The shortage for ICT personal in the EU is large and expected to increase. The aim of this research is to contribute to a better understanding of the roles and competences needed, so that education curricula can be better aligned to evolving market demand by answering the research question: Which competence gaps do we need to bridge in order to meet the future need for sufficiently qualified personnel in the EU Software sector? In this research, a mixed method approach was executed in twelve European countries, to map the current and future needs for competences in the EU. The analyses shows changes in demand regarding technical skills, e.g. low-code and a stronger focus on soft skills like communication and critical thinking. Besides this, the research showed educational institutes would do well to develop their curricula in a practical way by integration of real live cases and work together with organizations.
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"The booklet presents curated real-world good practice examples that help translate our strategy into concrete actions, and in turn, into the design of education and training programmes that will contribute to skill, upskill, or reskill individuals into high demand professional software roles."
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The COVID-19 pandemic has accelerated remote working and working at the office. This hybrid working is an indispensable part of today's life even within Agile Software Development (ASD) teams. Before COVID-19 ASD teams were working closely together in an Agile way at the office. The Agile Manifesto describes 12 principles to make agile working successful. These principles are about working closely together, face-to-face contact and continuously responding to changes. To what extent does hybrid working influence these agile principles that have been indispensable in today's software development since its creation in 2001? Based on a quantitative study within 22 Dutch financial institutions and 106 respondents, the relationship between hybrid working and ASD is investigated. The results of this research show that human factors, such as team spirit, feeling responsible and the ability to learn from each other, are the most decisive for the success of ASD. In addition, the research shows that hybrid working creates a distance between the business organization and the IT department. The findings are valuable for Managers, HR professionals and employees working in the field of ASD as emphasizing and fostering Team Spirit, Learning Ability, and a Sense of Responsibility among team members can bolster the Speed of ASD.
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Whitepaper: The use of AI is on the rise in the financial sector. Utilizing machine learning algorithms to make decisions and predictions based on the available data can be highly valuable. AI offers benefits to both financial service providers and its customers by improving service and reducing costs. Examples of AI use cases in the financial sector are: identity verification in client onboarding, transaction data analysis, fraud detection in claims management, anti-money laundering monitoring, price differentiation in car insurance, automated analysis of legal documents, and the processing of loan applications.
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This white paper is the result of a research project by Hogeschool Utrecht, Floryn, Researchable, and De Volksbank in the period November 2021-November 2022. The research project was a KIEM project1 granted by the Taskforce for Applied Research SIA. The goal of the research project was to identify the aspects that play a role in the implementation of the explainability of artificial intelligence (AI) systems in the Dutch financial sector. In this white paper, we present a checklist of the aspects that we derived from this research. The checklist contains checkpoints and related questions that need consideration to make explainability-related choices in different stages of the AI lifecycle. The goal of the checklist is to give designers and developers of AI systems a tool to ensure the AI system will give proper and meaningful explanations to each stakeholder.
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Context:Rapid developments and adoption of machine learning-based software solutions have enabled novel ways to tackle our societal problems. The ongoing digital transformation has led to the incorporation of these software solutions in just about every application domain. Software architecture for machine learning applications used during sustainable digital transformation can potentially aid the evolution of the underlying software system adding to its sustainability over time.Objective:Software architecture for machine learning applications in general is an open research area. When applying it to sustainable digital transformation it is not clear which of its considerations actually apply in this context. We therefore aim to understand how the topics of sustainable digital transformation, software architecture, and machine learning interact with each other.Methods:We perform a systematic mapping study to explore the scientific literature on the intersection of sustainable digital transformation, machine learning and software architecture.Results:We have found that the intersection of interest is small despite the amount of works on its individual aspects, and not all dimensions of sustainability are represented equally. We also found that application domains are diverse and include many important sectors and industry groups. At the same time, the perceived level of maturity of machine learning adoption by existing works seems to be quite low.Conclusion:Our findings show an opportunity for further software architecture research to aid sustainable digital transformation, especially by building on the emerging practice of machine learning operations.
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Assistive Technology (AT) is any technology that supports people with functional difficulties to perform their daily activities with less difficulty and/or obstruction, thus contributing to a more fulfilling life. This refers to people of all ages and to all kinds of functional limitations, either permanent or temporary. Assistive products can be traditional physical products, such as wheelchairs, eyeglasses, hearing aids, or prostheses, but they can also be special input devices, care robots, computers with accessible software, apps for smartphones, home automation solutions, virtual realities, etc. It is essential to understand that AT involves more than just familiar products, and that it also includes knowledge about the personalized selection of appropriate solutions, provisions, and services, as well as the training of all parties involved, the measurement of outcomes and impacts, awareness of ethical issues, etc.
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Recently, the job market for Artificial Intelligence (AI) engineers has exploded. Since the role of AI engineer is relatively new, limited research has been done on the requirements as set by the industry. Moreover, the definition of an AI engineer is less established than for a data scientist or a software engineer. In this study we explore, based on job ads, the requirements from the job market for the position of AI engineer in The Netherlands. We retrieved job ad data between April 2018 and April 2021 from a large job ad database, Jobfeed from TextKernel. The job ads were selected with a process similar to the selection of primary studies in a literature review. We characterize the 367 resulting job ads based on meta-data such as publication date, industry/sector, educational background and job titles. To answer our research questions we have further coded 125 job ads manually. The job tasks of AI engineers are concentrated in five categories: business understanding, data engineering, modeling, software development and operations engineering. Companies ask for AI engineers with different profiles: 1) data science engineer with focus on modeling, 2) AI software engineer with focus on software development , 3) generalist AI engineer with focus on both models and software. Furthermore, we present the tools and technologies mentioned in the selected job ads, and the soft skills. Our research helps to understand the expectations companies have for professionals building AI-enabled systems. Understanding these expectations is crucial both for prospective AI engineers and educational institutions in charge of training those prospective engineers. Our research also helps to better define the profession of AI engineering. We do this by proposing an extended AI engineering life-cycle that includes a business understanding phase.
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Bij de aanvang van het lectoraat 'sociale infrastructuur en technologie' was onze doelstelling te komen tot een inventarisatie van ict gebruik in de sociale sector. Daarbij ging het ons om praktijken en initiatieven in de sociale sector waarbij men gebruik maakt van moderne technologie ter versterking van de sociale infrastructuur, de leefbaarheid van samenlevingsverbanden, de participatie in de publieke besluitvorming, de hulp- en dienstverlening aan cliknten en deelnemers. Met de sociale sector worden alle institutionele arrangementen bedoeld die het werken aan welzijn als primaire doelstelling hebben. Het gaat hierbij niet om een zoveelste onderzoek teneinde een volledig, kwantitatief gericht beeld te krijgen. Er werd gestreefd naar een beschrijving van veelbelovende aanpakken, niet alleen binnen de institutionele welzijnszorg, maar ook projecten en activiteiten die op initiatief van burgers buiten de sociale sector-in strikte-zin zijn opgezet.
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A public sector that adequately makes use of information technology can provide improved government services that not only stimulates business development it also intensifies citizen participation and economic growth. However, the effectiveness of IT and its governance at both national as well as on municipality level leaves much to be desired. It is often stated that this is due to a lack of digital skills needed to manage the IT function and alignment with business. Therefore, the aim of this study is to determine the effect that digital leadership competences and IT capabilities have on digital transformation readiness within Dutch municipalities. Based on an analyses of survey data from 178 respondents we recommend municipalities to implement a range of activities that all are related to realize the ability to constantly apply strategic thinking and organizational leadership to exploit the capability of Information Technology to improve the business.
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