Artificial Intelligence Applied: Six Actual Projects in Big Organizations

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The purpose of the chapter is to present some real application of the most advanced information technology in complex adaptive systems as for-profit companies and organizations. In particular, we would like to present the application of Machine Learning and Artificial Intelligence to support some of the activities that are strategical for an effective management of Human Resources. The tools have been applied to analyze the professional profiles (competencies, skills, knowledge and activities), to evaluate the candidates for hiring and selection, to assess the competences in order to obtain a certification or to prove the results of a training course. For each project, we provide a description of: a) the context, b) the problem, c) the solution implemented, d) an analysis of the advantages and limits of the solution. All these cases offer also quantitative and qualitative data to sustain our view of Artificial Intelligence as a tool that can help humans managing the complexity levels of the so-called Anthropocene era we live in.

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  • A Brizio
  • B Brassesco
  • A Carpaneto
  • D Mate
  • R Rezzonico
  • D Rabellino
  • F Surra
  • C Tirassa
  • M Tirassa
Brizio, A., Brassesco, B., Carpaneto, A., Mate, D., Rezzonico, R., Rabellino, D., Surra, F., Tirassa, C., Tirassa, M. (2010). Il benchmark della formazione. Quando innovazione d'impresa e formazione si incontrano (in Italian). Torino: Fondazione HumanPlus.
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  • C N Knaflic
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  • G Ronsivalle
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  • M Sierhuis
  • W J Clancey
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