LIST OF PANELS

Active labour market policies (ALMPs) should address the so-called ‘new risks’ that have prevailed since the 90s as well as new challenges, for example those emerging from technological change, population aging and climate change.  In these respects, ALMP represent a crucial field to cushion the impact structural changes have had on employment by providing training, counselling and (subsidised) access into the labour market. However, ALMPs have recently attracted criticism for several reasons. Since they are subjected to fiscal pressures and performance targets, the access to ALMPs can be biased towards (unemployed) labour market insiders with better employment prospects. These biases, known as ‘Matthew effects’, result in insiders’ accumulation of advantages, leaving those most disadvantaged behind. Scholars are then questioning whether ALMPs promote sustainable employment or, rather, the expansion of low-skill short-term jobs. New concerns are rising as digital processes and artificial intelligence are being implemented within public employment services (PES). The use of more digitalised service can be unsuitable, complicated and estranging for the most vulnerable groups, which are at the core of ALMPs.
At the same time, digitalisation affects substantial policy tools, as well as organisational conditions and governance regimes in PES. Policy tools typically utilised to reform welfare-to-work, such as performance-based contracting, have already been driven by attempts to discipline frontline discretion. In several countries, these tools are now evolving towards new modes of digital governance that seek to reshape the delivery of services using algorithms and machine learning. From a welfare-to-work perspective, digital technologies become part of the process of making it easier for clients to be quickly re-employed. The logic is to standardise and automatise relatively routinised services and thereby free frontline employees to deal with the more complex tasks that require human interaction and discretion. In building a culture of data collection and performance monitoring, new concerns may be raised among frontline staff about a further potential reduction of their discretion in delivering ALMPs. This does not exclude that it is possible to see new types of coping strategies emerging among frontline workers as they seek to deal not only with performance management but also with the technology.
 
The aim of this panel is to provide an account of the role played by ALMPs and PES in recent times. The panel welcomes both theoretical and empirical contributions that offer new insights on: how ALMP interventions are designed as well as on their impact; the role of frontline discretion on service delivery; the ways in which governance systems could shape street-level delivery; the potential and limits of replacing human-to-human assistance with digital tools.

Active labour market policies (ALMPs) should address the so-called ‘new risks’ that have prevailed since the 90s as well as new challenges, for example those emerging from technological change, population aging and climate change.  In these respects, ALMP represent a crucial field to cushion the impact structural changes have had on employment by providing training, counselling and (subsidised) access into the labour market. However, ALMPs have recently attracted criticism for several reasons. Since they are subjected to fiscal pressures and performance targets, the access to ALMPs can be biased towards (unemployed) labour market insiders with better employment prospects. These biases, known as ‘Matthew effects’, result in insiders’ accumulation of advantages, leaving those most disadvantaged behind. Scholars are then questioning whether ALMPs promote sustainable employment or, rather, the expansion of low-skill short-term jobs. New concerns are rising as digital processes and artificial intelligence are being implemented within public employment services (PES). The use of more digitalised service can be unsuitable, complicated and estranging for the most vulnerable groups, which are at the core of ALMPs.
At the same time, digitalisation affects substantial policy tools, as well as organisational conditions and governance regimes in PES. Policy tools typically utilised to reform welfare-to-work, such as performance-based contracting, have already been driven by attempts to discipline frontline discretion. In several countries, these tools are now evolving towards new modes of digital governance that seek to reshape the delivery of services using algorithms and machine learning. From a welfare-to-work perspective, digital technologies become part of the process of making it easier for clients to be quickly re-employed. The logic is to standardise and automatise relatively routinised services and thereby free frontline employees to deal with the more complex tasks that require human interaction and discretion. In building a culture of data collection and performance monitoring, new concerns may be raised among frontline staff about a further potential reduction of their discretion in delivering ALMPs. This does not exclude that it is possible to see new types of coping strategies emerging among frontline workers as they seek to deal not only with performance management but also with the technology.
 
The aim of this panel is to provide an account of the role played by ALMPs and PES in recent times. The panel welcomes both theoretical and empirical contributions that offer new insights on: how ALMP interventions are designed as well as on their impact; the role of frontline discretion on service delivery; the ways in which governance systems could shape street-level delivery; the potential and limits of replacing human-to-human assistance with digital tools.