Why artificial intelligence (AI) systems are not always considered trustworthy?(1 point)
Responses
1. Lack of transparency: AI systems can often be seen as "black boxes," meaning that it is difficult to understand how they came to a certain conclusion or recommendation. This lack of transparency can lead to distrust among users.
2. Bias: AI systems can inherit bias from the data they are trained on, which can result in discriminatory or unfair outcomes. This can make users question the reliability and fairness of AI systems.
3. Errors and mistakes: AI systems are not infallible and can make mistakes or errors in their decision-making processes. This can lead to mistrust among users who may question the accuracy and reliability of AI systems.
4. Lack of accountability: Since AI systems are created by developers and programmers, there may be a lack of accountability in case something goes wrong. This lack of accountability can make users hesitant to trust AI systems.
5. Insecurity: AI systems can be vulnerable to cyber attacks, hacking, and manipulation, which can compromise the trustworthiness of the system. Users may be concerned about the security of their data and information when interacting with AI systems.