This new and growing field finds large cloud platforms like Microsoft and Google joining the ranks of startups to create and roll out explainable AI systems. In the book Sapiens: A Brief History ...

This is because AI and machine learning models are good at sifting through and analyzing large datasets to detect nuances that humans often cannot see. Maybe it’s Spotify’s ability to suggest you ...

That’s providing businesses the potential to achieve significant efficiencies. However, in order to realize this potential, AI also needs to be explainable, so that humans can interact with it and ...

Danks: AI is any system that replaces, enhances or augments human cognitive labor. Much like machines replaced physical labor ...

The Howso Engine is built on instance-based learning. Capps said that unlike neural networks, AI built on IBL is fully explainable. Examples of neural network machine learning technologies include ...

As the capabilities of artificial intelligence (AI) evolve, they push the boundaries of human understanding. Instead of transparent, explainable mechanisms, many AI applications are “black boxes,” ...

Explainable AI refers to the development of artificial intelligence systems that can provide clear and understandable explanations for their decisions, actions, and reasoning. As AI technologies ...

American insurers are being urged not to drag their feet on ensuring their use of AI is “explainable,” as regulators and consumers alike begin to demand it. “It’s not like this is a future ...

Explainable artificial intelligence startup Diveplane Corp. is hoping to make an impact by putting the “humanity” back into AI after closing on a new $25 million round of funding today.

A team has developed an explainable AI model for automatic collision avoidance between ships. The Titanic sunk 113 years ago on April 14-15, after hitting an iceberg ...

As increasing use cases of AI in insurance add urgency to the need for explainability and transparency, experts are recommending "explainable AI" best practices to follow and key challenges to ...