FIs looking to deploy AI-based models should strike a balance between innovation and responsible use of technology: RBI DG

Financial institutions looking to deploy AI (artificial intelligence)-based models may consider 10 aspects, including fairness, data privacy, explainability, accountability, and human oversight, while designing AI solutions in order to strike a balance between innovation and responsible use of technology, said RBI Deputy Governor M Rajeshwar Rao.

This will also ensure fairness, prevent biases, and safeguard consumer privacy.

Rao underscored that financial institutions should ensure that the AI algorithm does not discriminate against anyone based on attributes that are otherwise considered unethical or prohibited by law.

“This can be achieved by conducting regular fairness audits of the algorithms and outcomes, including external validation, and by employing techniques to identify and rectify any unintended biases,” he said at a recent Annual Conference of the Indian Economic Association in Delhi.

‘Aware of inputs’

Rao opined that all stakeholders should be aware of what the inputs are and how the decisions are being arrived at. This should be achieved by making the algorithmic decision-making process understandable and explainable to both regulators and consumers.

He emphasised that identifying and understanding the types of errors the AI models make and continuously working to minimise false positives and negatives is the key.

“The entities should ensure consistent application of the algorithm across different situations to avoid biases or unfair advantages and to ensure equitable outcomes.

“Parameters entering the models also need to be consistent, and too frequent changes to suit specific interests need to be eschewed,” suggested Rao.

He underscored that the AI model should be designed to adhere to data protection protocols and regulations, and entities should ensure that personal information is always handled securely and responsibly.

“Clear understanding of the inputs, processes, and outputs by the entities and establishing channels for redressal of customer queries or disputes will help in promoting trust.

Governance framework

“Entities should implement a comprehensive governance framework that includes regular audits, internal reviews, and external assessments to hold individuals responsible for addressing any issues related to the AI model,” the Deputy Governor said.

He stated that the entities should include human oversight to address complex or ambiguous cases and to ensure that ethical considerations are taken into account. This would also ensure that any unintended consequences and governance issues are detected in a timely manner and addressed.

“I think that incorporating these aspects would help in developing public trust if we truly want to exploit the transformative potential of AI. Let me also point out that, in addition to institution-specific challenges, there are several geopolitical and systemic issues that would also engage us going forward.

“For example, like any other technological development of the past, the access to technology is going to be uneven among countries,” Rao said.

Advanced economies may stand to benefit more than emerging market economies due to the fact that EMEs’ have a higher share of employment in sectors such as agriculture and construction, which would inherently have fewer opportunities for the application of AI.

The Deputy Governor noted that there are only a handful of entities globally that have a large amount of data available to train GenAI models. This could give rise to questions of market power, competition, and cross-jurisdictional issues, he added.

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