women-scientists-from-france

"Do they show science or wit? If their works are bad, they are jeered at; if they are good, they are taken from them, and they are left only with ridicule for letting themselves be called authors."

"Do they display science or pretty wit? If their works are bad, they get a bird; if they are good, one robbed them; they keep merely the ridiculousness of having presented themselves as the authoresses."

"Yes, my point of view is utilitarian and functional. Robots have a lot to offer us. When I see the percentage of the population that will be elderly in the next few years, it’s clear that we won’t have enough working people to look after them. So it could be interesting to have a robot in charge of monitoring these people when they are at the end of their lives for example. So robots are useful but we have to be aware that they should complement humans and not replace humans."

"The goal is not to replace the human. The machine is, for the moment, incapable of this. Our robots are not very precise yet. We are making more cognitive advances than physical ones. Mechatronics are going to need a lot more research. Making entirely humanoid robots remains complicated."

"We first need a certain set of ethics for designers, which is why researchers are in the loop. Then we need to give people the ability to understand the system they’re using. I’m part of a nudging project that aims to explain gently to people. We’ll also need to teach robotics at school so children can have perspective when it comes to questions of artificial intelligence and robotics. And then we’ll need legal rules. In the same way that there’s a committee who decides whether a medicinal product is put on the market or not, we’ll need an ethical committee who validates a robot or not before its market launch. But not everything should be constrained by ethical reasoning. We can do business that’s ethical and responsible. When I say ethics, I’m not talking about philosophy. I’m talking about making machines that respect our values. We have to ask ourselves how these new robots harbor a danger for humans and accordingly how we can regulate it."

"We understand ethics when it comes to data, this is why we need the new GDPR regulations. But when it comes to co-evolution with machines we aren’t talking about what changes it will lead to in terms of inter-human relations. Psychiatrists are interested in this question but the world of technology isn’t yet. Certain manufacturers I work with such as Softbank Robotics [who make the robots Pepper and Nao] are starting to understand the idea of ethics. But we still need to find a compromise between ethics and business. We need to agree together on a system of human values that will be respected by the robots who interact with us."

"Each country has its own values and robots should comply with the values of the country they are in, kind of like labor laws."

"Yes, I think that this is where Europe and also the United States can make a difference. Maybe the price will be the main argument for someone buying a robot. But maybe there will also be an ethical aspect that will influence their choice of one robot over another. For this we need to make ethics “fashionable”."

"Firstly, it is unconscionable to want to try to reproduce a human as we can easily deceive and manipulate. Here I am targeting for example Google Home and Sophia. Next we must be careful with attachment and empathy. If we live with machines all the time, there will be consequences on our relationships with others. Then there will be a division between those who have access to this technology and understand it and those who don’t. We are widening the gap of technological inequality, and long-term it’s anti-democratic."

"I suggest a COP [conference of parties] be held on artificial intelligence. It is urgent that we take an interest in the repercussions of what we’re doing. It’s our responsibility!"

"All of my work focuses on the idea that we need to keep a boundary between humans and robots. But Google is blurring the lines with this voice. It opens the door to unethical applications. The voice is what’s easiest to imitate for the moment, from a technological standpoint. It’s possible to trick the person who doesn’t know who they’re communicating with. You can make someone say things they never said. You can even make the dead speak. It’s a breach of trust."

"As soon as we hear a machine speak, it’s implied that the machine understands. That it has the capacity of a human. Which is not the case. For example Sophia from Hanson Robotics speaks in a way that is semantically coherent but she is following a script, she’s absolutely not autonomous, she has no desires or intentions. She’s a marionette. Engineers have given her a scripted dialog. Machine learning allows for learning from data, but without understanding. This machine has nothing to do yet with a living embryo."

"That is I think the case indeed for a lot of technologies. Technologies go faster than..."

"Yes, and I think in, you know, I’m a microbiologist and I have always been interested in infectious diseases and my field of research is not really well recognised at the fundamental level, and so it’s good to see that there is still a lot to be … to learn."

"One of the first pieces of advice I got as I was starting my Ph.D. was from Tristan Rivière (a previous student of my adviser, Fabrice Béthuel), who told me: People think that research in math is about these big ideas, but no, you really have to start from simple, stupid computations — start again like a student and redo everything yourself. I found that this is so true. A lot of good research actually starts from very simple things, elementary facts, basic bricks, from which you can build a big cathedral. Progress in math comes from understanding the model case, the simplest instance in which you encounter the problem. And often it is an easy computation; it’s just that no one had thought of looking at it this way."

"It’s the same kind of pleasure as with hiking: You hike uphill and it’s tough and you sweat, and at the end of the day the reward is the beautiful view. Solving a math problem is a bit like that, but you don’t always know where the path is and how far you are from the top. You have to be able to accept frustration, failure, your own limitations."

"...If you have enough ability, then you cultivate it and build on it, just as a musician plays scales and practices to get to a top level."

"I tell myself that there are always very bright people who have thought about these problems and made very beautiful and elaborate theories, and certainly I cannot always compete on that end. But let me try to rethink the problem almost from scratch with my own little basic understanding and knowledge and see where I go. Of course, I have built enough experience and intuition that I sort of pretend to be naive. In the end, I think a lot of mathematicians proceed this way, but maybe they don’t want to admit it, because they don’t want to appear simple-minded. There is a lot of ego in this profession, let’s be honest."

"In the labs, the young make things move, and the older ones follow like parents evolving with their children."