AI systems can inherit or amplify biases present in their training data or algorithms, leading to unfair or discriminatory outcomes. For instance, an AI model used in hiring could prefer candidates from a certain demographic over others, not because of their qualifications but due to biased training data.
It is not safe to assume that results from AI are reliable. This is true due to the possibility of inaccuracies in the AI's training data or potential problems that the algorithm may have run into when processing the data that it was trained on. AI is known to generalize based on trends that it has observed, which can result in broad generalization that are inaccurate. It is very important to remember that these algorithms are fallible and to validate results from AI to mitigate any concerns of reliability.
Hallucinations refer to instances where generative AI models produce false or nonsensical information and depict it as if it were true. This can be particularly problematic since the AI will often confidently present the information as fact, which can be particularly problematic in the case of educational content and medical information where accuracy is critical.
AI poses an array of ethical challenges, including questions of accountability (who is responsible when AI makes a wrong decision?), autonomy (to what extent should AI be allowed to act without human oversight?), copyright (who legally owns the content created by AI when this is not outlined in a software's terms and conditions), and many more ethical concerns.
AI systems require access to vast amounts of data to train and operate effectively. This raises concerns about privacy, as we are unsure of what (if any) personal or otherwise sensitive information the algorithm had access to during the training process. Also, it is worth being cautious about the potential for sensitive information shared with AI by users to be misused, either through data breaches or by design, for surveillance or other invasive purposes.
This is not an exhaustive list of the potential risks of AI. Rather, this list is meant to serve as a reminder of that there are risks involved in using AI and to highlight some key problems that AI users may run into. It is important to do your own research on the topic to better understand the various risks that accompany the benefits that AI provides.