🎧 Watch Video on YouTube : https://www.youtube.com/@shreyas768As 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 meansHow biased training data, flawed design, and proxy attributes contributeShocking real-world examples—from biased resume screening to discriminatory mortgage ratesActionable strategies to reduce bias in AI systemsWe’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

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