Periodic Reporting for period 2 - HECAT (Disruptive Technologies Supporting Labour Market Decision Making)
Periodo di rendicontazione: 2021-10-01 al 2023-07-31
Project Number 870702 Project Acronym HECAT
Project title Disruptive Technologies Supporting Labour Market Decision Making
Starting date 01/02/2020
Duration (42 months)
HECAT aims to investigate, demonstrate and pilot a disruptive technology (a new type of algorithmic approach that integrates the qualitative and experiential aspects of unemployment) to work with the unemployed rather than on them, to support public employment services (PES) and citizens in evidence-based decision-making around unemployment, work readiness and job-seeking.
OB 1 Define and develop a deep sociological-led understanding of the experience of unemployment and PES from a citizen perspective (MS1, MS2)
OB 2 Define and create a dynamic network model for accessing and analysing big data sets, including the statistical and metricisation practices around the labour market and unemployment data (MS1, MS2)
OB 3 Work out a model to deploy and validate the back-end reinforcement learning algorithmic analytical techniques and dynamic network modeling for the HECAT platform (MS3, MS5)
OB 4 Create, deploy and test the gamification visualization driven user interface with input from PES and Citizen stakeholders in a living laboratory simulation and pilot integration (MS4, MS5)
OB 5 Promote the sustainability of HECAT through detailed public service user-led assessments of pilot integration (MS5)
Through these five objectives, HECAT supports public servants and unemployed people and the social support infrastructure that they rely on, as they navigate uncertain, dynamic and increasingly brittle labour markets. The project will have a significant impact on the support provided by public servants, a social impact for citizen users of PES and an economic impact in making the labour market more efficient. Almost half of all EU citizens will at some stage, rely on a Public Employment Services (PES), and this is a key touchpoint of a contemporary state and has impacts on citizens' thinking about social cohesion, care and existential wellbeing. HECAT will improve citizen’s experience and outcomes of unemployment by offering real-time evidence-based insight into their personal position in the labour market. HECAT builds on the experience and learning of existing basic algorithmic techniques used by some European PES administrations to: - deliver labour market insight directly to unemployed citizen and so is built on European values of open data, collaboration, transparency and citizen-participation - broaden out the focus on quantity of jobs drawn from the ‘economic imagination’ to add a focus on job quality and sustainable employment - go beyond profiling the ‘stock’ unemployed people, to incorporate measures of labour demand, and so take a labour market approach - go beyond the profiling of ‘problem categories’ of citizens that current survey-data based systems use, to exploit emerging big-data processing and analytics to treat each individual as a unique complex subject in a real-time and near limitless database that leverages the insight trapped inside statistical agencies - frame the development in deep contextual insight into the origin and transformation of the experience of unemployment and its administration based on anthropological inquiry - bring this insight into the hands of decision makers with a a platform-UX that exploits novel artificial intelligence with learning capabilities and cutting edge, accessible visualisation and gamification techniques to support knowledge discovery and decision making at the critical moment, as a decision support system. HECAT aims to produce a state of knowledge on the experiences of the unemployed. Based on an analysis of social sciences literature, it highlights the salient features of these experiences and focuses on three major dimensions: (1) the ways of reacting to unemployment and the meanings that individuals attribute to job deprivation, i.e. "the lived experiences of the unemployed"; (2) public policies and institutional actions that target the unemployed and influence their experiences, i.e. "the government of the experiences of the unemployed"; (3) the situations of the unemployed in the labour market and with regard to employment that influence the attributed and experienced meanings of unemployment, i.e. "the inequalities within unemployment". In this state of the art we strive to articulate the most relevant knowledge devoted to unemployment condition in Europe. Getting an extensive understanding of qualitative and experiential aspects of unemployment is a crucial issue for HECAT project: it is a condition to develop tools and algorithms based on our fundamental ethics. The project is an interdisciplinary co-development process bringing together sociological, anthropological, metricisation/statistics, economics, algorithm and advanced mathematics, analytics, ICT techniques, UX design and gamification to improve the lives of unemployed people by putting useable and insightful information the hands of PES support officers and their citizen clients. The technology will be developed at TRL 5/6/7. Future plans are to bring the technology to TRL 8/9.
Project title Disruptive Technologies Supporting Labour Market Decision Making
Starting date 01/02/2020
Duration (42 months)
HECAT aims to investigate, demonstrate and pilot a disruptive technology (a new type of algorithmic approach that integrates the qualitative and experiential aspects of unemployment) to work with the unemployed rather than on them, to support public employment services (PES) and citizens in evidence-based decision-making around unemployment, work readiness and job-seeking.
OB 1 Define and develop a deep sociological-led understanding of the experience of unemployment and PES from a citizen perspective (MS1, MS2)
OB 2 Define and create a dynamic network model for accessing and analysing big data sets, including the statistical and metricisation practices around the labour market and unemployment data (MS1, MS2)
OB 3 Work out a model to deploy and validate the back-end reinforcement learning algorithmic analytical techniques and dynamic network modeling for the HECAT platform (MS3, MS5)
OB 4 Create, deploy and test the gamification visualization driven user interface with input from PES and Citizen stakeholders in a living laboratory simulation and pilot integration (MS4, MS5)
OB 5 Promote the sustainability of HECAT through detailed public service user-led assessments of pilot integration (MS5)
Through these five objectives, HECAT supports public servants and unemployed people and the social support infrastructure that they rely on, as they navigate uncertain, dynamic and increasingly brittle labour markets. The project will have a significant impact on the support provided by public servants, a social impact for citizen users of PES and an economic impact in making the labour market more efficient. Almost half of all EU citizens will at some stage, rely on a Public Employment Services (PES), and this is a key touchpoint of a contemporary state and has impacts on citizens' thinking about social cohesion, care and existential wellbeing. HECAT will improve citizen’s experience and outcomes of unemployment by offering real-time evidence-based insight into their personal position in the labour market. HECAT builds on the experience and learning of existing basic algorithmic techniques used by some European PES administrations to: - deliver labour market insight directly to unemployed citizen and so is built on European values of open data, collaboration, transparency and citizen-participation - broaden out the focus on quantity of jobs drawn from the ‘economic imagination’ to add a focus on job quality and sustainable employment - go beyond profiling the ‘stock’ unemployed people, to incorporate measures of labour demand, and so take a labour market approach - go beyond the profiling of ‘problem categories’ of citizens that current survey-data based systems use, to exploit emerging big-data processing and analytics to treat each individual as a unique complex subject in a real-time and near limitless database that leverages the insight trapped inside statistical agencies - frame the development in deep contextual insight into the origin and transformation of the experience of unemployment and its administration based on anthropological inquiry - bring this insight into the hands of decision makers with a a platform-UX that exploits novel artificial intelligence with learning capabilities and cutting edge, accessible visualisation and gamification techniques to support knowledge discovery and decision making at the critical moment, as a decision support system. HECAT aims to produce a state of knowledge on the experiences of the unemployed. Based on an analysis of social sciences literature, it highlights the salient features of these experiences and focuses on three major dimensions: (1) the ways of reacting to unemployment and the meanings that individuals attribute to job deprivation, i.e. "the lived experiences of the unemployed"; (2) public policies and institutional actions that target the unemployed and influence their experiences, i.e. "the government of the experiences of the unemployed"; (3) the situations of the unemployed in the labour market and with regard to employment that influence the attributed and experienced meanings of unemployment, i.e. "the inequalities within unemployment". In this state of the art we strive to articulate the most relevant knowledge devoted to unemployment condition in Europe. Getting an extensive understanding of qualitative and experiential aspects of unemployment is a crucial issue for HECAT project: it is a condition to develop tools and algorithms based on our fundamental ethics. The project is an interdisciplinary co-development process bringing together sociological, anthropological, metricisation/statistics, economics, algorithm and advanced mathematics, analytics, ICT techniques, UX design and gamification to improve the lives of unemployed people by putting useable and insightful information the hands of PES support officers and their citizen clients. The technology will be developed at TRL 5/6/7. Future plans are to bring the technology to TRL 8/9.
Revised our state of the art to transform it into articles for submission to peer-reviewed journals. Started a socio-political analysis of profiling in France. Conducted an empirical fieldwork on the subject and are currently preparing an article. In parallel, we have been working with our Irish colleagues on a comparison of the two countries, and have presented our analyses at the ESPAnet conference in August 2021. This paper investigates a case of datafication of welfare through the deployment of algorithmic-statistical profiling by public employment systems in France and Ireland to support job seekers and help find employment as soon as possible. We aim to contribute to the literature by studying how profiling came about and how it is lived in the field, instead of evaluating its efficiency and effectiveness or recommending a particular model per se. Furthermore, based on a fieldwork of unemployed people and vocational counsellors in Slovenia, we are working with our Danish colleagues to explore the dynamics of the professional projections that these actors mobilise. We presented a communication at the ESA Conference in August, titled "What is a "good" job? An analysis of the experiences of unemployed Slovenians". In international institutions and in the academic world, the quality of jobs has become a key issue. Based in in-depth interview with 15 unemployed people in Slovenia, we seek to explore ideas and visions about what a good job is, and to identify dynamics that shape such ideas.
All the network partners are interested in sustaining the network after the HECAT project- most network partners are already connected through an interest in disruptive technologies in PES and public services in general. The consortium members have a desire that the future legacy of the HECAT platform is sustainable and have agreed in principle to develop it to TRL8/9 after piloting is completed. The HECAT research output will comprise of the validated HECAT Platform and the software artefacts and user materials which will be Open Source and available for user communities to enhance and adopt in future. It is envisaged that the platform can also be commercialised through the development of bespoke platforms for user sites and the ongoing maintenance, upgrading and management of the system.