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Hacer la IA operacional en entornos del sector público restringidos
The AI boom has hit across industries, and public sector organizations are facing pressure to accelerate adoption. At the same time, government institutions face distinct constraints around security, governance, and operations that set them apart from their business counterparts. For this reason, purpose-built small language models (SLMs) offer a promising path to operationalize AI in…
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MIT Technology Review (United States) | Apr 16, 2026
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The unique constraints of public institutions necessitate a cautious approach to AI integration, prioritizing governance.
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Small language models can provide tailored solutions for public sector challenges without overwhelming existing systems.
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AI solutions must be critically evaluated for their ethical implications, especially in sensitive public sector environments.
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Rushing AI adoption in government may compromise security and privacy, risking public trust.
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Implementing AI in public sector can lead to increased efficiency and better service delivery for citizens.
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