- PPF Points
- 3,538
I was astounded by how intelligent and beneficial AI tools appeared when I first began researching them. But as time went on, I became aware of something a little troubling—at times, the responses seemed strange or even prejudiced. I came to the realization that AI is only as good as the data it is trained on at that point. Biases in the data may cause the AI to reflect those biases as well, which can be a major issue, particularly when it comes to hiring, lending, or law enforcement.
I think we need to be really deliberate about how we train AI if we want to make it more equitable. Making sure the data is inclusive and diverse is the first step. For instance, I would want to incorporate comments from people from a variety of backgrounds, languages, and geographical areas—not just one specific group—into an AI model that analyzes customer feedback. In this manner, the AI gains a more impartial perspective on the world.
Frequent auditing is also beneficial. When I tested a chatbot I was working on, I asked it the same question in different ways, and occasionally it would respond with entirely different answers. That indicated to me that there was a data-based inconsistency. We can identify unfair patterns and retrain the system by observing how AI acts in real-world situations.
human oversight is key. AI shouldn't be making final decisions on its own, especially in areas that affect people’s lives. I always try to remember that AI is a tool, not a judge. It can assist us, but it shouldn’t replace human judgment and ethics.
If we keep our eyes open and commit to fairness at every step, I think we can make AI not only smart but also just and trustworthy.
I think we need to be really deliberate about how we train AI if we want to make it more equitable. Making sure the data is inclusive and diverse is the first step. For instance, I would want to incorporate comments from people from a variety of backgrounds, languages, and geographical areas—not just one specific group—into an AI model that analyzes customer feedback. In this manner, the AI gains a more impartial perspective on the world.
Frequent auditing is also beneficial. When I tested a chatbot I was working on, I asked it the same question in different ways, and occasionally it would respond with entirely different answers. That indicated to me that there was a data-based inconsistency. We can identify unfair patterns and retrain the system by observing how AI acts in real-world situations.
human oversight is key. AI shouldn't be making final decisions on its own, especially in areas that affect people’s lives. I always try to remember that AI is a tool, not a judge. It can assist us, but it shouldn’t replace human judgment and ethics.
If we keep our eyes open and commit to fairness at every step, I think we can make AI not only smart but also just and trustworthy.
