Scaling AI Systems: Overcoming Data Quality Challenges

Today is Digital Social Impact Update Friday! 🎉📱

Deepika Sandeep, Director of AI at Honeywell, teaches us about the risks in AI systems:

🔍 Scaling AI Systems: Overcoming Data Quality Challenges 🤖

As AI becomes mainstream, scaling these systems presents significant challenges, mainly related to data quality. 📈 Here are some key issues:

🔸 Data Bias: Without diverse representation, AI systems, such as facial recognition, struggle to accurately identify people of different races, genders, and skin colors. Ensuring unbiased data is crucial for effective AI training. 🧑🏾👩🏻👨🏼‍🦰

🔸 Outliers: The definition of outliers varies across domains, making it crucial to identify and manage them appropriately to maintain data integrity. 🔍📊

🔸 Noisy and Missing Data: Data collection, especially from remote locations, often results in missing or erroneous data. Addressing these issues is essential for reliable AI performance. 📡🔧

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