INCAI – Inclusive Artificial Intelligence
Timespan of the project:
01-09-2020/ 31- 08 – 2022
- To compare, share and identify and promote good practice that can enhance the inclusion of adults from disadvantaged groups in education and learning.
- To enhance the provision of good quality learning opportunities to adult’s learners in particular those from excluded groups.
- To contribute to social inclusion in education across the EU using Artificial Intelligence.
- To develop and broaden the competences of adult education providers and organisations working with adult learners from excluded groups.
- To demonstrate the significant role Artificial Intelligence technology can play in improving inclusion in learning in current practices across EU.
- To present identified best practices and develop guidelines on how to prepare Artificial Intelligence wireframes.
- To drive social change and contribute to future development of inclusive Artificial Intelligence in education by producing sustainability plans for inclusive Artificial Intelligence tools co-produced in partner countries across the EU and by providing local, regional, national and EU level dissemination activities.
- 6 transnational meetings with 96 participants – 16 per meeting.
- 2 short-term joint training events with 48 participants – 24 per event from 8 partners.
- At least 8 identified examples of good practice in inclusive Artificial Intelligence.
- Creation of guidelines on how to produce an Artificial Intelligence wireframe for inclusive education.
- Usability plan for 8 Artificial Intelligence wireframes produced as a result of local co-production which can be replicated for identified target groups across the EU to improve access to education for adults from marginalized and disadvantaged groups.
- To increase the inclusion of adult learners.
- To increase ICT skills and competences for adult learners.
- To increase competences and skills for educators in partner organizations.
- To increase the capacity of partner organizations to serve adult learners from disadvantaged groups.