pop AI Stakeholder Policy Lab

Pop AI envisages the organisation of Six Stakeholder Policy Labs to facilitate exchange between relevant LEAs and related experts. The goal is to develop ideas for smart policies and test the solutions to identified controversies in experimental models.

The first five Labs will be 1-2-day virtual events in the five countries represented by pop AI LEA partners in order to engage their existing networks. Each policy lab will provide the local perspective of the five analysed countries by bringing together relevant stakeholders from each region. Each policy lab addresses a specific controversy. The 6th Lab will be held in Brussels in person, bringing together cross-regional stakeholders from the five virtual labs to assess recommendation trajectories at the EU level. The outputs will include both region-specific and EU-wide recommendations.

Timeline

2022
2022

25th May

Policy Lab 1 – Greece

2022
2022

December

Policy Lab 3 – Spain

2023
2023

February

Policy Lab 4 – Slovakia

2023

May

Policy Lab 5 – Italy

2023

September

Policy Lab 6 – Belgium

Participants

The experts invited to the labs include technology designers, policymakers, NGOs (e.g. human rights watch, privacy international, algorithm watch, justice league) from each region. During the labs, the LEA will engage their existing networks and expand the list of participants to further relevant stakeholders.

Methodology

Each Stakeholder Policy Lab will be based on four chapters:

  • Identification of best practices that can be shared with other actors throughout the EU;
  • development of ideas to overcome controversies;
  • testing the outcome of such development processes in an experimental setting; and
  • assessment whether or not public policy change is needed in order to ensure smart innovation.

Each lab will cover policy needs in relation to human rights, liabilities, proportionality, gender and diversity (building on T2.2, T2.4). They will also cover more organisational challenges around issues like automation bias, data preparedness, reporting practices, and gender and diversity in the workplace (building on T2.5).