View source for Instruction:C4523b81-9ff7-43af-ad8b-15dc95afcff5

{{Instruction
|Title=AI in Healthcare: Ethics Issues
|Has Related Initiative=Initiative:Ce2c53d3-722d-48f5-8e0d-140306b56c6e
|Instruction Goal='''The aim'''

To support students, researchers, and research ethics reviewers in learning about and reflecting upon the ethics issues associated with the development and use of AI technologies in healthcare.

'''Learning outcomes'''

At the end of this module, learners will be able to:

# Explain the relevance of informed consent, transparency and explainability for AI in healthcare.
# Describe the data-related ethics issues for AI in healthcare.
# Reflect upon broader ethics issues (like social values and the environmental impact) related to AI in healthcare.
# Access relevant guidelines and regulations for the use of AI in healthcare (e.g., the European Commission Guidelines for AI Research)
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|Important For=All stakeholders in research
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|Instruction Step Title=Opening Poll
|Instruction Step Text=How confident do you feel about navigating ethics issues related to the use of AI technologies in healthcare domains? Select the most appropriate response in the anonymous poll.
|Instruction Step Interactive Content=Resource:H5P-196
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|Instruction Step Title=Informed Consent, Transparency and Explainability
|Instruction Step Text=[[File:AI Img1.png|center|frameless|600x600px]]



Informed consent processes can be challenging when AI technologies are involved. Bearing the important concepts of transparency and explainability in mind when designing consent documents and processes will help to centralise patients/participants’ needs and ensure a fair process.


Answer the following questions to test your understanding of informed consent, transparency and explainability regarding the use of AI technologies in healthcare.
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|Instruction Step Title=Data-Related Ethics Issues for AI in Healthcare
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<div><div>
With the integration of AI technologies into healthcare, shaping diagnostic tools, treatment plans, and patient care, critical questions emerge about data-related ethics issues.

Here are some examples:
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|Instruction Step Title=Data-Related Ethics Issues for AI in Healthcare cont.
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|Instruction Step Title=Data-Related Ethics Issues for AI in Healthcare cont.
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How and at what points can bias be introduced into AI systems in healthcare? Click on the image below to find out more.

It is important for researchers and reviewers of research to be aware of the data-related ethics issues,  that may arise in projects using AI technologies in the healthcare domain.

Vigilance about these matters is essential at the initial design stages and throughout projects.
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|Instruction Step Title=The Protection and Promotion of Societal Values
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Societal values are the shared beliefs, principles, and norms that guide the behaviour and interactions of individuals within a society. These values play a crucial role in shaping the culture, social cohesion, and overall functioning of a community.


AI clearly has the potential to cause harms to society, as was evident in [https://ieeexplore.ieee.org/abstract/document/8436400 the case of Cambridge Analytica] when social media data was misused to manipulate the outcome of democratic elections. Concerns related to accountability/responsibility, patient-healthcare provider relationship, question of trust, surveillance, etc. in AI are significant [https://pubmed.ncbi.nlm.nih.gov/32702587/ and are being studied].  However, in such a rapidly changing field, questions around the continuing evolution and potential uses of AI in healthcare and their broader impacts upon individuals, communities, and society in general will remain open.


The use of robots in the delivery of care offers a useful illustration of the complexity of questions to be considered about the impact of AI machines for individuals, communities, and society. James Wright observed the trialling of three types of care robots in a Japanese care home:


* Hug, an assistive robot, which was used to lift patients out of bed and reduce the need for staff to undertake manual lifting.
* Paro, a robotic furry seal, which was used to provide a form of animal therapy and companionship for elderly residents.
* Pepper, a humanoid robot, which was used to lead activities such as karaoke or exercise sessions. 


The introduction of care robots into healthcare settings raises complex ethical and societal issues which extend beyond the concerns of dehumanisation of care, impact on staff morale, confusion of roles, and waste of resources highlighted by this case. Consideration also needs to be given to other values and principles including but not limited to: autonomy, moral agency, trust and reliability. [https://www.sciencedirect.com/science/article/pii/S0921889016305292?pes=vor The ethics of healthcare robotics] sets out the need for a dialogic and collaborative approach to embed ethics throughout such projects, ensuring a responsible approach to research and innovation in this developing field.
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|Instruction Step Title=Reflecting on the Broader Ethics Issues Relevant to The Use of AI in Healthcare cont.
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|Instruction Step Title=Reflecting on the Broader Ethics Issues Relevant to the Use of AI in Healthcare - Exercise
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As AI continues to reshape the healthcare landscape, it brings about a myriad of societal and ethical considerations. This sorting exercise aims to explore the broader issues surrounding the intersection of AI and healthcare.

Please categorise each scenario into the appropriate societal or ethical dimension:
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|Instruction Step Title=Guidelines and Regulations for the Use of AI in Healthcare
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It is important for students, researchers and research ethics reviewers involved with research using and/or developing AI technologies in the healthcare domain to be aware of relevant guidelines and regulations that apply to their projects.


The [https://www.who.int/publications/i/item/9789240029200 WHO’s Ethics and governance of artificial intelligence for health] calls for the embedding of ethics and human rights at the heart of AI design, deployment.


Click on the hotspots below to see WHO’s key ethical principles for research involving AI in healthcare.


The guidelines state that ‘each component in itself is necessary but not sufficient for the achievement of Trustworthy AI. Ideally, all three components work in harmony and overlap in their operation. If, in practice, tensions arise between these components, society should endeavour to align them’.
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|Instruction Step Title=Guidelines and Regulations for the Use of AI in Healthcare cont.
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|Instruction Step Title=Alexei Grinbaum - Considerations for Researchers and Ethics Reviewers
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Alexei Grinbaum shares some considerations for researchers and research ethics reviewers.  In this interview, you will hear Alexei discuss different categories of questions that need to be asked about studies involving the use of AI technologies in healthcare. [https://classroom.eneri.eu/sites/default/files/2024-10/20240513%20Checklist%20AI%20in%20health.pdf The Ethics of AI in Healthcare: A checklist for Research Ethics Committees], which we mentioned at the beginning of the module is a useful resource to identify relevant questions.
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|Instruction Step Title=End of Module Quiz
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You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected.    
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|Instruction Step Title=Module Evaluation
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|Instruction Step Title=References and Further Resources:
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Comité Consultatif National D’Ethique pour les Sciences de la Vie et de la Santé: 

Medical Diagnosis and Artificial Intelligence: Ethical Issues. Joint opinion of the CCNE and CNPEN, 

CCNE Opinion 141, CNPEN Opinion 4. November 2022  

https://www.ccne-ethique.fr/sites/default/files/2023-05/Opinion%20No.141.pdf   


Council of Europe: 

Guidelines on artificial intelligence and data protection (2019) 

https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf] 


Deutscher Ethikrat (German Ethics Council): 

Opinion: Humans and Machines – Challenges of Artificial Intelligence (2023) https://www.ethikrat.org/en/publications/publication-details/?tx_wwt3shop_detail%5Bproduct%5D=168&tx_wwt3shop_detail%5Baction%5D=index&tx_wwt3shop_detail%5Bcontroller%5D=Products&cookieLevel=accept-all&cHash=4d430bf45ea980ea5f83daad9550ef88 (currently only available in German, an English translation will be available in due course) 


European Commission: 

Ethics By Design and Ethics of Use Approaches for Artificial Intelligence (2021) 

https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf] 


European Commission Science Policy, Advice & Ethics Unit, DG Research & Innovation:

The ethics appraisal scheme in Horizon Europe (2021)

https://www.bbmri-eric.eu/wp-content/uploads/The-Ethics-Appraisal-Scheme-_BBMRI-webinar-september-2021_version-for-dessimination.pdf 

Chapter 8 of the ethics issues table in the EU ethics appraisal scheme is of particular importance in Horizon Europe as it specifically addresses research ethical aspects of AI. Other relevant chapters include chapter 1 on human participants, chapter 4 on personal data and chapter 10 on the potential misuse of results. The inclusion of a chapter on AI in Horizon Europe is a recent addition. The EC introduced this chapter because it identified pressing ethical concerns related to discrimination and bias, safety and liability, transparency and opaque algorithms, as well as privacy and data protection. These concerns were deemed highly urgent and thus warranted a dedicated section within the ethics appraisal scheme. The key values to be respected within the projects submitted to the EU appraisal scheme are (1) human agency and oversight, (2) privacy and data protection, (3) fairness, diversity and non-discrimination, (4) accountability, (5) transparency, and (6) societal and environmental wellbeing.


Ethics guidelines for trustworthy AI (2019) 

https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines- [https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai trustworthy-ai] 


OECD Legal Instruments:

Recommendation of the Council on Artificial Intelligence (2019) 

https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449 


UNESCO: 

Recommendations on the Ethics of Artificial Intelligence (2022)  

https://unesdoc.unesco.org/ark:/48223/pf0000381137  


World Health Organisation: 

Ethics and governance of artificial intelligence for health (2021)  

https://www.who.int/publications/i/item/9789240029200  

See Chapter 4 for an overview of laws, policies, and principles that apply to the use of AI in healthcare. Chapter 5 proposes six key ethical principles which can serve as useful reminders for those involved in research utilising AI in healthcare


Also worth exploring are guidelines produced by [https://blog.neurips.cc/2021/12/03/a-retrospective-on-the-neurips-2021-ethics-review-process/ Stanford University], [https://unesdoc.unesco.org/ark:/48223/pf0000380455#:~:text=AI%20actors%20and%20Member%20States,law%2C%20in%20particular%20Member%20States%27 UNESCO] and the Horizon Europe Project [https://www.sienna-project.eu/ SIENNA] which developed ethical frameworks and recommendations for AI and robotics.  


Isaak, J., & Hanna, M. J. (2018). User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), 56-59. https://ieeexplore.ieee.org/abstract/document/8436400
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