Digitalization and ALMPs: a new paradigm for the labor market

Anna Bebber (Trento)


This paper aims to analyze the phenomenon of digitization as a new way of managing the labor market, highlighting its organizational structures, the obsolescence of certain skills, and possible new professions. The aim is to draw a theoretical framework that can identify the link between two streams of research, whose comparison may mistakenly seem oxymoronic: the digitalization of the public sector, and the active labor market policies (ALMPs), whose main providers are the employment services (PES).
The role of ALMPs proves to be crucial in taking advantage of the opportunities offered by the digital transition, in ensuring interventions aimed at fostering the employability of those affected by the ongoing transformations and enhancing the human-machine interaction. Moreover, ALMPs are key to bring to light the digital divide, the job polarization and, more generally, the skill mismatch.
Consequently, the challenges triggered by the digital revolution involve first and foremost employment services, which, although partly absorbed the inevitable and unexpected stimulus to technological innovation caused by the pandemic and the NRRP (National Recovery and Resilience Plan), they are still far from reaching the most challenging digitalization goals, especially if viewed in comparison. However, the «late mover» position of our legal system allows us to assume the implementation of a digital strategy for active policies, oriented to the foreign best practices.
Indeed, at the EU level, there is a pervasive spread of “digital first” approaches, for which the digital active policies’ delivery is increasingly adopted, to facilitate the employment of a ready-to-work segment of the population, thus allowing resources to be better expended for those in need of more intensive assistance, e.g. for people lacking digital literacy.
Exploring the issue from a different perspective, it is also the active policies themselves that are being overwhelmed by technological change: indeed, the ways in which interventions are programmed and administered have changed, especially through data-intensive technologies that allow significant amounts of data to be processed.
Implementing such innovations would also allow some decision-making processes to be more efficient than before: this is why the present paper will also discuss the topic of Artificial Intelligence, capable of reproducing human decision-making in multiple application spheres, sometimes with better outcomes in terms of accuracy, swiftness, completeness, and adaptability. One of AI’s best potentials emerges in reference to the profiling procedure, by being a valuable support in the measurement and analysis of the user's attitudinal characteristics, facilitating the decision-making procedure, as well as ensuring a proper response to a person’s employment status. This is why the second part of the discussion will be devoted extensively to this phenomenon. Profiling enriches data coming from administrative sources, by including behavioral variables in the database, used for predictive analysis. As it is already happening in the Belgian Flanders, the abundance of administrative data leads to the assumption of profiling models that are not only statistical, but also AI-based, using advanced machine learning techniques, as well as click data from job seekers.
Also in the light of comparative analysis, these introductory indications show «the framework of what would be a Copernican revolution» in employment services and labor policies. Such a revolution should not necessarily start at a central level, but nonetheless it should be welcomed at the level of local and territorial public administration.

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