Article type
Abstract
Background
With the recent and rapid advances of artificial intelligence (AI) technologies, and the plethora of new tools being deployed, there is an urgent need for producers and publishers of high-quality systematic reviews to provide guidance on the appropriate use of these new tools to support evidence synthesis.
Objectives
To:
-Share draft guidelines on responsible use of AI in evidence synthesis
-Inform the community that evidence synthesis organizations are collaborating to develop 1 set of standards, which tool developers could use as the standards to work toward when developing AI tools to facilitate their endorsement within the organizations
-Enable the community as a whole to contribute to the process, calling for collaborators
Description and Activities/Interaction Plans
Representatives of the International Collaboration for Automation in Systematic Reviews (ICASR), Cochrane, Campbell, JBI, and GIN (tbc) will introduce draft guidance on the responsible use of AI in systematic reviews. They will clarify what is in scope (including why guidelines are needed; consideration of data and algorithmic bias; the longevity and sustainability of tools; their transparency, reliability, and validity; and fairness and equity). The implications of the guidance for organizational policy and implementation will also be discussed.
Participants will be able to view the draft guidance online before the session and interact with the panel throughout the session. Rather than a block of presentations at the start, followed by discussion, we are planning short "lightning" presentations covering the topics mentioned above followed by discussions focused on some of the core elements of the draft guidelines, engaging with the panel of representatives and the audience via Menti and direct dialogue.
The session will conclude with discussion about how the community as a whole can feed into guideline development (including online discussion and surveys), and how the guidance might need regular updating as tools and technologies evolve.
With the recent and rapid advances of artificial intelligence (AI) technologies, and the plethora of new tools being deployed, there is an urgent need for producers and publishers of high-quality systematic reviews to provide guidance on the appropriate use of these new tools to support evidence synthesis.
Objectives
To:
-Share draft guidelines on responsible use of AI in evidence synthesis
-Inform the community that evidence synthesis organizations are collaborating to develop 1 set of standards, which tool developers could use as the standards to work toward when developing AI tools to facilitate their endorsement within the organizations
-Enable the community as a whole to contribute to the process, calling for collaborators
Description and Activities/Interaction Plans
Representatives of the International Collaboration for Automation in Systematic Reviews (ICASR), Cochrane, Campbell, JBI, and GIN (tbc) will introduce draft guidance on the responsible use of AI in systematic reviews. They will clarify what is in scope (including why guidelines are needed; consideration of data and algorithmic bias; the longevity and sustainability of tools; their transparency, reliability, and validity; and fairness and equity). The implications of the guidance for organizational policy and implementation will also be discussed.
Participants will be able to view the draft guidance online before the session and interact with the panel throughout the session. Rather than a block of presentations at the start, followed by discussion, we are planning short "lightning" presentations covering the topics mentioned above followed by discussions focused on some of the core elements of the draft guidelines, engaging with the panel of representatives and the audience via Menti and direct dialogue.
The session will conclude with discussion about how the community as a whole can feed into guideline development (including online discussion and surveys), and how the guidance might need regular updating as tools and technologies evolve.