Machine Learning

How Do You Handle Bias in ML Training?

Vatsal Ghiya, CEO and co-founder of the Shaip in the special guest feature shared some insights on bias in machine learning. Additionally, he also stressed the reason behind biases in AI and how to eliminate bias in AI/ML models.

The Key Take-Aways from Article are:

  • From restaurant suggestions to service ticket resolution, AI chatbot is increasingly being put to good use across industries such as healthcare, banking, and finance, and fixing wages gaps. With a large number of use cases what becomes inevitable is fairness associated with the entire process.
  • Bias in the AI model occurs during the training phases where AI experts feed volumes of data with certain inclinations and preferences. Particularly there are two types of biases, first cognitive bias and second are, biases that occur due to lack of data. 
  • But, the good news is that biases in AI models can be eliminated by using the right set of data along with real-time data monitoring and representative data models. As it is dominating our daily lives, it’s eventually important to be careful with our input to maintain quality.

Read the full article here:

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