Bias and Fairness in AI: Uncovering the Encoded Biases and Ensuring Ethical Decision-Making

Bias and Fairness in AI
Bias and fairness in AI are critical issues that demand attention. AI algorithms can inadvertently encode biases, leading to discriminatory outcomes. Ensuring fairness in AI decision-making is essential to mitigate harm and uphold ethical standards. Transparency, diverse data, and algorithmic fairness techniques play crucial roles in addressing biases and promoting a more inclusive and equitable AI ecosystem.

The Sunk Cost Fallacy

The sunk cost fallacy
In the realm of decision-making, there lurks a deceptive mental trap known as the sunk cost fallacy. It's a subtle and insidious bias that tugs at our emotions, whispering in our ears to persist even when it defies reason. The sunk cost fallacy tricks us into valuing what's already been invested over what truly matters in the present moment.