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SINGAPORE, June 16, 2021 /PRNewswire/ -- Singapore Management University (SMU)'s Centre for AI and Data Governance (CAIDG), has launched a research initiative "AI in Community" to locate AI and Big Data within communities. The outcomes would transform the relationship between AI designers and the community, such that AI technology would not only be customised for AI clients, but designed for the community in mind.
The research will identify AI as a trusted tool to nurture positive community perspectives and to improve the public's understanding of it. By exploring the way that AI and data can be a part of the community, CAIDG aims to debunk the public's perception that benefits and risks associated with AI and mass data sharing are beyond their control.
AI in Community allows people to see where AI is, what it does, why it is doing what it does, and have a say in the data it produces. For example, job applications processed by AI that are rejected without explanation, on information that was incorrect. AI in community would reveal these problems and allow timely corrections. You want your personal data to travel with you when you switch banks. AI in community can ensure this. You may be fine with having a robot assist your surgeon in performing a delicate operation, but would you go to a robot dentist? AI in community will offer opportunities to discuss and determine when AI is appropriate and when it is not. Have you been frustrated by chatbots that never seem to listen or have the right answers? AI in community can help develop chatbots that service customer need and not just streamline enquiry administration.
Professor Mark Findlay, Director, CAIDG, said, "This new initiative is especially significant for post-COVID recovery. AI In Community is designed as a people-first research commitment in CAIDG to ensure the expansion of AI and mass data use. Communities should be involved in the important stages of AI creation and deployment to ensure that technology sits comfortably within the societies in which we prefer to live. Our work on building trust and ensuring AI-to-humans accountability has clearly shown that public confidence in AI depends on answering social concerns and explaining risks."
