Clarifying Ethical Research
What makes research ethical? There are many ways we can approach this question. One way is from the tradition of philosophy of science. Here, we can ask about the many “value judgements” made throughout a research project; for example, how one decides what to study, or how it is reasoned that some data collection method is better than another. Values might here be categorised as epistemic and non-epistemic or contextual. “Objectivity”, “truth” and “neutrality” would be deemed epistemic values — clearly valuable to science. In the meantime, other values that do not initially strike us as playing a role in science would be contextual values. The question is then what types of values appear throughout academic research, what role they play in science at large, and which ones are indeed ethical.
Another approach might be to discuss the concept of ethics through the lens of moral philosophy, which studies the morality of actions and has a long and complex history. We can here ask what ethical means, how it relates with good and evil, and how these concepts translate to the practice of research. We could take this discussion to a more concrete level and discuss what different ethical theories would mean to specific research questions.
The approach I wish to follow is intended to be quite practical. That said, “values” in the sense mentioned above, and the focus on the morality of actions are inevitable in these discussions. My aim is to work with two terms commonly employed in discussions about ethical research: responsible research and innovation (RRI), and research integrity. I will introduce these in turn and then argue that they generally raise different types of ethical questions in science that are equally important. I will then turn to a discussion about whether this distinction holds in relevant ways. In conclusion, I take my claim to be weak enough to not be too controversial: that the distinction between RRI and research integrity is of use insofar that it encourages reflection on a broad set of considerations covered by research ethics.
Responsible Research and Innovation
RRI is a term which has been around for several decades but which gained traction in 2011, when becoming an important term in the context of European policy (Owen & Macnaghten, 2012). Turning to the EU’s “Horizon 2020” strategy, we can find one definition of RRI:
“[RRI is] an approach that anticipates and assesses potential implications and societal expectations with regard to research and innovation, with the aim to foster the design of inclusive and sustainable research and innovation” (European Commission).
There are numerous aspects of this definition worthy of inspection, but I focus on only two for the purpose of this piece. Firstly, RRI refers to “potential implications and societal expectations.” Secondly, it is about “the design of inclusive and sustainable research”. These are two traditionally important aspects of the ethics of science: how research is set up or designed, and what societal consequences this set up has.
But what might it look like to conduct research in line with this definition of RRI? I take it to mean research conducted with its societal implications, as well as its sustainability and the value of inclusiveness, in mind from the start. The ongoing Autistica Project (Whitaker et al., 2020), I believe, offers a useful case study.
The goal of the Autistica Project is to create a citizen science platform where people who live with autism can share information on how they navigate the world. The societal consequences are therefore outlined from the outset: it is about supporting a proportion of the population. Sustainability is also built into the goal by the creation of a platform that can continue to engage with a community of people who can have their voices amplified. This highlights the “inclusiveness” of this work insofar that the research subjects — people with autism — are actively brought into the conversation with the researchers. This is further shown in the “participatory” approach to building the platform, whereby “members of the affected community […] are active contributors on a number of levels, for instance by setting direction, having influence over critical decisions, or designing the procedures and modes of the study itself” (ibid.). These ideals are made tangible thanks to the project’s transparency, as we can see how people with autism play an important role in the design and development of this project (see comments from focus groups here, for example).
Research Integrity
However, I do not believe that RRI — understood in the above way — is sufficient to describe research conducted in an ethical way. I therefore introduce research integrity as a supplement.
Defined by the Office for Research Integrity in the US:
“[Research integrity refers to] active adherence to the ethical principles and professional standards essential for the responsible practice of research” (Teaching the Responsible Conduct of Research in Humans).
What is specific to this definition is the reference of “professional standards” and “responsible practice”. Unlike in RRI, the question is no longer on the ethics of scientific output and its consequences, but on the ethics of how scientists conduct themselves in practice. My contention is that this captures the ethics of the work done “behind the scenes”, outside the view of the general public. This “hidden” nature of scientific practice is not what is up for questioning — most professions operate in a way that the general public needn’t fully understand. What is up for debate is the ethics of the internal operations of scientific production. I do not take this aspect of research ethics to be clearly described under the umbrella of RRI.
Comparing RRI to Research Integrity
To explore the distinction between RRI and research integrity, I will briefly outline three ways both terms differ.
Firstly, we can see that who perceives the ethical questions differs in either case. To start with, RRI can be understood as outward-looking, or visible to the public. For example, we might ask for the effects brought about by facial recognition software being used in cameras across London (The Verge, 2020), or what it means for the meaning of death for scientists to keep pigs’ brains alive hours after their decapitation (Reardon, 2019). In the meantime, research integrity refers to how research findings are produced — it is inward-looking. A common term to describe a lack of research integrity is “research misconduct”, for which there are many examples (one fun — although deplorable — one is the case of Wansinck’s food science, which relied on false data; see Retraction Watch, 2019).
Secondly, each term refers to different relationships held by researchers. On the one hand, RRI questions how scientists engage with research subjects. Consider again the case of the Autistica Project, or how volunteers are treated during clinical trials. The point is to work with data subjects in a respectful and inclusive way. One famous case in which there was no respect for data subjects was the Tuskagee experiments, wherein African-American men were recruited to study the development of untreated syphilis, but the volunteers were falsely told they were receiving free treatment — the monitoring and lies persisted for forty years (CDC, 2020). On the other hand, we can question how scientists engage with fellow researchers. We can here discuss the importance of codes of conduct in open source collaborations (see The Turing Way’s as an example), or — returning to “research misconduct” — how one might engage in authorship fraud. Once again, there are many examples of this sort of practice. From lying about who contributed to a paper because the system almost encourages this (see Harvey, 2018) to inventing entirely fictional authors (see this piece by Marcus & Oransky, 2016), these are questions that are not within the public’s purview.
Thirdly, RRI and research integrity question the ethics of how scientific solutions are framed and shaped by society (RRI) or by institutional practices (research integrity). With our RRI hat on, we can ask how we communicate the validity of scientific outputs. Whilst how scientific findings are communicated is not a new question, it is worth highlighting how artificial intelligence (AI) and machine learning might be framed as the holy grail of scientific knowledge and the answer to all fields of inquiry. Along these lines, we can ask about the role of “AI” as a marketing tool, as a way to grant research findings undeserved credibility (Lanier and Weyl, 2020). One specific example of this is described by Nagendran et al., (2020), who raise concerns over exaggerated claims of AI outperforming doctors. Switching to our research integrity goggles, we can question how academic infrastructures shape scientific work. Consider, for example, how researchers must weigh the noble pursuit of truth, with the need to earn credit (on this weighing of options, see, for example, Zollman, 2018). We can also consider the impact of funding on scientific endeavours. Questions can be raised regarding the size of research grants (Bloch & Sorensen, 2014) and even the values that motivate the funding of some research projects and not others. Institutional norms then might encourage a “publication bias” whereby positively framed findings will be more publishable (see Kaiser et al.’s, 2009, finding that studies showing differences in sex/gender are easier to publish than studies not supporting such differences).
Before moving onto the discussion about this distinction, I wish to briefly mention one way the two concepts overlap. The values of grant-givers intuitively relates with the question of RRI regarding how an individual scientist chooses which field of inquiry to specialise in and what projects to undertake — there are plenty of stakeholders of scientific work and they all hold non-epistemic values. I will expand on this below, but note that I spoke of an RRI hat and research integrity goggles — the point of this was that the two can (and should!) be worn at the same time.
Fuzzy distinctions
The argument so far has been that there is a conceptual distinction that can be made within “research ethics” whereby we can identify both RRI and research integrity. However, why should we draw the line of division in this way at all? W for example, couldn’t we speak of the different stakeholders and their unique interests in scientific work, from funders and universities, to industry and the general population? Furthermore, is there even a need for such a conceptual distinction? After all, do RRI and research integrity not overlap in important ways? Do both concepts not refer to the need for increased reflexivity from researchers? I do not consider these questions to be trivial, and they do constitute valid paths of inquiry in their own right. My response is, simply, that the very specific distinction I propose enables us to ask rather different questions in research ethics. This distinction allows us to cover a greater range of ethical dimensions when considering the ethics of research. In what regards the shared requirement of increased reflexivity, I would even venture to say that its directedness is different in either case. By this I mean that, whilst RRI asks us to reflect on our values as scientists qua participants of a social world, research integrity requires we reflect on the values we hold as scientists quaparticipants of specific institutional norms.
A related question regards the motivation of this distinction: is it for purely theoretical purposes or is it to provoke some change in practice? Similarly to the above response, I take the distinction to be useful to focus what can be two discussions — in the way outlined throughout this text — that do, nevertheless, interrelate. Indeed, the distinction is not perfect, but it is useful. It is not clear, for example, how one could conduct research without integrity — seeking unearned credit and prioritising the production of papers — whilst conducting research that places sufficient emphasis on its societal consequences. This very example highlights the fuzziness of the distinction, as it seems that one sometimes weighs against the search of credit not that of truth, but the importance of the societal implications of one’s work. Given my distinction of societal considerations sitting under RRI and the truth-credit tradeoff under research integrity, the interrelatedness of these weaken the status of the conceptual distinction. Furthermore, is it not intuitive that some values we hold can shape both how we relate with our peers and how we frame solutions for society? If I hold certain views about socioeconomic classes below my own (imagine I were classist), might this not shape both how I work with peers from poorer backgrounds and not ivory-league universities, as well as how I proceed in my research about, say, wealth distribution? Once again, I do not take the clarity of the distinction to be my focus, but it’s usefulness. In the case where I am classist, both forms of research ethics highlight downfalls I might not otherwise consider.
Finally, why these terms? Why “RRI” and “research integrity”? To be perfectly honest, I am not wedded to these terms and am open to terms that better track the concepts I am referring to. I believe “research integrity” to be commonly used in the literature in a sense similar to what is here discussed. RRI, though, might refer to much broader phenomena we have not discussed. For example, the I for innovation means the term does not refer only to research. I take there to be a much more complex question underlying the use of this word: which are the boundaries of research? The implementation of research findings into technological innovations make any thoughtful response quite convoluted. Furthermore, innovation these days might be brought about through the analysis of vast amounts of data, which takes us into the realm of data ethics. And questions about technology and data might take us to those of research within industry, whilst we have focused on research integrity within academia… In other words, there is a lot that has been set aside in this short article. This has not been to disregard their importance. These are all complicating factors that are very relevant questions to ethical research. And you might guess my response: I return to the instrumental status of the claim that there is a useful distinction between RRI and research integrity, a claim I take to be quite uncontroversial and narrow in practice.
Concluding
There are many paths to take when asking for a definition of ethical research. The one I have gone down is quite simplistic: ethical research is a compendium of questions captured by RRI and research integrity. We have seen very briefly how these terms are different, and we have then turned to a broader discussion of how such a distinction can be put into question. I have defended the distinction on the basis that it simply helps focus discussions about research ethics. But many other questions and concepts interrelate, such as that of research outside of academia, data ethics and technology more broadly. I only suggest that this distinction serve to highlight ethical questions in research that may otherwise go undetected, as it encourages us to think about societal consequences, inclusive science and professional integrity.
