In a rapidly developing labor market, in which some parts of jobs disappear and new parts appear due to technological developments, companies are struggling with defining future-proof job qualifications and describing job profiles that fit the organization’s needs. This is even more applicable to smaller companies with new types of work because they often grow rapidly and cannot hire graduates from existing study programs. In this research project, we undertook in-depth, qualitative research into the five roles of a new profession: social media architect. It has become clear which 21st century skills and motivations are important per role and, above all, how they differ in subcategory and are interpreted by a full-service team in their working methods, in a labor market context, and in the talents of the professional themselves. In a workshop, these “skills” were supplemented through a design-based approach and visualized per team role in flexibly applicable recruitment cards. This research project serves as an example of how to co-create innovative job profiles for the changing labor market. Ellen Sjoer, Petra Biemans. “A design-based (pre)recruitment approach for new professions: defining futureproof job profiles.” Információs Társadalom XX, no. 2 (2020): 84–100. https://dx.doi.org/10.22503/inftars.XX.2020.2.6
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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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The world needs more jobs to meet United Nations Sustainable Development Goal 8 and to keep up with expected population growth. Policymakers stimulate start-ups due to their expected job-generating effect. Despite the increased number of solo self-employed, percentages on graduation from small to larger enterprises are low. This study focuses on entrepreneurs who create jobs, and have passed ‘the one-employee threshold’. What are the considerations of the solo self-employed when making the decision to hire their first employee? 27 Interviews were conducted with entrepreneurs in developed and developing countries. The analysis shows that solo self-employed have considerations about time, skills, trust and opportunities when hiring their first employee. The study finds evidence of effectual behaviour. Trust is important: trust in others (the first employee) and trust in yourself (becoming an employer). To stimulate job creation, policymakers should stimulate effectual behavior that enhances the self-efficacy of the solo self-employed. This is a draft chapter/article. The final version is available in Unlocking Regional Innovation and Entrepreneurship edited by Iréne Bernhard, PhD, Urban Gråsjö, PhD, School of Business, Economics and IT, University West and Charlie Karlsson, Professor Emeritus, Jönköping University and Blekinge Institute of Technology, Sweden, published in 2021, Edward Elgar Publishing Ltd https://doi.org/10.4337/9781800371248
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It is predicted that 5 million rural jobs will have disappeared before 2016. These changes do notonly concern farmers. In their decline all food chain related SMEs will be affected severely. Newbusiness opportunities can be found in short food supply chains. However, they can onlysucceed if handled professionally and on a proper scale. This presents opportunities on 4interconnected strands:Collect market relevant regional dataDevelop innovative specialisation strategies for SMEsForge new forms of regional cooperation and partnership based on common benefits andshared values.Acquire specific skillsREFRAME takes up these challenges. In a living lab of 5 regional pilots, partners willdemonstrate the Regional Food Frame (RFF) as an effective set of measures to scale up andaccommodate urban food demands and regional supplies. New data will reveal the regions’ ownstrengths and resources to match food demand and supply. REFRAME provides a supportinfrastructure for food related SMEs to develop and implement their smart specializationstrategies in food chains on the urban-rural axis. On their way towards a RFF, all pilots will use a5-step road map. A transnational learning lab will be set up in support of skill development andtraining of all stakeholders. REFRAME pools the know-how needed to set up these Regional FoodFrames in a transnational network of experts, each closely linked and footed in its own pilotregion.
