I was invited this Monday to participate in a Sorbonne Université event, part of the “Les Lundis de la Sorbonne” discussion series. The main theme of the day was about the potential impacts of AI on the job market, aimed at an audience of career guidance professionals. The central point of the event was the presentation by Salima Benhamou, economist at France Stratégie, of her recently released report, “Intelligence artificielle et travail”.
The report focused on three sectors (healthcare, transportation, retail banking) and interviewed researchers, startup founders and union leaders in several countries to get a better grasp on the potential impact of the deployment of AI technologies in the workplace.
What made this study different, is that they worked at a more granular level than previous ones. Instead of trying to come up with a number quantifying the overall risk of automation for a job as a whole, they acknowledged the multifaceted nature of today’s professions and reasoned on the tasks making up the job. The result is a more nuanced and realistic perspective on the changes to come; all jobs have, to a different degree, some kind of repetitive and mind-numbing tasks that, if automated away, could allow workers to focus on those generating more business or social value. This is especially true for healthcare professionals. However, perhaps unexpectedly, an identified risk of this scenario could be a potential cognitive overload for workers.
The main takeaway of the report is that wide deployment of this kind of technology would impact a large share of the workforce, deeply transforming jobs. However, it is difficult to quantify the phenomenon since AI is still only in early stages of widespread adoption.. As it matures, a likely consequence would be a widespread need for continuous training.
In this context, two AI and robotics master programs were introduced by Professor Mohamed Nadif and Professor Philippe Gaussier. With a heavy focus on Maths and Computer Science, they promise to kickstart students’ careers by preparing them to work on challenging and thrilling problems. They can also boast excellent hiring stats for fresh graduates.
However, the scientific track is definitely not for everyone. And it was nice to listen to Benjamin Gans, director of EdFab, an education and innovation hub, who presented their offering of multi day training and short acculturation sessions on a wide range of new technologies (AI, big data, chatbots, VR, digital manufacturing…), aimed at non-technical employees.
Pitched by some as the “hottest job of the century”, the Data Scientist job is at the heart of the promises and hopes, but also the fantaisies and exaggerations brought on by the AI revolution. Despite their ubiquitous presence in the specialized and not-so-specialized medias, Data Scientists can be quite elusive in the real world. And I’m not sure that guidance counsellors, confronted to questions by high school or university students, run into data scientists that they can interview everyday. So I was happy to be offered a chance to share my experience and give a (hopefully) down-to-the-earth view on my training, responsibilities, and day-to-day job.
The event ended with Juliette Mattioli giving a historical perspective on the use of AI technologies at Thales from her experience as Senior Expert. I strongly agreed with her insistence on the crucial need of humanities and soft skills (particularly communication and ethics) for professionals in the AI domain. The large gender imbalance, although things seem to be improving (particularly in NLP), is also deeply disappointing.
The event was perfectly organized by Véronique Renault-Fusco and Lydie Offner-Coutant, psychologists at the Ministry of National Education, in the beautiful Liard Amphitheater in the historical buildings of the Sorbonne University. My only criticism is that, with this many interesting interventions, the program was perhaps a little ambitious for the allocated time, allowing for too few questions and interaction with the audience.
In conclusion, there is a strong will to anticipate consequences and defuse concerns from the general public over the question of AI and labor. The offering of training programs is already rich and it is expanding to non-technical tracks. It is great that such events take place to make them more visible. I’m convinced that the Data Scientist job has still a lot to bring to the business world and the public sector alike. But it is only a small part of the revolution taking place — one that will, hopefully, change the nature of work for the better.