Artificial Intelligence in Social Security Organizations
Zaber, Moinul, Casu, Oxana and Brodersohn, Ernesto (2024). Artificial Intelligence in Social Security Organizations. International Social Security Association.
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Author Zaber, Moinul
Casu, Oxana
Brodersohn, ErnestoTitle Artificial Intelligence in Social Security Organizations Publication Date 2024 Place of Publication Genebra Publisher International Social Security Association Pages XLIII, 43 Language eng Abstract Social security institutions worldwide encounter formidable obstacles in delivering quality services in an increasingly challenging environment. Challenges include limited resources and infrastructure, with escalating demands, which hinder their ability to provide comprehensive support to their members and overall target population. Overcoming these hurdles necessitates innovative strategies and international cooperation to ensure comprehensive service delivery as well as equitable and sustainable social security provision. This is where Artificial Intelligence (AI) becomes a critical and enabling technology in social security. It can help significantly depressurize resources to focus on specific segments of the population, help gain insights into patterns previously undetected, and in general improve service delivery. The rise of AI capable of leveraging diverse data types to construct efficient tools, or glean insights, has demonstrated the potential to revolutionize service delivery and decision-making processes within institutions, notably at social security organizations. Integrating AI and data facilitates proactive and automated delivery of services. Yet, owing to AI's developmental stage as a science, and deploying diverse AI tools within institutional frameworks proves challenging, the primary hurdle stems from the nature of the data itself – the fundamental ingredient of AI. At social security institutions, the imperative for high-quality data, contextually relevant models, and stringent AI safety measures becomes paramount. To avert the peril of underutilizing AI, institutions are striving to implement AI tools in different ways. From leveraging intelligent chatbots for improved service delivery, to data-centric decision-making, or by leveraging machine learning, institutions must adapt to the use of AI as part of the new paradigms of digital transformation in order to fulfil their mission objectives. This article outlines the diverse facets of AI-empowered digital transformation, which is essential for social security organizations, emphasizing the importance of robust data quality, context-sensitive models and prioritizing safety standards. By focusing on these elements, it paves the way for AI-focused automation, ensuring that social security institutions harness AI effectively while safeguarding against potential risks. This report examines different factors that can help social security institutions harness AI. It will look at advantages and challenges in onboarding AI projects to aid social security institutions to embrace it as a key component of their technology portfolio. Keyword Artificial Intelligence
Social security
Machine Learning
Data QualityCopyright Holder International Social Security Association and United Nations University Copyright Year 2024 Copyright type Creative commons -
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