David Resnik

In Chaps. 5, 6, 7, 8, 9, and 10 I examined various ethical and policy issues pertaining to research with human subjects through the lens of five principles—respect for autonomy and dignity, non-maleficence, beneficence, justice, and trust. Along the way, I also discussed how federal regulations, agency guidance, and professional codes apply to those issues and mentioned recent changes to the Common Rule. In this chapter I will turn my focus to critiques of the current oversight system and recent changes to the regulations. At the end of Chap. 2, I raised the issue protectionism and suggested the determining the right level of protection for human subjects requires one to balance conflicting values, i.e. protection of human welfare and rights vs. the advancement of scientific knowledge. In this chapter, I will consider how regulatory reform efforts achieve this balance.

Research with human subjects exemplifies the perennial conflict between the good of the individual and the good of society. Policies and procedures that protect the rights and welfare of human subjects may hinder scientific research that benefits society. Due to this conflict, research with human subjects continues to be one of the most controversial topics in bioethics, despite ample government regulation, institutional oversight, and professional guidance. Nearly every week, the media brings a new issue, problem, or scandal to the public spotlight, with predictable responses from concerned citizens, compliance officials, and investigators. Concerned citizens and compliance officials often react to new developments by calling for additional regulation and oversight, while investigators frequently object that they are already inundated with red tape and that new rules will impede important scientific research without yielding significant benefits for human subjects or society (Klitzman 2015). The following examples illustrate some of the ethical dilemmas that arise in research involving human subjects.

In previous chapters, we have touched on some ethical issues pertaining to research involving vulnerable subjects, such as risks to children and pregnant women/fetuses. In this chapter, we will focus on dilemmas faced by investigators, institutions, IRBs, and sponsors related to research involving vulnerable subjects. In Chap. 2, we noted that the federal regulations include a general requirement for protecting vulnerable subjects (45 CFR 46.111a3, 45 CFR 46.111b) as well as specific requirements pertaining to pregnant women, fetuses and neonates (Subpart B), prisoners (Subpart C), and children (Subpart D). The Helsinki Declaration also provides guidance on research involving vulnerable subjects: All vulnerable groups and individuals should receive specifically considered protection. Medical research with a vulnerable group is only justified if the research is responsive to the health needs or priorities of this group and the research cannot be carried out in a non-vulnerable group. In addition, this group should stand to benefit from the knowledge, practices or interventions that result from the research (World Medical Association 2013). Likewise, CIOMS guidelines requires additional protections for vulnerable subjects: When vulnerable individuals or groups are considered for recruitment in research, researchers and research ethics committees must ensure that specific protections are in place to safeguard the rights and welfare of these individuals and groups in the conduct of research (Council for the International Organizations of Medicals Sciences 2016:70). The 2002 and 2016 versions also includes sections which address research involving children, pregnant women, and adults with mental disabilities or diseases that affect decision-making (Council for the International Organizations of Medicals Sciences 2002, 2016). Research regulations an ethical guidance include the following types of additional protections for vulnerable subjects: Justification for including vulnerable subjects in research. The CIOMS guidelines recommend that a justification be provided for including vulnerable subjects. For example, children should not be included in a study if the research objectives can be accomplished by enrolling only adults (Council for the International Organizations of Medicals Sciences 2002, 2016). The federal research regulations require that the selection of research subjects be equitable (45 CFR 46.111a3), which implies that vulnerable subjects should not be unfairly included in research (Mastroianni and Kahn 2001). Limits on research risks. Federal regulations place limits on the risks that fetuses, neonates, children, pregnant women, and prisoners can be exposed to in research that does not offer them direct benefits (45 CFR 46, Subparts B, C, D). Rules for IRB Composition. Federal regulations require that an IRB which reviews research on prisoners include a prisoner or prisoner representative (45 CFR 46.304). Commentators have argued that IRBs which review research on mentally disabled people, children, and other vulnerable subjects also should include members with the appropriate background and experience concerning the study population or that they should consult with outside experts (National Bioethics Advisory Commission 1998; Institute of Medicine 2004). Safeguards for Consent. Federal regulations specify procedures for obtaining consent from the parent(s) and assent from the child in pediatric research (45 CFR 46 Subpart D). The National Bioethics Advisory Commission (1998) recommends that investigators follow procedures for assessing decision-making capacity in mentally disabled or ill adults and identifying surrogate decision-makers for subjects who are incapable providing consent. In some cases, an IRB might require independent monitoring of the consent process to protect vulnerable subjects. Safeguards for privacy /confidentiality. Additional protections for privacy and confidentiality might be appropriate for research involving students or employees to prevent their professors or employers from having access to private information that could be used against them (Bonham and Moreno 2008; Resnik 2016b). Benefit sharing. Some ethical guidelines include procedures for sharing benefits with research subjects or host communities/nations to minimize the potential for exploitation (see discussion in Chap. 8 ).

In Chaps. 5, 6, 7, 8, and 9 I have focused on specific issues related to research with human subjects, such as informed consent, confidentiality, risks, benefits, and vulnerability. In this chapter, I will shift gears and examine a topic that indirectly impacts human subjects but which is nevertheless very important: research integrity. Research integrity (or responsible conduct of research, RCR) has to do with following ethical and legal standards in the conduct of research (Shamoo and Resnik 2015). These include rules pertaining to research with human and animals subjects as well as those concerning the conduct of science itself, such as norms for recording, reporting, analyzing, sharing, publishing and interpreting data; assigning authorship; disclosing and handling conflicts of interest; working with collaborators, students, and trainees; reviewing manuscripts and grants; managing financial and other resources; and investigating allegations of misconduct (Shamoo and Resnik 2015). This chapter will consider some RCR issues which have an important bearing on research with human subjects. But first, I will explain why investigator integrity is essential to research with human subjects.

To understand the ethics of research with human subjects it is important to have some familiarity with important events and trends that have entered the public’s consciousness. (See Table 2.1 for a summary of important events.) Examining this historical background will help to frame the issues and provide us with the social, political, economic, and legal context for the current oversight system. The main thesis of this chapter is that the current system has emerged in response to unethical—and in some cases horrific—treatment of human research subjects. According to Alexander Morgan Capron (1989, p. 127), “the darkest moments in the medical annals have involved abuses of human research subjects.” Existing guidelines, regulations, principles, and policies are understandably protectionistic because they seek to prevent the kinds of abuses that have generated moral outrage and undermined the public’s trust in the research enterprise.

The COVID-19 pandemic has highlighted the importance of biosafety in the biomedical sciences. While it is often assumed that biosafety is a purely technical matter that has little to do with philosophy or the humanities, biosafety raises important ethical issues that have not been adequately examined in the scientific or bioethics literature. This article reviews some pivotal events in the history of biosafety and biosecurity and explores three different biosafety topics that generate significant ethical concerns, i.e., risk assessment, risk management, and risk distribution. The article also discusses the role of democratic governance in the oversight of biosafety and offers some suggestions for incorporating bioethics into biosafety practice, education, and policy.

Journals and publishers are increasingly using artificial intelligence (AI) to screen submissions for potential misconduct, including plagiarism and data or image manipulation. While using AI can enhance the integrity of published manuscripts, it can also increase the risk of false/unsubstantiated allegations. Ambiguities related to journals’ and publishers’ responsibilities concerning fairness and transparency also raise ethical concerns. In this Topic Piece, we offer the following guidance: (1) All cases of suspected misconduct identified by AI tools should be carefully reviewed by humans to verify accuracy and ensure accountability; (2) Journals/publishers that use AI tools to detect misconduct should use only well-tested and reliable tools, remain vigilant concerning forms of misconduct that cannot be detected by these tools, and stay abreast of advancements in technology; (3) Journals/publishers should inform authors about irregularities identified by AI tools and give them a chance to respond before forwarding allegations to their institutions in accordance with Committee on Publication Ethics guidelines; (4) Journals/publishers that use AI tools to detect misconduct should screen all relevant submissions and not just random/purposefully selected submissions; and (5) Journals should inform authors about their definition of misconduct, their use of AI tools to detect misconduct, and their policies and procedures for responding to suspected cases of misconduct.

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work.

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work.

Green bioethics is an area of research and scholarship that examines the impact of healthcare practices and policies on the environment and emphasises environmental values, such as ecological sustainability and stewardship. Some green bioethicists have argued that healthcare providers should inform patients about the environmental impacts of treatments and advocate for options that minimise adverse impacts. While disclosure of information pertaining to the environmental impacts of treatments could facilitate autonomous decision-making and strengthen the patient–provider relationship in situations where patients have clearly expressed environmental concerns, it may have the opposite effect in other situations if makes patients feel like they are being judged or manipulated. We argue, therefore, that there is not a generalisable duty to disclose environmental impact information to all patients during the consent process. Providers who practice green bioethics should focus on advocating for system-level changes in healthcare financing, organisation and delivery and use discretion when bringing up environmental concerns in their encounters with patients.

To promote ethical conduct in science, government funding agencies, academic institutions, and professional journals have defined some types of seriously unethical behaviors as research misconduct and have developed policies and procedures for reporting, investigating, and adjudicating allegations of misconduct. Behaviors that are not as egregious as misconduct but are still regarded as unethical are called questionable research practices. Although there is considerable variation in research misconduct definitions used by different organizations and nations, most of them classify data fabrication or falsification or plagiarism as misconduct. This chapter will distinguish between research misconduct, questionable research practices, and fraud; describe policies and procedures related to misconduct; review some famous cases of misconduct; examine the prevalence and causes of misconduct; and discuss ways of preventing misconduct.

In this article, we discuss ethical issues related to using and disclosing artificial intelligence (AI) tools, such as ChatGPT and other systems based on large language models (LLMs), to write or edit scholarly manuscripts. Some journals, such as Science, have banned the use of LLMs because of the ethical problems they raise concerning responsible authorship. We argue that this is not a reasonable response to the moral conundrums created by the use of LLMs because bans are unenforceable and would encourage undisclosed use of LLMs. Furthermore, LLMs can be useful in writing, reviewing and editing text, and promote equity in science. Others have argued that LLMs should be mentioned in the acknowledgments since they do not meet all the authorship criteria. We argue that naming LLMs as authors or mentioning them in the acknowledgments are both inappropriate forms of recognition because LLMs do not have free will and therefore cannot be held morally or legally responsible for what they do. Tools in general, and software in particular, are usually cited in-text, followed by being mentioned in the references. We provide suggestions to improve APA Style for referencing ChatGPT to specifically indicate the contributor who used LLMs (because interactions are stored on personal user accounts), the used version and model (because the same version could use different language models and generate dissimilar responses, e.g., ChatGPT May 12 Version GPT3.5 or GPT4), and the time of usage (because LLMs evolve fast and generate dissimilar responses over time). We recommend that researchers who use LLMs: (1) disclose their use in the introduction or methods section to transparently describe details such as used prompts and note which parts of the text are affected, (2) use in-text citations and references (to recognize their used applications and improve findability and indexing), and (3) record and submit their relevant interactions with LLMs as supplementary material or appendices.

According to some estimates, less than 10% of the world's biomedical research funds are dedicated to addressing problems that are responsible for 90% of the world's burden of disease. This paper explains why this disparity exists and what should be done about it. It argues that the disparity exists because: 1) multinational pharmaceutical and biotechnology companies do not regard research and development investments on the health problems of developing nations to be economically lucrative; and 2) governmental agencies that sponsor biomedical research face little political pressure to allocate funds for the problems of developing nations. This paper argues that developed nations have an obligation to address disparities related to biomedical research funding. To facilitate this effort, developed countries should establish a trust fund dedicated to research on the health problems of developing nations similar to the Global AIDS Fund

This essay analyzes the concept of public trust in science and offers some guidance for ethicists, scientists, and policymakers who use this idea defend ethical rules or policies pertaining to the conduct of research. While the notion that public trusts science makes sense in the abstract, it may not be sufficiently focused to support the various rules and policies that authors have tried to derive from it, because the public is not a uniform body with a common set of interests. Well-focused arguments that use public trust to support rules or policies for the conduct of research should specify (a) which public is being referred to (e.g. the general public or a specific public, such as a particular community or group); (b) what this public expects from scientists; (c) how the rule or policy will ensure that these expectations are met; and (d) why is it important to meet these expectations

Sometimes researchers explicitly or implicitly conceive of authorship in terms of moral or ethical rights to authorship when they are dealing with authorship issues. Because treating authorship as a right can encourage unethical behaviours, such as honorary and ghost authorship, buying and selling authorship, and unfair treatment of researchers, we recommend that researchers not conceive of authorship in this way but view it as a description about contributions to research. However, we acknowledge that the arguments we have given for this position are largely speculative and that more empirical research is needed to better ascertain the benefits and risks of treating authorship on scientific publications as a right.

Various U.S. laws, such as the Clean Air Act and the Food Quality Protection Act, require additional protections for susceptible subpopulations who face greater environmental health risks. The main ethical rationale for providing these protections is to ensure that environmental health risks are distributed fairly. In this article, we (1) consider how several influential theories of justice deal with issues related to the distribution of environmental health risks; (2) show that these theories often fail to provide specific guidance concerning policy choices; and (3) argue that an approach to public decision making known as accountability for reasonableness can complement theories of justice in establishing acceptable environmental health risks for the general population and susceptible subpopulations. Since accountability for reasonableness focuses on the fairness of the decision-making process, not the outcome, it does not guarantee that susceptible subpopulations will receive a maximum level of protection, regardless of costs or other morally relevant considerations.