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Another significant advantage is in identifying and mitigating bias. We touched on this earlier, but it's worth reiterating. AI systems are trained on data, and if that data reflects existing biases, the AI will likely perpetuate those biases. With explainability, you can examine the data the AI is using and see if it's over-representing certain demographics or under-representing others. For example, if an AI used to detect skin cancer is trained mostly on data from a specific ethnic group, it might be less accurate for patients from other backgrounds. Explainability helps identify these disparities so that developers can adjust the data and retrain the AI, leading to more equitable outcomes.
Firstly, keep a close watch on the *financial news*. What are the headlines saying? Are companies reporting solid earnings? Are there new government policies that could impact the market? Secondly, understand the *economic indicators*. This includes things like GDP growth, inflation rates, and interest rates. These numbers give you a sense of the overall health of the economy, which in turn affects the stock market. And finally, don’t ignore the global landscape. What’s happening in other major economies? Are there any international conflicts or trade disputes? These events can all have an impact on the **_PSEi_**. The key is to piece together all these different pieces of information to get a clearer picture of the *market trends*.
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