Framework for meaningful engagement of external stakeholders in AI development

The use of artificial intelligence (AI) is accelerating. So is the need to ensure that AI systems are not only effective, but also fair, non-discriminatory, transparent, rights-based, accountable, and sustainable – in short, responsible. An important step for preventing and mitigating harm from AI systems is to identify and assess their impacts on human rights, so that adequate measures can be taken to address negative impacts. AI impact assessments need to include diverse voices, disciplines and lived experiences from a variety of external stakeholders. A key question inevitably arises: how can AI developers and deployers meaningfully engage stakeholders, so that their crucial input informs and shapes the AI impact assessment?

Three questions essentially come up:

1. What makes engagement ‘meaningful’?
2. What does a trustworthy engagement process look like?
3. How to distinguish the meaningful from the meaningless?

In an appeal to see that the time and energy invested in the engagement leads to concrete results, both convenors (such as public institutions and private sector companies) as well as potential participants in such engagement processes increasingly expect clear answers to the above questions.

This Framework attempts to provide some answers. ECNL in collaboration with numerous contributors from all sectors, have been developing a Framework for meaningful engagement of external stakeholders in the context of impact assessments of AI systems.