The avenues of artificial intelligence and machine learning research are expanding widely and rapidly. Meta says it plans to tailor its AI explorations by analyzing the structures and networks of the human brain, hoping to map better deep learning algorithms by patterning them on the neural activities of real human cells. Over at Google, meanwhile, one of its top engineers says he’s convinced a chatbot he worked with has achieved human-like sentience.
What does it all mean? And what could it mean for AI applications across healthcare?
We spoke recently with Chirag Shah, associate professor in the Information School at the University of Washington. With expertise include interactive information retrieval and recommender systems, Shah – read his recent HITN article on Google’s LaMDA – spoke about recent advances in computational models and research techniques and discussed some of the challenges, opportunities and risks as AI gains ground in healthcare.
Shah’s work at UW, and his specific areas of research
Where healthcare it right now with AI & ML – and where it’s headed
Where do you expect we’ll be five or 10 years from now?
How AI and similar to – and different from – the human brain
The ethical concerns facing healthcare AI deployments, now and in the future
The opportunities advanced AI & ML could enable
More about this episode:
Sentient AI? Convincing you it’s human is just part of LaMDA’s job
Metaverse and virtual reality are gaining a foothold in healthcare
New York State Office for the Aging deploys AI robots as companions for older adults
Study: AI deep learning models can predict race from imaging results
AI-enabled app evaluates MRI data to help analyze dementia
Google and DeepMind face legal claim for unauthorised use of NHS medical records
Nuance, Health Management Academy launch artificial intelligence collaborative
Spotting bias in AI requires a holistic approach, says study
What does the future hold for AI in healthcare?