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Algorithmic Decision-Making

Algorithmic decision-making refers to the use of computer algorithms to analyze data and make choices or predictions. These algorithms follow a set of programmed rules and models, often learning from patterns in large datasets. They can help in various domains, from recommending movies to determining credit scores. While they can improve efficiency and consistency, it's important to recognize that they can also perpetuate biases if the data they learn from is flawed. Understanding these systems is crucial as they increasingly influence our everyday decisions.

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    Algorithmic Decision Making refers to the use of computer algorithms to make choices or predictions based on data. Instead of humans making decisions, computers analyze large amounts of information to identify patterns and trends. This process is used in various fields, such as finance for credit scoring, healthcare for diagnosing diseases, and online platforms for personalizing user experiences. While it can lead to efficient and unbiased decisions, it also raises questions about transparency, accountability, and fairness, as algorithms can reflect the biases present in the data they use.