Singapore businesses looking to adopt artificial intelligence (AI) technologies responsibly now can access a reference document to help them do so. The AI Ethics & Governance Body of Knowledge (BoK) is touted to provide a reference guide for business leaders and IT professionals on the ethical aspects related to the development as well as deployment of AI technologies.
Launched by industry group Singapore Computer Society (SCS), the BoK was put together based on the expertise of more than 60 individuals from multi-disciplinary backgrounds, with the aim to aid in the “responsible, ethical, and human-centric” deployment of AI for competitive advantage. It encompasses use cases to outline the positive and negative outcomes of AI adoption, and looks at the technology’s potential to support a “safe” ecosystem when utilised properly.
The BoK was developed based on Singapore’s latest Model AI Governance Framework, which was updated in January 2020, and will be regularly updated as the local digital landscape evolved, said SCS during its launch Friday.
Founded in 1967, the industry group has more than 42,000 members and offers a range of services to support its members, including training and development and networking opportunities. SCS comprises 11 chapters including AI and robotics, cybersecurity, and Internet of Things, as well as five interest groups that include blockchain and data centre.
Noting that AI sought to inject intelligence into machines to mimic human action and thought, SCS President Chong Yoke Sin noted that rogue or misaligned AI algorithms with unintended bias could cause significant damage. This underscored the importance of ensuring AI was used ethically.
“On the other hand, stifling innovation in the use of AI will be disastrous as the new economy will increasingly leverage AI,” Chong said, as she stressed the need for a balanced approach that prioritised human safety and interests.
Speaking during SCS’ Tech3 Forum, Singapore’s Minister for Communications and Information S. Iswaran further underscored the need to build trust with the responsible use of AI in order to drive the adoption and extract the most benefits from the technology.
“Responsible adoption of AI can boost companies’ efficiencies, facilitate decision-making, and help employees upskill into more enriching and meaningful jobs,” Iswaran said. “Above all, we want to build a progressive, safe, and trusted AI environment that benefits businesses and workers, and drives economic transformation.”
The launch of a reference guide would provide businesses access to a counsel of experts proficient in AI ethics and governance, so they could deploy the technology responsibly, the minister said.
“[The BoK] will guide the development of curricula on AI ethics and governance. It will also form the basis of future training and certification for professionals — both in the ICT and non-ICT domains. These professionals will serve as advisors for businesses on the responsible implementation of AI solutions,” he said.
Chong noted that the focal point was the individual using or affected by AI.
“It is not merely the technology and methodologies, but the human that should be at the centre of our analysis and decision-making,: she said. “Around this core are secondary principles and values, such as auditability and robustness, that help us achieve this core set of putative global norms for ethical AI.”
Alongside the release of the reference guide, SCS also announced a partnership with Nanyang Technological University (NTU) to develop an AI ethics and governance certification course for professionals.
Slated for launch next year, the course aimed to train and certify professionals to help and advise organisations on AI ethics and governance. It would be incorporated into NTU’s upcoming MiniMasters programme in AI and AI ethics, designed to guide participants in understanding and solving problems brought about by the adoption of AI.
Singapore in May announced plans to develop a framework to ensure the “responsible” adoption of AI and data analytics in credit risk scoring and customer marketing. Two teams comprising banks and industry players were tasked to establish metrics to help financial institutions ensure the “fairness” of their AI and data analytics tools in these instances. A whitepaper detailing the metrics was scheduled to be published by year-end, along with an open source code to enable financial institutions to adopt the metrics.