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6.2: Protecting Personal Privacy

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    207243
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    As I covered in the first post in this series, AI systems have the potential to perpetuate and amplify biases in data, leading to discrimination against certain groups or individuals. This is a serious concern when it comes to privacy, as these biases can lead to the exclusion or mistreatment of individuals based on their personal characteristics. It can lead to members of the public being surveilled based on skin colour, place of residence, or other factors which are part of the data used when training the models. These concerns extend into many areas of the AI industry including facial and affect recognition, which I’ll talk about in a later post.

    The storage of personal data in AI training data is also a significant privacy concern. In the creation of these models, personal data has been collected without explicit consent or knowledge of the individuals affected, and there may be inadequate protections in place to ensure that this data is used ethically and responsibly. Data breaches and cyber attacks also a huge risk for AI systems. Several weeks ago, OpenAI experienced a breach due to a bug in one of their code libraries which revealed the first and last names and email addresses of ChatGPT Plus subscribers, along with financial details.


    6.2: Protecting Personal Privacy is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by LibreTexts.

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