Christoph Schommer, associate professor of Artificial Intelligence at the University of Luxembourg since 2003, began working on artificial intelligence concepts in the early 1990s. So he’s had plenty of time to study the subject. The technology that everyone is talking about today was at the heart of the research projects he accompanied as a student at the DFKI in Saarbrücken. He then joined IBM, a pioneer in the fields of business intelligence and data exploitation and enhancement, gradually broadening his field of expertise.

New perspectives

At the University of Luxembourg, Schommer supervises several interdisciplinary groups working on various AI-related applications. “In the medical field, for example, one of the projects involves an innovative medical dispenser. In another, we are working on analysing the watch and voice data of Parkinson’s and Alzheimer’s patients, with a view to detecting the early signs of these diseases,” he explains. The teams are also exploring the role of equity in AI, chatbots as stimulators of human-to-human conversations, and AI in storytelling and learning. “We are working on knowledge transmission using generative AI. The technology can be used, for example, to retrace events or draw up descriptions based on documents from the First World War. The aim is to make history accessible to a wide audience,” explains the professor.

Putting expectations into perspective

In recent months, AI has been the talk of the town, arousing both enthusiasm and fears. It has to be said that this technology is already having an impact on the day-to-day work of many people, changing the way we interact with information and affecting our productivity.

Its promoters are everywhere announcing that the technology will enable us to be more efficient. For Schommer, however, there is reason to temper any over-enthusiasm. “AI is already enriching our daily lives as a tool for collaboration. It offers new opportunities for entrepreneurship. But we will also have to face new challenges, linked to forecasting or data errors or problems of security and fairness,” he explains. In view of the technology introduction curve theorised by Gartner, we need to be prepared to go through the “peak of inflated expectations,” the moment preceding the trough of disillusionment, as has already happened in the past.

A new collaboration between man and machine

This in no way detracts from the disruptive potential of AI, which is set to reshape our relationship with technology. “In particular, it introduces a hybrid form of working, where humans and machines collaborate closely,” explains the expert. “It’s not a question of substitution, but of collaboration. We need to learn to work with these systems, taking advantage of the possibilities they offer and making sure we understand their limitations.”

Faced with these expected transformations, the professor points to the challenges associated with its adoption by different generations, who do not have the same relationship with technology. The deployment of this technology, given its potential, raises legitimate questions. Companies, at the very least, need to ensure responsible integration. “One of the main risks lies in relying on the results provided by AI without questioning them,” warns Schommer. “There is also cause for concern about the risk associated with excessive standardisation of thinking and a reduction in critical thinking.”

Rethinking learning and training

In education, AI offers prospects for individualised learning, but also raises fundamental questions. “For example, we must ensure that AI does not call into question the integrity of the teacher. If a system contradicts a teacher on a historical fact, how will students trust the knowledge they are being taught?”

Integrating AI into education means rethinking the way we teach. “The emphasis must be placed on critical thinking and the co-responsibility of pupils,” argues Schommer. He imagines a hybrid approach in which AI would coexist with teachers without ever replacing them. AI could, for example, help to generate exam questions or adapt individual learning to each pupil. It allows us to enter the era of “personalised learning.” Education must also prepare individuals to verify the information and knowledge they receive. “We must always ask ourselves: is this true? Has it been checked? This is essential to avoid misinformation,” he explains.

A catalyst for creativity

AI presents us with major challenges, but it also offers enormous opportunities. The real challenge is to succeed in using it to sublimate our human capacities. If used properly, it can enhance creativity. “AI can stimulate our imagination, allowing us to explore new ideas and take new paths. In art, it can suggest colours or styles that the artist might not have considered. In medicine, it can help develop new drugs. In the fight against crime, it can help you characterise blackmail letters,” illustrates Schommer.

It is through our approach, our human intention, that humans create and invent. AI, on the other hand, enables people to explore new avenues. The way in which the technology is used, what we build from the capabilities it offers, ultimately belongs to the user. “AI is creative, up to a point,” stresses professor Schommer, before referring to an experience he had in connection with a police investigation. “We used AI to reconstruct the scene of a crime on the basis of the factual elements available to us. Through what it comes up with, the AI demonstrates its creativity. It will suggest an atmosphere, taking into account, for example, the time of day when the crime took place, or the layout of the objects found. But in the process, it can also make mistakes. Verification and interpretation remain crucial,” he explains.

Gradual, measured adoption

Faced with these upheavals, how should companies approach AI? Professor Schommer recommends a gradual approach. “The mistake would be to want to change everything at once. We need a gradual introduction that allows employees to accept, learn and adapt,” he explains. He sums up his approach with a maxim he learned when he worked at IBM: Think big, start small. “You have to have an ambitious vision, but move forward cautiously,” he says. “There should be no rush, but no standstill either. Each company needs to find its own pace of adoption.”

AI is a revolution in the making, and for the professor at the University of Luxembourg, the real challenge is to make it a tool at the service of human beings, always bearing in mind that it is up to us to understand it, to question it and to steer it in the right direction.

This article was originally published in .