An AI productivity boom is coming. Here’s what managers need to know to roll out intelligent technology that’s ethical and worker-centric.
New research from MIT Sloan shows that companies can see substantial gains by putting AI to work — with that growth translating into jobs.
Using the wrong datasets to train AI models can result in legal risks, bias, or lower-quality models. The Data Provenance Initiative’s tool can help.
Artificial intelligence has the ability to transform finance, but caution is needed, says the SEC chair. Here are four of Gensler’s takeaways.
The use of artificial intelligence to create art raises questions about how credit and responsibility should be allocated.
Machine learning pioneer Andrew Ng argues that focusing on the quality of data fueling AI systems will help unlock its full power.
‘We should probably relax about this,’ MIT professor says.
Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.
Siemens, Mastercard, and John Deere combine big data with machine learning to improve the customer experience and reduce fraud.
Industrial robots do reduce jobs and wages — especially for workers in the automotive industry and certain parts of the country.
