Last December I was honored to deliver a commencement address at the University of Queensland. I spoke about AI, jobs, our futures and education. Here is a video and a transcript. I covered a bunch of key points in this brief address, and I hope to elaborate on these points in a longer post soon.
Honorable Chancellor, honorable Vice Chancellor, distinguished leaders of this great university, the graduates and the guests, it’s a great honor for me to be here today and thank you so much for this amazing recognition, for which I’m deeply grateful.
It is a big day for all of you, for the graduates a culmination of a long journey of education that many of you have been on. But is it a culmination?
As I think about our future, and your future, and the times ahead I would like to make three points -about AI, about jobs and your learning abilities and I hope you will find these useful.
My first point is that we are living in, we certainly are entering, the times of AI and the jobs that you will go through over the course of your lifetime, will go through a radical change. Earlier today, today’s New York times, it’s still the 14th in the US, had an article about the great AI awakening and also today in the New Yorker magazine there was an article about our automated future and it is just today just two of their publications. There is no doubt when we look around that the AI technologies will have a profound impact on the jobs that we see around us today. Increasingly we have to assume that the jobs that can be precisely articulated and specified, are going to be automated. Much has been written about this. I will not belabor this point but we all have heard about jobs from truck drivers, to retail store owners, medical diagnosis to legal research and in my own world of IT services, various forms of system administration, business process operation and even operation and maintenance of complex systems are going to be automated. And yet we have to live and we have to thrive in these times. So the question is, can we?
My second point is that, yes we can. Of course we must, but also that we can. We are still in the early stages of these technologies and the pervasive role that they will ultimately play in our lives. Recently we have seen, no doubt, some remarkable successes, some remarkable applications and some amazing achievements of these AI technologies and AI systems. But when I think about this and when I look at the state of the art, I realize that we are still quite far from the Society of Mind that Marvin Minsky wrote about in mid 1980s. We are still quite far from thinking about enabling a great symbiosis between intelligent systems and people. We are still quite far from being able to imbibe and impart our contexts into the contexts of our systems and vice versa. Being able to achieve shared perspective with ourselves and using technology to enable that, and being able to achieve shared perspectives with machines, is still quite a way into our future.
Also when we think about the role of technology in creating jobs we have to realize that as technology takes away jobs, the creation and the enabling and scaling of that technology ends up creating more new kinds of jobs. People say that it is different this time around with AI because this is about our minds and not just about our bodies. But nonetheless, the reality is that every technology that will displace the jobs of today, is going to be followed by the enabling and the construction of those kinds of technologies. So, despite being early in these times the second key question becomes how do we thrive in these times, what are we and especially what are you as young graduates to make of this?
My third and final point is that I see only one way for us to thrive in these times and that way is learning, “EDUCATION”. We have to learn to build these systems. We have to understand and learn to construct these systems of our future. Even if a system can drive a truck, a human still has to buy that software and build that system and that system is written by us. We need to understand computing and artificial intelligence as fundamental enabling technologies and scale the education of these. Given that every walk of life around us is going to be transformed by computing, we are still quite in the early days of this and we have to think about enabling and equipping ourselves with these technologies.
My wife Vandana runs our Infosys foundation in United States, and she recently made this great observation that in the dark ages 6% of the world’s population could read and write and if you are to think about the computing and AI as the new forms of literacy, today less than half a percent of the world’s population can understand and program what you do implying therefore that we are still in the dark ages when it comes to computing and the ability to build the systems. And even when we look at the further out future, at a time when we are able to build systems that can take precise specifications and do those jobs, no matter what those jobs might be, in other words, systems that become perfect and problem solving, those problems that can be precisely defined, we still have the human frontier of problem finding. Of being able to look into great unknown and identifying and articulating problems that are yet to be solved. That problem finding, that act of creativity, that act of innovation is still in our frontier is, still ahead of us.
Techniques like design thinking which the University of Queensland has been working on are quite fundamental to that future. We still live in times where innovation is seen as something mystical, something that is done by a chosen few who somehow are born with the ability to innovate but when we look around us we realize that innovation is no more than the act of seeing something that is not there. Seeing something that is yet to be invented, that if it were to be invented, that would lead to the world that is more desirable, that is more feasible, that is more viable, a world that would be better.
So when I think about these times of AI, it seems that our destiny is quite straight forward. We all have to become ignorant, and why not. Nonetheless, whether it is to build these systems to be relevant in the times of these systems or to be able to become innovators, the key is ‘learning’. We can no longer believe that going to school that all of you have done for the first 17 or 20 or 25 years of our lives and then stopping going to school, is the way of life. We have to think about learning for life, for our entire lives. We have to learn all of this, but most importantly, we have to learn to learn itself. We have to ask ourselves what is the world that we are living in, what is it that makes it what it is and how might I create the future of this world, a great future of this world.
Alan Kay, a great teacher of my life, famously said that, “the best way to predict the future is to invent it”. I believe that the invention of our future is what is in our future. In the age of AI, we have to switch our context from making a living to making a life, a life that may be artificial OR more importantly a life that may be ours. That in building the AI’s of our future we end up amplifying ourselves, we end up improving our own humanity.
I wish you all the very best in these times ahead, for you and for all of us. Thank you!