Executive summary. This article argues for the importance of diversity and inclusion in research amid political controversies surrounding DEI, proposing a broader, fourfold understanding of inclusion: bringing in people from different knowledge traditions, which requires expanding research frameworks, integrating multi or post disciplinary knowledge, which means moving beyond narrow single discipline boundaries, incorporating technology, which raises questions of research autonomy and integrity, and embracing multiple conceptions of the good, which challenges researchers to pursue wider notions of societal benefit through their work.

Key takeaways

• The best defence against DEI critique in research is to make and demonstrate the case that diversity and inclusion are, in fact, preconditions for good science.  
• One may, with confidence, claim that inclusive science – other than a narrow DEI focus – is marked by a variety of epistemic perspectives, involves multiple disciplines, makes responsible use of technology, and pursues expanded personal and societal purposes.

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The recent political-ideological attack by the Trump administration on policies related to diversity, equity and inclusion resulted in significant changes to research agendas and a reduction in funding allocations. Other political actors and funders may follow suit

It is no use to respond to ideology with equally loaded ideological language. As scientists, our trusted recourse is to continuously make a rational case why ‘inclusivity’ – interpreted in a wider fourfold sense below – is essential for responsible and good science.

There is, of course, a clear link between ‘inclusivity’ and ‘diversity’. The former presupposes the inclusion of a broader range of actors or perspectives, which naturally leads to a more diverse overall context. It may be instructive to learn from ecosystem research about the differences between contexts of high and low biodiversity and the clear benefits associated with the former:

“We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16-32 species was more resistant, changing by only approximately 25%.²”

Let us extract a few points:

A high-diversity ecosystem is a multi-species environment characterised by complex and multiple forms of interaction among its various members. By contrast, a low-diversity environment is typically dominated by a single or very limited number of species and exhibits a much simpler, more linear mode of interaction.

High-diversity ecosystems have been shown to be resilient in the face of adversity, such as climate change, while low-diversity ecosystems tend to be fragile and less responsive under similar pressures. Moreover, high-diversity systems demonstrate a greater productive and reproductive capacity, allowing them to regenerate more rapidly and in more varied ways. Low-diversity ecosystems, on the other hand, tend to exhibit limited productivity and reproductive potential, which restricts their ability to recover.

From an aesthetic perspective, high-diversity ecosystems reveal beauty in their heterogeneity, while low-diversity ecosystems are, naturally, far less appealing. One might think here of the contrast between a monotonous sandy plain and a rich forest teeming with multiple species coexisting within the same environment.

In summary: Ecosystems with high diversity (‘inclusion’) have significant advantages over low diversity environments. Although one should be careful to directly transfer insights from one context to the other, this biodiversity research might provide some clues about the advantages of ‘inclusion’ in human research efforts.

In this short reflection, I wish to explain inclusivity and its importance for good science by referring to four interrelated aspects of inclusivity:

1. The inclusion of peoples from different knowledge traditions. This is the challenge of knowledge framework expansion.
2. The inclusion of multi- or post-disciplinary knowledge. This is the challenge of transcending the narrow boundaries of single-discipline research.
3. The inclusion of technology. This is the challenge of research autonomy and integrity.
4. The inclusion of multiple forms of the good in our research efforts. This is the challenge of realising expanded notions of societal benefits via research.

The Inclusion of Peoples and Different Knowledge Traditions

The inclusion of different knowledge traditions is crucial for good science. Knowledge in its current dominant form is a product of modernism and has developed largely through Western Enlightenment trajectories. This means that our default perspective, when thinking about science, is anchored in the specific scientific traditions that emerged in the West, which have now become the global standard.

The result – often couched in decolonisation terms – is that when we conduct research or analyse society, our default frameworks reflect the societies that occupy the centres of power, while marginalising those at the periphery. One only needs to consider where major journals are published, who writes influential books, and where most conferences are held. In this way, the asymmetry of power in a highly successful and valuable modern Western tradition becomes the reference point, often excluding other ‘local’ forms of knowledge associated with subjects like history, medicine, management and leadership – think of Africa’s ubuntu, China’s Doaism and Japan’s kaizen.

A key part of inclusivity involves challenging this dominance of Western epistemologies and amplifying voices from the so-called margins. This has significant implications for research itself. It shapes the questions we ask, which subjects are selected, and which problems are addressed. Simply living within a particular context can lead us to overlook important and interesting questions, not because they lack value, but because they are absent from our frame of reference.

At its core, the epistemic question is profound: What does knowledge actually mean? Who decides when knowledge is credible? And how can so-called ‘indigenous’ knowledge systems enrich the current valuable and successful Western scientific tradition?

The Inclusion of Multi- or Post-Disciplinary Knowledge

Most of us in universities have been educated within the tradition of a specific discipline, such as economics, mathematics, psychology, or philosophy. It is, however, an interesting feature of management education that many of the subjects in our curricula imply a multi- and even post-disciplinary knowledge approach. Consider, for instance, subjects like strategy, marketing, and corporate finance.

Thomas Kuhn’s famous paradigm theory teaches us that normal science is constituted by a community of scholars who share the same assumptions and traditions, constructing reality or a knowledge domain based on these shared premises. It is therefore extremely difficult to move beyond the confines of a single discipline. This difficulty is also evident in the organisation of universities, where departments are generally structured around disciplines, making collaboration across disciplinary boundaries challenging.

The distinction between so-called Mode 1 and Mode 2 knowledge is helpful here. Mode 1 knowledge is typified by a single-discipline approach, with a fairly strict separation between research and application. Mode 2 knowledge, by contrast, is constituted by multiple disciplines and transcends the dualism between theory and practice. It evaluates knowledge not only conceptually but also pragmatically, in terms of its real-world applications.

Most of the pressing economic, social, and political questions of our time—the so-called wicked problems—cannot be addressed by a single-discipline approach. In this context, the principle of inclusivity increases the likelihood that scientists can both analyse problems more comprehensively and propose multiple, actionable solutions with greater tangible societal impact.

The Inclusion of Technology

In a digital society, there is no way that researchers can escape the impact of technology whilst at the same time trying to optimise the huge potential of different technologies. Technology increases the efficiency of research, facilitates data collection, extracts results and enhances the quality and quantity of scholarly outputs. Yet, in a highly volatile technological environment, it is essential to retain a critical and reflective mindset.

As Martin Heidegger observed, the purpose of technology is not itself a technological question. Its use is determined by us—the human users—and requires reflection rather than purely technical reasoning. A key aspect of responsible engagement with technology is maintaining at least relative autonomy in decision-making regarding its application.

The advent of large language models has particularly complicated traditional ethical concerns, including authenticity of authorship, biased algorithmic data interpretation, privacy, and informed consent. Legal disputes have arisen over the use of authors’ journalistic or literary works in the training of large language models, often without consent or remuneration. In education, technology complicates assessment: How can we distinguish between genuine student reflection and a simple copy-paste exercise from online resources? Universities remain divided on these issues, highlighting the ethical complexity of technological engagement.

Moreover, technology is fundamentally reshaping the nature of work, including academic labour, with robotics, machine learning and automation altering the roles of research assistants and professors alike. Ethical considerations also extend to potential abuse of technology, such as infringements on civil liberties, creating more and more ‘big brother’ realities. It also raises the difficult question about human augmentation, which could lead to a form of ‘speciation’ between biologically unenhanced humans and those augmented through implants or devices.

As researchers see the potential of technology, the temptation is to fall into a solely pragmatic approach (‘what works is good’). Responsible scientists will retain a sense of distance and a critical, ethical mindset.

The Inclusion of Multiple Forms of the Good

The final aspect of inclusivity involves recognising multiple forms of the good and expanding our understanding of why we conduct research. Narrowly, academics may conduct research for career advancement, personal benefit, or funded projects, which enhance their professional standing and, in some cases, provide additional remuneration. While private benefit is legitimate, it is insufficient for what we might call responsible and good research.

Elinor Ostrom argued that knowledge should also serve the common good. When research addresses pressing societal or global challenges—economic inequality, peace and conflict, climate change—it produces results that go beyond individual advancement, contributing instead to a shared knowledge base from which better policies and actions can emerge.

Ernst Bloch spoke of the principle of hope guiding human action, a concept reinterpreted by Viktor Frankl in his Logotherapy, emphasising that life without purpose is devoid of meaning. This ‘transcendent good’ may sound theoretical, but responsible research as meaning-making activity can indeed generate hope: Hope that problems can be addressed – sometimes partially, sometimes fully – and that scientific breakthroughs—sometimes revolutionary, in Kuhn’s terms—can inspire progress.

In summary, I conduct research not only for personal benefit, but also to serve the common good and to embody hope. These three dimensions—private, communal, and transcendent—together define the ethical and practical significance of inclusive, responsible science.

Conclusion

Let us return to the advantages of a multi-species environment:

One may with confidence claim that inclusive science – other than a narrow DEI focus – is marked by a variety of epistemic perspectives, involves multiple disciplines, makes responsible use of technology and pursues expanded purposes. This type of science equals the benefits and efficacy of a high-diversity ecosystem: It harnesses resilience.  It demonstrates regenerative capacity in adverse (political, financial) situations exactly because of the multiplicity of actors/perspectives that spin a web of safety and reduce external risk.

Best of all, inclusive science is beautiful.

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Footnotes

1 This contribution has its origin in a June 2023 conference in France of The Responsible Research in Business and Management forum. The RRMB is guided by seven principles which at that point were interpreted from the perspective of ‘inclusivity’ as a core value. https://www.rrbm.network/executive-briefing/eb-principles/

2 Isbell, F., Craven, D., Connolly, J. et al. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature 526, 574–577 (14 Oct 2015). https://www.nature.com/articles/nature15374