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UID:556@bmi-online.nl
DTSTART;TZID=America/Chicago:20240418T130000
DTEND;TZID=America/Chicago:20240502T143000
DTSTAMP:20240223T121025Z
URL:https://www.bmi-online.nl/events/communicating-with-researchers-about-
 the-benefits-and-risks-of-ai-for-evidence-synthesis-online/
SUMMARY:Communicating with Researchers about the Benefits and Risks of AI f
 or Evidence Synthesis (online)
DESCRIPTION:It seems that everyone is talking about AI and what it can do\,
  can’t do\, and seems to do but doesn’t really. If you work on systema
 tic reviews\, you may be especially interested in the answers to these que
 stions that go to the heart of how librarians collaborate with researchers
  on reviews:\n\n 	Can AI tools automate and expedite systematic reviews an
 d other types of evidence synthesis without compromising the rigor and rep
 roducibility that are the hallmark of systematic reviews?\n 	How do you cr
 itically appraise a study that uses AI?\n 	How do you have informed conver
 sations with and advise researchers on the use of AI in reviews in this ti
 me of uncertainty and rapid change?\n\nGregory Laynor\, a systematic revie
 w expert who has been studying the impact of AI on evidence synthesis\, wi
 ll be your guide to having conversations with research teams about the cap
 abilities of current AI tools and the risks they present for systematic re
 view rigor and reproducibility. You’ll learn:\n\n 	the questions to ask 
 researchers who are interested in using AI for evidence synthesis\n 	how t
 o report the use of AI in an evidence synthesis project\n 	what tools are 
 available for critically appraising studies conducted with AI methods.\n\n
 Through interactive scenarios\, you will practice examining and communicat
 ing with research teams about the benefits and risks of AI.\n\nYou’ll le
 ave the webinar with new knowledge and increased confidence in your abilit
 y to discuss AI with researchers\, and you’ll join the company of librar
 ians able to build on their expertise in the rigor and reproducibility in 
 systematic reviews to help shape the future of AI.\n\nMore information. 
CATEGORIES:Cursussen en congressen,Webinar
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DTSTART:20240310T030000
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