Using AI to manage minimum income benefits and unemployment assistance: Opportunities, risks and possible policy directions
While means-tested benefits such as minimum income benefits (MIB) and unemployment assistance (UA) are an essential safety net for low-income people and the unemployed, incomplete take-up is the rule rather than the exception. Building on desk research, open-ended surveys and semi-structured intervi...
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| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Paris
OECD Publishing
2024
|
| Series: | OECD Artificial Intelligence Papers
no.21 |
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | While means-tested benefits such as minimum income benefits (MIB) and unemployment assistance (UA) are an essential safety net for low-income people and the unemployed, incomplete take-up is the rule rather than the exception. Building on desk research, open-ended surveys and semi-structured interviews, this paper investigates the opportunities and risks of using artificial intelligence (AI) for managing these means-tested benefits. This ranges from providing information to individuals, through determining eligibility based on pre-determined statutory criteria and identifying undue payments, to notifying individuals about their eligibility status. One of the key opportunities of using AI for these purposes is that this may improve the timeliness and take-up of MIB and UA. However, it may also lead to systematically biased eligibility assessments or increase inequalities, amongst others. Finally, the paper explores potential policy directions to help countries seize AI's opportunities while addressing its risks, when using it for MIB or UA management. |
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| 520 | |a While means-tested benefits such as minimum income benefits (MIB) and unemployment assistance (UA) are an essential safety net for low-income people and the unemployed, incomplete take-up is the rule rather than the exception. Building on desk research, open-ended surveys and semi-structured interviews, this paper investigates the opportunities and risks of using artificial intelligence (AI) for managing these means-tested benefits. This ranges from providing information to individuals, through determining eligibility based on pre-determined statutory criteria and identifying undue payments, to notifying individuals about their eligibility status. One of the key opportunities of using AI for these purposes is that this may improve the timeliness and take-up of MIB and UA. However, it may also lead to systematically biased eligibility assessments or increase inequalities, amongst others. Finally, the paper explores potential policy directions to help countries seize AI's opportunities while addressing its risks, when using it for MIB or UA management. | ||
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| spelling | Verhagen, Annelore VerfasserIn aut Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions Annelore, Verhagen Paris OECD Publishing 2024 1 Online-Ressource (53 Seiten) 21 x 28cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OECD Artificial Intelligence Papers no.21 While means-tested benefits such as minimum income benefits (MIB) and unemployment assistance (UA) are an essential safety net for low-income people and the unemployed, incomplete take-up is the rule rather than the exception. Building on desk research, open-ended surveys and semi-structured interviews, this paper investigates the opportunities and risks of using artificial intelligence (AI) for managing these means-tested benefits. This ranges from providing information to individuals, through determining eligibility based on pre-determined statutory criteria and identifying undue payments, to notifying individuals about their eligibility status. One of the key opportunities of using AI for these purposes is that this may improve the timeliness and take-up of MIB and UA. However, it may also lead to systematically biased eligibility assessments or increase inequalities, amongst others. Finally, the paper explores potential policy directions to help countries seize AI's opportunities while addressing its risks, when using it for MIB or UA management. Employment Governance Social Issues/Migration/Health Australia Austria Belgium Brazil Canada Colombia Costa Rica Czechia Denmark Estonia Finland Germany Netherlands New Zealand Sweden United Kingdom |
| spellingShingle | Verhagen, Annelore Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions Employment Governance Social Issues/Migration/Health Australia Austria Belgium Brazil Canada Colombia Costa Rica Czechia Denmark Estonia Finland Germany Netherlands New Zealand Sweden United Kingdom |
| title | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions |
| title_auth | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions |
| title_exact_search | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions |
| title_full | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions Annelore, Verhagen |
| title_fullStr | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions Annelore, Verhagen |
| title_full_unstemmed | Using AI to manage minimum income benefits and unemployment assistance Opportunities, risks and possible policy directions Annelore, Verhagen |
| title_short | Using AI to manage minimum income benefits and unemployment assistance |
| title_sort | using ai to manage minimum income benefits and unemployment assistance opportunities risks and possible policy directions |
| title_sub | Opportunities, risks and possible policy directions |
| topic | Employment Governance Social Issues/Migration/Health Australia Austria Belgium Brazil Canada Colombia Costa Rica Czechia Denmark Estonia Finland Germany Netherlands New Zealand Sweden United Kingdom |
| topic_facet | Employment Governance Social Issues/Migration/Health Australia Austria Belgium Brazil Canada Colombia Costa Rica Czechia Denmark Estonia Finland Germany Netherlands New Zealand Sweden United Kingdom |
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