The problem, however, is that there are lots of examples of AI algorithms producing racist or misogynist results, leaving companies exposed to the risk of being sued for hiring discrimination.

Detection often starts with cues users pick up during interactions, unexpected outcomes, repetitive patterns, or ...

Another example of an AI algorithm where indications of bias occurred was the risk-assessment software COMPAS (Correctional Offender Management Profiling for Alternative Sanctions), which was used ...

Artificial intelligence (AI) models are computer programs designed to mimic human intelligence. Once an algorithm is trained on massive datasets to recognize patterns, make decisions, and generate ...

AI algorithms can perpetuate and amplify existing biases in the data on which they are trained, resulting in unequal treatment of particular groups based on race, gender, or other characteristics.

Here we will look at real-world examples, good and bad, that illustrate the benefits of transparent AI and the dangers of obscure or unexplainable algorithms.

These examples illustrate a fundamental truth: Companies that defy standard practices in algorithm development and deployment can achieve market dominance and access new opportunities. Navigating ...

For example, a predictive AI algorithm can identify which patients with pneumonia are most likely to require hospitalization. Let’s say you’re the patient.

I’m on a personal quest to make AI more trustworthy Adobe By Amber Nigam Nov. 13, 2024 Nigam is the co-founder and CEO of basys.ai, a generative AI-driven health care company.