01 Oct Recommendations for an AI Strategy in Switzerland
Swiss Academy of Engineering Sciences (SATW) October 2019
Authors: Alessandro Curioni, Lukas Czornomaz, Joachim Buhmann, Ernst Hafen, Manuel Kugler, Hervé Bourlard, Jana Koehler, Matthias Kaiserswerth, Anika Schumann
Main themes: artificial intelligence
Digital transformation is radically reshaping almost every aspect of our society. The explosion of artificial intelligence (AI) and big data analytics applications is enabled by the extreme availability of data in combination with the substantial computing power of modern highly distributed computing infrastructures connected by high-speed networks. Machine learning technologies can be trained to perform specific tasks with an efficiency and an accuracy that can supplement and, in some cases, outperform that of humans. These systems provide deep insights by learning from data and interactions with users, which is already leading to a profound transformation of numerous industries, professions, and society at large. The current state of AI is, however, still far from delivering truly intelligent behaviour that is comparable to human intelligence. An AI research strategy should therefore carefully analyse AI’s history with its various waves of large promises and conceptual shortcomings. Leading Swiss experts in AI have published their recommendations for a Swiss AI strategy. They advocate more intensive use of the technology and the creation of national data platforms, as data is a prerequisite for powerful algorithms.