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    1. Generative AI models are trained on vast amounts of internet data. This data, while rich in information, contains both accurate and inaccurate content, as well as societal and cultural biases. Since these models mimic patterns in their training data without discerning truth, they can reproduce any

      this part of the text highlights why ai might be inaccurate and biased in most cases stating that it contains a large amount of information that might be accurate and inaccurate ,it is also a way to emphasizes the purpose of the article.

    2. . These generative AI biases can have real-world consequences. For instance, adding biased generative AI to “virtual sketch artist” software used by police departments could “put already over-targeted populations at an even increased risk of harm ranging from physical injury to unlawful imprisonment”

      it is really overwhelming to know that if we used biased and inaccurate ai in our society how much of damage it might cause.

    1. Others have been tempted to argue that implicit bias is overrated (maybe even justified) and that minorities simply need to toughen up.

      it is surprisingly to find that peoples still try to disprove implicit bias despite there being numerous researches and daily every day examples clearly observed still people try to avoid this idea , implicit bias is something deep within every person , you will not be aware of it consciously but your actions will show it. but it will be also interesting to see the proves and claims of the people who are trying to debate this matter.

    2. Take the example of the Müller-Lyer illusion. Your task is to decide whether line A or line B is the longer one.

      this is a great example used in the article to make readers really visualize what the article trying to prove and shed light to and also a good way to grab the readers attention more to the matter.