V LAIKA workshop
Last Friday 13th December, V LAIKA workshop was celebrated at the Open University of Catalonia in Barcelona.
15 People from several organizations and institutions (Talentfy, Eurecat, Everis, Open Evidence, Universitat Pompeu Fabra, Universitat Oberta de Catalunya) participated in this event.
The main objective of this workshop was sharing experiences regarding data-driven design of competence profiles.
“Cómo navegar con tecnología en esta tormenta del mercado laboral”, by Alejandro González (Taalentfy)
He posed the main aspects about the design and implementation of a system where users and organizations find the best solution for their expectations: looking for jobs, training and growing their potential (users) and looking for the best talent to join their company (organizations).
He emphasized some key elements in his proposal:
Personal experience: “I don’t need a universitary degree to start working”; there are other alternatives, such as non-universitary advance degrees or professional training.
Staff selection processes have become out-dated, especially in big projects outsourcing. Keywords-based selection processes do not really evaluate skills.
Technology should be used as a disruptive tool in order to improve these processes.
The rising of AI applications is a short- and mid-term risk for many jobs; e.g. self-driving cars.
The very concept of job is changing, its type and duration, as well as new yet non-existing jobs.
It is necessary to be able to move from knowledge-based models to soft skills-based models, to consider aspects such as globalization and both cultural and ethnic diversity, and to foster the concept of “talent driven organization”.
A “enriched talent profile” is proposed, as a result of assessment (of skills and talent), learning (what are the users telling and doing, their social network presence, etc.) and recommendation (of training, employment, partners, etc.).
A big data-, machine learning- and gamification-based algorithm has been developed in order to obtain such a profile.
Active non-discrimination policies have been implemented so that the algorithm is free of a priori biases (such as sex, age, etc.).
Regarding sensitive information, the user decides what to reveal and he/she is responsible for the veracity of the revealed information as well, so that a third party blockchain-based validation can be implemented.
First, Vanessa Paulino (Everis) talked about the paradox of the lack of job and the scarcity of talent in the recruiting processes. Furthermore, there exists a gender bias problem regarding the candidates in fields such as IT. It is also necessary to have specific processes at our disposal in order to identify young talent. Majors and degrees are important, but experience is the key element in the long position.
Then, Lourdes Morales (Eurecat) explained how different the problem can be in technological/research centers, with a high profile variability. In these scenarios, the recruiting process has to be flipped: a high amount of previous work regarding resumes, social network analysis, etc. is necessary, and the interview provides with qualitative information about the reasons of the candidates. Qualitative-kind of resumes and motivation letters are more profitable instead standard (quantitative-kind of) resumes, which are no longer useful.
Then, Simone Vitiello (Open Evidence) talked about the lack of STEM profiles in the european sphere (H2020 project), as well as other STEM-skills related profiles. There is only a 31% of feminine talent in the STEM field, and a much lower rate in engineering and IT fields.
Then, Fanny Lichtenstein (Pràctiques en empresa, UOC) emphasized that the students’ employability is the real target. The current academic record is poor, since it does not actually show the skills of the candidate. In many cases, we have recruitment processes with non-qualified students, which can lead to situations where administrative requirements are not fulfilled. More flexibility is needed.
And finally, Oscar Moreno (Alumni UOC) talked about the importance of leadership and candidate’s empowerment. Maybe we are wrong when we pose the issue in terms of university vs. professional training; maybe we should see it in terms of different and intertwined stages.