Ethics in artificial intelligence — many questions, but few answers

Huge Two-Day Clean Sweep Auction July 24-25th. Click Here to Bid!

advertisement
Current Location:
>
> This Story


Log in or Register to rate this News Story
Forward Printable StoryPrint Comment
advertisement

 

advertisement

 

Artificial Intelligence Homepage

Balancing AI and the human touch with two new approaches Technology shouldn't sacrifice the clinician-patient relationship

FDA gives RaySearch green light for RayStation 8B platform First treatment planning system to offer machine learning applications

Imaging deep learning AI successes kick off SIIM 2019 Researchers show how they are using AI to enhance imaging capabilities

AI model predicts malignant breast cancer as well as humans: IBM Incorporates mammogram and EHR data in predictions

Siemens showcases works in progress at SNMMI Includes TeamPlay, syngo Virtual Cockpit and a number of AI algorithms

AI tool for Alexa and smart devices detects cardiac arrest in sleeping patients Monitors patients for agonal breathing

Silicon Valley investor paints dire picture for future of radiologists Claims they should no longer exist in a decade

AMA issues recommendations for accountability of AI in healthcare Aid in advancing quadruple aim

New algorithm better predictor of readmission following discharge, says study Final model drew predictions from 382 variables

Understanding 'data cleaning' in equipment service, and the tools used to do it Acquiring data is only the beginning, insights from AAMI

Ethics in artificial intelligence — many questions, but few answers

by John W. Mitchell , Senior Correspondent
The Socratic method was in full force over the matter of sharing patient data for AI algorithm deep learning during an afternoon session at SIIM 2019 titled Ethics in Radiology: the European and North American Multisociety Statement.

The interactive session intended to solicit input from SIIM expert attendees on a draft paper about the ethics of sharing patient data in both Europe and the U.S. Some of the authors, from Kenya, the Netherlands, and the U.S., seemed pleased with the responses that raised more questions than definitive answers.

Story Continues Below Advertisement

THE (LEADER) IN MEDICAL IMAGING TECHNOLOGY SINCE 1982. SALES-SERVICE-REPAIR

Special-Pricing Available on Medical Displays, Patient Monitors, Recorders, Printers, Media, Ultrasound Machines, and Cameras.This includes Top Brands such as SONY, BARCO, NDS, NEC, LG, EDAN, EIZO, ELO, FSN, PANASONIC, MITSUBISHI, OLYMPUS, & WIDE.



Participating groups include American College of Radiology (ACR), European Society of Radiology (ESR), Radiology Society of North America (RSNA), Canadian Association of Radiologists (CAR), Society for Imaging Informatics in Medicine (SIIM), European Society of Medical Imaging Informatics (EuSoMII), and American Association of Physicists in Medicine (AAPM).

Moderator Dr. J. Raymond Geis, assistant clinical professor of radiology at the University of Colorado, acknowledged that the topic was still unsettled and radiologists and others have strong opinions about the matter. His colleagues — Dr. Judy Gichoya, fellow and interventional radiologist at Oregon Health & Sciences University's Dotter Institute, and Dr. Erik Ranschaert, radiologist at the Netherlands Cancer Institute — helped lead the interactive session.

"I sent the draft to a colleague at Princeton, and he shared it with his grad students," reported Geis. "They pretty much chewed my butt about some things.”

He made the point to reinforce that the paper, titled with the same name as the session, was very much a work in progress. The audience spent most of the 90-minute session highly engaged in discussing the topic.

The opening paragraph set the tome for the interactive session:

Artificial intelligence (AI), defined as computers that behave in ways that, until recently, were thought to require human intelligence, has the potential to substantially improve all facets of radiology. AI is complex, has numerous potential pitfalls, and is inevitably biased to some degree. Radiologists and all others who build and use radiology AI products have a duty to understand AI deeply, to provide the most benefit to patients, to understand when and how hazards manifest, to be transparent about benefits and risks, and as much as possible to mitigate any harm they might cause. AI will cause dramatic clinical, social and economic changes. Most changes will be positive, but some may be for the worse.
  Pages: 1 - 2 >>

Artificial Intelligence Homepage


You Must Be Logged In To Post A Comment