Democratised Ethnography for Collective Intelligence in Design Practices

Naoya Tojo; Tomoko Oto

doi:10.1111/epic.70019

Introduction

Ethnography is founded in anthropology and sociology, but its applications have expanded into diverse applied domains. In the rapidly evolving fields of design and innovation, ethnography is now widely applied (Gregory 2018; Sperschneider and Bagger 2003). No longer a specialised methodology used only by educated and trained researchers, it has become an accessible tool for a broader audience (Badami and Goodman 2021; Moss 2024; Levin 2024). This shift reflects broader trends in open innovation (Chesbrough 2003) and participatory design (Blomberg and Karasti 2012), where collective intelligence and diverse perspectives contribute to understanding societal changes and user needs. However, increased accessibility doesn’t guarantee effective practice. As its adoption grows, new challenges emerge. Unlike structured methodologies, ethnographic inquiry is inherently situated, non-linear and deeply reliant on tacit knowledge, making it difficult to adopt without adequate preparation. Without proper training and theoretical grounding, ethnography risks misapplication, superficial insights and reduced rigour (Forsythe 1999).

The current landscape for ethnography is complex. As it is applied to various fields and contexts, often deviating from traditional academic methodologies, misunderstanding and concerns have arisen. One persistent challenge is the perception that ethnography can be performed by anyone, is unsystematic, an ‘anything goes’ approach, and merely involves observing behaviour and culture to detect patterns (Forsythe 1999). This often stems from a philosophical divergence between the interpretivist and relativist foundations of ethnography and the positivist thinking prevalent in fields like natural sciences and engineering. Additionally, ethnography is sometimes criticised for issues like observer effects, subjectivity and lack of generalisability. While traditional ethnography addresses these through prolonged field presence, deep community immersion, multi-method data collection and robust theoretical grounding, industrial ethnography, with its inherent constraints on time and budget, necessitates a careful balance between practicality and methodological rigour (Oto 2020). To enable non-experts to apply ethnographic approach in an industry context, democratised ethnography must address the trade-offs between industrial constraints and the proper selection of methods, along with validation by theory and intellectual tradition (Atkinson and Pugsley 2005).

The history of design thinking offers a potential analogue to draw insights from to address these concerns. Design thinking was embraced as a means to democratise design expertise and gained traction with the expectation that anyone could become a designer and drive innovation, responding to increasingly complex and wicked problems (Rittel and Webber 1972; Johansson-Sköldberg, Woodilla, and Çetinkaya 2013). However, its rapid adoption often overlooked its epistemological foundations. This widened the research-practice gap, a longstanding concern in design research (Zimmerman, Forlizzi, and Evenson 2007; Norman 2010). This led to criticisms that design thinking had been reduced to a superficial toolkit rather than a transformative methodology. While design thinking continues to be referenced in industry, several scholars and critics argue that its promise of transformation has not been realised, and in this sense, it is viewed as a failure (Ketterman 2019; Ackermann 2023; Elmansy 2023). Such critiques highlight how design thinking was frequently applied as a set of workshops and canvases rather than as a sustained epistemological shift, often resulting in incremental product improvements rather than the systemic innovation it promised. By analogy, the discussion on democratised ethnography requires academic engagement because opening ethnography to wider audiences involves both opportunities and challenges. Explicitly articulating the practical skills and competencies of expert ethnographers provides pedagogical support for newcomers, while bridging theory and practice helps establish shared standards rigour. Incorporating simplified forms of ethnographic methods into academic and professional discussions is not intended to dilute the discipline, but to make its principles accessible to interdisciplinary teams and organisational contexts. Reflecting on the shortcomings of design thinking, democratised ethnography must be more substantial and meaningfully linked to academic discourse to ensure its robustness and impact. This requires not only clearly articulating expert knowledge but also engaging in academic dialogue about its conceptualisation and connection to the education of ethnographic practitioners.

This paper presents a case study of what we term ‘pseudo-democratised ethnography’ within a global technology company’s design research team. We use the term ‘pseudo-’ to describe a collaborative approach where a team of non-specialists worked with a formally trained ethnographer. This case study explores how this form of interdisciplinary collaboration facilitates learning and knowledge transfer. The authors have engaged in co-reflection on their experiences in the design team, where non-expert team members engaged in various ethnographic processes, including decision-making, negotiation, research planning, field participation, data collection and analysis. The first author spent seven years in the team, initially as an ethnographic novice but later leading projects. The second author, a cultural anthropologist with formal training in ethnography, was a former team member and collaborated closely with the first author. The team’s fluid and interdisciplinary structure allowed newcomers with no prior ethnographic experience to gradually develop expertise through legitimate peripheral participation (LPP) (Lave and Wenger 1991), eventually taking leadership roles in ethnographic projects. Although the team occasionally included members with advanced education in ethnography, this was rare.

This case study highlights key challenges and opportunities associated with democratised ethnography. We examine the implications of power dynamics in participatory practice, unpacking strategies to promote genuine collaboration. Our experience at the team revealed three pillars crucial for truly democratised practice: collaborative practice, collective intelligence and strategic use of methods and tools. We also explore potential pitfalls in democratised ethnography.

Furthermore, we discuss the impact of technology, particularly artificial intelligence (AI), on democratised ethnography. The anthropological field is experiencing a ‘digital turn’ (Artz 2023), with AI holding potential to introduce new possibilities for ethnography’s democratisation through tools like automatic transcription and summarisation. However, we critically examine how these tools influence the fundamental ‘question’ of ethnography. More important than the tools themselves is the nature of the questions they generate or suppress. Can AI provide more than procedural support for non-experts, genuinely assisting with the critical and reflective inquiry into ‘what is ethnography?’ and the often-unpredictable and messy work that accompanies it? Without critical reflection, the use of technological interventions can lead to superficial data collection and decontextualised analysis, reinforcing the very methodological gaps that democratised ethnography seeks to overcome.

By framing democratised ethnography within the broader discourse on collective intelligence, this paper argues that it represents a paradigm shift in how team-based intelligence is harnessed for design and innovation. Democratisation of ethnography doesn’t simply mean making research methods more accessible, it requires the development of frameworks that support learning, ensure methodological rigour and foster reflective practice. Decentralising the traditional person-dependent practices of ethnography enhances interpretative capabilities and unlocks the potential of collective intelligence in user-centred innovation. In essence, our proposal isn’t simply to provide methods or frameworks, but to foster a shared inquiry. This paper contributes to ongoing discussions on the role of democratised ethnography in contemporary practice, advocating for a balanced approach that bridges accessibility with epistemological integrity.

Background

Tradition and Expanding Applications of Ethnography

In traditional ethnography as represented by the ‘Malinowski’s style’, a single researcher participates in each field, conducts research and performs microscopic and holistic description and analysis based on individual expertise. In recent years, applied styles such as collaborative ethnography (May and Pattillo-McCoy 2000) and digital ethnography (Masten and Plowman 2003) have emerged in anthropology and sociology. Tailored approaches that are inspired by ethnographic practice and theoretical underpinnings have also been derived in the context of design and ethnography. For example, ethnography is applied within approaches such as human-centered design (HCD) and participatory design, which promote deep user understanding (Sperschneider and Bagger 2003; Blomberg and Karasti 2012; Gregory 2018). In such contexts, ethnography tends to be concurrent, quick and dirty, evaluative and re-examination of previous studies (Hughes et al. 1995). Further examples include rapid ethnography (Millen 2000) and business ethnography (Boden, Müller, and Nett 2011), which are adapted to service and product development sites, and approaches that integrate ethnographic analysis with agile software development methods (Meligy, Dabour, and Farhat 2018) have been reported. Compared to academic ethnography, industrial ethnography differs in its purpose, awareness of time and budget, selection of subjects and themes and scopes (Oto 2020).

As ethnography is applied to various fields and contexts deviating from traditional methodology, misunderstandings and concerns have also arisen. One is the perception that ethnography can be performed by anyone, is unsystematic and ‘anything goes’ and is simply about observing and hearing about behaviour and culture to detect patterns (Forsythe 1999). For those with positivistic and realist thinking, the open-ended nature of ethnographic fieldwork can even seem dangerously chaotic and unpredictable (Ikeya, Vinkhuyzen, and Yamauchi 2007). This stems from the philosophical difference between the (cultural) relativistic and interpretive thinking on which ethnography is based and academic fields which have the positivistic and realist thinking (e.g. natural sciences, computer science and engineering). In order to properly understand and practice ethnography, it is necessary to recognise this underlying ideological difference between the two.

Furthermore, ethnography is sometimes criticised for being invalid due to observer effects, being subjective and generating only self-contained case studies that have little or no continuity. In traditional ethnography, researchers participate in their fields for a long period of time and become part of the community, thereby gaining access to mundane daily life of the field. Then, they collect data using multiple methods and approaches, analyse it based on theories and interpret it in all aspects, grounding it to intellectual tradition such as the relevant ethnographic studies and cohesive research stand. In this respect, the criticisms mentioned above turn out to be a misunderstanding. However, another attention is needed in ethnography of industrial contexts, which has different characteristics from traditional ethnography. To enable non-experts to perform ethnography more appropriately and obtain more reliable findings, democratised ethnography needs to address the trade-offs between various constraints of industrial contexts and proper selection of methods and methodologies as well as validation by theory and intellectual tradition.

Lessons Learnt from Design Thinking

Both ‘design’ and ‘ethnography’ can be used as nouns as well as verbs. Designers make design by doing design, while ethnographers make ethnography by doing ethnography. Research on design and ethnography is driven by both theory and practice. Design thinking is also a concept used in both aspects of theory and practice. It originally includes two threads of discussion: designerly thinking, which is an academic field that constructs practical skills and abilities of professional designers and connects theory and practice, and design thinking, which is a simplified version that incorporates design methods into academic and practical discussions. Design thinking has attracted the attention of many organizations as an approach to creating sustainable and sometimes disruptive innovation, driven by social factors such as the shift in market value from technology to experience and the emergence of wicked problems (Rittel and Webber 1972).

However, design thinking could not avoid the adverse effects of its rapid diffusion. A prominent example is the cognitive and epistemological gap caused by its commodification and popularisation as a buzzword. The framework of design thinking, such as the five-stage process model visualised by d.school (Dam 2025), appeared simple and was accepted with the expectation that anyone could become a designer and create innovations by following it. The misunderstanding was that this simple, linear process could be applied as a rigid checklist, overlooking the foundational mindsets of empathy, reflective practice and the iterative nature of the work. This simplicity was a powerful driver of its diffusion, on the other hand, these misunderstandings also led to broader questions about its methodology and effectiveness. As a result, the gap between research and practice has widened, without the academic foundations of designerly thinking and the essential mindset of design thinking being adequately reflected in its implementation. Instead, the framework has been taken out of context, and many organisations were unable to adopt it as an effective approach beyond the scope of experimental initiatives.

By analogy with design thinking, the discussion on democratised ethnography can be seen as twofold: one aspect involves academically articulating the practical skills and competencies of expert ethnographers and bridging theory and practice; the other concerns incorporating ethnographic methods into academic and professional discussions in a simplified form. Furthermore, reflecting on the shortcomings of design thinking, such as its reduction to a superficial checklist that overlook its core mindsets, democratised ethnography must be more substantial and meaningfully linked to academic discourse. Achieving this requires not only to clearly articulate expert knowledge, but also to engage academic dialogue about how such knowledge is conceptualised, and consider how to connect it to the education of non-experts who practice ethnographic approach as well as formally trained ethnographers while drawing on the success of design thinking in democratising design methods through education and widespread adoption.

Practicing Ethnography, Together

This section utilises autoethnography to describe the process of how I, a design researcher without prior experience in anthropology or ethnography, developed my practices, skills and identity as an in-house ethnographer within a corporate setting. These descriptions are drawn from a range of primary sources, including outputs, deliverables, field notes, reflection notes and research logs from the projects I worked on.

Encountering as a Novice, Onboarding as a Bystander

After gaining experience in design, particularly in HCD research and practice within the contexts of human-computer interaction (HCI) and human-robot interaction, I joined the Interaction Design Laboratory (the Lab). This was a research institution owned by a company in the information and communications industry. In this lab, researchers from diverse fields such as cognitive psychology, linguistics, engineering and cultural anthropology worked together, with interaction design serving as their common ground. As membership-based rather than job-focused employment was common in Japanese companies at the time, I joined the Lab as a ‘researcher’ and was given considerable discretion in deciding my specific research themes. Consequently, my initial work began by joining two projects as a project member.

One of these was a preliminary research project that included a qualitative survey on mobile phone users in emerging Asian economies. The goal of this project was to understand the contextual and cultural factors that shape mobile phone usage in these markets, in order to inform the design of future services and products. In this project, I travelled to countries where the language differed from my native tongue. There, I conducted home-visit in-depth interviews to understand the lives, household finances and technology use of both mobile phone users and non-users. I also undertook fieldwork to observe the information environment and people’s behaviour in local living contexts. A project leader from the Lab, who had experience in ethnographic surveys, and I conducted this project. The leader led the design and implementation of the survey. Under the leader’s supervision, I was responsible for several tasks. Before the survey, I handled the administrative procedures for the business trip and gathered facts about the local population, politics, culture and climate through desk research. During the field research, I acted as a bystander who watched how the survey was performed, rather than an active field researcher. In the post-survey analysis phase, I was responsible for creating profile sheets that summarised facts of the interviewees and the fields and extracting commonalities and differences among them. This series of processes was, in essence, industrial ethnography. We were only on-site for one week, and the entire process, from research design to completion of primary analysis, took less than six months.

Another project was a survey of mamatomo (ママ友) and papatomo (パパ友) communities. Both mamatomo and papatomo are Japanese terms, corresponding to the English terms mum friends and dad friends and referring to friendships formed through children. These communities typically emerge through children’s nurseries or schools and serve as a platform for exchanging local and childcare information, as well as providing mutual support. The Lab aimed to gain insights into the design of mobile phone service touchpoints and user communities by understanding how parents during the child-rearing period join, engage with and leave such communities. The lead for this project was an ethnographer with an academic background in cultural anthropology. I joined this project midway through, accompanying them on home-visit surveys and attending the post-survey reflection and analysis sessions.

Simultaneously with my participation in these projects, I began studying ethnography. My studies primarily involved reading introductory books on ethnography and academic literature on cases where ethnography was utilised within my own research fields, such as design and HCI. When I first started participating in these ethnographic projects, I didn’t yet fully grasp what constituted ethnographic practice and what didn’t. However, through these project experiences, I learned methods for designing and arranging surveys, understood the multi-method nature of ethnography and became familiar with its non-problem-solving approach.

Practicing as a Researcher

After that, I continued to participate in several projects that utilised ethnographic approaches. For instance, in one project, as a user experience (UX) researcher, I conducted participant observations during service prototyping and follow-up interviews after its completion. In another, I participated as a UX researcher who designed, observed and analysed user tests for a mobile application on tablet devices. Additionally, I was involved in quantitative surveys and interviews in the context of marketing and user understanding. In these instances, rather than the projects themselves being fully ethnographic, we often selectively adopted individual methods that form part of ethnography’s multi-method approach.

Furthermore, given ethnography’s strong affinity with participatory design and co-design, which are my areas of specialisation, I began to incorporate ethnographic approaches into the projects I led using these methods. For example, I led a design project to renovate a public facility over several years. This project progressed through continuous engagement with its stakeholders, including the local government and citizens. I facilitated periodic meetings and participatory workshops. In such contexts, I typically behaved as a project participant with an empathetic and cooperative attitude, rather than providing strong leadership.

Consequently, my involvement in ethnography gradually increased. This was certainly due to my recognition of its effectiveness in understanding people and environments and in problem framing. However, it was also influenced by my empathy for its sense of ‘being there’ and its stance unconstrained by technology or pure problem-solving. Approximately five years after I joined the research institution, that is, after I began engaging with ethnography, the ethnographic approach and mindset became a defining characteristic of my approach to design research. Simultaneously, ethnography gradually evolved from being merely a means of research to becoming a subject of research itself.

Exploring as Scholar

It is well known that ethnographic practices in academia and industry differ significantly (Levin 2019; Oto 2020). I became interested in what was missing in my practice of ethnography compared to the academic practice, as I realised I was utilising parallel, quick and dirty and evaluative approaches. Consequently, I began conducting ‘experiments’ with a researcher who was an ethnographic expert in both academia and industry, and with whom I had previously collaborated on the project of mamatomo and papatomo communities. These experiments initially explored the interplay between design and ethnography. We had previously utilised ethnographic methods in design projects, as in the project described above. Additionally, we began to experiment with incorporating design methods and technology interventions in ethnographic projects. For example, we explored: What if we utilised cultural probes in ethnography? What if we performed a participatory service walkthrough? What if we divided the ethnographic work among project members? What if we employed head-mounted displays and omnidirectional cameras? These experiments were not simply about improving efficiency. They were driven by a more fundamental question: ‘how will ethnography itself change when we introduce these new tools and methods?’, rather than ‘how will these new tools and methods improve or enhance ethnography?’ This approach provided us with a continuous opportunity to reflect on the core question of ‘what is ethnography?’ as we navigated the differences between academic and industrial practice.

Concurrently, this period coincided with the Covid-19 pandemic’s disruption to fieldwork participation and the subsequent emergence of various remote research tools. It was also the time of a bloom in large language models (LLMs) and generative AI with interactive interfaces. We, too, explored the potential of various tools within ethnography. While tools such as automatic transcription and summarisation are primarily designed for efficiency, we found that they also held the potential to bridge the skill gap between experts and novices. This was not because the tools themselves inherently taught ethnography, but because their use became a focal point for discussion and learning. Indeed, we integrated some of them into our practices: for example, we began conducting interviews and project meetings using teleconferencing services (e.g. Zoom) and visualising and organising field data with digital whiteboard tools (e.g. Miro and Mural). Conversely, some tools presented challenges: automatic transcription was often insufficiently accurate (especially for Japanese, which we used most frequently), and AI-supported analyses such as qualitative coding, thematic analysis and persona generation raised issues regarding explainability and bias. Furthermore, application of real project data to AI still entails numerous confidentiality and ethical considerations.

Our experiments developed further, leading us to discuss ‘how non-ethnographers can conduct ethnographic research?’ By ‘non-ethnographer(s)’, we refer to citizens and other stakeholders who participate in participatory design and co-design, or individuals working in practical settings such as medicine and education. It was clear that there was an increasing demand for ethnography in these fields; however, to the best of our knowledge, there was no established method or methodology for ethnography by non-ethnographers.

Lessons for Democratised Ethnography

Reflecting on the series of experiences described in the previous section, this section initiates a discussion on ethnography by non-ethnographers. Our experience recounts the journey of an individual who initially lacked ethnographic experience but subsequently became an ethnographic practitioner through their work. This section explores what was effective in enabling a novice to perform ethnographic work and what facilitated that process, aiming to extract implications that can be applied to a truly democratised ethnography.

The first key factor, collaborative practice, is a process of learning for individuals. While concepts such as team ethnography (Erickson and Stull 1997), collaborative ethnography (May and Pattillo-McCoy 2000) and duo- or trio-ethnography (Sawyer and Norris 2015; Agosto, Marn, and Ramirez 2015) already exist, where which multiple ethnographers conduct research and analysis together, the process of acquiring explicit and tacit knowledge in ethnography, as described in the previous section, was more daily-based and proceeded with a community-centred engagement rather than being solely activity-based. This process featured a flatter power structure and involved mutual and interactive learning and knowledge transfer. This can be connected to the discourse of LPP within a community of practice (Lave and Wenger 1991), where novices learn and gradually move toward the centre of a community by participating in its daily activities. In this context, the community was the Lab, the domain was qualitative approaches, primarily multi-methods of ethnography for design and the practice comprised the project activities. I initially participated in ethnography as a novice in a peripheral role within projects, gradually began to practice individual ethnographic methods and processes and eventually took the lead in projects. Within the Lab, researchers engaged in daily exchanges of not only work-related interactions but also information concerning ethnographic media, literature, cases and study groups. This occurred through communication tools (e.g. Slack), regular and irregular meetings, workshops and casual chats in their workplaces. In such a community, my learning about ethnography was deepened through participation in ethnographic projects and a transformation of identity from novice to bystander, practitioner and finally scholar. Reflecting on this, the implications for democratised ethnography include the knowledge exchange and reflexivity inherent in a community of practice through LPP, as well as the norms associated with experts and masters within such a framework.

The second factor, collective intelligence, is the outcome of that collaborative practice and serves as the intellectual foundation for democratised ethnography. It focuses on how the community collectively ensures methodological rigour in the face of constraints. Communities of practice and collaborative forms of ethnography offer various intellectual possibilities, such as the distribution of cognitive labour, the diversification, sharing and transfer of knowledge and interpretation, as well as triangulation and reflexivity. Here, however, we particularly emphasise the aspect of collective intelligence that serves as the foundation of democratised ethnography. In the face of various trade-offs, including business constraints such as time and financial resources, commitment to key performance indicators and client demands, how can we preserve the authenticity of ethnography? More fundamentally, what aspects of the effort must be preserved for it to remain ethnography, and at what point does its distortion render it no longer ethnography? This is a question that also relates to the validity, reliability, robustness and ethics of ethnographic practice. Fortunately, as the Lab was part of a research institution, a cost centre, these trade-offs were less severe than for teams in profit centres. Furthermore, the Lab was keenly aware of this question because they knew both the successes and failures of design thinking. Consequently, they consistently posed questions such as ‘what is ethnography?’ and ‘is this effort truly ethnography?’ The lifeline for this continuous inquiry was dialogue with ethnographic experts. While the Lab sometimes had researchers with an academic background in ethnography, this was not always the case. When such experts were unavailable, they diligently pursued reflection and review by continually maintaining connections with academia. This involved occasional collaboration with university experts, seeking their advice and participating in academic meetings and conferences. Reflecting on this, the implications for democratised ethnography include a mindset to ensure authenticity of ethnography, and a critical and continuous verification on practices.

The third factor is the use of methods and tools. In the Lab, various methods and tools were routinely introduced and shared among members. These included templates for consent forms, research plan documents and interview guides, as well as omnidirectional and action cameras, AI-supported automatic transcription tools and coding assistance applications. This suit of tools not only enhanced work efficiency but also helped bridge the skill gap between novices and experienced researchers, thereby facilitating cooperative work. Moreover, these interventions also increased the feasibility and capability of ethnography for individuals unfamiliar with it such as designers, engineers and marketers and served as a common basis for communication. For example, the process of sharing video clips from field research and annotating them to discuss ‘what does this interaction imply?’ within a project team fostered interpretations and empathy rooted in on-site sensibilities, without relying on specialised theoretical terms.

Conversely, the introduction of new interventions also carries the risk of threatening the essential values of ethnography, namely, deep participation in fields, building relationships and sensitive responses to contextual situations. For instance, automated analysis utilising AI or standardisation of procedures and processes could potentially encourage the black-boxing of research and cultural decontextualisation. To mitigate these risks, the Lab consistently posed meta-questions whenever new interventions were introduced, such as ‘how does this intervention affect our observations and interpretations?’ and ‘can its validity as ethnography be maintained?’ These questions were continuously discussed reflectively. In other words, the effective utilisation of methods and tools was not an end in itself; rather, it was carefully positioned as a support for practice and invariably employed in conjunction with critical and reflective dialogue. Reflecting on this, the implications for democratised ethnography include the strengthening of ethnography (and ethnographers) in terms of accessibility, feasibility, capability, efficiency and sophistication through the introduction of methods and tools.

In this way, the experience at the Lab, viewed through the three perspectives of collaborative practice, collective intelligence and methods and tools, elicited the opportunities and requirements for democratised ethnography. These observations suggest that ethnography, in this context, should be understood as a community-rooted mode of learning supported by an interplay between practice and reflection, rather than merely a set of technical training exercises or standardised manuals. In that sense, democratisation may need to be reconceptualised: it is not about something that ‘anyone can do’ but rather something that ‘everyone can cultivate collectively, in continuous inquiry with others.’

Towards Democratisation of Ethnography

Expectations and demand for ethnography have grown in industry and public sectors. If every organisation could employ educated and trained ethnographers, the problem would be straightforward. However, the reality is not merely a matter of skill supply, but also a structural issue concerning who conducts ethnography (Lombardi 2009). As more individuals begin to engage with ethnographic practices and participate in ethnography, leveraging opportunities, for example, those afforded by design thinking, HCD and UX, ethnography finds itself at a crossroads of democratisation. This situation is akin to what design itself once confronted with the unintentional diffusion of design thinking into industry (Hasbrouck 2015). The challenge is not a simple binary opposition between opening ethnography up for anyone to practice, or retaining it exclusively in the hands of experts. Rather, we must explicitly attempt to address the question: ‘what is ethnography?’ Historically, such a question has, at least, been posed (Cefkin 2006; Ingold 2014; Dorland 2016). However, the responses to this question have often been tacitly preserved and passed down through a certain artisanal tradition, where knowledge is acquired not from formal instruction but through observation, mentorship and practical experience. This has allowed the practice to remain flexible and deeply contextual, but it has also avoided the need for an explicit and widely accessible definition, thereby limiting its democratisation. However, if ethnography now faces the risk of being misunderstood and commodified, much like design thinking, can we afford to remain silent on this crucial question?

The crucial starting point for democratised ethnography isn’t merely a collection of universally applicable templates and techniques. Indeed, it is a critical, reflective and continuous attitude of re-examination towards the question: ‘what is ethnography?’ This question repeatedly re-emerges, is adjusted and negotiated in practice, rather than reconfirming a static definition. Indeed, the environment that fosters such question(ing) is precisely what makes democratised practice sustainable. Our experience at the Lab revealed multiple pillars built upon this foundational question and implications: knowledge exchange, reflexivity, a mindset, meta-level verification and the complementation and enhancement through methods and tools.

For many individuals and organisations, ‘democratising ethnography’ might evoke the idea of packaging reproducible methods and making them widely distributable and teachable. While this is certainly one practical objective and explicit knowledge can help bridge practice and theory, knowledge doesn’t necessarily emerge solely from formalised structures. As this paper has demonstrated, merely assembling such explicit knowledge does not, in itself, guarantee authentic practice. Rather, the impulse to structure knowledge itself risks eliminating the inherent openness of inquiry and the contextual richness of practice. The Lab’s practices fostered learning within unstructured relationships, such as casual chats on Slack, informal reflection meetings or interactions outside meeting rooms. The democratisation of ethnography, therefore, shouldn’t be framed as a completed state, but rather depends on the sustainability of a dynamic practice centred on the question: ‘how can we continue to ask?’ In essence, our proposal isn’t simply to provide methods or frameworks, but to foster a shared inquiry.

It is argued that a ‘digital turn’ has arrived in the field of business anthropology, responding to the rapid digitalisation of both academia and industry (Artz 2023). In particular, AI holds the potential to facilitate the democratisation of ethnography. This is not simply by making ethnographic work faster for experts, but crucially, by lowering the barrier for non-experts to engage in ethnographic practices. While tools like automatic transcription and summarisation primarily serve to increase efficiency for experienced researchers, other AI-powered tools can be designed to guide novices through the research process, helping them to navigate complex data and contribute meaningfully to the project. While numerous tools designed to make the practice faster and easier have been introduced, such as automatic transcription, summarisation, gaze analysis keyword extraction, their impact on the fundamental question of ethnography is considerable. More important than the introduction of such tools themselves is the nature of the questions they generate or suppress. In this sense, democratisation doesn’t imply that anyone can conduct research through intervention; rather, it means that everyone bears the right and responsibility to ask: ‘what is ethnography?’ Furthermore, the Lab maintained a crucial connection between theory and practice by fostering ties with ethnographers both within and outside the team. Can AI offer more than mere procedural support for such efforts? Can AI participate in the critical and reflective questioning of ‘what is ethnography?’ for non-ethnography experts, and the often-awkward work that accompanies it?

Conclusion

This paper has explored the expanding applications of ethnography in design and innovation, alongside the challenges inherent in its increased accessibility. Drawing insights from the trajectory of design thinking, we have argued that the democratisation of ethnography should not be merely a simplification or popularisation of methods. Rather, it represents a more nuanced engagement, fundamentally shifting towards a community-rooted mode of learning underpinned by continuous critical inquiry. Our case study of a ‘pseudo-democratised ethnography’ within a corporate design team, particularly informed by experiences at the Lab, highlighted three pillars for fostering authentic and rigorous practice among non-specialists: collaborative practice, collective intelligence, and the strategic use of methods and tools.

Our analysis suggested that collaborative practice, often manifested through legitimate peripheral participation, can facilitate the organic acquisition of both explicit and tacit ethnographic knowledge within a community. Collective intelligence, driven by an ethos of sustained questioning and expert dialogue, appeared instrumental in navigating the inherent tensions between ethnographic authenticity and the practical constraints often encountered in industrial contexts. Furthermore, while the strategic integration of methods and tools, including emerging digital technologies like AI, demonstrably enhances accessibility and efficiency, our findings indicated that their true potential extends beyond being simple instruments for a fixed set of procedures. Instead, these tools become catalysts for new forms of dialogue, collaboration and learning. It lies in their capacity to provoke deeper meta-reflection on the very nature of ethnographic inquiry. The ‘digital turn’ in anthropology highlights AI’s potential to accelerate democratisation, yet it concurrently compels a critical examination of how these tools might reshape, or even inadvertently obscure, the fundamental question of ‘what is ethnography?’. Consequently, we propose that the democratisation of ethnography is not a fixed outcome or a definitive set of procedures to be codified. Instead, it seems to entail a continuous, evolving practice—one that thrives on the shared responsibility to persistently interrogate ‘how can we continue to ask?’. This inherently open-ended approach, however, necessitates profound ethical considerations that transcend traditional research ethics.

As ethnography becomes increasingly integrated into diverse sectors, the ethical landscape becomes multifaceted, potentially encompassing ethnographic ethics (regarding participant relationships and representation), research ethics (data privacy, informed consent), technological ethics (bias in AI tools, data security), corporate ethics (commercial interests versus research integrity), and public ethics (societal impact, accountability). Navigating this intricate ethical terrain will likely demand ongoing, explicit dialogue rather than reliance on pre-defined or standardised solutions.

Finally, the convergence of design and ethnography has recently spurred more philosophical dialogues, giving rise to concepts such as design anthropology (Donovan and Gunn 2012), design ethnography (Salvador and Mateas 1997), anthropocene (Slaughter 2012) and pluriversal approaches (reference). These emerging discourses offer significant opportunities for deepening the theoretical and practical conversation, moving beyond mere methodological deployment towards more fundamental ontological and epistemological engagement. For these critical insights to be meaningfully integrated into industrial contexts without succumbing to oversimplification, the ‘shared inquiry’ we advocate may need to extend to embrace these philosophical depths. This suggests the continuous cultivation of environments where the challenging, yet essential, questioning of ‘what is ethnography?’ (and its broader implications) is not just accommodated, but actively nurtured, fostering an organic and evolving bridge between cutting-edge academic thought and the complexities of applied practice.

Ultimately, democratised ethnography may not present a straightforward blueprint for harnessing collective intelligence in user-centred innovation. Instead, it appears to propose a more nuanced and dynamic engagement: one that champions a balanced approach, valuing accessibility not as an end in itself, but as an ongoing invitation to persistent epistemological and ethical interrogation.

About the Authors

Naoya Tojo(東條直也), Ph.D., is a Core Researcher at KDDI Research, Japan, and a Visiting Research Fellow at Helen Hamlyn Centre for Design, Royal College of Art, UK. His research focuses on co-design and participatory design for democratised innovation, combining ethnography and design research.

Tomoko Oto (大戸朋子), Ph.D., is an Assistant Professor at Tokyo Medical University and a cultural anthropologist. Her research explores the application of ethnographic methods through the use of new tools.