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SINGAPORE \u2013 Researchers in Singapore are building an artificial intelligence tool that can predict how economic policies such as cash handouts may boost the economy.<\/p>\n
The tool forecasts economic outcomes, such as whether people will save or spend their money, with far greater accuracy than traditional simulation models. This allows policymakers to test more alternative policies to achieve the desired economic outcome.<\/p>\n
Developed by four researchers at Nanyang Technological University, it is among 14 projects worldwide to receive funding from OpenAI as part of the company\u2019s commitment to promoting economic opportunity and societal resilience through AI.<\/p>\n
The 14 projects were selected from over 400 submissions to OpenAI\u2019s call for proposals in April.<\/p>\n
The NTU team, led by Nanyang Business School Provost\u2019s Chair Professor in Information Systems Hyeokkoo Eric Kwon, will receive US$100,000 (S$126,800).<\/p>\n
He said the money will go towards developing and testing the tool, which has not been named, over the next six months.<\/p>\n
The NTU team\u2019s AI prediction system is trained on real transaction data from more than one million users of a South Korean mobile budgeting app, which Kwon declined to name.<\/p>\n
The data contains information on how much users spend, which retailers they spend at, and how much monthly income they received between 2023 and 2025.<\/p>\n
The app obtains the data by tracking notifications, messages and e-mails that are sent to users by banks when transactions are made. Names and bank account numbers are removed. Spending amounts, income and purchase times are also grouped into broader ranges.<\/p>\n
The NTU team\u2019s AI tool ingests only the anonymised data to prevent the identification of users.<\/p>\n
\u201cThere should never be a situation where the data can only be matched to one profile. Depending on the level of sensitivity of the data, a profile is sufficiently anonymised if a minimum of three, five or 10 users share those exact same characteristics,\u201d said Kwon.<\/p>\n
AI agents are then used to simulate how households may respond to a proposed government policy.<\/p>\n
For example, if the government is planning to give $100 in cash vouchers to every citizen, the system aims to estimate how much additional spending it could generate, what it would be spent on, and how the outcome would change with a different policy, said Kwon.<\/p>\n
As AI understands complex patterns and has a vast knowledge of human behaviour, it can predict human behaviour better than traditional simulations based on deterministic rules, he said.<\/p>\n
\u201cQualitative interviews and surveys are conducted to set these rules, but there is often a gap between how people actually behave and how they respond in surveys,\u201d said Kwon, adding that the complex relationship between factors such as income and age cannot be represented in traditional simulation models.<\/p>\n
To ensure that the system does not hallucinate and can accurately predict real-world outcomes, it will be validated against real spending data in 2025.<\/p>\n
This data was recorded before and after the South Korean government distributed two tranches of cash handouts in July and September 2025. These handouts had to be spent at eligible retailers by November 2025.<\/p>\n
Half of the NTU team\u2019s US$100,000 funding will be in cash, while the other half will be in credits for OpenAI\u2019s AI model subscription plans.<\/p>\n
By February 2027, the NTU researchers aim to have the tool work for any population.<\/p>\n
The tool, which will be made open-source, will also be able to analyse sentiments such as interests and political views to improve prediction accuracy and explain how it arrives at its conclusion.<\/p>\n<\/div>\n
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SINGAPORE \u2013 Researchers in Singapore are building an artificial intelligence tool that can predict how economic policies such as cash handouts may boost the economy….<\/p>\n","protected":false},"author":1,"featured_media":84704,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"","fifu_image_alt":"","footnotes":""},"categories":[2611],"tags":[],"class_list":["post-84703","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-buzz-headlines","wpcat-2611-id"],"brizy_media":[],"_links":{"self":[{"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/posts\/84703","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=84703"}],"version-history":[{"count":0,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/posts\/84703\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=\/wp\/v2\/media\/84704"}],"wp:attachment":[{"href":"https:\/\/sgbuzz.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=84703"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=84703"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sgbuzz.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=84703"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}