Datos sintéticos y hasta "gemelos digitales": cómo la IA irrumpe en el mercado de encuestas e incluso en el Censo

Artificial intelligence is transforming research and statistical production by generating “digital twins” and automating processes, which enables the prediction of responses and the optimization of timeframes. However, this efficiency carries significant risks related to algorithmic biases, ethical dilemmas, and the potential distortion of social dynamics, leading consulting firms to exercise caution regarding the validity and legitimacy of synthesized data compared to real human opinion. In the public sector, institutions such as the National Statistics Institute (INE) have integrated these technologies to improve efficiency in censuses and economic indices, reducing dependence on manual data collection. Although greater precision and cost savings have been achieved, institutions maintain a hybrid approach, using AI to complement rather than entirely replace human judgment, ensuring that results uphold statistical rigor and methodological transparency. This article is relevant to open data because it illustrates how algorithm-based automation affects the transparency, traceability, and quality of public data. The transition toward administrative sources and predictive models demands new forms of auditing and information access to ensure that open datasets accurately reflect social reality, mitigating bias risks and preserving the democratic legitimacy of official statistics.

Source: gda.com
Published on 2025-09-08

Datos sintéticos y hasta "gemelos digitales": cómo la IA irrumpe en el mercado de encuestas e incluso en el Censo

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