Telecommunication Engineering Centre, which firms up standards for communication products sold in the country, has started a consultation process to develop a framework for fair assessment of (AI) and (ML) systems to build public trust.

The technical arm of the has invited inputs from the public by March 8 to develop the framework to resolve various ethical, social and legal issues that may arise from AI and ML systems.

TEC said and applications are increasingly being used in all domains such as healthcare, agriculture, smart cities, smart homes, finance, defence, transport, logistics, natural language processing, surveillance, and so on.

“With the aim to build public trust in AI/ ML Systems, TEC is working on Voluntary Fairness Assessment of AI/ ML Systems. Accordingly, TEC is initiating stakeholder consultations and has invited suggestions for framing procedures for assessing fairness for different types of AI/ ML Systems,” TEC said in a statement.

Various government organisations are also using AI/ ML systems for delivery of public services and e-governance and bias in AI/ ML systems raise various “ethical, social and legal issues”, it said.

“While the users expect these systems to be fair in their outcomes, a biased AI/ ML System prefers a certain demography while discriminating against others. When AI/ ML Systems are used for e-governance or by the judiciary, checking for their fairness would become a legal requirement.

“Therefore, one important requirement of Responsible AI is that the AI/ ML Systems should be unbiased or fair,” TEC said.

The telecom engineering body added, “As these systems are being used in all aspects of our lives, the initiative of TEC would benefit every citizen of the country.”

“Startups and MSMEs in particular and even large enterprises will benefit as their products will be more credible and acceptable if they are assessed and certified by a neutral government agency such as TEC,” the statement said.

(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)

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