Generative artificial intelligence is transforming technological interaction by creating new content based on learned patterns. However, this advancement relies on the analysis of large volumes of data, which introduces significant privacy risks if adequate measures are not implemented during model training. The main dangers include the unauthorized processing of personal data, the generation of deceptive content for identity spoofing, and a lack of algorithmic transparency. To mitigate these effects, it is essential to adhere to the principles of transparency and explainability, ensuring that individuals understand how their information is used and protecting their human rights in the face of these technologies. This issue is crucial for open data, as it underscores the need for responsible governance of both public and private information. By integrating ethical practices, security, and clear policies, we can promote an ecosystem where technological innovation coexists with data protection. This requires developers and regulators to collaborate to ensure that data access and use respect fundamental rights, thereby fostering the trust necessary for the open and secure exchange of information.
Source: eluniversal.com.mxPublished on 2024-10-22
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