clinical research studies ethics committee

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You are here, reviewing clinical trials: a guide for the ethics committee.

Created with the intention to promote human research protection of participants in clinical trials internationally. Edited by Johann P.E. Karlberg (Clinical Trials Centre, Univ. of Hong Kong) and Marjorie Speers of AAHRPP. Sponsored by Pfizer, an AAHRPP accredited pharmaceutical company, through a "non-binding" grant.

Committees: Research Ethics Committees

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• Ana Borovecki 2  

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Research ethics committees have become a permanent fixture when it comes to ethics of research. They are essential part of quality control of research protocol, and their existence and work are thoroughly described in all important international documents dealing with research ethics issues. In this contribution history, development and different types of research ethics committees are discussed. The functions, structure, and locale of research ethics committees are also addressed. The global dimension of the work of research ethics committees is also discussed.

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Borovecki, A., ten Have, H., & Oreskovic, S. (2009). Ethics committees in Croatia: Studies in bioethics . Saarbrücken: VDM Verlag Dr. Müller.

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Huriet, C. (2009). Article 19: ethics committees. In H. A. M. J. ten Have & S. J. Michele (Eds.), The UNESCO universal declaration on bioethics and human rights background principles and application (pp. 265–270). Paris: UNESCO.

Jonsen, A. R., Veatch, R. M., & le Roy, W. (1998). Source book in bioethics. A documentary history . Washington, DC: Georgetown University Press.

Levine, R. J. (2004). Research ethics committees. In W. T. Reich (Ed.), Encyclopaedia of bioethics (Vol. IV, pp. 2311–2316). New York, NY: Macmillan Simon and Schuster.

ten Have, H. (2005). Establishing bioethics committees guide No. 1 (pp. 40–52). Paris: UNESCO.

Further Readings

Amdur, R., & Bankert, E. A. (2011). Institutional review board: Member handbook (3rd ed.). Sudbury, MA: Jones and Bartlett Publishers.

Emanuel, E. J., et al. (Eds.). (2008). The Oxford textbook of clinical research ethics (pp. 541–588). Oxford/New York: Oxford University Press.

Schrag, Z. M. (2010). Ethical imperialism. Institutional Review Boards and the Social Sciences, 1965–2009 . Baltimore: The Johns Hopkins University Press.

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Andrija Stampar School of Public Health, School of Medicine, University of Zagreb, Zagreb, Croatia

Ana Borovecki

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Center for Healthcare Ethics, Duquesne University, Pittsburgh, PA, USA

Henk ten Have

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Borovecki, A. (2016). Committees: Research Ethics Committees. In: ten Have, H. (eds) Encyclopedia of Global Bioethics. Springer, Cham. https://doi.org/10.1007/978-3-319-09483-0_104

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Ethics and approvals

1. introduction.

This section provides guidance on the regulations and approvals that may be required for specific types of research.

If your research will involve human participants, their biosamples (tissues) or data, then you should consider and address any relevant ethical issues in your application.

The lists below include some common considerations for research involving people as participants, their biosamples or data. If any of the following are relevant to your research, and you have not already covered these in your application, you should confirm how you intend to address them.

Benefits and risks: you should describe the nature and extent of any benefits likely to come from your research and outline how you will mitigate any risks (such as risks to the safety, dignity, rights or wellbeing of participants, potential participants and staff working on the study).

Consent for research: appropriately informed, voluntary consent is the most common way to recruit human participants into research. You should indicate whether there are specific considerations in relation to consent in your application. Learn more on consent for research .

Information management: your data management plan should describe how you will manage participant confidentiality, data security and any data sharing.

Management of biosamples or biobanks: if you will access biosamples for your research from a biobank, then the biobank should review and confirm the feasibility of your sample access request before submission of your application for funding.

You should also work with local contacts to ensure appropriate transfer and storage arrangements will be provided. Learn more in ‘ using human samples ’ in section 8.

Patient and public involvement: we encourage you to consider how to involve patients or the public, or both, in developing your research. If you have undertaken preliminary engagement work or have plans for future engagement, you should state these in your application.

Learn more about patient and public involvement .

Ensure research outputs reflect diversity in society: to ensure that research brings fair benefits to all in society, it is important that the participants, proposed analysis and outputs from your research reflect the diversity of the population that you are studying. Learn about MRC’s expectations on embedding diversity in research design .

We have the following expectations when your research involves people as participants, their biosamples or data.

You must comply with all relevant regulatory, policy and ethical requirements. While your research organisation is responsible for ensuring compliance, you have a role to play (for example, in securing the relevant approvals or sponsorship, or both). For further guidance, visit your local research office .

You should comply with relevant MRC policies and guidance . This includes open research policies that promote sharing of data, samples, materials, reagents, code and more.

Your research should not start before the necessary approvals are in place. Approvals do not need to be in place at the time of applying for a grant.

You can find further guidance on requirements that may be relevant to your research below. You can also seek guidance and advice to help you understand specific requirements for your research from the MRC Regulatory Support Centre .

2. Embedding diversity in research design

Your application should meet the requirements of MRC’s embedding diversity in research design policy by embedding consideration of the relevant diversity characteristics in the design and conduct of your research.

This policy is relevant to all studies involving human participants, samples and data, including, but not limited to:

• clinical studies
• public health and population-based research
• observational studies
• studies using data from people or the use of human biological material (for example, cells and tissues)

Relevant guidance, resources and toolkits are available at embedding diversity in research design and sex in experimental design .

3. Clinical staff

If you intend to employ any clinically trained individuals to undertake research on your grant, and they remain interested in pursuing a clinical career, they must discuss these plans with their postgraduate medical dean or equivalent.

This will ensure that, where appropriate, one year of MRC-funded research counts towards the certificate of completion of their specialist training.

4. Approvals

The types of approvals you will need for your research will depend on your research, what it will involve and where it will take place.

If your research involves human participants, ethical review by a research ethics committee (REC) is the most common approval we require.

Ethical approval may be from your research organisation (for example university REC), or an NHS (or Health and Social Care in Northern Ireland) REC.

To learn when you need NHS REC review, visit do I need NHS REC review?

You may also need approvals from places such as schools or other establishments, depending on the nature of your project.

There are times when you need no REC approval (usually for studies considered low risk). Work with your local research office to understand your local policy.

You should not start any research before the necessary approvals are in place. Approvals do not need to be in place at the time of applying for a grant.

5. Interventional research involving people as participants

If your research involves an intervention or action(s) expected to result in change, such as providing your participants with a drug treatment, a surgery or different surgical technique or approach, altering diet, exercise or some other lifestyle aspect, then we have the following additional expectations:

• you should consider how to involve people with lived experience in appropriate aspects of your study, considering study design, management, conduct and dissemination
• trial registration and dissemination
• you should include adequate information in each application to enable MRC to evaluate any physical or psychological hazard to which participants may be exposed
• you should specify in each application the number, sex, age range and state of health of the human participants
• you should indicate whether participants are patients, healthy volunteers or individuals in a control cohort and how you will obtain consent
• you can pay participants to take part in your research, provided that the payment is to reimburse expense or compensate for time and inconvenience and not at a level that would constitute an inducement to take part

Clinical trials of investigational medicinal products, including advanced therapies

These interventional trials test the safety and or efficacy of medicinal products and include trials of advanced therapies, which are governed by the Clinical Trials Regulations. You can find further guidance on the regulatory requirements of these trials in:

• clinical trials regulations for our expectations on the sponsorship of these trials
• clinical trials of medicines and advanced therapies , which signposts Medicines and Healthcare products Regulatory Agency (MHRA) guidance
• National Institute for Health and Care Research Clinical Trials Toolkit for practical guidance on running a clinical trial in the UK

If you are proposing a clinical trial of an investigational medicinal product, you will need to apply for combined review from the NHS REC and MHRA, using a new part of the Integrated Research Application System (IRAS).

Ionising radiation in human participants

Ionising radiation includes, but is not limited to:

• X-rays, CT scans, DXA scans
• radiotherapy (including brachytherapy and therapy using unsealed sources)
• radionucleotide imaging
• administration of radioactive substances (for example, nuclear medicine and PET or CT scanning)

Neither MRI nor ultrasound involve ionising radiation.

You have a legal and ethical requirement to justify the use of ionising radiation in your application. Be aware that the Ionising Radiation (Medical Exposure) Regulations (IRMER) relate to any research exposure, not only to those additional to routine clinical care.

Guidance is available on this and other relevant legal frameworks in the HRA website .

Where research involves the administration of radioactive substances, this must also be approved by the Administration of Radioactive Substances Advisory Committee (ARSAC) .

All imaging technologies have the potential to uncover previously unknown pathology. You should always consider how likely such a discovery may be and, if appropriate, describe in your application how you would handle such discoveries.

For further guidance see the MRC-Wellcome Trust Framework on the feedback of health-related findings in research .

Testing a medical device or an in vitro diagnostic

Testing a medical device, including software products, may be regulated under the Medical Device Regulations depending on the purpose of the device, commercial intent and whether an exemption applies. Discuss with your sponsor’s office, as local interpretation of the exemption differs.

If you are within scope of the Medical Devices Regulations, you may be conducting a clinical investigation that requires an application to MHRA and NHS REC.

For in vitro diagnostics you may be conducting a performance evaluation, which you will need to register with MHRA.

Learn more about the regulation of medical devices and in vitro diagnostics .

6. Using data and information about people

When your research involves data or information about people, requirements largely depend on whether you will access or use identifiable or anonymised data.

You can find out more about these requirements in using data about people in research .

If you plan to access confidential patient information without consent in England and Wales, you will need section 251 support from the Confidentiality Advisory Group . Scotland and Northern Ireland have equivalent arrangements.

To learn more, visit ‘accessing identifiable information without consent’ in using information about people in health research .

Health data discovery and access

Use the Health Data Research Innovation Gateway to discover what data is available from central NHS providers and others.

Data is not held by Health Data Research UK (HDRUK) but by different organisations. The gateway provides the means to contact some organisations and apply for data access, although for most you will need to apply directly to individual organisations (or data custodians).

See the MRC Health Data Access Toolkit for the approvals you will need. This includes details of the approvals you will need when accessing NHS data from central providers or direct from NHS care organisations.

Accessing data takes time. If there are bespoke linkages and complex approvals, it can take over six months. You should build this into your grant.

If you are accessing identifiable information or collecting data from research participants, consent and confidentiality are very important.

We expect your research organisation to have policies in place to manage confidentiality and the privacy of your participants.

7. Artificial intelligence

If your research involves the development of AI algorithms, you need to take steps to assess and reduce potential bias. You might consider carrying out an AI impact assessment (AIA).

The data used for the development and training of algorithms needs to represent the diversity of the target population as closely as possible. Learn more about AIA from the Ada Lovelace Institute .

8. Using human samples

If you are establishing a new collection of human samples, it is important to seek consent that is both broad in scope and duration to allow for storage and future use.

We recommend two-phase consent, where you ask donors about the initial project, and for storage and future use in other research projects. A research ethics committee should review your consent arrangements.

If you intend to access an existing collection of human samples for your research, for example from a biobank or a collaborator, you should work with them to determine what is required in terms of ethical approval.

You should also speak to your local research office for their policy on human samples and ethical review, as well as about how to manage any transfer of samples.

If parties agree that appropriate consent is in place, and your project does not pose any ethical issues, you may not require REC review.

You can search the UK Clinical Research Collaboration (UKCRC) tissue directory to discover human samples available for use in research.

You should speak to relevant local contacts to discuss storage arrangements and ensure that these can be provided.

Exactly who you should speak to will depend on how your research organisation manages human samples, but this is likely to be your:

• local lab manager
• health and safety contact
• designated individual (if you have one)

If you are based in England, Wales or Northern Ireland, your lab may operate under a Human Tissue Authority research licence (supervised by a designated individual).

If you are based in England, Wales or Northern Ireland and your lab is not covered by a licence, you will need to meet the licensing requirement of the Human Tissue Act 2004 if you intend to ‘store’ relevant material for your research.

The most common way to meet the licensing requirement on unlicensed premises is with NHS or Health and Social Care REC approval (as this provides a legal exemption for licensing).

If you are accessing relevant material from a UK-based biobank that has generic ethical approval, then their approval can extend to you and provide you with a legal exemption for licensing.

If you need a legal exemption for licensing, check whether the biobank provides such ethical approval and whether it places any other conditions on your use of their samples.

There are other licensing exemptions. You can find more in using human samples in research .

If you are accessing samples from a biobank you should attach a ‘letter of support’ or equivalent that confirms that your request is feasible and has been adequately costed. If you need additional storage for your research (for example, a new freezer or off-site storage), you can cost this into your grant.

Using human embryos, admixed embryos or embryonic stem cells and lines

If your research involves embryos or the derivation of embryonic stem cells and lines, then it may be regulated by the Human Fertilisation and Embryology Authority (HFEA).

You can read about HFEA’s requirements for research in section 22 of their code of practice . ‘Licences for research’ details when you need an HFEA research licence.

Learn more about applying for an HFEA research licence .

Xenotransplantation

If your application includes the use of animals containing human material, you must follow the Home Office guidance on the use of human material in animals .

Developing cell and tissue-based therapies

If your research will develop a cell or tissue-based therapy, then human application requirements apply pre-trial stage.

You can learn more about these requirements (procurement, testing, processing, storage, distribution, import and export of tissues and cells) in the Human Tissue Authority’s guidance on human application .

For guidance on the trial stage, see clinical trials of investigational medicinal products, including advanced therapies in section 5.

9. Induced pluripotent stem cells

If your research involves the use of induced pluripotent stem cells (iPSC) you should make a strong case in support of the proposed iPSCs being able to appropriately recapitulate the natural state or diseased condition of interest versus other means of gaining similar insight.

You must adhere to relevant UK regulations and guidelines. For guidance see the code of practice for the use of human stem cell lines .

iPSC collections should ideally be based on well phenotyped cohorts with linked clinical and lifestyle data. Donations should be altruistic, anonymised and traceable.

You must secure appropriate consent for all proposed uses. To futureproof derived lines, you should consider seeking generic consent for a broad range of potential uses, given their pluripotent nature.

Depending on the specific project, you should consider seeking specific consent for areas of particular interest including:

• genetic analysis of derived cells
• potential use in animal research, clinical transplantation or reproductive medicine
• potential commercial applications of cell lines but without donors receiving personal financial benefit
• the feedback of data from derived cell lines
• documenting and banking for future reference the tissue source of cells from which the iPSC lines are derived

Derivation and characterisation

This is a fast-moving field with numerous derivation approaches emerging. You should use comparable methods of iPSC generation where possible and provide full details of the reprogramming method.

You should calibrate lines derived using novel methodologies against lines derived using established protocols and ideally human embryonic stem cell lines.

You should characterise lines to establish features including clonal purity, absence of expression of reprogramming factors, self-renewal capacity, genetic stability and pluripotency.

Characterisation should take into account uncertainties regarding the degree of reprogramming and the extent and durability of epigenetic memory.

We note that fully characterising lines may be costly and time consuming. The level of characterisation should be fit for purpose.

Robust quality control systems should be in place to ensure the identity and specification of banked and released cells.

Internationally agreed standards and guidance for stem cell line banking are available from the International Stem Cell Banking Initiative , and you can seek advice through the UK Stem Cell Bank and the European Bank for Induced pluripotent Stem Cells (EBiSC) .

You can access existing healthy and disease-relevant lines from the European Collection of Authenticated Cell Cultures (ECACC) , the UK Stem Cell Bank or EBiSC.

Collections should detail how access will be provided to third parties in line with MRC policy on data sharing and cohort resource policy.

You should consider material and data transfer agreements (MDTAs), intellectual property licensing and freedom to operate, where appropriate, to ensure the broadest utility of derived lines.

MDTAs should control third-party use and ensure UK guidelines and ethical procedures are followed, for example, in relation to potential use in animals, clinical studies or reproductive science.

You should mandate equivalent standards if you are exporting stem cells for international use.

10. Research in low and middle-income countries

Applications for research involving human participants in lower and middle-income countries may have additional ethical implications that you should consider in developing the research protocol.

We expect any partnership between the UK and research organisations in these countries to be fair and ethical. See UKRI equitable partnerships guidance .

Research involving human participants requires approval from an independent ethics committee in the UK. You should also seek ethical review from an independent ethics committee in any developing country where there are study participants.

If you are struggling to obtain a UK REC review, email: [email protected] .

In the ethics and responsible research and innovation section of the grant application form, you should describe any ethical implications relevant to your application and confirm that these are being addressed.

The following is a list of ethical considerations that might arise when designing and conducting research in lower and middle-income countries.

If any of these are relevant to your research and not discussed elsewhere, you should confirm how you will address these issues. You do not need to make a statement about issues that are not relevant to the application.

Research approvals

You should confirm that you will seek appropriate ethics review, and any other relevant approvals, in the UK and in any other countries involved. No research should start until these approvals are in place. They do not need to be in place at the time of applying for a grant.

Vulnerable groups

You should state whether any participants will be from vulnerable groups, justify their involvement and briefly clarify how the study design takes account of their needs.

Examples of vulnerable groups might include children, prisoners, victims of violence, military conscripts, and individuals lacking capacity or disadvantaged by poverty or gender.

Informed consent

You should indicate if there are specific considerations in relation to consent influencing the proposal, for example, providing information to participants whose language has no written form, or seeking consent from community leaders as well as participants when this is expected.

Managing participant care

You should state whether, in the design of the research, you have considered the risks of any intervention, the standard of care to be offered to participants (including controls) during the research, continuing care after the research ends and ancillary care.

Information management

Describe how you will manage participant confidentiality and data security, including transfer outside the developing country or sharing of data in a registry.

You should consider all relevant information formats, including conversations, medical consultations, written data, images, sample analyses and research outputs.

You should describe research data management in the data management pan. However, you can also highlight specific issues in the ‘ethical implications’ section of the application form.

Management of biosamples and biobanks

If your application involves the collection or use of biosamples, then you should confirm you will comply with relevant local or UK codes of practice or legal requirements.

For example, this may influence arrangements for transfer of biosamples outside the developing country for analysis

Adverse impacts of the research

You should consider the wider impact of the research, negative as well as positive, on participants and communities and state how you will manage this.

For example, this may include engagement with local stakeholders to ensure that the outputs of the research are used to benefit the local population and reduce inequity or discrimination.

Public and community engagement in the developing countries

We encourage you to involve community and patient advocate groups in designing and conducting the research to increase the acceptability of the study and its findings.

If you have undertaken preliminary engagement work or there are plans for future engagement, you should state this.

If all public engagement activities have taken (or will take) place only in the UK, then you should demonstrate that these are relevant to the participant population in the developing country and that you have considered capacity-building in developing countries.

11. Health and Safety

Genetic modification.

The Genetically Modified Organisms (Contained Use) Regulations 2014 require laboratories that intend to carry out genetic modification to assess the risks of all activities and make sure that any necessary controls are in place.

Genetically modified organisms (GMOs) may be plants, animals or (most commonly) microorganisms (including bacteria, viruses, parasites and fungi). Humans are not regarded as GMOs under this legislation.

Further information about the legislation and relevant approvals required is available on the Health and Safety Executive website .

Dangerous pathogens

Research organisations proposing to accommodate projects that will involve the use of dangerous pathogens must comply with the safeguards recommended by the Advisory Committee on Dangerous Pathogens (ACDP).

Read ACDP publications on guidance and regulation .

12. Controlled drugs

If your research requires the use of drugs controlled under the Misuse of Drugs Act, 1971, and its subsequent amendments, you must seek a Home Office licence directly through the host institution’s normal channels.

You should refer to the Psychoactive Substances Act: guidance for researchers to ensure you comply with the Psychoactive Substances Act 2016.

13. Development of software as part of a grant

In accordance with government policy on open source software (OSS), if your research aims to produce software outputs you must specify a proposed software exploitation route in the case for support.

When the project is completed, the software should be exploited either commercially, within an academic community or as OSS.

Further information on OSS can be found on the Open Source Initiative website .

Note: the policy on exploiting research and development software does not apply to software developed in the areas of defence, national security or law enforcement. Neither does it apply to software developed by trading funds.

Visit developing healthcare products if you are developing an app or other software with a medical purpose. These may be medical devices.

14. Research misuse and biosecurity

Some biomedical research, while having potential to greatly benefit society, carries the risk that the research outcomes or technologies used in research could be deliberately misused or unintentionally result in harm (for example, certain gain-of-function studies with the potential to enhance the pathogenicity or transmissibility of pathogens).

UKRI is committed to ensuring that applications for funding consider and manage these types of risks appropriately.

Refer to MRC’s policy statement on managing the risks of research misuse for more information.

You must identify risks associated with the unethical use of your proposed research and other biosecurity implications of your study and detail how you will mitigate them. Considerations may include, for example:

• measures for safe and secure access to the project data, information or outcomes
• access to research infrastructure or certain technologies

When collaborating internationally, you should ensure that you apply UKRI trusted research and innovation principles .

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Patient Recruitment

Ethics in clinical research, ethical guidelines.

The goal of clinical research is to develop generalizable knowledge that improves human health or increases understanding of human biology. People who participate in clinical research make it possible to secure that knowledge. The path to finding out if a new drug or treatment is safe or effective, for example, is to test it on patient volunteers. But by placing some people at risk of harm for the good of others, clinical research has the potential to exploit patient volunteers. The purpose of ethical guidelines is both to protect patient volunteers and to preserve the integrity of the science.

The ethical guidelines in place today were primarily a response to past abuses, the most notorious of which in America was an experiment in Tuskegee, Alabama, in which treatment was withheld from 400 African American men with syphilis so that scientists could study the course of the disease. Various ethical guidelines were developed in the 20th century in response to such studies. 

Some of the influential codes of ethics and regulations that guide ethical clinical research include:

• Nuremberg Code (1947)
• Declaration of Helsinki (2000)
• Belmont Report  (1979)
• CIOMS (2002)
• U.S. Common Rule (1991)

Using these sources of guidance and others, seven main principles have been described as guiding the conduct of ethical research:

Social and clinical value

Scientific validity, fair subject selection, favorable risk-benefit ratio, independent review, informed consent, respect for potential and enrolled subjects.

Every research study is designed to answer a specific question. Answering certain questions will have significant value for society or for present or future patients with a particular illness. An answer to the research question should be important or valuable enough to justify asking people to accept some risk or inconvenience for others. In other words, answers to the research question should contribute to scientific understanding of health or improve our ways of preventing, treating, or caring for people with a given disease. Only if society will gain useful knowledge — which requires sharing results, both negative and positive — can exposing human subjects to the risk and burden of research be justified.

A study should be designed in a way that will get an understandable answer to the valuable research question. This includes considering whether the question researchers are asking is answerable, whether the research methods are valid and feasible, and whether the study is designed with a clear scientific objective and using accepted principles, methods, and reliable practices. It is also important that statistical plans be of sufficient power to definitively test the objective, for example, and for data analysis. Invalid research is unethical because it is a waste of resources and exposes people to risk for no purpose

Who does the study need to include, to answer the question it is asking? The primary basis for recruiting and enrolling groups and individuals should be the scientific goals of the study — not vulnerability, privilege, or other factors unrelated to the purposes of the study. Consistent with the scientific purpose, people should be chosen in a way that minimizes risks and enhances benefits to individuals and society. Groups and individuals who accept the risks and burdens of research should be in a position to enjoy its benefits, and those who may benefit should share some of the risks and burdens. Specific groups or individuals (for example, women or children) should not be excluded from the opportunity to participate in research without a good scientific reason or a particular susceptibility to risk.

Uncertainty about the degree of risks and benefits associated with a drug, device, or procedure being tested is inherent in clinical research — otherwise there would be little point to doing the research. And by definition, there is more uncertainty about risks and benefits in early-phase research than in later research. Depending on the particulars of a study, research risks might be trivial or serious, might cause transient discomfort or long-term changes. Risks can be physical (death, disability, infection), psychological (depression, anxiety), economic (job loss), or social (for example, discrimination or stigma from participating in a certain trial). Has everything been done to minimize the risks and inconvenience to research subjects, to maximize the potential benefits, and to determine that the potential benefits to individuals and society are proportionate to, or outweigh, the risks? Research volunteers often receive some health services and benefits in the course of participating, yet the purpose of clinical research is not to provide health services.

To minimize potential conflicts of interest and make sure a study is ethically acceptable before it even starts, an independent review panel with no vested interest in the particular study should review the proposal and ask important questions, including: Are those conducting the trial sufficiently free of bias? Is the study doing all it can to protect research volunteers? Has the trial been ethically designed and is the risk–benefit ratio favorable? In the United States, independent evaluation of research projects is done through granting agencies, local institutional review boards (IRBs), and data and safety monitoring boards. These groups also monitor a study while it is ongoing.

For research to be ethical, most agree that individuals should make their own decision about whether they want to participate or continue participating in research. This is done through a process of informed consent in which individuals (1) are accurately informed of the purpose, methods, risks, benefits, and alternatives to the research, (2) understand this information and how it relates to their own clinical situation or interests, and (3) make a voluntary decision about whether to participate.

There are exceptions to the need for informed consent from the individual — for example, in the case of a child, of an adult with severe Alzheimer’s, of an adult unconscious by head trauma, or of someone with limited mental capacity. Ensuring that the individual’s research participation is consistent with his or her values and interests usually entails empowering a proxy decision maker to decide about participation, usually based on what research decision the subject would have made, if doing so were possible.

Individuals should be treated with respect from the time they are approached for possible participation—even if they refuse enrollment in a study—throughout their participation and after their participation ends. This includes:

• Respecting their privacy and keeping their private information confidential.
• Respecting their right to change their mind, to decide that the research does not match their interests, and to withdraw without penalty.
• Informing them of new information that might emerge in the course of research, which might change their assessment of the risks and benefits of participating.
• Monitoring their welfare and, if they experience adverse reactions, untoward events, or changes in clinical status, ensuring appropriate treatment and, when necessary, removal from the study.
• Informing them about what was learned from the research. Most researchers do a good job of monitoring the volunteers’ welfare and making sure they are okay. They are not always so good about distributing the study results. If they don’t tell you, ask

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Ezekiel J. Emanuel, MD, PhD; David Wendler, PhD, and Christine Grady, PhD. " What Makes Clinical Research Ethical? " Journal of the American Medical Association, Vol. 283, No. 20, May 24, 2000, pp. 2701-2711.

Dr. Grady is acting chief of the Bioethics Department and head of the Section on Human Subjects Research. Dr. Wendler heads the Unit on Vulnerable Populations. Dr. Emanuel was chief of the CC Bioethics Department  1996-2011.

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Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Peer Review reports

Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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Caesar A. Atuire

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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Received : 31 October 2023

Accepted : 01 April 2024

Published : 18 April 2024

DOI : https://doi.org/10.1186/s12910-024-01044-w

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