First EthicalAI Initiative: Open and Collaborative Development of AI Policy for Digital Health Solutions

The introduction of AI in healthcare offers numerous potential benefits and profound implications for the sector and the wider population. Critically, it requires careful consideration of how the technology should be developed and used [1], and what guardrails need to be in place to ensure positive patient outcomes [2]. Furthermore, many technology companies and healthcare organisations (both public and private) are developing AI-related frameworks and policies to satisfy stakeholders or anticipate future regulatory requirements [3]. Meeting these requirements can be a time-consuming and challenging undertaking, often involving the review of published guidelines, standards, and legal frameworks, or adapting publicly available examples that are not well understood or effectively utilised. Therefore, there is an urgent need for an openly available AI ethics framework and policies that facilitate regular updates, feedback, and broad input and enable active discourse among collaborators. This ensures that policies are easily understood and impactful for all stakeholders within the healthcare sector, from those offering digital solutions to those benefiting from care services. In this case study, the HIGOE team describes a newly designed collaborative initiative, First EthicalAI, with a goal to promote open, ethical, and responsible policy development within healthcare, beginning with an AI ethics framework.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-03
DOI
https://doi.org/10.5281/zenodo.15132294
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

First EthicalAI Initiative: Open and Collaborative Development of AI Policy for Digital Health Solutions

Zenodo (CERN European Organization for Nuclear Research)
Ecology and Vegetation Dynamics Studies
article

First EthicalAI Initiative: Open and Collaborative Development of AI Policy for Digital Health Solutions

article en

Abstract

The introduction of AI in healthcare offers numerous potential benefits and profound implications for the sector and the wider population. Critically, it requires careful consideration of how the technology should be developed and used [1], and what guardrails need to be in place to ensure positive patient outcomes [2]. Furthermore, many technology companies and healthcare organisations (both public and private) are developing AI-related frameworks and policies to satisfy stakeholders or anticipate future regulatory requirements [3]. Meeting these requirements can be a time-consuming and challenging undertaking, often involving the review of published guidelines, standards, and legal frameworks, or adapting publicly available examples that are not well understood or effectively utilised. Therefore, there is an urgent need for an openly available AI ethics framework and policies that facilitate regular updates, feedback, and broad input and enable active discourse among collaborators. This ensures that policies are easily understood and impactful for all stakeholders within the healthcare sector, from those offering digital solutions to those benefiting from care services. In this case study, the HIGOE team describes a newly designed collaborative initiative, First EthicalAI, with a goal to promote open, ethical, and responsible policy development within healthcare, beginning with an AI ethics framework.

Zenodo (CERN European Organization for Nuclear Research)
The Alan Turing Institute (GB), Yangon University of Education (MM), OLS
Partnerships for the goals
Openalex Percentile: Top 50%
Ecology and Vegetation Dynamics Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

First EthicalAI Initiative: Open and Collaborative Development of AI Policy for Digital Health Solutions · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS