A recent study conducted by the Centre for Responsible AI at IIT Madras and the Vidhi Centre for Legal Policy advocates for participatory approaches in AI development and governance, emphasizing the importance of stakeholder involvement.

The research stresses the necessity of participatory governance in AI, supported by real-world use cases and interdisciplinary collaboration.

The study's model promotes stakeholder engagement throughout the AI lifecycle, from design to implementation and oversight.

Involving diverse communities in AI development is crucial to mitigate risks such as bias and privacy violations, ultimately fostering public trust in these technologies.

As automation increases across various sectors, the potential for opaque decision-making processes raises concerns about accountability.

Facial Recognition Technology (FRT) poses risks of societal bias and privacy concerns, making stakeholder engagement essential for its fair deployment.

The study examined two case studies: one in law enforcement and another in healthcare, highlighting the potential for bias in FRT and inaccuracies in large language models.

In healthcare, involving doctors, patients, and developers can ensure that AI systems are accurate, equitable, and help reduce disparities.

Increasing transparency and accountability in AI is vital for building public trust and facilitating broader acceptance of these technologies.

Ethical considerations must be prioritized throughout the AI development process, ensuring fairness and accountability are addressed at every stage.

The report highlights the absence of a clear framework for implementing participatory principles in AI governance, suggesting a sector-agnostic approach to identify and involve stakeholders.

Experts like Shehnaz Ahmed from the Vidhi Centre for Legal Policy argue that participatory processes can significantly enhance AI solutions in critical areas such as facial recognition and healthcare.