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What is biased data ?

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By Team EasyExamNotes

Biased data refers to information that’s skewed or incomplete in a way that misrepresents the reality it’s supposed to depict.

Here’s how biased data can happen:

  • Selection bias: This occurs when the data collection process isn’t random or representative. Imagine a survey on social media habits, only reaching people who actively post. It wouldn’t capture the whole picture.
  • Data collection methods: The way data is gathered can introduce bias. For instance, if a creditworthiness score relies heavily on factors like zip code, it might disadvantage people from certain neighborhoods.
  • Historical bias: Data that reflects past prejudices can perpetuate them. For example, an algorithm trained on biased news articles might reinforce stereotypes.

The consequences of biased data can be serious. It can lead to unfair or inaccurate decisions in areas like loan approvals, job applications, or even criminal justice.

Here are some additional points to consider:

  • Machine learning algorithms are particularly susceptible to biased data, as they can amplify existing biases in the data they’re trained on.
  • Biased data can have a negative impact on individuals, businesses, and even entire societies.
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