or exclusions in the space of data science? How do you make sure that it is an ethical application of these technologies? And so it’s up to us as data scientists to make sure we’re not using data science just for selling, gambling, spy and killing, but we’re actually using it to build a better world and that we are leading by example. And if we do create general artificial intelligence, we will see that technology is generally used for benevolent reasons for good of humanity, good of the world. And that’s the best we can do at this stage.
There you go. That’s five opinions on the future of data science, on the future of the world of technology, of artificial intelligence. Pick your best influencer, pick whom you agree with the most. We talked about Ray Kurzweil, Bill Gates, Yuval Noah Harari, Dr. Ben Goertzel, and of course, Dr. DJ Patil as well.
There you go. Hope you enjoyed this episode and enjoyed our mini-series on the history of data science, and now the future of data science as well. Look out for that episode of DJ Patil. I think it’s going to be a blast. You’re going to love it. I guess as a summary is, make sure that you know what you’re doing data science for. What is the impact and what are the ethical considerations behind the things that you are creating, the technologies that you’re empowering. And on that note, I look forward to seeing you back here next time. Until then, happy analyzing.
