DEFTECH-SCAN January 2020

This report contains mentions of developments, activities, and entities in 14 countries / regions. The breadth of countries referenced is both intentional and indicative; that is, it is designed to demonstrate at least three levels of impact of technology and capability development, diffusion, and deployment beyond large militaries such as those in the United States, China, and Russia.

First, more small and mid-sized militaries are taking advantage of technology diffusion and new requirements to develop advanced technology-enabled capabilities. Saudi Arabian Military Industry’s decision in January to develop a national counter-drone program is a useful example. So, too, is the recent incorporation of facial recognition software into Turkey’s KARGUS drone. This dynamic is unlikely to slow.

Second, the implications of new technology-enabled capabilities and the military and geopolitical competitions they create or amplify are broad and frequently unpredictable. The C4ISTAR section of this report details use of tools and technologies in support of layered Russian disinformation campaigns that affected entities in countries as diverse as the United Kingdom, Lithuania, and Switzerland. Similarly, the emphasis on uses of technologies such as artificial intelligence and bio and neuro-technologies has already generated important questions about ethics and norms of use that are of interest to militaries of all sizes.

Third, as new technology-driven capabilities are actually deployed the need for small and mid-sized militaries to prioritize capabilities critical to complementing the new capabilities of allies and partners or counter ingthose of potential competitors or adversaries becomes more urgent.

Source & Full Report : DEFTECH

Künstliche Intelligenz: Schweiz befindet sich in guter Ausgangslage

Künstliche Intelligenz (KI) hat bereits zu zahlreichen, aufsehenerregenden Anwendungen geführt, beispielsweise in der Bilderkennung, der medizinischen Diagnostik, der Sprachübersetzung oder der Mobilität. Wie ein vom Bundesrat in Auftrag gegebener Bericht zeigt, ist die Schweiz für die Anwendung und die Herausforderungen von künstlicher Intelligenz grundsätzlich gut aufgestellt. In verschiedenen Bereichen besteht jedoch in unterschiedlichem Ausmasse Handlungsbedarf. Dieser ist erkannt und wird weitgehend bereits angegangen. Der Bundesrat hat den unter Federführung des Eidgenössischen Departements für Wirtschaft, Bildung und Forschung (WBF) verfassten interdepartementalen Bericht an seiner Sitzung vom 13. Dezember 2019 zur Kenntnis genommen. Auf der Grundlage des Berichts werden nun strategische Leitlinien erarbeitet.

Für die Schweiz ist es zentral, die Potenziale, die sich durch die neuen Möglichkeiten der künstlichen Intelligenz ergeben, zu nutzen. Dazu gilt es, bestmögliche Rahmenbedingungen zu gewährleisten, damit die Schweiz sich als einer der führenden innovativen Standorte für Forschung und Entwicklung im Bereich von KI weiter etablieren kann. Gleichzeitig gilt es, die mit der Anwendung von künstlicher Intelligenz verbundenen Risiken zu erkennen und rechtzeitig Massnahmen zu ergreifen.

Der vom Bundesrat in Auftrag gegebene Bericht nimmt eine breite Auslegeordnung und sorgfältige Analyse der relevanten Rahmenbedingungen im Hinblick auf eine verantwortungsvolle Nutzung von künstlicher Intelligenz vor. Weiter beleuchtet er die spezifischen Herausforderungen in verschiedenen Anwendungsfeldern über alle Politikbereiche der Bundesverwaltung hinweg und diskutiert möglichen Anpassungsbedarf auf Bundesebene.

Source : Bund

Recommendations for an AI Strategy in Switzerland

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.

Recent advancements in machine learning have enabled AI technologies to become extremely successful. Speech recognition, natural language interaction with machines and facial recognition based on deep learning are now commodities that have changed the way people interact. The machine learning strategy of emulating human performance by learning from human experience promises a solution to the knowledge extraction problem. However, the automated reasoning process is as opaque as human decision making. Evolution has enabled humans to collectively reason and act on our collective experience, though other humans are often black boxes. Today, we are confronted with computational artefacts that are adapted to complex human decision making and, thereby, have inherited a similar “black box” behaviour.

Given the penetration of AI across most industries, its potential impact on GDP promises to be very high. In Switzerland, AI is already reshaping industries such as banking, insurance, pharmaceuticals and manufacturing. Furthermore, Switzerland is the European country that has the highest number of AI start-ups per citizen, with more than 100 startups. Many leading countries are heavily investing in AI development strategies and the establishment of technology transfer centres in this field.

To date, Switzerland has not developed a dedicated AI strategy. AI is one of many topics covered in the strategy “Digitale Schweiz”. An interdepartmental working group on AI which should ensure knowledge exchange in the domain of AI within the federal administration and coordinate Switzerland’s positions in international bodies, is mandated to submit a report to the Federal Council by September 2019. Furthermore, an interdisciplinary study on behalf of TASWISS is evaluating the opportunities and risks of AI on the basis of various focal points: work, education, media, consumption and administration. The publication of that study is planned for the end of 2019.

Read more here : SATW