Tres claves para el uso responsable de los datos sintético en el mercadeo

Articles on synthetic data highlight its potential to accelerate data collection and simulate consumption scenarios, transforming market research by significantly reducing costs and time. This technology enables brands to explore hypotheses with greater flexibility, overcoming the traditional limitations of in-person methods. However, it is crucial to recognize that artificial intelligence cannot fully replicate the complexity of human experience, which demands a balanced combination of computational capability and human ethical judgment. The relevance of this topic to the field of open data and access to information lies in the critical need for validation and transparency. Since the accuracy of synthetic data inherently depends on the representativeness of the real data used to train models, there is an inherent risk if the source data are not diverse or are biased. Therefore, these data must be constantly cross-checked against verified real-world information, underscoring the importance of maintaining rigorous standards of quality and openness in the foundational datasets that feed artificial intelligence systems. Ultimately, the responsible application of this tool requires organizations to act with caution, prioritizing complementarity with human intelligence rather than its replacement. Sustainable innovation in this area depends on strategic partners who integrate data science, sector-specific expertise, and ethical principles. This ensures that operational agility does not compromise accuracy or consumer trust, establishing a framework where technology enhances but does not replace the deep understanding of human behavior.

Source: revistaeyn.com
Published on 2025-09-23

Tres claves para el uso responsable de los datos sintético en el mercadeo

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