This episode of The Healthier Tech Podcast jumps straight into the surprising ways algorithmic bias shapes financial decisions, hiring processes, and even healthcare outcomes. If you have ever wondered how an invisible line of code could influence real life opportunities, this is the deep dive you will want to hear.

We explore how AI systems quietly inherit decades of human bias through historical data and why this leads to unfair credit scores, skewed hiring recommendations, and medical risk assessments that miss the mark for entire groups of people.

Key highlights include

• The real credit scoring controversy where women were consistently assigned lower limits despite identical financial profiles

• A hiring model that downgraded resumes containing women centered keywords and how that mistake went unnoticed

• A widely used hospital risk tool that underestimated the needs of Black patients due to flawed data assumptions

• Why people tend to trust algorithmic decisions more than human ones and how this psychological blind spot opens the door to harm

• What companies are doing today to clean up biased datasets and build AI that supports fairness instead of undermining it

If you care about digital wellness, tech ethics, and how AI intersects with everyday health and financial wellbeing, this episode brings clarity and practical insight without the jargon.

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