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Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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AI is not a well-defined technology and no universally agreed definition exists
Artificial Intelligence is hard to pin down as a concept. Most definitions of AI are constructed with similar elements. For example, both definitions below suggest that AI is a technology that is responsiveto its environment and learnsfrom it whilst being relatively autonomous.“Artificial Intelligence’ (AI) can be used to indicate any technology (software, algorithm, a set of processes, a robot, etc.) that is able to function appropriately with foresight of its environment” -N. J. Nilsson 1“Artificial intelligence (AI) refers to systems that show intelligent behaviour: by analysing their environment they can perform various tasks with some degree of autonomy to achieve specific goals” -European Commission2However, “AI is not a well-defined technology and no universally agreed definition exists”.3To tackle this, in this report we refer to AI as a collection of approachesand technologies that are capable of achieving business goals, and what innovation frontiersthere currently are that challenge work towards these goals. Here we summarize these topics to provide a good understanding of the spectrum of AI.The boundaries of AI and between Data Science and AI are fuzzyA first distinction to make is the difference between Data Scienceand Artificial Intelligence. A good way to distinguish between these concepts is to examine their end-products.This distinction is not without overlap. Data Science methods are often used in designing models for AI and AI applications often do have humans in the loop. In practice, the distinction is too vague to be of use. Instead, we will note when a company or industry leans more to either Data Science (insights) or Artificial Intelligence (actions and outcomes).