HECAT is a research consortium carefully brought together to achieve the mammoth task of developing an ethical algorithmic based platform to assist Public Employment Services (PES) and Unemployed people in making informed, transparent and integrated decisions.
The research aims to use sociologically and anthropological insight into unemployment and the labour market to guide technical developers of the back-end algorithms and front-end user interface with the objective of creating an ethical and equal platform. Consortium partners are drawn from AHSS and STEM disciplines, academics, NGOs and PES.
Hecat aims to investigate, demonstrate and pilot a disruptive technology to support labour market decision making by unemployed citizens and those seeking to help them. At one stage or another, almost half of all EU citizens will rely on Public Employment Services (PES), and so this is a key touchpoint of a contemporary state and has impacts on citizen’s thinking about social cohesion, care and existential wellbeing. The ambition of the project is to 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 citizens and so is built on European values of open data, collaboration, transparency and citizen-participation
- broaden out the focus on the number 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 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
Where are we located?
SETU (formerly WIT) is coordinating the Hecat project. Bringing more than 8 years of experience in the study of unemployment from the Waterford Unemployment Experiences Research Collaborative (WUERC). WIT's approach is person centred, and emphasises that research must be done with the unemployed, rather than on them.
Institutional lead: Ray Griffin, Principal Investigator. Contact: email@example.com
With the growth of algorithmic profiling systems and big data, it has become increasingly necessary for us to develop an understanding of these systems which is nuanced and holistic. CBS contributes this understanding to our project through an analysis of labour market metricisation.
Institutional lead: Janine Leschke. Contact: firstname.lastname@example.org
Sciences Po is ensuring that our project is sociologically led by maintaining a focus on the experiences of unemployed people. This perspective is different than (for example) studying unemployment through institutions or statistics. This will ensure that the final tool we produce will have the context of the lived experiences of unemployment embedded within it.
Institutional lead: Didier Demaziere. Contact: email@example.com
JSI brings a sophisticated and rich analysis of statistical modelling and data processing to the Hecat project. JSI will help us bring our sociologically led vision of an unemployment support tool to life. This involves not only analysis and critique of existing support tools, but the know-how and skill to build a tool with a different focus to what is already available.
Institutional lead: Pavle Boskoski. Contact: firstname.lastname@example.org
Tecnalia is working closely with JSI to build a platform which is engaging, intuitive, and useful to the end users. Their efforts are therefore concentrated on the final user experience, and Tecnalia has an important role not only in developing this user interface, but field testing it so that the final result is accessible and useful.
Institutional lead: Jorge Garcia Valbuena. Contact: Jorge.Garcia@tecnalia.com
One of the most exciting aspects of H2020 projects is being able to work directly with partners who are on the front lines of contemporary issues. We aim to pilot our tool in Slovenia and are working closely with ESS, who have supplied us with invaluable data, information, and resources about the nature and scope of unemployment in Slovenia.
Institutional lead: Tjaša Fužir Koporec. Contact: email@example.com
Roskilde are working with Tecnalia to pilot and validate the platform at various phases of its implementation. To achieve this, Roskilde will be collecting feedback from a variety of sample users on the performance of the platform, and working with Tecnalia to incorporate this feedback into future iterations. This ensures that the platform will be valid after the project ends by working through unforeseen issues before the platform goes to final deployment.
Institutional lead: Magnus Paulsen Hansen Contact: firstname.lastname@example.org
While Sciences Po and WIT add the sociological imagination to the project, UL adds the economists perspective. This grounds our sociologically driven analysis in a structured and nuanced understanding of market systems. This broader picture is essential for a holistic understanding of unemployment.
Institutional lead: Marko Pahor Contact: email@example.com
NFJ offers a wide ranging and contextual understanding of unemployment through the collection of survey data. This will give us a clearer picture of the issues facing unemployed people and will add a huge body of data to the smaller quantities of qualitative data collected by the other partners.
Institutional lead: Roxana Paz. Contact: firstname.lastname@example.org