🎧 Watch Video on YouTube : https://www.youtube.com/@shreyas768

As AI continues to shape decisions in hiring, finance, healthcare, and beyond, there's a growing concern about algorithmic bias—when machines learn from flawed data and end up making unfair or discriminatory decisions.

In this episode, we break down:

• What algorithmic bias really means

• How biased training data, flawed design, and proxy attributes contribute

• Shocking real-world examples—from biased resume screening to discriminatory mortgage rates

• Actionable strategies to reduce bias in AI systems

We’ll also explore the importance of diverse datasets, human oversight, and inclusive development teams in building fair, transparent, and responsible AI.

🌐 Website: https://www.shreyshukla.com/
💼 LinkedIn: https://www.linkedin.com/in/shreyas768/
🎧 Audiobooks on Spotify: https://open.spotify.com/show/1dUzmPWk2Ua9Q0uDCJpR3U
🎵 Audiobooks on YouTube Music: https://music.youtube.com/channel/UCxsa4SRe-CsQFDa09XHy9cg?si=9rT2A1C6o1o4etBa