When we talk about artificial intelligence (AI), we very often speak and write in the future tense. How many robots will be added? How will we integrate AI? What will that mean for employment? While trying to figure that out, we sometimes forget that AI and robotisation are already a daily reality. In its study 'The Future of Work – Work of the Future', the European Commission points out that companies worldwide will spend 188 billion dollars on robots in 2020. Specifically for AI, spending will reach 59 billion dollars by 2025. The reason is clear: these are investments that will lead to higher output growth, which is desperately needed in times of an ageing population.
However, the breakthrough of AI and robotisation also brings new challenges. One of the most pertinent questions is how people should deal with the arrival of the robot. We see macro-tinted questions emerging: does it threaten jobs and will our labour market fundamentally shift? But at the same time, it is a practical question: how can man and machine best work together? We spoke to the international authority and fellow Belgian to get the answer to that question. Pattie Maes is affiliated with the prestigious Massachusetts Institute of Technology. She is head of the 'Fluid Interfaces Group', a research cell at MIT Media Lab that investigates new ways for people to interact with digital machines. “The way that's happening right now isn't the best,” she says.
“You usually have a screen and a keyboard and you have to look at that screen all the time to get something done. That's totally inefficient, you don't pay attention to your environment, other people, or the context in which you work.”
The arrival of the smartphone has made that problem even more acute. According to Maes, “About a third of the world's population has a smartphone right now.” “And just about all the research shows that this smartphone has a negative impact on people's performance, their memory, and their creativity. The explanation for this is simple: anyone with a smartphone will assume that it'll do the work for them. What's more: if we let people run tests, the results will be negatively affected if a smartphone is lying on the table unused. Even then, we're unconsciously distracted by what's happening on Facebook and Instagram.”
three defining trends
Maes and her Fluid Interfaces Group team are looking for new ways to solve that problem and make people work better with machines. Maes believes that there are three technological trends that will improve this man-machine relationship in the future. “The first is the emergence of sensors. Smartphones are blind today, they don't know where you are, who you're there with, who you're talking to, or how you feel. However, machines will be able to find out using more sensors. The second technology is artificial intelligence, which will enable machines to respond much more intelligently to what is happening and also help you much better. Recognising things on a photo or translating texts in real time, for example. It's possible now, but we're only at the beginning of that revolution. The third novelty is the emergence of new display technology that will replace traditional displays. This includes things like VR goggles and augmented reality helmets. They will be equipped with microphones, sensors, and speakers which will make the interaction much more natural.”
with Einstein in the workplace
Maes gives several examples from her lab to show how these kinds of technologies can also prove their usefulness in the workplace.
“Attention issues can be remedied, for example, with glasses that detect eye movements and measure brain activity. Every time the subject's attention drops below a certain level, he or she is made aware of this. We see that test subjects with such glasses score a lot higher in tests than those who have to take the test without them. Augmented Reality (AR) also makes it easier to learn things. Experiments show that it is much easier to learn a language by walking around in a virtual game and seeing a translation of all the objects you see. Those applications are endless: you can also use the glasses to repair a machine, step by step, for example.”
Maes's team has also designed a platform that can solve motivation problems by providing virtual mentors.
“The system reads all possible online interviews and texts from specialists and makes that knowledge available to the test subject. Suppose you have to solve a physics problem and Einstein is your mentor and you can ask him questions in real time: that's fantastic!”
In the field of 'smart wearables', Maes focuses on smart clothing, among other things. “Suppose you could build sensors into jackets and shoes that measure your heart rate and your breathing and also monitor your surroundings. If, for example, an odourless gas was detected, you could be notified immediately. Or you could use sensors in your shoes to determine whether the weight you are carrying is not too heavy and therefore cause you back pain. The possibilities are endless.”
impact of technology on your business model
The changes that Pattie Maes outlines, together with figures on the growth of AI and robotisation, make it clear that these technologies have and will have an impact on the business model of many companies. Even those who do not apply the technology today will have to find out as soon as possible what AI or robotisation will bring to their sector. Employees, for their part, must be aware of the emergence of new jobs and of possible shifts. This is also evident from the European Commission's figures. This means that between 14% and 47% of jobs are under pressure from automation, but at the same time, digitisation has created as many as two million new jobs in the EU over the last decade. The Commission expects an additional 1.75 million jobs in IT alone over the next ten years. How smoothly we glide through this technological shift will largely depend on how people deal with the new technology. In the practical sense, as the examples of Pattie Maes indicate, but also in the ethical sense of the word. Many of the discussions in Maes's lab are about ethical issues, she confides in us, in conclusion. “Of course, the collected data is only stored locally and not passed on,” she says.
“But we also design our inventions with specific target groups in mind and we don't want to force users to use them. Freedom of choice is paramount. In this way, we also want to use the machines to train users and make them better, not to make them dependent on them.”