Artificial intelligence (AI) will be increasingly incorporated into business processes, as suggested by IDC’s forecast that Asia Pacific spending on AI systems will rise from US$17.6 billion in 2022 to around US$32 billion in 2025.
While AI can help improve efficiency and provide customer insights, it could also cause biased decision-making. For example, studies have shown instances of AI-powered lending algorithms automatically rejecting loan applications from minorities.
This is why business analytics software and services firm SAS Institute believes organisations should embrace responsible AI as they embed intelligence into their decision-making processes. Responsible AI is the practice of designing, developing, and deploying AI with good intentions to empower employees and businesses, and fairly impact customers and society.
“Organisations should infuse responsible AI capabilities across the entire analytics lifecycle. This will not only help them achieve their corporate social responsibility goals, but also drive business profitability. A recent McKinsey study found that leaders in digital trust [which hinges on responsible AI] are more likely to see revenue and EBIT growth of at least 10% annually,” says Lim Hsin Yin, managing director for Singapore at SAS Institute, during a media roundtable yesterday.
To help financial institutions adopt responsible AI in a repeatable manner, SAS is working with the Monetary Authority of Singapore (MAS)-led Veritas consortium to integrate and operationalise the Veritas toolkit with the SAS Viya platform.
The Veritas initiative is part of Singapore’s National AI Strategy that aims to provide financial institutions with a verifiable way to incorporate principles of fairness, ethics, accountability and transparency.
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By integrating the SAS Viya analytics lifecycle framework with the Veritas toolkit, analytical models can be assessed for fairness through out-of-the-box natural language generation and workflow capability in SAS Viya.
The SAS Viya framework also extends to other areas of AI governance, including explainability, auditability, accountability and transparency. It also interacts with open source to enhance automation and governance.
“We are honoured to support MAS in implementing its AI strategy and achieving its vision to be a leader in deploying scalable, impactful AI solutions. We see this work as very beneficial for financial institutions, given that regulatory and audit reports require both accuracy and timeliness in submissions,” says Lim.
Reggie Townsend, SAS Institute’s chief data ethics practice officer, adds: “The need for a regulatory framework to capitalise on the promise of AI while mitigating risks is not only important but urgent in these times. Both technology providers and regulators have a critical role to play to ensure that AI development is centred around people to ensure a positive impact on our society.”
