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Bad Data Exists. What Can AI Do About It?

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          🞛 This publication is a summary or evaluation of another publication 🞛 This publication contains editorial commentary or bias from the source
It's no surprise to anyone who works with data—it's messy. In every industry and every business, there are data anomalies and issues that can impact the story data tells.
The article from Forbes Technology Council, published on April 30, 2025, discusses the pervasive issue of bad data in AI systems and explores potential solutions. It highlights that bad data, including inaccurate, incomplete, or biased data, can severely impact the performance and reliability of AI models. The article suggests several strategies to mitigate these issues, such as implementing robust data validation and cleaning processes, using advanced algorithms to detect and correct errors, and fostering a culture of continuous data quality improvement. Additionally, it emphasizes the importance of human oversight and ethical considerations in managing data to ensure AI systems remain trustworthy and effective.

Read the Full Forbes Article at:
[ https://www.forbes.com/councils/forbestechcouncil/2025/04/30/bad-data-exists-what-can-ai-do-about-it/ ]