legal ethics research paper

Georgetown Journal of Legal Ethics

Remedying conflict of interest issues in public health bodies, the inadequacy of objectivity for a feminist movement: how the pro-choice movement failed women of color and its own agenda, time to end the chaos: a call for regulatory reform on the online food labeling system, under pressure: the effects of dobbs on lawyers advising abortion providers, the intersection of civil rights, religious liberty, and infectious disease, fairness and due process in class settlements: analyzing amchem and stephenson, environmental (non)disclosure and the sec’s proposed solution, lawyers’ obligation to decline representation for morally reprehensible clients in animal law, ethical lawyering, attorney-client privilege, and dual–purpose communications in light of in re grand jury, non-disclosure provisions in medical malpractice settlements: the silent killer of accountability and patient safety, the independent attorney general: an analysis of why the office should be insulated from presidential political imperatives, the office of congressional discipline: reforming congressional misconduct investigations by bringing investigations in-house, the vaccine monologues: federal vaccine policy and sirva’s place in the vaccine injury compensation program, practicing ethically in virtual environments and the rise of remote proceedings in a post covid-19 era, erisa as a solution to insurer abrogation of responsibility in the face of the opioid crisis, balancing liberal ideals with the use of a cultural defense, plain language in the written law, the dobbs leak as an illustration of the impasse between legal ethics and reality, the georgetown journal of legal ethics 2024 symposium.

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Legal Ethics

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I. Introduction

Researching issues in professional responsibility is a complex process and requires use of materials beyond judicial decisions and statutes. At the core of issues of legal ethics are the rules governing the conduct of lawyers and judges that are adopted by each jurisdiction. These state rules are based on model rules adopted by the American Bar Association, most recently the Model Rules of Professional Conduct and the Code of Judicial Conduct. In addition, each state bar association has some mechanism for enforcing the rules through disciplinary proceedings and through the issuance of opinion letters on ethical issues submitted to it.

You may need to consult bar association ethics opinions, the Model Rules, and the version of the rules of professional conduct for your particular jurisdiction. Case law research can also be complicated because ethics issues can arise from attorney discipline proceedings and such diverse substantive areas as legal malpractice and criminal appeals. This research guide concentrates on materials other than case law, although a few tips on finding judicial decisions in the area of legal ethics are included.

II. Getting Started

If you need some basic background on professional responsibility or an overview of key issues, start with these texts:

• The Law of Lawyering (4th ed.) by Geoffrey C. Hazard, Jr (online in Fastcase & Cheetah & updated to 2017 at KF306 .H333)
• Legal Ethics in a Nutshell (5th ed) by Ronald Rotunda ( online & KF306.Z9 R668 2018),
• Legal Ethics, Professional Responsibility, and the Legal Profession , by Sisk et al (KF306 .S57 2018 & online )
• Mastering Professional Responsibility (2d ed.) by Grace M. Giesel (KF306 .G547 2015)
• Understanding Lawyers' Ethics by Monroe Freedman (KF306 .F76 2016).

There are numerous treatises on legal ethics and professional responsibility. Generally these materials can be found in the KF306 area of the library collection, but can be searched in the catalog under the subject headings: Legal Ethics -- United States and Attorney and Client -- United States .

To access legal ethics resources electronically, follow these research trails:

• Westlaw : Secondary Sources > By Topic > Ethics & Professional Responsibility
• Lexis+ : Explore > Practice Area > Legal Ethics
• Bloomberg Law : Browse > Practice Centers > Legal Ethics & Professional Responsibility

American Bar Association, Legal Ethics: The Lawyer's Deskbook on Professional Responsibility (KF306 .R68 & online in Westlaw ) is a comprehensive volume by the Center for Professional Responsibility of the ABA that discusses current issues using up-to-date case references, commentary and discussion. It is organized around the Model Rules and includes references to the Restatement (Third) of the Law Governing Lawyers .

ABA/BNA Lawyer's Manual on Professional Conduct (online in Bloomberg Law ) is the electronic equivalent of a looseleaf service (no longer published in print) that takes a comprehensive approach to providing materials on legal ethics. It provides text and commentary of the ABA Model Rules and Model Code and ethics rules for all of the states, as well as opinions from the ABA and digest summaries of opinions from various states.

Restatement (Third) of the Law Governing Lawyers (KF395.G613 A7 2000 & online), like all Restatements, has been developed over many years by legal experts and states the best practice in the area, with commentary. The Restatement is much broader in scope than the ABA rules and includes many areas of law affecting legal practice such as civil liability, evidence and agency. The Restatement is available electronically on HeinOnline 's American Law Institute Library, Lexis , and Westlaw .

If your issue is legal malpractice, Ronald Mallen & Jeffrey Smith, the annual edition of Legal Malpractice (KF313 .M342 & online in Westlaw ) is a good overview of the subject.

For criminal lawyers, John Wesley Hall, Jr, Professional Responsibility in Criminal Defense Practice [revised ed. of Professional Responsibility of the Criminal Lawyer ], 3d ed. (KF306 .H25 & online in Westlaw ) will help you spot potential problems.

III. Codes of Professional Responsibility for Lawyers

The American Bar Association has provided leadership in legal ethics through the adoption of professional standards that serve as models of the law governing lawyers since the adoption of the Canons of Professional Ethics in 1908. The latest version of these standards is the Model Rules of Professional Conduct , first adopted in 1983 and amended a number of times since then. The Model Rules of Professional Conduct consist of a Preamble, a statement of their scope, and a list of approximately 60 rules, organized into eight subject areas. Each Rule is followed by a comment explaining the Rule.

The Model Rules replaced the Model Code of Professional Responsibility , which was adopted in 1969. The Model Code of Professional Responsibility is divided into three types of provisions: Canons, Disciplinary Rules, and Ethical Considerations, plus a set of Definitions. The Canons are general statements, defined as "axiomatic norms." The Disciplinary Rules (DR) are considered to be mandatory. Ethical Considerations (EC) contain objectives towards which lawyers should strive.

The text of the current and historical versions of the Model Code and Rules with comments can be found in many places, including most of the resources listed at the end of this guide. A few convenient sources are:

• The American Bar Association's Center for Professional Responsibility maintains a page for the Model Rules of Professional Conduct . Included are the full text of the current Rules, the Model Code and the 1908 Canons of Professional Ethics . Also included are lists detailing state adoption of the Rules and links to state ethics rules and opinions. In addition, it provides commentary, legislative history and a comparison of the Rules to the ALI Restatement (3d) of the Law Governing Lawyers .
• American Bar Association, Model Rules of Professional Conduct (annual) (Reserve KF306 .A74816). Includes a Table of Amendments and Correlation Table between the Model Code and Rules and subject index.
• American Bar Association, Annotated Model Rules of Professional Conduct , 8th ed. (Reserve KF305.A26 2015). Includes comparisons between the Rules and the Code , narrative on the legal background of each rule, discussion of related legal issues, and citations to supporting cases and opinions.
• To access the Model Rules on Lexis , follow the path Practice Area > Legal Ethics > All Legal Ethics Administrative Materials to view available sources, including "ABA Model Rules of Professional Conduct and Code of Judicial Conduct." On Westlaw , use the path Secondary Sources > By Topic > Ethics & Professional Responsibility to find annotated and unannotated versions of the Rules. In Bloomberg Law , visit Practice Centers > Legal Ethics & Professional Responsibility.
• ABA Compendium of Professional Responsibility Rules and Standards (current year ed.) (Reserve KF305.A2 A23). Includes Table of Amendments and a Correlation Table between the Model Code and Rules and a subject index, as well as selected federal procedural rules and a few well-known ABA Ethics Opinions.

The Model Code and Model Rules are not binding on anyone, but serve as a model for adoption by states. Their interpretation in case law and ethics opinions also serves as guidance, since the state rules are based on these models. Since 1983 almost all of the states have adopted some form of the ABA Model Rules. The others use a version of the Model Code . California is the only state that has never adopted either model and has its own rules of professional responsibility. Many of its provisions are, of course, similar to the model acts, and a 2017 revision brought their organization closer to that of the Model Rules. The states can modify the model rules when adopted or at any later time.

Codes or rules of professional conduct for lawyers and judges function much like statutes. However, most are not adopted by the legislature, but instead by state bar associations or the highest court of the jurisdiction. Because these model codes have effect in a state only as they are adopted by that state, begin your research by finding your state’s version of the Model Code or Model Rules .

IV. Sources for State and Other Ethics Codes

• American Bar Association Center for Professional Responsibility Other Links of Interest links to state codes, codes of other countries and those of other legal entities.
• Court Rules books . West and/or Lexis publishes separate paperback volumes of court rules for many states which contain the current version of the rules or code of ethics. These books are found at the end of the code for each state (Level 3), and may also be found in the online catalog with a subject heading search for court rules – [state] .
• For state rules on Westlaw ,  Lexis and Bloomberg Law : Ethics rules are included in the databases for a state's statutes and court rules.

V. Interpreting the Rules

A good way to begin interpreting ethics rules is to consult the Annotated Model Rules of Professional Conduct , 9th ed. (Reserve KF305 .A26 2019 & online in Westlaw ), which includes comparison between the Model Rules and the Code, a narrative on the legal background of each rule and paragraphs on each rule and sub-rule, describing the legal issues and giving citations to supporting cases and ethics opinions.

Another good source to determine the intent of the rules is the American Bar Association's A Legislative History: the Development of the ABA Model Rules of Professional Conduct 1982-2013 (KF306 .L45 2013). Its stated intent is to "lead researchers to a better understanding of the Model Rules...and to aid all those who interpret or apply the Model Rules." It does that by tracing the evolution of the rules from the inception of the commission that created them to the present iteration, providing information on amendments proposed along the way and the arguments given for and against their adoption.

Some states also offer annotated versions of their ethics rules. Search the online catalog for the subject heading court rules – [state] to locate available annotated titles.

VI. Ethics Opinions

The ABA and each state’s bar association issue ethics opinions . These opinions are written in response to requests for advice from lawyers who want to know whether a past or contemplated future action violates an ethical code. There are usually both formal and informal opinions. Formal opinions are those the ABA deems relevant to a large number of attorneys and tend to contain more in-depth discussion, while informal opinions are given in cases where the ABA does not believe there will be as much general interest. These opinions are recommendations to the attorney and are not enforceable. They may be cited in another case as persuasive authority to show how the ABA or the state bar has interpreted the Code or Rules. Formal and Informal ABA opinions are available on Westlaw  (Administrative Decisions & Guidance > Ethics & Disciplinary Opinions > ABA Ethics Opinions) and in Lexis (Practice Area > Legal Ethics) where they can be searched in full text. Formal opinions began in 1924 and informal opinions began publication in 1961.

ABA/BNA Lawyer's Manual on Professional Conduct is an electronic database (available in Bloomberg Law ) that includes recent legal ethics news stories, the full text of ABA ethics opinions as well as a digest of state ethics opinions, and links to additional ethics resources by state. The site also provides the full text of the ABA's Model Rules of Professional Conduct as well as a link to the ABA's comparison chart between the ABA Model Rules and the adopted rules of each jurisdiction.

In addition to the online services listed above, full texts of ABA ethics opinions appear in a series of volumes published by the ABA. Informal opinions were published only in summary form prior to 1960.

• Opinions of the Committee on Professional Ethics (KF305.A19 O6 1967) includes Formal Opinions 1-315.
• Informal Ethics Opinions (KF305 .A2 1975) is a two-volume set which includes all known Informal Opinions from 1961-1973.
• Formal and Informal Ethics Opinions (KF305 .A2) continues the prior volumes, compiling both types of opinions into a single publication.

New ABA Formal opinions are published regularly in the ABA Journal (Periodicals & online ). Recent opinions are available for free on the ABA Center for Professional Responsibility website, but archived opinions are available only to members or for a fee at this location. For the full text of state bar association ethics opinions, a comprehensive historical compilation was the National Reporter on Legal Ethics and Professional Responsibility , which is available in paper (1982-2004) (KF305 .A8 N37), on microfiche in the Microforms Room (1983-2007), and in Lexis (up to 2011).  This  Reporte r contains sections on ethics opinions, including both bar association opinions and some court decisions, for most states and the District of Columbia. Although this is the one set that collected the full text of all this material, it was not always complete and it can be cumbersome to use without a known citation.

Many state ethics opinions are published in state bar journals . Titles in the library's collection may be in paper (Periodicals, Level 4) or in microfiche, with many titles also available in HeinOnline’s Bar Journals Library . Links to state ethics opinions available on the Web can be accessed from the state bar or bar association (accessible through the ABA's interactive map ) , or through Westlaw  (Administrative Decisions & Guidance > Ethics & Disciplinary Opinions) or Lexis (Practice Area > Legal Ethics > filter by state).

VII. Disciplinary Proceedings

Lawyers can, of course, be disciplined for a breach of state ethics rules in the state where they are licensed. Each state has its own disciplinary procedure for violations of its rules, but generally there is an initial, informal process to determine whether the charge or complaint filed requires a full administrative hearing. If a hearing is held, it is before an administrative board, usually created under the authority of the state's highest court. Results of disciplinary proceedings are most often found on the disciplinary body's website and in the state's bar journal , but few states publish detailed "opinions" or orders regarding these hearings.

To search for attorney discipline records and any available opinions from state bars, begin at the ABA Directory of Lawyer Disciplinary Agencies (last updated 2020). Most state bars provide public access to attorney disciplinary records as part of a member directory search.  

Appeals from these hearings are allowed, generally directly to the state’s highest court. Appellate court opinions will likely contain more detailed analysis of the ethics violation than the bar’s notice of disciplinary action.

VIII. Case Law

In determining issues of legal ethics, court opinions carry more weight than the bar association ethics opinions described above. The context of case law involving legal ethics issues can be diverse, including appeals of disciplinary proceedings, legal malpractice, sanctions under FRCP 11, 26 and 37 and their state counterparts, and criminal appeals where ineffective assistance of counsel is alleged. Fortunately, they are easier to find using standard research tools, such as case law databases in Bloomberg Law , Lexis , Westlaw , or Fastcase .

Another way to find historical cases interpreting the Model Rules and Code is to Shepardize using Shepard's Professional and Judicial Conduct Citations (Ref KF308.A535 S46, updated through 2008). Shepard's will provide citations to court opinions, ethics opinions and law review articles dealing with a provision of the Model Code or Model Rules, beginning in 1980. You cannot Shepardize or KeyCite these electronically on Lexis or Westlaw.

You can also use digests in print or online to find ethics cases. When using the digest, try the key numbers under the topic Attorney and Client .  In Westlaw , the digest key number outline can be browsed at the Tools tab; in addition, there are individual state databases and databases for all federal and all state cases. In other online services, a search of case law for a particular jurisdiction will retrieve case results dealing with legal ethics topics.

IX. Judicial Ethics

Judges are bound by the general rules of professional conduct for all lawyers, but special rules of professional conduct for judges also exist.  The ABA Model Code of Judicial Conduct was adopted in 1972 and revised most recently in 2010.  It consists of a Preamble, Terminology section, and 4 Canons with comments.   Prior to this there was the ABA Canons of Judicial Conduct .  The text of the model code is usually included in most sources that have the Model Rules and Code for lawyers. The current Model Code is available online , along with comparisons to prior editions.

The Model Code of Judicial Conduct is also reprinted in the ABA’s annual publication Model Rules of Professional Conduct (Reserve KF306 .A74816). An annotated version of the most recent judicial code is also available (KF8779 .A96 2016).

Like the rules for lawyers, each state adopts its own rules for judicial conduct, and most are based on this ABA model. State judicial conduct codes are generally reproduced as part of state court rules publications and databases (see section IV).

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Introduction

This guide will give you an overview of the materials available, both print and online, that you will need to conduct your research in legal ethics. This also guide identifies resources available for researching the legal profession, focusing on materials for the management of law offices and corporate legal departments.

Getting Started

• Westlaw: All ABA Ethics Materials
• Lexis: All Legal Ethics Materials
• Bloomberg Law: All Professional Responsibility Materials
• ABA/Bloomberg Law Lawyer's Manual on Professional Conduct

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Reference Desk : Atrium, 2nd (Main) Floor (202) 662-9140 Request a Research Consultation  

Update history.

Updated 6/15 (SG) Links 6/16 (AWL) Updated 5/21 (DGD)

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• Last Updated: Jun 21, 2024 1:51 PM
• URL: https://guides.ll.georgetown.edu/legal_ethics

Ethical and Legal Issues of Research

• First Online: 01 January 2022

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• Indian J Anaesth
• v.60(9); 2016 Sep

Legal and ethical issues in research

Camille yip.

1 Department of Women's Anaesthesia, KK Women's and Children's Hospital, Bukit Timah, Singapore

Nian-Lin Reena Han

2 Division of Clinical Support Services, KK Women's and Children's Hospital, Bukit Timah, Singapore

Ban Leong Sng

3 Anesthesiology and Perioperative Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore

Legal and ethical issues form an important component of modern research, related to the subject and researcher. This article seeks to briefly review the various international guidelines and regulations that exist on issues related to informed consent, confidentiality, providing incentives and various forms of research misconduct. Relevant original publications (The Declaration of Helsinki, Belmont Report, Council for International Organisations of Medical Sciences/World Health Organisation International Guidelines for Biomedical Research Involving Human Subjects, World Association of Medical Editors Recommendations on Publication Ethics Policies, International Committee of Medical Journal Editors, CoSE White Paper, International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use-Good Clinical Practice) form the literature that are relevant to the ethical and legal aspects of conducting research that researchers should abide by when conducting translational and clinical research. Researchers should note the major international guidelines and regional differences in legislation. Hence, specific ethical advice should be sought at local Ethics Review Committees.

INTRODUCTION

The ethical and legal issues relating to the conduct of clinical research involving human participants had raised the concerns of policy makers, lawyers, scientists and clinicians for many years. The Declaration of Helsinki established ethical principles applied to clinical research involving human participants. The purpose of a clinical research is to systematically collect and analyse data from which conclusions are drawn, that may be generalisable, so as to improve the clinical practice and benefit patients in future. Therefore, it is important to be familiar with Good Clinical Practice (GCP), an international quality standard that is provided by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH),[ 1 ] or the local version, GCP of the Central Drugs Standard Control Organization (India's equivalent of US Food and Drug Administration)[ 2 ] and local regulatory policy to ensure that the research is conducted both ethically and legally. In this article, we will briefly review the legal and ethical issues pertaining to recruitment of human subjects, basic principles of informed consent and precautions to be taken during data and clinical research publications. Some of the core principles of GCP in research include defining responsibilities of sponsors, investigators, consent process monitoring and auditing procedures and protection of human subjects.[ 3 ]

ISSUES RELATED TO THE RESEARCH PARTICIPANTS

The main role of human participants in research is to serve as sources of data. Researchers have a duty to ‘protect the life, health, dignity, integrity, right to self-determination, privacy and confidentiality of personal information of research subjects’.[ 4 ] The Belmont Report also provides an analytical framework for evaluating research using three ethical principles:[ 5 ]

• Respect for persons – the requirement to acknowledge autonomy and protect those with diminished autonomy
• Beneficence – first do no harm, maximise possible benefits and minimise possible harms
• Justice – on individual and societal level.

Mistreatment of research subjects is considered research misconduct (no ethical review approval, failure to follow approved protocol, absent or inadequate informed consent, exposure of subjects to physical or psychological harm, exposure of subjects to harm due to unacceptable research practices or failure to maintain confidentiality).[ 6 ] There is also scientific misconduct involving fraud and deception.

Consent, possibility of causing harm

Based on ICH definition, ‘informed consent is a process by which a subject voluntarily confirms his or her willingness to participate in a particular trial, after having been informed of all aspects of the trial that are relevant to the subject's decision to participate’. As for a standard (therapeutic) intervention that carries certain risks, informed consent – that is voluntary, given freely and adequately informed – must be sought from participants. However, due to the research-centred, rather than patient-centred primary purpose, additional relevant information must be provided in clinical trials or research studies in informed consent form. The essential components of informed consent are listed in Table 1 [Adapted from ICH Harmonised Tripartite Guideline, Guideline for Good Clinical Practice E6(R1)].[ 1 ] This information should be delivered in the language and method that individual potential subjects can understand,[ 4 ] commonly in the form of a printed Participant Information Sheet. Informed consent is documented by means of written, signed and dated informed consent form.[ 1 ] The potential subjects must be informed of the right to refuse to participate or withdraw consent to participate at any time without reprisal and without affecting the patient–physician relationship. There are also general principles regarding risk assessment, scientific requirements, research protocols and registration, function of ethics committees, use of placebo, post-trial provisions and research publication.[ 4 ]

Essential components of an informed consent

Special populations

Informed consent may be sought from a legally authorised representative if a potential research subject is incapable of giving informed consent[ 4 ] (children, intellectual impairment). The involvement of such populations must fulfil the requirement that they stand to benefit from the research outcome.[ 4 ] The ‘legally authorised representative’ may be a spouse, close relative, parent, power of attorney or legally appointed guardian. The hierarchy of priority of the representative may be different between different countries and different regions within the same country; hence, local guidelines should be consulted.

Special case: Emergency research

Emergency research studies occur where potential subjects are incapacitated and unable to give informed consent (acute head trauma, cardiac arrest). The Council for International Organisations of Medical Sciences/World Health Organisation guidelines and Declaration of Helsinki make exceptions to the requirement for informed consent in these situations.[ 4 , 7 ] There are minor variations in laws governing the extent to which the exceptions apply.[ 8 ]

Reasonable efforts should have been made to find a legal authority to consent. If there is not enough time, an ‘exception to informed consent’ may allow the subject to be enrolled with prior approval of an ethical committee.[ 7 ] Researchers must obtain deferred informed consent as soon as possible from the subject (when regains capacity), or their legally authorised representative, for continued participation.[ 4 , 7 ]

Collecting patient information and sensitive personal information, confidentiality maintenance

The Health Insurance Portability and Accountability Act has requirements for informed consent disclosure and standards for electronic exchange, privacy and information security. In the UK, generic legislation is found in the Data Protection Act.[ 9 ]

The International Committee of Medical Journal Editors (ICMJE) recommendations suggest that authors must ensure that non-essential identifying information (names, initials, hospital record numbers) are omitted during data collection and storage wherever possible. Where identifying information is essential for scientific purposes (clinical photographs), written informed consent must be obtained and the patient must be shown the manuscript before publication. Subjects should also be informed if any potential identifiable material might be available through media access.

Providing incentives

Cash or other benefits ‘in-kind’ (financial, medical, educational, community benefits) should be made known to subjects when obtaining informed consent without emphasising too much on it.[ 7 ] Benefits may serve as appreciation or compensation for time and effort but should not result in the inducement to participation.[ 10 ] The amount and nature of remuneration should be compared to norms, cultural traditions and are subjected to the Ethical Committee Review.[ 7 ]

ISSUES RELATED TO THE RESEARCHER

Legal issues pertaining to regulatory bodies.

Various regulatory bodies have been constituted to uphold the safety of subjects involved in research. It is imperative to obtain approval from the appropriate regulatory authorities before proceeding to any research. The constitution and the types of these bodies vary nation-wise. The researchers are expected to be aware of these authorities and the list of various bodies pertinent to India are listed in the article “Research methodology II” of this issue.

Avoiding bias, inappropriate research methodology, incorrect reporting and inappropriate use of information

Good, well-designed studies advance medical science development. Poorly conducted studies violate the principle of justice, as there are time and resources wastage for research sponsors, researchers and subjects, and undermine the societal trust on scientific enquiry.[ 11 ] The Guidelines for GCP is an international ethical and scientific quality standard for designing, conducting, recording and reporting trials.[ 1 ]

Fraud in research and publication

De novo data invention (fabrication) and manipulation of data (falsification)[ 6 ] constitute serious scientific misconduct. The true prevalence of scientific fraud is difficult to measure (2%–14%).[ 12 ]

Plagiarism and its checking

Plagiarism is the use of others' published and unpublished ideas or intellectual property without attribution or permission and presenting them as new and original rather than derived from an existing source.[ 13 ] Tools such as similarity check[ 14 ] are available to aid researchers detect similarities between manuscripts, and such checks should be done before submission.[ 15 ]

Overlapping publications

Duplicate publications violate international copyright laws and waste valuable resources.[ 16 , 17 ] Such publications can distort evidence-based medicine by double-counting of data when inadvertently included in meta-analyses.[ 16 ] This practice could artificially enlarge one's scientific work, distorting apparent productivity and may give an undue advantage when competing for research funding or career advancement.[ 17 ] Examples of these practices include:

Duplicate publication, redundant publication

Publication of a paper that overlaps substantially with one already published, without reference to the previous publication.[ 11 ]

Salami publication

Slicing of data from a single research process into different pieces creating individual manuscripts from each piece to artificially increase the publication volume.[ 16 ]

Such misconduct may lead to retraction of articles. Transparent disclosure is important when submitting papers to journals to declare if the manuscript or related material has been published or submitted elsewhere, so that the editor can decide how to handle the submission or to seek further clarification. Further information on acceptable secondary publication can be found in the ICMJE ‘Recommendations for the Conduct, Reporting, Editing, and Publishing of Scholarly Work in Medical Journals’.

Usually, sponsors and authors are required to sign over certain publication rights to the journal through copyright transfer or a licensing agreement; thereafter, authors should obtain written permission from the journal/publisher if they wish to reuse the published material elsewhere.[ 6 ]

Authorship and its various associations

The ICMJE recommendation lists four criteria of authorship:

• Substantial contributions to the conception of design of the work, or the acquisition, analysis or interpretation of data for the work
• Drafting the work or revising it critically for important intellectual content
• Final approval of the version to be published
• Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Authors and researchers have an ethical obligation to ensure the accuracy, publication and dissemination of the result of research,[ 4 ] as well as disclosing to publishers relevant corrections, retractions and errata, to protect scientific integrity of published evidence. Every research study involving human subjects must be registered in a publicly accessible database (e.g., ANZCTR [Australia and NZ], ClinicalTrials.gov [US and non-US], CTRI [India]) and the results made publicly available.[ 4 ] Sponsors of clinical trials must allow all study investigators and manuscript authors access to the full study data set and the right to use all study data for publication.[ 5 ] Source documents (containing trial data) and clinical study report (results and interpretation of trial) form part of the essential documentation that must be retained for a length of time prescribed by the applicable local legislation.[ 1 ] The ICMJE is currently proposing a requirement of authors to share with others de-identified individual patient data underlying the results presented in articles published in member journals.[ 18 ]

Those who have contributed to the work but do not meet all four criteria should be acknowledged; some of these activities include provision of administrative support, writing assistance and proofreading. They should have their written permission sought for their names to be published and disclose any potential conflicts of interest.[ 6 ] The Council of Scientific Editors has identified several inappropriate types of authorship, such as guest authorship, honorary or gift authorship and ghost authorship.[ 6 ] Various interventions should be put in place to prevent such fraudulent practices in research.[ 19 ] The list of essential documents for the conduct of a clinical trial is included in other articles of the same issue.

The recent increase in research activities has led to concerns regarding ethical and legal issues. Various guidelines have been formulated by organisations and authorities, which serve as a guide to promote integrity, compliance and ethical standards in the conduct of research. Fraud in research undermines the quality of establishing evidence-based medicine, and interventions should be put in place to prevent such practices. A general overview of ethical and legal principles will enable research to be conducted in accordance with the best practices.

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• Ethical Considerations in Research | Types & Examples

Ethical Considerations in Research | Types & Examples

Published on October 18, 2021 by Pritha Bhandari . Revised on May 9, 2024.

Ethical considerations in research are a set of principles that guide your research designs and practices. Scientists and researchers must always adhere to a certain code of conduct when collecting data from people.

The goals of human research often include understanding real-life phenomena, studying effective treatments, investigating behaviors, and improving lives in other ways. What you decide to research and how you conduct that research involve key ethical considerations.

These considerations work to

• protect the rights of research participants
• enhance research validity
• maintain scientific or academic integrity

Table of contents

Why do research ethics matter, getting ethical approval for your study, types of ethical issues, voluntary participation, informed consent, confidentiality, potential for harm, results communication, examples of ethical failures, other interesting articles, frequently asked questions about research ethics.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe for research subjects.

You’ll balance pursuing important research objectives with using ethical research methods and procedures. It’s always necessary to prevent permanent or excessive harm to participants, whether inadvertent or not.

Defying research ethics will also lower the credibility of your research because it’s hard for others to trust your data if your methods are morally questionable.

Even if a research idea is valuable to society, it doesn’t justify violating the human rights or dignity of your study participants.

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Before you start any study involving data collection with people, you’ll submit your research proposal to an institutional review board (IRB) .

An IRB is a committee that checks whether your research aims and research design are ethically acceptable and follow your institution’s code of conduct. They check that your research materials and procedures are up to code.

If successful, you’ll receive IRB approval, and you can begin collecting data according to the approved procedures. If you want to make any changes to your procedures or materials, you’ll need to submit a modification application to the IRB for approval.

If unsuccessful, you may be asked to re-submit with modifications or your research proposal may receive a rejection. To get IRB approval, it’s important to explicitly note how you’ll tackle each of the ethical issues that may arise in your study.

There are several ethical issues you should always pay attention to in your research design, and these issues can overlap with each other.

You’ll usually outline ways you’ll deal with each issue in your research proposal if you plan to collect data from participants.

Voluntary participation means that all research subjects are free to choose to participate without any pressure or coercion.

All participants are able to withdraw from, or leave, the study at any point without feeling an obligation to continue. Your participants don’t need to provide a reason for leaving the study.

It’s important to make it clear to participants that there are no negative consequences or repercussions to their refusal to participate. After all, they’re taking the time to help you in the research process , so you should respect their decisions without trying to change their minds.

Voluntary participation is an ethical principle protected by international law and many scientific codes of conduct.

Take special care to ensure there’s no pressure on participants when you’re working with vulnerable groups of people who may find it hard to stop the study even when they want to.

Informed consent refers to a situation in which all potential participants receive and understand all the information they need to decide whether they want to participate. This includes information about the study’s benefits, risks, funding, and institutional approval.

You make sure to provide all potential participants with all the relevant information about

• what the study is about
• the risks and benefits of taking part
• how long the study will take
• your supervisor’s contact information and the institution’s approval number

Usually, you’ll provide participants with a text for them to read and ask them if they have any questions. If they agree to participate, they can sign or initial the consent form. Note that this may not be sufficient for informed consent when you work with particularly vulnerable groups of people.

If you’re collecting data from people with low literacy, make sure to verbally explain the consent form to them before they agree to participate.

For participants with very limited English proficiency, you should always translate the study materials or work with an interpreter so they have all the information in their first language.

In research with children, you’ll often need informed permission for their participation from their parents or guardians. Although children cannot give informed consent, it’s best to also ask for their assent (agreement) to participate, depending on their age and maturity level.

Anonymity means that you don’t know who the participants are and you can’t link any individual participant to their data.

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, and videos.

In many cases, it may be impossible to truly anonymize data collection . For example, data collected in person or by phone cannot be considered fully anonymous because some personal identifiers (demographic information or phone numbers) are impossible to hide.

You’ll also need to collect some identifying information if you give your participants the option to withdraw their data at a later stage.

Data pseudonymization is an alternative method where you replace identifying information about participants with pseudonymous, or fake, identifiers. The data can still be linked to participants but it’s harder to do so because you separate personal information from the study data.

Confidentiality means that you know who the participants are, but you remove all identifying information from your report.

All participants have a right to privacy, so you should protect their personal data for as long as you store or use it. Even when you can’t collect data anonymously, you should secure confidentiality whenever you can.

Some research designs aren’t conducive to confidentiality, but it’s important to make all attempts and inform participants of the risks involved.

As a researcher, you have to consider all possible sources of harm to participants. Harm can come in many different forms.

• Psychological harm: Sensitive questions or tasks may trigger negative emotions such as shame or anxiety.
• Social harm: Participation can involve social risks, public embarrassment, or stigma.
• Physical harm: Pain or injury can result from the study procedures.
• Legal harm: Reporting sensitive data could lead to legal risks or a breach of privacy.

It’s best to consider every possible source of harm in your study as well as concrete ways to mitigate them. Involve your supervisor to discuss steps for harm reduction.

Make sure to disclose all possible risks of harm to participants before the study to get informed consent. If there is a risk of harm, prepare to provide participants with resources or counseling or medical services if needed.

Some of these questions may bring up negative emotions, so you inform participants about the sensitive nature of the survey and assure them that their responses will be confidential.

The way you communicate your research results can sometimes involve ethical issues. Good science communication is honest, reliable, and credible. It’s best to make your results as transparent as possible.

Take steps to actively avoid plagiarism and research misconduct wherever possible.

Plagiarism means submitting others’ works as your own. Although it can be unintentional, copying someone else’s work without proper credit amounts to stealing. It’s an ethical problem in research communication because you may benefit by harming other researchers.

Self-plagiarism is when you republish or re-submit parts of your own papers or reports without properly citing your original work.

This is problematic because you may benefit from presenting your ideas as new and original even though they’ve already been published elsewhere in the past. You may also be infringing on your previous publisher’s copyright, violating an ethical code, or wasting time and resources by doing so.

In extreme cases of self-plagiarism, entire datasets or papers are sometimes duplicated. These are major ethical violations because they can skew research findings if taken as original data.

You notice that two published studies have similar characteristics even though they are from different years. Their sample sizes, locations, treatments, and results are highly similar, and the studies share one author in common.

Research misconduct

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement about data analyses.

Research misconduct is a serious ethical issue because it can undermine academic integrity and institutional credibility. It leads to a waste of funding and resources that could have been used for alternative research.

Later investigations revealed that they fabricated and manipulated their data to show a nonexistent link between vaccines and autism. Wakefield also neglected to disclose important conflicts of interest, and his medical license was taken away.

This fraudulent work sparked vaccine hesitancy among parents and caregivers. The rate of MMR vaccinations in children fell sharply, and measles outbreaks became more common due to a lack of herd immunity.

Research scandals with ethical failures are littered throughout history, but some took place not that long ago.

Some scientists in positions of power have historically mistreated or even abused research participants to investigate research problems at any cost. These participants were prisoners, under their care, or otherwise trusted them to treat them with dignity.

To demonstrate the importance of research ethics, we’ll briefly review two research studies that violated human rights in modern history.

These experiments were inhumane and resulted in trauma, permanent disabilities, or death in many cases.

After some Nazi doctors were put on trial for their crimes, the Nuremberg Code of research ethics for human experimentation was developed in 1947 to establish a new standard for human experimentation in medical research.

In reality, the actual goal was to study the effects of the disease when left untreated, and the researchers never informed participants about their diagnoses or the research aims.

Although participants experienced severe health problems, including blindness and other complications, the researchers only pretended to provide medical care.

When treatment became possible in 1943, 11 years after the study began, none of the participants were offered it, despite their health conditions and high risk of death.

Ethical failures like these resulted in severe harm to participants, wasted resources, and lower trust in science and scientists. This is why all research institutions have strict ethical guidelines for performing research.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

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The Deepfake Defense—Exploring the Limits of the Law and Ethical Norms in Protecting Legal Proceedings from Lying Lawyers

Loyola Law School, Los Angeles Legal Studies Research Paper No. 2023-02

84.5 Ohio St. L.J. 1068 (2024)

58 Pages Posted: 13 Feb 2023 Last revised: 22 Feb 2024

Rebecca Delfino

Loyola Law School Los Angeles

Date Written: February 12, 2023

Thousands of audiovisual images documented the insurrectionists who stormed the United States Capitol on January 6, 2021. Authorities subsequently collected those images and charged some for their criminal conduct. Given the overwhelming audiovisual evidence implicating the insurrectionists, it should be impossible to assert a plausible defense claiming that those unmistakably depicted in the images were not present. Right? Wrong. As the defense in the federal criminal trial of January 6th insurrectionist leader Guy Reffitt illustrated, the emergence of “deepfakes” has changed the landscape of plausible defenses to crimes. Reffitt led the attack on the Capital. Videos and other visual images showed him at the head of the crowd advancing on the Capitol’s West Terrace. He was arrested and charged with multiple crimes. And although the evidence, including audiovisual images, against Reffitt, was clear and overwhelming, his lawyer undermined it, arguing to the jury that the evidence against Reffitt was a “deepfake” – an audiovisual recording created using Artificial Intelligence technology that allows anyone with a smartphone to believably map one person’s movements and words onto the image of another person. Unfortunately, the law does not provide a clear response to Reffitt’s lawyer’s reliance on deepfakes as a defense. But this much is clear—the “deepfake defense” is a new challenge to our legal system’s adversarial process and truth-seeking function. Because the norms of professional ethics require lawyers to advocate zealously, deepfakes invite lawyers to raise objections and arguments to evidence to exploit juror bias and skepticism about what is real. Thus, lawyers may plant the seeds of doubt in jurors’ minds to question the authenticity of all digital audio and visual images, even those counsel knows to be genuine. Currently, no rule of procedure, ethics, or legal precedent directly addresses the presentation of the “deepfake defense” in court. The existing standards provide scant guidance because they were developed before the advent of deepfake technology. As a result, they do not solve the concern of how to deter lawyers from exploiting it. Although in the last several years, legal scholarship and the popular news media have addressed certain facets of deepfakes, there has been no in-depth commentary on the “deepfake defense.” This article is the first to explore the deepfake defense, locating it within the historical and current framework of lawyers’ efforts to fabricate evidence and the laws and the practice norms that exist to curb that conduct. It proposes a reconsideration of the ethical rules governing candor, fairness, and the limits of zealous advocacy and urges a re-examination of the court’s role in sanctioning such conduct. Thus, this article offers novel proposals to guide the way forward for lawyers and courts as they traverse this new technological landscape.

Keywords: Deepfakes, ethical rules, procedural rules, Lawyer deception, lying, deepfake defense, liars dividend

JEL Classification: K41

Suggested Citation: Suggested Citation

Rebecca Delfino (Contact Author)

Loyola law school los angeles ( email ).

919 Albany Street Los Angeles, CA 90015-1211 United States

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MINI REVIEW article

Legal and ethical consideration in artificial intelligence in healthcare: who takes responsibility.

• 1 Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
• 2 International Training and Research in Uro-Oncology and Endourology Group, Manipal, India
• 3 Department of Urology, Father Muller Medical College, Mangalore, India
• 4 Department of Humanities and Management, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
• 5 Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
• 6 Robotics and Urooncology, Max Hospital and Max Institute of Cancer Care, New Delhi, India
• 7 Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
• 8 Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
• 9 Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India
• 10 Department of Oral Medicine and Radiology, Manipal College of Dental Sciences, Manipal, Manipal Academy of Higher Education, Manipal, India
• 11 Department of Urology, Freeman Hospital, Newcastle upon Tyne, United Kingdom
• 12 Department of Urology, Jagiellonian University in Krakow, Kraków, Poland
• 13 Department of Urology, University Hospital Southampton National Health Service (NHS) Trust, Southampton, United Kingdom

The legal and ethical issues that confront society due to Artificial Intelligence (AI) include privacy and surveillance, bias or discrimination, and potentially the philosophical challenge is the role of human judgment. Concerns about newer digital technologies becoming a new source of inaccuracy and data breaches have arisen as a result of its use. Mistakes in the procedure or protocol in the field of healthcare can have devastating consequences for the patient who is the victim of the error. Because patients come into contact with physicians at moments in their lives when they are most vulnerable, it is crucial to remember this. Currently, there are no well-defined regulations in place to address the legal and ethical issues that may arise due to the use of artificial intelligence in healthcare settings. This review attempts to address these pertinent issues highlighting the need for algorithmic transparency, privacy, and protection of all the beneficiaries involved and cybersecurity of associated vulnerabilities.

Introduction

Increasing patient demand, chronic disease, and resource constraints put pressure on healthcare systems. Simultaneously, the usage of digital health technologies is rising, there has been an expansion of data in all healthcare settings. If properly harnessed, healthcare practitioners could focus on the causes of illness and keep track of the success of preventative measures and interventions. As a result, policymakers, legislators, and other decision-makers should be aware of this. For this to happen, computer and data scientists and clinical entrepreneurs argue that one of the most critical aspects of healthcare reform will be artificial intelligence (AI), especially machine learning ( 1 ). Artificial intelligence (AI) is a term used in computing to describe a computer program's capacity to execute tasks associated with human intelligence, such as reasoning and learning. It also includes processes such as adaptation, sensory understanding, and interaction. Traditional computational algorithms, simply expressed, are software programmes that follow a set of rules and consistently do the same task, such as an electronic calculator: “if this is the input, then this is the output.” On the other hand, an AI system learns the rules (function) through training data (input) exposure. AI has the potential to change healthcare by producing new and essential insights from the vast amount of digital data created during healthcare delivery ( 2 ).

AI is typically implemented as a system comprised of both software and hardware. From a software standpoint, AI is mainly concerned with algorithms. An artificial neural network (ANN) is a conceptual framework for developing AI algorithms. It's a human brain model made up of an interconnected network of neurons connected by weighted communication channels. AI uses various algorithms to find complex non-linear correlations in massive datasets (analytics). Machines learn by correcting minor algorithmic errors (training), thereby boosting prediction model accuracy (confidence) ( 3 , 4 ).

The use of new technology raises concerns about the possibility that it will become a new source of inaccuracy and data breach. In the high-risk area of healthcare, mistakes can have severe consequences for the patient who is the victim of this error. This is critical to remember since patients come into contact with clinicians at times in their lives when they are most vulnerable ( 5 ). If harnessed effectively, such AI-clinician cooperation can be effective, wherein AI is used to offer evidence-based management and provides medical decision-guide to the clinician (AI-Health). It can provide healthcare offerings in diagnosis, drug discovery, epidemiology, personalized care, and operational efficiency. However, as Ngiam and Khor point out if AI solutions are to be integrated into medical practice, a sound governance framework is required to protect humans from harm, including harm resulting from unethical behavior ( 6 – 17 ). Ethical standards in remedy may be traced lower back to the ones of the health practitioner Hippocrates, on which the idea of the Hippocratic Oath is rooted ( 18 – 24 ).

Machine Learning-healthcare applications (ML-HCAs) that were seen as a tantalizing future possibility has become a present clinical reality after the Food and Drug Administration (FDA) approval for autonomous artificial intelligence diagnostic system based on Machine Learning (ML). These systems use algorithms to learn from large data sets and make predictions without explicitly programming ( 25 ).

Applications of AI for Health Research

The use of data created for electronic health records (EHR) is an important field of AI-based health research. Such data may be difficult to use if the underlying information technology system and database do not prevent the spread of heterogeneous or low-quality data. Nonetheless, AI in electronic health records can be used for scientific study, quality improvement, and clinical care optimization. Before going down the typical path of scientific publishing, guideline formation, and clinical support tools, AI that is correctly created and trained with enough data can help uncover clinical best practices from electronic health records. By analyzing clinical practice trends acquired from electronic health data, AI can also assist in developing new clinical practice models of healthcare delivery ( 26 ).

Artificial Intelligence in Drug Development

In the future, AI is expected to simplify and accelerate pharmaceutical development. AI can convert drug discovery from a labor-intensive to capital- and the data-intensive process by utilizing robotics and models of genetic targets, drugs, organs, diseases and their progression, pharmacokinetics, safety and efficacy. Artificial intelligence (AI) can be used in the drug discovery and development process to speed up and make it more cost-effective and efficient. Although like with any drug study, identifying a lead molecule does not guarantee the development of a safe and successful therapy, AI was used to identify potential Ebola virus medicines previously ( 26 ).

Ethical Challenges

There is a continuous debate regarding whether AI “fits within existing legal categories or whether a new category with its special features and implications should be developed.” The application of AI in clinical practice has enormous promise to improve healthcare, but it also poses ethical issues that we must now address. To fully achieve the potential of AI in healthcare, four major ethical issues must be addressed: (1) informed consent to use data, (2) safety and transparency, (3) algorithmic fairness and biases, and (4) data privacy are all important factors to consider ( 27 ). Whether AI systems may be considered legal is not only a legal one but also a politically contentious one (Resolution of the European Parliament, 16 February 2017) ( 28 ).

The aim is to help policymakers ensure that the moral demanding situations raised by enforcing AI in healthcare settings are tackled proactively ( 17 ). The limitation of algorithmic transparency is a concern that has dominated most legal discussions on artificial intelligence. The rise of AI in high-risk situations has increased the requirement for accountable, equitable, and transparent AI design and governance. The accessibility and comprehensibility of information are the two most important aspects of transparency. Information about the functionality of algorithms is frequently deliberately made difficult to obtain ( 29 ).

Our capacity to trace culpability back to the maker or operator is allegedly threatened by machines that can operate by unfixed rules and learn new patterns of behavior. The supposed “ever-widening” divide is a cause for alarm, as it threatens “both the moral framework of society and the foundation of the liability idea in law.” The use of AI may leave us without anyone to hold accountable for any sort of damage done. The extent of danger is unknown, and the use of machines will severely limit our ability to assign blame and take ownership of the decision-making ( 30 ).

Modern computing approaches can hide the thinking behind the output of an Artificial Intelligent System (AIS), making meaningful scrutiny impossible. Therefore, the technique through which an AIS generates its outputs is “opaque.” A procedure used by an AIS may be so sophisticated that for a non-technically trained clinical user, it is effectively concealed while remaining straightforward to understand for a techie skilled in that area of computer science ( 5 ).

AISs, like IBM's Watson for oncology, are meant to support clinical users and hence directly influence clinical decision-making. The AIS would then evaluate the information and recommend the patient's care. The use of AI to assist clinicians in the future could change clinical decision-making and, if adopted, create new stakeholder dynamics. The future scenario of employing AIS to help clinicians could revolutionize clinical decision-making and, if embraced, create a new healthcare paradigm. Clinicians (including doctors, nurses, and other health professionals) have a stake in the safe roll-out of new technologies in the clinical setting ( 5 ).

The scope of emerging ML-HCAs in terms of what they intend to achieve, how they might be built, and where they might be used is very broad. ML-HCAs range from entirely self-sufficient synthetic intelligence diabetic retinopathy prognosis in primary care settings, to non-self-sufficient death forecasts, to manual coverage and resource allocation ( 25 ). Researchers ought to describe how those outputs can be included in the research, along with predictions. This information is essential to setting up the cost of the scientific trial and guiding scientific research ( 31 ).

AI applied in healthcare needs to adjust to a continuously changing environment with frequent disruptions, while maintaining ethical principles to ensure the well-being of patients ( 24 ). However, an easy, key component of figuring out the protection of any healthcare software relies upon the capacity to check out the software and recognize how the software would fail. For example, the additives and physiologic mechanisms of medications or mechanical devices are comparable to the technique for software programmes. On the other hand, ML-HCAs can present a “black box” issue, with workings that aren't visible to evaluators, doctors, or patients. Researchers ought to describe how those outputs can be included in the research, along with predictions. This information helps assess the cost of the scientific trial and guides scientific research ( 25 ).

Global Legislations

The Resolution of the European Parliament was based on research commissioned, supervised, and published by the policy department for “Citizens' Rights and Constitutional Affairs” in response to a request from the European Parliament's Committee on Legal Affairs. The report emphasizes the critical nature of a resolution calling for the immediate creation of a legislative instrument governing robots and AI, capable of anticipating and adapting to any scientific breakthroughs anticipated in the medium term ( 29 ). The various ethical and legal concerns associated with the use of AI in healthcare settings have been highlighted in Figure 1 .

Figure 1 . Various ethical and legal conundrums involved with the usage of artificial intelligence in healthcare.

Why is Responsibility Necessary?

When the setting or context changes, AI systems can fail unexpectedly and drastically. AI can go from being extremely intelligent to extremely naive in an instant. All AI systems will have limits, even if AI bias is managed. The human decision-maker must be aware of the system's limitations, and the system must be designed so that it fits the demands of the human decision-maker. When a medical diagnostic and treatment system is mostly accurate, medical practitioners who use it may grow complacent, failing to maintain their skills or take pleasure in their work. Furthermore, people may accept decision-support system results without questioning their limits. This sort of failure will be repeated in other areas, such as criminal justice, where judges have modified their decisions based on risk assessments later revealed to be inaccurate ( 32 ).

The use of AI without human mediation raises concerns about vulnerabilities in cyber security. According to a RAND perspectives report, applying AI for surveillance or cyber security in national security creates a new attack vector based on “data diet” vulnerabilities. The study also discusses domestic security issues, such as governments' (growing) employment of artificial agents for citizen surveillance (e.g., predictive policing algorithms). These have been highlighted as potentially jeopardizing citizens' fundamental rights. These are serious concerns because they put key infrastructures at risk, putting lives and human security and resource access at risk. Cyber security weaknesses can be a severe threat because they are typically hidden and only discovered after the event (after the damage is caused) ( 28 ).

In recent years, there has been an uptick in the feasibility, design, and ethics of lethal autonomous weapon systems (LAWS). These machines would have AI autonomy's vast discretion combined with the power to murder and inflict damage on humans. While these advancements may offer considerable advantages, various questions have been raised concerning the morality of developing and implementing LAWS ( 33 ).

The problem of selection bias in datasets used to construct AI algorithms is a typical occurrence. As established by Buolamwini and Gebru, there is bias in automated facial recognition and the associated datasets, resulting in lower accuracy in recognizing darker-skinned individuals, particularly women. A huge number of data points are required for ML, and the majority of frequently utilized clinical trial research databases come from selected populations. As a result, when applied to underserved and consequently probably underrepresented patient groups, the resulting algorithms may be more likely to fail ( 34 ).

Who Bears the Responsibility?

Unlike doctors, technologists are not obligated by law to be accountable for their actions; instead, ethical principles of practice are applied in this sector. This comparison summarizes the dispute over whether technologists should be held accountable if AIS is used in a healthcare context and directly affects patients. If a clinician can't account for the output of the AIS they're employing, they won't be able to appropriately justify their actions if they choose to use that data. This lack of accountability raises concerns about the possible safety consequences of using unverified or unvalidated AISs in clinical settings. Some scenarios show how opacity affects each stakeholder. Table 1 shows the necessary considerations for procedural and conceptual changes to be taken for ethical review for healthcare-based Machine learning research. It is indeed a challenging aspect of technology. We think that new framework and approach is needed for approval of AI systems but practitioners and hospitals using it need to be trained and hence have the ultimate responsibility of its use. Medical devices based AI will facilitate the decision making too carry out treatment and procedures by the individuals, and not to replace them in entirety. There is dearth of literature in this regard and a detailed frame-work needs to be developed by the highest bodies of policy makers.

Table 1 . Considerations for ethical review for healthcare-based Machine learning research: procedural and conceptual changes ( 31 ).

AISs should be evaluated and validated, according to the Association for the Advancement of Artificial Intelligence. It is critical to establish, test, measure, and assess the dependability, performance, safety, and ethical compliance of such robots and artificial intelligence systems logically and statistically/probabilistically before they are implemented. If a clinician chooses to employ an AIS, verification and validation may help them account for their activities reasonably. As previously mentioned, clinical rules of professional conduct do not allow for unaccountable behavior. It has been suggested, however, that AIS is not the only thing that may be opaque, and doctors can also be opaque. If AIS cannot be punished, it will be unable to take on jobs involving human care. Managers of AIS users should make it clear that physicians cannot evade accountability by blaming the AIS ( 5 ).

Assistive ML-HCAs provide resources to healthcare providers by providing “ideas” for treatment, prognosis, or control while relying on individual interpretation of any suggestions to make judgments. Autonomous ML-HCAs provide direct prognostic and control statements without the intervention of a clinician or any other human. Because the developer's preference for an ML-autonomy HCA's stage has clear implications for the assumption of responsibility and liability, this autonomy stage must be visible ( 25 ). Instead of asking if they were aware of the hazards and poor decision-making, the question should be asked if they could grasp and recognize those risks ( 35 ).

Bias in the Use of AI

Evidence suggests that AI models can embed and deploy human and social biases at scale. However, it is the underlying data than the algorithm itself that is to be held responsible. Models can be trained on data which contains human decisions or on data that reflects the second-order effects of social or historical inequities. Additionally, the way data is collected and used can also contribute to bias and user-generated data can act as a feedback loop, causing bias. To our knowledge there are no guidelines or set standards to report and compare these models, but future work should involve this to guide researchers and clinicians ( 36 , 37 ).

AI is moving beyond “nice-to-have” to becoming an essential part of modern digital systems. As we rely more and more on AI for decision making, it becomes absolutely essential to ensure that they are made ethically and free from unjust biases. We see a need for Responsible AI systems that are transparent, explainable, and accountable. AI systems increase in use for improving patient pathways and surgical outcomes, thereby outperforming humans in some fields. It is likely to meager, co-exist or replace current systems, starting the healthcare age of artificial intelligence and not using AI is possibly unscientific and unethical ( 38 ).

AI is going to be increasingly used in healthcare and hence needs to be morally accountable. Data bias needs to be avoided by using appropriate algorithms based on un-biased real time data. Diverse and inclusive programming groups and frequent audits of the algorithm, including its implementation in a system, need to be carried out. While AI may not be able to completely replace clinical judgment, it can help clinicians make better decisions. If there is a lack of medical competence in a context with limited resources, AI could be utilized to conduct screening and evaluation. In contrast to human decision making, all AI judgments, even the quickest, are systematic since algorithms are involved. As a result, even if activities don't have legal repercussions (because efficient legal frameworks haven't been developed yet), they always lead to accountability, not by the machine, but by the people who built it and the people who utilize it. While there are moral dielemmas in the use of AI, it is likely to meager, co-exist or replace current systems, starting the healthcare age of artificial intelligence, and not using AI is also possibly unscientific and unethical.

Author Contributions

NN, DSh, BH, and BS contributed to the conception and design of the study. MS, SI, DSw, SS, and KA organized the database. DSw, KA, VP, KS, SS, and SI wrote the first draft of the manuscript. NN, DSh, KS, BR, VP, and BH wrote sections of the manuscript. PC, BR, and BS critically reviewed and edited the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: artificial intelligence, machine learning, ethical issues, legal issues, social issues

Citation: Naik N, Hameed BMZ, Shetty DK, Swain D, Shah M, Paul R, Aggarwal K, Ibrahim S, Patil V, Smriti K, Shetty S, Rai BP, Chlosta P and Somani BK (2022) Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? Front. Surg. 9:862322. doi: 10.3389/fsurg.2022.862322

Received: 25 January 2022; Accepted: 18 February 2022; Published: 14 March 2022.

Reviewed by:

Copyright © 2022 Naik, Hameed, Shetty, Swain, Shah, Paul, Aggarwal, Ibrahim, Patil, Smriti, Shetty, Rai, Chlosta and Somani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Dasharathraj K. Shetty, raja.shetty@manipal.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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• Pass the tissue: restoring researcher access to legal human donations
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• http://orcid.org/0000-0003-0891-714X Meredith Leston ,
• Simon De Lusignan ,
• Richard Frederick Hobbs
• Nuffield Department of Primary Care Health Sciences , University of Oxford , Oxford , UK
• Correspondence to Ms Meredith Leston, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; meredith.leston{at}phc.ox.ac.uk

The sensitivity of human tissue and previous instances of misuse have, rightfully, led to the introduction of far-reaching oversight and regulatory mechanisms for accessing, storing and sharing samples. However, these restrictions, in tandem with more broad-based privacy regulations, have had the unintended consequence of obstructing legitimate requests for medical materials. This is of real detriment to ambitions for biomedical research, most notably the precision medicine agenda. As such, this paper makes the case for facilitating authorised researcher access to human tissue and associated data along practical medical ethics lines, detailing how liberating samples from unfit regulations, re-evaluating biobanks, diversifying considerations for donor benefit-risk, future proofing donor consent and flattening hierarchies of donation acceptability equate to a more cohesive and respectful means of managing biological samples and information than is achieved at present.

• Ethics- Medical
• Informed Consent
• Tissue and Organ Procurement

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/jme-2023-109033

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Recognising the sensitivity of human tissue donation and the historical 1 and contemporary abuses 2 thereof, strict regulations now govern sample sourcing, supply, retention and destruction. European mandates, including the Tissue and Cells Directives (2004/23/EC 3 ; 2006/17/EC 4 ; 2006/86/EC 5 ), have set standards for the quality, safe passage and testing protocols of human tissues intended for biomedical research while the Human Tissue Act of 2004 6 regulates the life cycle of these samples in the UK. However, the expansive nature of these legislative changes has often had the unintended consequence of obstructing researcher access to human samples via authorised pathways. 7 The scope of these restrictions, and their accompanying bureaucratic burden, has been criticised as stifling to scientific innovation and discovery. 8 This is especially apparent during times of public health emergency where inflexible regulations delay critical research. 9 Additionally, meeting broad consent and privacy requirements is challenging, especially when work leverages retrospective data or biobank stock. It may not be possible to confirm sample origins or previous terms of consent in these contexts. 10

Consequently, this paper will make the case for improving researcher access to human tissue along practical medical ethics lines. It will demonstrate how streamlining regulations, reforming biobanking, diversifying donor benefit-risk, future-proofing donor consent and tackling hierarchies of donation acceptability represents a more cohesive and ethically rigorous approach to the access and appropriate use of human tissue than we are achieving at present.

A regulatory oversight

Biological samples are best analysed in the context of the body they were extracted from. Doing so at scale not only reveals patterns of disease specific to the individual but those of potential relevance to entire populations. However, by labelling human tissues (annotating the gender, age, race, blood type or even lifestyle of the person they were extracted from) or providing researchers with wraparound access to relevant medical records, we increase the risk of donor reidentification during data security breaches. 11

Efforts to mitigate this risk have produced a daunting regulatory environment, with legislation including General Data Protection Regulation, 12 the Oviedo Convention 13 and the US Health Insurance Portability and Accountability Act 14 enforcing levels of data accountability that our current research landscape is insufficiently resourced to meet in all instances. Inequalities emerge in laboratory capacity to take on the associated administrative burden or to plan for the retrospective, collaborative or longitudinal research efforts that present greater consent challenges: these barriers select for only the most established and well funded. 15 Meanwhile, inflexible, and sometimes incomprehensible, tissue and data sharing agreements are disincentivising to industry and academia and the time and expense taken to secure them can be financially prohibitive to both. 16 Worse still, while official channels of procuring tissue data remain this challenging, private or black market channels will continue to proliferate. 17

As a collective, these obstacles carry substantial consequences for patient outcomes. The prioritisation of privacy over prognosis is especially poignant for those without the luxury of time. The concept of reciprocal altruism is a recurrent theme in research into patient motivations for donating biological samples: here the expectation, or at least hope, is that these donations lead to the discoveries that facilitate their recovery or that of patients just like them. 18 Though not strictly a violation of terms of consent, restricting researcher access in this way is arguably a violation of the spirit, or social contract, by which that consent was given.

While necessary, regulation also inhibits drug discovery and—with digital, cultured or synthetic tissue research in its infancy 19 —fosters an overreliance on animal samples 20 that are usually poorly generalisable to human outcomes 21 and ethically dubious. 22 As such, it is recommended that regulators pursue a more streamlined approach, ringfencing medical data and materials away from domain-general privacy regulations and constructing terms of access that can flex to patient preferences and prognoses.

The biobanking crisis

Red tape is far from the only bottleneck in biomedical research, however. The activities of biobanks, facilities dedicated to the processing, storage and onward distribution of biomedical donations, have also faced criticism. For example, the ways in which their performance is currently evaluated—most notably stocklist size and measures of capacity—can perversely incentivise donation hoarding. 23 This prolonged storage—and the destruction of expired samples that often occurs as a consequence 24 — is a direct violation of donor good faith and the aforementioned Oviedo Convention. 13 As per Article 22 (‘ the use of parts of the human body must be restricted to that for which specific information and consent was given’ ), the indefinite retention of samples invalidates consent taken from donors expecting them to be used for biomedical research.

As a bank, and not a vault, the health of these facilities must instead be appraised through metrics including collection-distribution turnaround time. Initiatives such as the Ethical Tissue Bank based out of University of Bradford 25 have been stood up to answer this call, countering the underutilisation of donations. Here, success is measured against the pace of sample churn, the breadth of sample distribution and the scale of research impact as access requests are trimmed down to a 3-week approval process. This is an asset for time-sensitive research; entire granting periods can expire in the time taken to secure samples from conventional biobanks, by comparison. 26 It is, therefore, recommended that this model of biobanking be considered best practice going forwards. As echoed in work by the European Commission 27 and Makhlouf and colleagues, 28 this will only be achieved if biobanking governance models and accreditation systems are aligned internationally—better coordinating access to donations and collaborations between entities in the process.

A new benefit system

At present, these opportunity costs of failing to use tissue samples for their donated purposes are poorly incorporated into the utilitarian benefit–risk calculations at the centre of medical ethics. 29 Moreover, while these concepts of benefit and risk should have parity, the legal protections associated with risk are far weightier in biomedical research than those associated with patient benefit: legal recourse can be sought for damages, but not so easily for lost opportunities.

There are multiple examples where this institutionalised risk-aversion has led to the termination of potentially high-reward investigations. Recent disruptions to the male contraceptive campaign are notable example—products that only spelled additional risk for its intended consumers (mild side effects) despite sizeable benefits for fertile partners who do not wish to conceive. 30 This conservative mindset has likewise undermined the use of human tissue and associated data as the hypothetical risks of reidentification or tissue misuse supersedes indirect, shared or other more distal forms of donor benefit. The sharp consequences of violating tissue protections only exacerbates the likelihood of their underuse and subsequent destruction. This, again, is in direct conflict with the tacit assumption or explicit assurance of onward usage that underpins donor consent. Failing to use what has been freely given out of fear of the ramifications that come with doing so improperly constitutes a violation of this consent.

Therefore, just as the advent of shared patient benefit–risk has seen the renewal of male contraceptive research, 31 this paper recommends that biomedical research stretch its own conceptualisation of the ways in which patients can benefit from donating their tissue and give even the most invisible positive externalities appropriate weighting in ethical evaluations in the process. The risk of sample expiration must also be fully costed, with biobanks reprimanded or fined when samples are stored indefinitely or data access is obstructed arbitrarily.

Consent à la carte

This paper has evidenced the primacy of both obtaining and honouring donor consent for ethical conduct in the biomedical sciences. In this, a prospective donor must be fully aware of what their contribution to research amounts to and the way their data, or donations, will be stored. However, due to the aforementioned legalities around this process, consenting a patient can be a narrow exercise: patients are typically invited to support a specific research endeavour in a specific way with data retained for a specific time and purpose. Changes to a research protocol will, therefore, need to reconsent the original patient set to go ahead. This can be cumbersome, especially when aiming to reanalyse data from the now-deceased, and frustrating for living donors who are repeatedly contacted to update their permissions. 10

Such ‘single-use’ consent conflicts with the experimental or expansive mindset that necessitates scientific discovery. It allows little room for nuance or conditionality, especially from the patient-side. This can be disempowering as individual patient preferences cannot be incorporated into standard legal documents. That said, obtaining broad or flexible consent at the point of extraction also poses problems: presenting patients with extensive lists of possible uses of their data, sometimes at the most stressful moment of their lives, can blur the line between consent and duress. 32

To counter these opposing criticisms, this paper recommends a middle way be found between one-time and open-ended consenting. A menu-style approach could be a viable way forward, if presented in plain language. Here, donors would be at liberty to consent via standard text or, if preferable, use additional opt-in clauses to stretch their consent to broader research interests or make it conditional to specific time windows or use-cases (vetoing pluripotent stem cell use in animal research, eg). This enhanced consenting process could also include accelerated data-sharing agreements, providing those who value research participation above extensive privacy protections with a mechanism to fast-track their samples and associated data to researchers. This tailoring process future-proofs donor consent and elevates their wishes above overfitting bureaucracy. It is acknowledged that this will have implications for online tissue directories—platforms that, based on researcher specifications, collate decentralised samples and their associated data. They will be required to adjust cataloguing methods to indicate when donor consent is no longer harmonised across intended research cohorts.

Emotional hierarchies

Beyond the structural, bureaucratic and legal challenges outlined, it is important to acknowledge the more psychological factors that influence tissue donation and the disparities in giving that these have engendered.

While strict rationalists are loathe to admit it, emotion plays a considerable role in the causes we prioritise and the way we legislate. Disgust is a key example: our aversion to pursuing urgent medical and moral agendas including tissue donation, abortion and euthanasia sees simple squeamishness at its root as visibly as economics or religious difference. 33 However, this disgust is not elicited evenly, with hierarchies emerging in all areas cited. This is especially true within tissue donation.

Research has demonstrated how superficial tissues are donated far more readily than visceral or self-identified counterparts in the brain, heart or eyes. 34 Perhaps a human trait, this acceptability gradient is paralleled in carnism where the extent of our emotional distance from an animal—or our ability to personify it—determines our likelihood of consuming it. 35 Despite the recent change from opt-in to opt-out donation models, 36 the persistence of this cognitive bias undermines the biodiversity of our tissue pipeline and the quality of our research by extension. Tackling this uphill battle takes on Sisyphean qualities as patient mistrust in donation cannot be countered by the scientific success stories that encourage a culture of universal giving.

This is a catch-22 that our regulatory environment is enshrining, not dismantling. For example, abortive tissue is still far harder for researchers to access than its less value-laden alternatives despite the pluripotency it offers and the informed consent of its donors. 37 Its prevalence means that it is indeed its perceived sanctity, and not scarcity, that is responsible for this. This is a sanctimoniousness we can ill-afford given our designs for treating, preventing and even eliminating disease. It is also one that has historically amounted to white exceptionalism in practice. Such deference has not been extended to persons of colour (where the examples of Henrietta Lacks, Tuskegee and the use of enslaved bodies as ‘anatomical materials’ are top of mind 38 ) or protected environments where our appetite for extraction goes far deeper than the topsoil we are willing to offer of ourselves. 39

Unless biomedical materials are destigmatised wholesale, public trust will continue to collapse when ‘undesirable tissues’ are discovered in the products we benefit from—just as we saw when the use of fetal cells in certain COVID-19 vaccines was disclosed. 40 This paper calls for policymakers to combat these taboos head on—consciousness raising in close collaboration with aligned community leaders and educators to divorce legitimate donation from trafficking and promote the value of such altruism for population health. Meanwhile, our regulations and codes of ethical conduct cannot be permitted to continue to prop up or pander to our most irrational instincts.

Underutilised and underserved

To conclude, the consequences of failing to act on the recommendations proposed ( table 1 ) are considerable. Until cloning, cultivation or digital twinning technologies reach maturity, the gap between the biomedical discoveries we are making and of those we are capable will only be closed by public engagement with donation drives. While their privacy and bodily autonomy are inalienable in this, patients will be underserved if legitimately acquired samples remain underutilised. Moreover, the inertia, overregulation and irrationalities that contribute to this will undermine the biomedical field’s sincerity if widely publicised and disillusion patients from participating within it going forwards.

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Summary of problem areas discussed and solutions proposed

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Not applicable.

Ethics approval

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Contributors ML was responsible for the research and write-up of the provided manuscript; she therefore acts as guarantor. SDL and RFH provided editorial oversight.

Competing interests ML has supported the Linked Data work of HDRUK. Sat within the RCGP RSC, she is also a member of the HDRUK Alliance; it is here that she became familiar with the issues summarised in this original research. Presentations given by the Brain Tumour Charity inspired this work. Meredith’s doctoral research is funded by an Oxford-MRC iCASE studentship in which her industrial partner is EMIS Health.

Provenance and peer review Not commissioned; externally peer-reviewed.

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