EDITOR’ S QUESTION

Hemanta Banerjee, Vice President of Public Cloud Data Services, Rackspace Technology

When discussing talk about " responsible AI," it is referring to an overall commitment to develop, deploy, and use AI in ethical, transparent, and beneficial ways.

How is this different from accountability? Instead of the responsibility falling on individuals or groups, responsible AI is about making sure, collectively, that AI is used as a tool to support and enhance decisions instead of relying on it to make decisions. By making this clear distinction, we can ensure fairness, trustworthiness, and eliminate potential biases in the decision-making process.

It can be done in several ways. Ethical use is emphasised through model supervision, explainability, and safeguards against harmful biases, reinforcing transparency, accountability, and fairness. The AI system follows the same purchasing and internal oversight procedures as other applications to ensure consistency in deployment.

Additionally, there are strict guidelines governing the handling of confidential and sensitive information. This will ensure that AI systems comply with intellectual property protections and data regulations. Data retention, privacy and security measures follow corporate policies to ensure compliance and protect user information. Employees are also encouraged to report violations of AI standards in good faith.

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