AI auditing / bias mitigationbias mitigation in AI systemsParticipation documented
MAMMOth
Thessaloniki, Greece
Project documentation and associated publications describe stakeholder engagement and co-creation activities with civil-society actors and vulnerable or underrepresented groups around bias evaluation and mitigation.
fairnessbias mitigationstakeholder engagementproblem formulationauditingmodel evaluationgovernance
- Region
- Europe
- Lead organization
- MAMMOth Consortium
- Organization type
- research consortium
- Technology group
- auditing / risk assessment
- Activity status
- completed
- Start year
- 2022
- Last updated
- Mar 25, 2026
- Participation mode
- civil-society workshops + co-creation for bias mitigation
- Participants
- civil society organizations; underrepresented groups; researchers; developers
- Methods
- co-creation workshops; stakeholder engagement; training materials; collaborative evaluation
- AI lifecycle stages
- problem formulation; auditing; model evaluation; governance
- Evidence summary
- Project documentation and associated publications describe stakeholder engagement and co-creation activities with civil-society actors and vulnerable or underrepresented groups around bias evaluation and mitigation.
- Atlas assessment
- Cautious · Medium confidence · evidence grade A
- Uncertainty
- Public evidence shows real stakeholder workshops and civil-society involvement, but direct affected-community power over the technical agenda is not fully clear.
- Participation group
- Participatory Governance
- Technology description
- auditing / risk assessment
- Funding
- Not documented
- Region of activity
- international
- Verification status
- Live Verified
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