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Hybridization

aivancity
 

The need for a total hybridization model between Artificial Intelligence, Business and Management

Artificial intelligence dates back to the 1950s, but today it is experiencing such a boom that machines are now capable of outperforming humans in some areas.

Artificial intelligence can legitimately replace humans in the accomplishment of tedious and time-consuming tasks, allowing them to pursue more rewarding activities. The challenge of AI is therefore to train the young and old to these new challenges.

Beyond its technical challenges (Web Crawling, Data Mining, Data Science, Machine Learning, Deep learning, etc.), hybridization between AI and management is a necessity to face the major technological changes, the challenges of scientific evolution and the societal constraints that will shape tomorrow's world. A total integration of content, pedagogy, research in AI and social sciences thus enables the emergence of a new model capable of facing the major scientific, industrial and societal challenges.

Our school project does not seek to compete with engineering schools or business schools, both secular and recognized in France, but to invest in the field that lies between these two pillars of excellence, successfully demonstrated in some world-class institutions such as Stanford University or the Ecole Polytechnique Fédérale de Lausanne (EPFL).

“The teaching [of AI ethics] is almost absent from engineering school curricula or university computer science courses, even though the volume and complexity of the ethical issues that these future graduates will be confronted with is constantly growing”.

Villani Report, 2018

An Artificial Intelligence based on trust and accountability

In AI, the issue of trust is obviously essential. When one takes a drug without knowing its chemical formula, one trusts the manufacturer about the effect of the drug to treat their condition. In the same way, we trust the recommendation algorithms: the first results of a search engine, Netflix proposals to watch a movie or Amazon to buy a product, the route suggested by your GPS...
But what are the reasons and objectives behind these recommendations? Are they “customer-oriented” recommendations, to satisfy the customer, or “service-oriented”, to meet the needs of the company only (liquidation of a stock, valuation of a product, etc.)? And what are the optimization functions? A video search engine on the Internet can be optimized according to the time spent by the user in front of the screen. This leads the AI to offer more and more addictive content (violence, rumors, fake news...).

It is therefore essential to integrate these issues related to ethics, in the broadest sense, in AI training programs: from matters of the sociology of work (click workers), to data issues (RGPD), to questions of algorithm robustness, their explicability, their biases, but also "customer relations", governance issues (social credit ...), and philosophy (free will, will ...).

Aivancity’s degree programs are defined around a balance of three components: 50% technological skills, 25% business management and 25% AI ethics. These skills are declined through pedagogical contents (teachings, applications, AI clinic, personal development) in which the three components are fully integrated.

All our professional training programs also systematically integrate the business and ethical implications of the technological aspects of AI and or Data that are being addressed.

This hybrid approach is the hallmark of aivancity School for Technology, Business & Society Paris-Cachan.