Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

6.Q. Round table: Artificial Intelligence in healthcare: navigating ethically with equity and workforce empowerment

View through CrossRef
Abstract Background Artificial Intelligence (AI) is emerging as a pivotal technology with vast promises for healthcare. However, integrating AI into clinical and public health settings must be cautiously approached to ensure that it does not inadvertently exacerbate existing health system problems. The healthcare workers, already under severe stress, could view AI as a threat to job security rather than as a support mechanism. Moreover, past experiences with digital transformations, such as Electronic Health Records, have shown that technological integration can sometimes increase rather than decrease the burden on healthcare workers, leading to burnout and dissatisfaction, and thus worsening the healthcare workforce crisis. Furthermore, equity and ethical considerations are paramount in the deployment of AI in healthcare. Data privacy, patient consent, and algorithmic bias must be addressed to ensure that AI applications are designed to support and enhance human decision-making that is sensitive to the social determinants of health and accountable to equity and social inclusion, to the needs and rights of the healthcare workforce, and the dignity of the patients and populations. While AI presents significant opportunities for health systems and healthcare workers, there is a lack of knowledge, evidence-based policies, and ethical frameworks that support equitable and human-centred approaches to AI implementation. Objectives This round table workshop aligns three major public health challenges: the integration of AI in health systems, the global healthcare workforce crisis, and the improvement of equity and equality. It critically explores capacity building for AI, equity in AI implementation, and regulatory measures for ethical and responsible AI deployment, addressing the following major questions: What are the critical impacts of AI on the healthcare workforce? How can the healthcare workforce be effectively upskilled and supported to adapt to the changes brought by AI technologies? What regulatory frameworks and governance models are necessary to ensure AI’s safe and ethical implementation in healthcare, that is also sensitive to equity, gender equality and the needs of minority groups? Finally, what actionable steps and leadership can public health take to implement AI technologies while addressing the healthcare workforce needs, equity issues, and ethical guidelines? The panellists will illuminate these questions from different disciplinary approaches, helping us to disentangle complexity and to build capacity for evidence-based and socially inclusive AI policies. The workshop contributes to better understand the risks and benefits of AI. It seeks to advance knowledge exchange of good practice experiences and effective implementation. Key messages • The effects of AI on the healthcare workforce must be monitored and strategies adapted to mitigate the healthcare workforce crisis and to upskill and empower healthcare workers. • There is a need for human-centred and ethically responsive AI implementation and governance measures that support equity, gender equality, and diversity in healthcare settings. Speakers/Panelists Abi Sriharan Schulich School of Business York University, York, Canada Kasia Czabanowska Maastricht University, Maastricht, Netherlands Bernadette Kumar Migration Health Unit, Norwegian Institute of Public Health, Oslo, Norway Marius-Ionuț Ungureanu Babeș-Bolyai University, Cluj-Napoca, Romania Farhang Tahzib Faculty of Public Health, Haywards heath, UK
Oxford University Press (OUP)
Title: 6.Q. Round table: Artificial Intelligence in healthcare: navigating ethically with equity and workforce empowerment
Description:
Abstract Background Artificial Intelligence (AI) is emerging as a pivotal technology with vast promises for healthcare.
However, integrating AI into clinical and public health settings must be cautiously approached to ensure that it does not inadvertently exacerbate existing health system problems.
The healthcare workers, already under severe stress, could view AI as a threat to job security rather than as a support mechanism.
Moreover, past experiences with digital transformations, such as Electronic Health Records, have shown that technological integration can sometimes increase rather than decrease the burden on healthcare workers, leading to burnout and dissatisfaction, and thus worsening the healthcare workforce crisis.
Furthermore, equity and ethical considerations are paramount in the deployment of AI in healthcare.
Data privacy, patient consent, and algorithmic bias must be addressed to ensure that AI applications are designed to support and enhance human decision-making that is sensitive to the social determinants of health and accountable to equity and social inclusion, to the needs and rights of the healthcare workforce, and the dignity of the patients and populations.
While AI presents significant opportunities for health systems and healthcare workers, there is a lack of knowledge, evidence-based policies, and ethical frameworks that support equitable and human-centred approaches to AI implementation.
Objectives This round table workshop aligns three major public health challenges: the integration of AI in health systems, the global healthcare workforce crisis, and the improvement of equity and equality.
It critically explores capacity building for AI, equity in AI implementation, and regulatory measures for ethical and responsible AI deployment, addressing the following major questions: What are the critical impacts of AI on the healthcare workforce? How can the healthcare workforce be effectively upskilled and supported to adapt to the changes brought by AI technologies? What regulatory frameworks and governance models are necessary to ensure AI’s safe and ethical implementation in healthcare, that is also sensitive to equity, gender equality and the needs of minority groups? Finally, what actionable steps and leadership can public health take to implement AI technologies while addressing the healthcare workforce needs, equity issues, and ethical guidelines? The panellists will illuminate these questions from different disciplinary approaches, helping us to disentangle complexity and to build capacity for evidence-based and socially inclusive AI policies.
The workshop contributes to better understand the risks and benefits of AI.
It seeks to advance knowledge exchange of good practice experiences and effective implementation.
Key messages • The effects of AI on the healthcare workforce must be monitored and strategies adapted to mitigate the healthcare workforce crisis and to upskill and empower healthcare workers.
• There is a need for human-centred and ethically responsive AI implementation and governance measures that support equity, gender equality, and diversity in healthcare settings.
Speakers/Panelists Abi Sriharan Schulich School of Business York University, York, Canada Kasia Czabanowska Maastricht University, Maastricht, Netherlands Bernadette Kumar Migration Health Unit, Norwegian Institute of Public Health, Oslo, Norway Marius-Ionuț Ungureanu Babeș-Bolyai University, Cluj-Napoca, Romania Farhang Tahzib Faculty of Public Health, Haywards heath, UK.

Related Results

Perceptions of Telemedicine and Rural Healthcare Access in a Developing Country: A Case Study of Bayelsa State, Nigeria
Perceptions of Telemedicine and Rural Healthcare Access in a Developing Country: A Case Study of Bayelsa State, Nigeria
Abstract Introduction Telemedicine is the remote delivery of healthcare services using information and communication technologies and has gained global recognition as a solution to...
Iøjnefaldende arkitektur – Nordens middelalderlige rundkirker
Iøjnefaldende arkitektur – Nordens middelalderlige rundkirker
Conspicuous architecture. Medieval round churches in ScandinaviaThe aim of this article is partly to argue why round churches were built and partly to present an updated overview o...
Multimodal Emotion Recognition and Human Computer Interaction for AI-Driven Mental Health Support (Preprint)
Multimodal Emotion Recognition and Human Computer Interaction for AI-Driven Mental Health Support (Preprint)
BACKGROUND Mental health has become one of the most urgent global health issues of the twenty-first century. The World Health Organization (WHO) reports tha...
EMPOWERMENT KEPALA RUANGAN TERHADAP KOMPETENSI PERAWAT PELAKSANA DI RUMAH SAKIT : SYSTEMATIC REVIEW
EMPOWERMENT KEPALA RUANGAN TERHADAP KOMPETENSI PERAWAT PELAKSANA DI RUMAH SAKIT : SYSTEMATIC REVIEW
Abstract Backgound: Nurse competence can be influenced by the empowerment of head nurse. Empowerment is how head nurse conditions the climate and work culture in the nursing ward t...
Section-level genome sequencing and comparative genomics of Aspergillus sections Cavernicolus and Usti
Section-level genome sequencing and comparative genomics of Aspergillus sections Cavernicolus and Usti
Fig. S1. A cladogram representation of the phylogenetic relations between the species in this paper. The red labels show bootstrap values of 100 % and the black labels show bootstr...
Influences of Structural Empowerment and Demographic Factors on Nurses’ Psychological Empowerment
Influences of Structural Empowerment and Demographic Factors on Nurses’ Psychological Empowerment
Aim. The objective was to investigate the impact of structural empowerment and demographic factors on the psychological empowerment of nurses. Background. The empowerment of nurses...
Analysis of Mustahik Economic Empowerment Model in Pekanbaru
Analysis of Mustahik Economic Empowerment Model in Pekanbaru
In Pekanbaru, Indonesia, mustahik empowerment has two model approaches for running the mustahik economic empowerment programs,  namely individual empowerment  and groups empowermen...

Back to Top