This guide was developed for designers and developers of AI systems, with the goal of ensuring that these systems are sufficiently explainable. Sufficient here means that it meets the legal requirements from AI Act and GDPR and that users can use the system properly. Explainability of decisions is an important requirement in many systems and even an important principle for AI systems [HLEG19]. In many AI systems, explainability is not self-evident. AI researchers expect that the challenge of making AI explainable will only increase. For one thing, this comes from the applications: AI will be used more and more often, for larger and more sensitive decisions. On the other hand, organizations are making better and better models, for example, by using more different inputs. With more complex AI models, it is often less clear how a decision was made. Organizations that will deploy AI must take into account users' need for explanations. Systems that use AI should be designed to provide the user with appropriate explanations. In this guide, we first explain the legal requirements for explainability of AI systems. These come from the GDPR and the AI Act. Next, we explain how AI is used in the financial sector and elaborate on one problem in detail. For this problem, we then show how the user interface can be modified to make the AI explainable. These designs serve as prototypical examples that can be adapted to new problems. This guidance is based on explainability of AI systems for the financial sector. However, the advice can also be used in other sectors.
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In the aftermath of the systemic financial crises of 2007-9, several scholars argued that the problem of systemic financial crises is not well understood. At the same time, the introduction of digital technologies led to new threats and opportunities for the design of the monetary and financial system. For example, thousands of private cryptocurrencies have been implemented and hundreds of research papers on the (possible) introduction of public digital currencies have been published. It is often not explained why these new forms of digital money are needed and which (systemic) problems they (can) solve. In addition, the literature does not provide requirements nor guidelines to shape the development of the monetary and financial system in the digital age. This thesis applies design science to the monetary and financial system as a whole. The application of this novel methodology offers new possibilities to examine this complex system. The contribution of this thesis is threefold. First, different theories on money, banking and systemic financial crises have been researched through an extensive literature review and balance sheets. Second, those theories have been used to develop design requirements and guidelines. Finally, the consensus and pivotal dissensions about the systemic problem(s) of the current monetary and financial system, requirements and guidelines among experts have been identified through semistructured interviews. This research process results in widely supported requirements that demarcate the design space and widely supported guidelines that aim to give direction within the design space, that is, to the future development of the monetary and financial system.
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Chronic diseases represent a significant burden for the society and health systems; addressing this burden is a key goal of the European Union policy. Health and other professionals are expected to deliver behaviour change support to persons with chronic disease. A skill gap in behaviour change support has been identified, and there is room for improvement. Train4Health is a strategic partnership involving seven European Institutions in five countries, which seeks to improve behaviour change support competencies for the self-management of chronic disease. The project envisages a continuum in behaviour change support education, in which an interprofessional competency framework, relevant for those currently practising, guides the development of a learning outcomes-based curriculum and an educational package for future professionals (today’s undergraduate students).
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