In this episode of Generative AI 101, we’re exploring the various flavors of generative AI bias and inaccuracy—those pesky issues that make your AI sound like it’s stuck in a 1950s sitcom. From data-driven biases baked into AI’s training to sneaky algorithmic quirks and the all-too-human flaws we project onto our creations, we explore how to recognize and mitigate these pitfalls. Learn how strategic prompting can tone down clichés and overgeneralizations, making your AI smarter and fairer. Plus, we’ll share tips on using tools like IBM’s AI Fairness 360 to keep your AI from going rogue.

Connect with Us: If you enjoyed this episode or have questions, reach out to Emily Laird on LinkedIn. Stay tuned for more insights into the evolving world of generative AI. And remember, you now know more about generative AI bias and inaccuracy than you did before!

Connect with Emily Laird on LinkedIn