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Shahid Akhter, editor, ETHealthworld spoke to Dr. John Danaher, President, Clinical Solutions, Elsevier, to know what role artificial intelligence plays in healthcare and how Elsevier plans to improve diagnostic outcomes by way of AI and machine learning. Clinical errors and role of AI and health analytics There are three examples. The first one is making an initial diagnosis. What can be achieved with artificial intelligence, machine learning and actual language processing is the ability to assist doctors to make more accurate initial diagnosis. Second is the work being done in the area of image recognition with radiology and pathology.
"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.