In the second episode of the interview series in which we welcome some of the keynote speakers of the Zukunft Personal in 2017 we spoke with Nell Watson. In a truly mind-opening conversation we touched upon human resource management, her experience in teaching in Brazil and many more. Nell is a super insightful, inspirational, imaginative and broadly-aware communicator whose talk you surely don’t want to miss at the conference.
You just got back from Brazil where you taught machine intelligence over the course of the summer. What do you think? What is your experience? Is there any difference in terms of how people (students) approach machine intelligence in comparison to European countries?
People in different countries may have different impressions of what machine intelligence can and should be used for. For example, amongst my students in Brazil we had people wanting to apply that they had experienced in their lives, or that they had become concerned about and really wanted to solve. These are things like creating computer vision techniques or heart monitoring and breathing monitoring that they would like to use on babies. Other examples, for instance, are when machine intelligence is used to spot smoke in forced fire so to be able to discern smoke from a campfire even though it isn’t necessary a forced fire yet, and to be able to send either drones or human beings to look at the location. Other aspects include using things like machine intelligence to classify vegetables into different classes based on their regularity, colours, size, shape etc. These are much more practical problems that can have a massive economic, health and social impact. I find this interesting that these are the cases that my Latin American students were seeking out, rather than some sort of Silicon valley tasked marketing or chatbot cases. These are real problems that need real solutions. My students managed prototype some really impressive and inspiring solutions to these kinds of problems based on machine intelligence.Machine Intelligence can solve real practical problems #machinelearning #KI Click To Tweet
I have recently listened to one of your presentations at a small event in Belgium. The talk was indeed mind-blowing and some of the slides you shared with us truly took away our breath. Where do you get your inspiration from? What drives you in putting together such inspiring speeches?
Thank you! I read actively, maybe 3 to 4 hours a day. I read all about the general space, a lot of it is machine intelligence, but also often about the wider space of things such as other aspects of cognitive science and that includes things like philosophy, linguistics or anthropology. But I also read about animal cognition and even plant cognition. Across all of these different domains there are a lot of really interesting correlations between things that may not appear obvious from the outside, but might seem counterintuitive in fact. This is why I keep a wide net for selecting a little bits of information, because often where domains finally meet for the first time there, there is a crossover and that’s where you get real innovation. Therefore, I am often looking for how something from history, or something from psychology, or even anthropology, or something you can learn from the animal world, for example the wonderful cognition of the octopus, can fit together. Because that informs us how we can better understand intelligence in general and how we can design better machine intelligence.
I also think a lot about how we can better understand intelligence in general, and how we can design better machine intelligence. I also think a lot about where society is today and where it has been in the past. I think about how history doesn’t repeat itself but it often rhyme. I think of history and think of society in terms of lots of ways that operate in different frequencies but sometimes they find an interesting harmonic in between them. Sometimes described as Kondratiev Waves. Difference of relations in between technology and fashion, and even governance or geology; they all come together and sometimes different ways crest at the same time and that can produce very interesting effects as well. These are the ways in which I think about the future. I also try to to break down problems into their very basic praxis and trying to figure out what is fact and what is an assumption, what everybody has come to believe as a fact, but is in fact not a fact. It may just be that everyone making the same assumption. And sometimes if you can spot where people have made assumptions and not actually looking to dig down and trying to find the truth, you can potentially revolutionize an industry, like for example Elon Musk has done with SpaceX.Machine replaced tasks cannot replace individuals #machinelearning Click To Tweet
Couple of years ago in one of your presentations you famously said that ‘Robots could murder us out of kindness’. The comment really got the attention of international media. Indeed, this can sound scary for some, but I believe that it is sometimes necessary to use such divisive scenarios to drive the attention of ordinary people to important changes. Technology changes by the wind. From a three years of time do you see this scenario (sentence) differently?
In a sense, what I said was twisted by the media. This often happens. (laughs) I guess, it is just something one has to live with. What I really said was; I was paraphrasing Arthur C. Clark’s famous saying about “Any sufficiently advanced technology is indistinguishable from magic”. And I said that it might be possible for ‘any sufficiently benevolent action being indistinguishable from malevolence’ to a culture that has not achieved the same level of moral development. So, I am confident that you might have a super moral intelligence that has effectively a more advanced set of morality than most human beings. And I also posited that even a very moral machine, or a very moral agent, have a right to defend itself and a machine might legitimately defend itself for being attacked by human beings that one could destroy or one could deactivate, and this could be another potential cause of tragedy simply because the machine is trying to defend itself. These are the points I was making and it was the last about machine going rough and killing us all. But, the media reframed what I have said, and of course, they had to include the terminator vs. human kind of staff. It is fine, these things can happen and at least there is a dialogue and people started paying attention to the space, which wasn’t the case 3-4 years ago. Obviously, in the academic world there are some very influential writers discussing these questions in a much more serious way. But I am glad when these kinds of ideas and conversations enter the public sphere, and hopefully they didn’t create too much alarmism, but at least the window of discourse for what is acceptable have been widened, and I think that in itself is broadly helpful.
Digitalisation is changing the world of work. To keep up with and lead this development the German government aims to become ‘the digital growth motor of Europe’. For this, it has launched several initiatives, among many the flagship Work 4.0. Programme is driving conversation and innovation in the social market economy. What is your opinion? What it takes for such programmes to succeed in the digital economy?
Recently, China has laid out plans to become the leader of AI by 2030. Of course, China is able to consolidate things, also, some of its actions, in ways that West cultures can not. I think China potentially has a lot of potential, because, it’s my understanding that they are trying to put together a whole bunch of datasets, so to create collaborative datasets on which people would work together and to pool lots of personal data in ways that people in the West would find little bit unsettling to do so. This may give them an advantage certainly. I am a little bit sceptical of many government initiatives, often the greatest driver of innovation is getting out of the way or making it easier for people to create new products and compete. I find lot of the initiatives well meaning, but I am a little bit sceptical as to how meaningful they can be in terms of actually advancing the space. I think it turns to more open datasets, for example like what we are creating at OpenEth.org and, I think, that might be a good way of accelerating machine intelligence development, which we have seen in the past in terms of how datasets made a huge difference. But as for simply setting an intention, or creating forums, I don’t know of that necessary gonna need too much progress, personally.
What do you think? How AI / Machine Learning impacts HR?
For all of human history, generally, all activities were done by hand, and human resources provided the complete resources of civilization. In the past 100 years we managed to bring new technology such as elecricization and, in the past 50 years or so, meaningful computing systems to our lives. These have all augmented our civilization with new capabilities, for example, for profiting, or for the use of power, that did not require the use of humans for animals. I find HR fascinating because it is a balance of multiple different disciplines. It consists many aspects from psychology to organizational science to economics, and it is all about trying to make the most of precious resources. I am fascinated by how machines can be in augmenting functions for human beings and not a replacement. Essentially, machine replaced tasks cannot replace individuals, what it means is that machine intelligence can help us to perform functions much more efficiently and to automate some of the least agreeable aspects of those jobs and tasks that are the most dangerous socially. And that is the perspective that I like to bring to the conversation. It is not about replacing people or putting people out of work. It’s about making work happier, safer, more meaningful and enabling people to live happier, healthier and more enjoyable lives. That’s why I really value being able to join this conversation on HR.#MachineIntelligence can help us to automate some of the least agreeable aspects of those jobs Click To Tweet
What can participants of the Zukunft Personal expect from you? What are you going to cover in your presentation, The Human Factors of Machine Intelligence, at the event?
Often human intelligence or AI discussions focus on just the technology, capability or statistics. For instance, it is often touted how AI is finally getting better in performing human tasks. But what does this mean for our daily lives, and what does this mean for our experience as humans, or our interactions within society. How is this meaningful for you or for I or for other people? How does machine intelligence relate directly to the lives we live, to the tasks we want to accomplish, or to the relationships we seek to improve? Machine intelligence can be used to help us to lead much better lives and to help us to streamline our lives and to mitigate some of the most unfortunate aspects on the human condition. Particularly, as to get into areas as persuasive technologies that can help us to lead better and healthier lives or to find options that we may not have considered before. Also, we need to pay attention to areas such as machine ethics and its emerging aspects of arts, philosophy and science, which helps us to teach machines about human values and to enable machines to act in ways that we would most prefer. Of course, if you can teach a machine about moral values than perhaps a machine can advise human beings on certain course of actions on which maybe more or less preferable, or may have a better end consequence. These technologies are going to change the shape of our civilization across the next generation in a profoundly positive way, I believe. This is the message of how we can unite machine and human intelligence for the betterment of both what I really wish to convey at the Zukunft Personal.#AI is about making work happier, safer and more meaningful Click To Tweet
About Nell Watson
Nell Watson is an entreprenerd, engineer, public speaker and future thinker who grew up in Northern Ireland. Nell has a longstanding interest in the philosophy of technology and how extensions of human capacity drive emerging social trends. Nell lectures globally on Machine Intelligence, AI philosophy, Human-Machine relations and the Future of Human Society, serving as Associate Faculty at Singularity University.
In 2010 Nell founded Poikos, a machine learning-driven AI for for body measurement. Nell patented technology dematerialises the 3D body scanner, by providing accurate 3D scans of the body with only 2D camera hardware, such as that found within smartphones, or laptops. This may then be applied to a range of markets, such as mass customisation, and health.
Possessing a long-term mindset, Nell serves as Senior Advisor to The Future Society at Harvard, as well as serving as an advisory technologist to several startups, accelerators, and venture capital funds. She is also Co-Founder of OpenEth, an ethical explication engine that aims to crowdsource ethical heuristics for autonomous systems.
As a keynote speaker Nell have presented for Ericsson, Credit Suisse, MIT and many, many others. She has taught and presented in India, Morocco, Chile, Brazil, the Nordics, the UK and cross America.
Tap into the fantastic expertise of Nell at this year’s Zukunft Personal. She is delivering her keynote presentation, The Human Factors of Machine Intelligence, on Wednesday, 20 September 2017, 10.00 – 11.15 a.m., on the Keynote Arena stage (Koelnmesse).