Documents Medas, Gabriele 3 results

"Artificial intelligence (AI) systems are increasingly being used in various industries in connection with algorithmic management, chatbots, geopositioning, and other processes. AI refers to machine-based systems that can make predictions, recommendations, or decisions with only limited human input/oversight. To understand the challenges that are emerging in relation to the increased use of AI in human resource management, the report examines the current situation in collective bargaining regarding the use of AI-related tools by employers vis-àvis workers, especially in the service sector. The findings are based on desk research, an original survey of 148 trade union representatives affiliated to UNI Europa in 32 countries, and an analysis of 31 collective agreements that already contain provisions relating to the use of AI. Results reflect current experience, general opinions on bargaining on AI-related challenges, and expected union actions to develop bargaining in this area, as well as some good practices on AI-related clauses in collective agreements. The analysis has produced the following key conclusions: – Bargaining on AI is emerging and is not yet as widespread as bargaining on other elements of working conditions. – Out of 90 survey responses, only 20% of trade unions reported having a collective agreement that addresses AI-related issues at the organisation or sector level. This implies that the majority of trade unions (69%) do not have any collective bargaining agreements related to AI, and 11% are unaware of any such agreements.
– Existing collective agreements mostly make general reference to the use of technology. However, several agreements were identified (e.g. in Italy, Germany, Norway and Spain) that can serve as examples of more detailed rules and arrangements on the right to disconnect, digital rights of the workers at the workplace, information-sharing and business control. – With the increasing use of technology at the workplace, it can be expected that collective bargaining on AI will further increase in relevance. 42% of the UNI Europa affiliates that participated in the survey are already engaged in discussions and negotiations on various topics related to AI, even if this is not collective bargaining in the strict sense. Unions prioritise issues of data protection, worker privacy, the impact of AI on working hours, monitoring of worker activities, and automated scheduling of work shifts. – In the process of developing collective bargaining on AI-related issues, unions prioritise bargaining on workers' right to challenge decisions made through automated decision-making, and their right to receive advice from an external data expert. Additionally, there is an intense desire among unions to have a right to information and consultation on the use and evaluation of AI tools.
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"Roma are, all over the world, a particularly segregated and unhealthy minority group. The causes of poor health among Roma people will be analysed to find out if such causes are ethnically-related or, rather, socially-determined. A comparison between Roma health status and the health condition of the general population will point to the main differences, showing to what extent Roma suffer from health inequalities. The study will provide evidence and reliable information on the most important social determinants responsible for the health status of the Roma community in Hungary, such as poverty; low education; employment; discrimination; segregation; poor and unhealthy housing; relationships between health care providers and Roma patients; the unequal distribution of power, money and resources; and the burdens in accessing health care services. The relation between health condition and socio-economic status will be analysed to understand whether social determinants of health are sufficient fully to explain the poorer health status of Roma in Hungary"

"Collective bargaining is central to wage-setting and working conditions, but knowledge about what exactly has been concluded in collective bargaining agreements (CBAs) in Europe is limited. In light of the debate about a European Minimum Wage, whereby some countries set wage floors in collective agreements and not through legislation, this information gap has become evident. Based on desk research and experience with the WageIndicator CBA Database and similar databases, this article aims to explore the feasibility of an EU-wide CBA data collection to tackle these blind spots. We estimate a total of over 85,000 CBAs are in force in EU27, of which the large majority in Germany. Almost all EU countries maintain a CBA registry, covering either all CBAs or only multi-employer CBAs. In 20 EU countries full-texts CBAs can even be found online. We conclude that an EU-wide CBA database could cover all CBAs for nine countries, all multi-employer CBAs for another nine countries and a partial selection of CBAs for two countries. Data collection for the remaining countries has to rely on CBAs collected from social partners individually. Realisation of an EU-wide CBA database seems a doable but definitely very challenging task, though less so when targeting one or a few sectors. When these CBA texts would be collected and coded, the content of CBAs could be compared across EU member states. We present the WageIndicator CBA database as an example of a cross-country coding scheme for CBA texts and explore text-mining options as a promising way forward as to reduce coding efforts."