If a machine-learning model is trained using an unbalanced dataset, such as one that contains far more images of people with lighter skin than people with darker skin, there is serious risk the ...

GAINESVILLE, Fla.--(BUSINESS WIRE)--Exactech, a developer and producer of innovative implants, instrumentation, and smart technologies for joint replacement surgery, reports a new study 1 that ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

CHICAGO--(BUSINESS WIRE)--InRule Technology ®, provider of AI-enabled, end-to-end automation for the enterprise, today introduced bias detection features within xAI Workbench, the company’s suite of ...

Japan's leading developer of new AI technologies Fujitsu accelerates its commitment to open source innovation with new projects hosted in LF AI & Data Fujitsu accelerates its commitment to open source ...

AMHERST, Mass. - Seventy years ago, science fiction writer Isaac Asimov imagined a world where robots would serve humans in countless ways, and he equipped them with built-in safeguards ¬now known as ...

Unfairly trained Artificial Intelligence (AI) systems can reinforce bias, therefore AI systems must be trained fairly. Experts say AI fairness is a dataset issue for each specific machine learning ...

Bias is machine learning’s original sin. It’s embedded in machine learning’s essence: the system learns from data, and thus is prone to picking up the human biases that the data represents. For ...

Applying machine learning to a U.S. Environmental Protection Agency initiative, researchers reveal how key design elements determine what communities bear the burden of pollution. The approach could ...

Scientists have introduced a new framework for designing machine learning algorithms that make it easier for users of the algorithm to specify safety and fairness constraints. Seventy years ago, ...