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There remain many unknowns about the capabilities of large language models (LLM’s), but their limitations are beginning to reveal some interesting boundaries. More specifically, by accelerating or automating certain functions, their irrelevance in other areas is gradually exposed. In the shadow of all those over-hyped stories about how LLM’s are going to “change everything” there remains an array of human interactions that are ‘untouched.’ By examining what’s both in and out of the purview of these models, this post considers how ‘untouchable’ practices might gradually garner more attention, as well as how their value may shift.

Let’s start with three broad use cases for LLM’s that have drawn a lot of media attention: companionship, creativity, and productivity.

For the first of these, a whole crop of tools have emerged that are designed to serve as LLM-driven ‘companions.’ From conversations with historical figures (hellohistory.ai, character.ai) to virtual boyfriends/girlfriends (replika.ai, candy.ai) to remarkably personalized advisors (pi.ai), these models have been trained to mimic language patterns that convey familiarity to their human users. Of course, this comes with risk. Some particularly newsworthy instances where these models fall short include at least one suicide as a result of a user’s immersion with an LLM-driven ‘companion.’ This is clearly tragic and unacceptable. However, over time, it does seem possible that the most common patterns of communication that occur within the context of close human relationships, as well as boundaries for safety, could eventually be captured by these models to the point where they can offer familiar and trusted interactions that trigger human responses resembling ‘companionship’ — if we want them.

Next, let’s consider models that generate content (images, audio, video, text, etc.), a category of use cases we might label ‘creativity.’ The generative capabilities of tools like Mid-Journey or Dall-E, which can produce images in a vast range of styles, are familiar to many by now. As these models are trained, their capabilities are becoming increasingly more fine-grained and ‘realistic.’ Those following the industry will remember quite vividly how early models had trouble generating images of hands, or inadvertently added extra limbs to figures. But regardless of how much more ‘accomplished’ these models become, ultimately they are incapable of being truly original. They’re locked within the datasets from which they were trained. While they may be able to masterfully iterate on a theme at super-human rates, their outputs are inevitably derivative.

Finally, another set of broad use cases for which these models are touted could be classified as ‘productivity,’ which includes LLM capabilities such as summarizing, reformatting, translating, classifying, and automating. This is where we’re starting to see increased attention in the workplace, including a great deal of curiosity among corporate leaders. It’s not difficult to imagine accelerated workplace productivity with these capability-enhancers at our fingertips. However, we also now know that LLM’s are prone to hallucinate, or generate responses that sound feasible, but are factually incorrect. This is because the predictive modeling they enlist prioritizes the most likely next piece of content based on the initial prompt and the set of data from which it was trained — and then iterates. Anyone who’s played with some of these models and tried to ‘correct’ inaccuracies they produce will quickly realize that all versions of the ‘reality’ they produce are treated as equally valid by the model, even if contradictory. You might get wildly different responses from the same prompt, or even within a string of prompts, yet all are presented as equally ‘factual.’

There are many people working on ‘correctives’ (and ‘alignment’) for model hallucination. The jury’s still out on whether they can completely solve this challenge, especially in instances where accuracy is critical. Still, with improvement, it’s not hard to imagine a future in which LLM’s retrieve information, process it (e.g., summarization, translation, etc.), and (re)format it ways that are reliable enough to make them commonplace for non-critical tasks. Use cases like learning, planning, and shopping come to mind.

Where does all this lead? The scale and speed at which LLM’s can iterate means that they can offer capabilities that outstrip ours when we need to classify, personalize, reformat, translate, summarize, converse, recommend, generate, or automate digital content. Yet, as LLM’s and other machine learning models proliferate over time, their output will become increasingly common. While compute costs are high now, it will be interesting to see whether tech companies can continue to charge premiums for tools that are inherently designed to endlessly churn out more X and iterate on it at a faster pace — hardly a formula for market scarcity or price stability (unless we start to see demonstrably valuable specialization). Many industry observers have already commented on the AI ‘gold rush’ as a race toward mediocrity. They clearly recognize that iteration is not the same thing as innovation.

However, when we drill down on what these models CAN’T do, things get more interesting. The question then becomes, ‘where ISN’T the spotlight shining?’ Here, I’m drawn toward recognizing that ‘analog anything,’ by virtue of its inability to scale or iterate at the pace of LLM’s, seems destined to increase in value. So, instead of ‘replacing’ traditional arts, the capabilities of these models may very well drive the value of things like original paintings or live performances up. This also extends beyond the cluster of ‘creativity’ use cases. Let’s go back to the companionship category. In a future with increasing availability of virtual companionship, ‘real’ companions (especially the exchange of stimulating original thoughts) will only become more valuable — cue the renaissance of salons. Even in use cases focusing on productivity, the risk of hallucination will place increasing value on human interpretation when the stakes are high.

I would argue that this is good news for ethnography. After the novelty of these models wears off, and the dust settles from their disruption, the limitations listed above (and likely others) will become increasingly apparent. In the process, understanding and interpreting the consequences of human-to-human interactions and characteristics like intent, morality, motivation, emotion, inspiration, frustration, implication, etc. will become increasingly valuable. While advances in tech may shift this (I’m looking at you, metaverse), they may also contribute even further to increasing the value of non-digitally-mediated human-to-human interactions. Surprise! — these are exactly the realms in which ethnographers thrive.

Of course, ethnographers may find LLM’s useful for things like summarization, research planning, or pattern recognition within a data set, but ultimately our focus is on human experiences and interactions, and our HUMAN interpretations of them (original insight). These attributes should increase in value precisely because their unique and non-predictive qualities lie outside the purview of LLM’s. All of this doesn’t preclude the value ethnographers can extend to interpretations of human-AI interactions, including the ways less predictable human characteristics intersect with the ‘logic’ of LLM’s, but I’m focusing more specifically on where we might see unexpected increases value.

What types of organizations are likely to benefit most from ethnographers’ unique offerings in this shifting landscape? If digitally-driven experiences and products churned out by LLM’s remain trapped in iterative cycles of mediocrity, demand for live, original, and interactive experiences with other humans may increase. These may include components driven by LLM’s that shape aspects of these offerings (crowd management, interest-matching, adaptive pricing, etc.), but the draw itself would remain focused on human-to-human interaction. In contrast to passive experiences, we could witness significant growth in amusement-park-like offerings, where mutual experience and human interactions are privileged, fostered, and facilitated. (For a somewhat more dystopian view, see Daniel Miessler’s take on how AI might evolve, or watch the clip from AI, below).

The skills ethnographers could bring to these settings are those we’ve been offering for more than 100 years. I’ll pull from Ethnographic Thinking here, as a means of summarizing some of those methods and their continued value:

Many ethnographers have spent countless hours in the homes, workplaces, and communities of people who are initially strangers to them. Among all the stimuli they encounter in these settings, there is no prescribed set of observations that are always key to forming an understanding of a culture. Instead, ethnographers are continually on the lookout for cues that will help them paint a fuller picture of the culture they’re exploring. While observing, the ethnographer’s aim is to look beyond the obvious and discover the key components that collectively make up an “ecosystem” of observations. These ecosystems are always complex and are made up of many different cues. To demonstrate the wide range and level of their complexity, here’s a sampling of some of the most common observations ethnographers consider: body language, interpersonal interactions, behavioral triggers, contradictions, unspoken priorities, normalized practices, sequences of events, affinities, attachments, repellants, workarounds, social transgressions, implicit hierarchies, priorities, neglected people/places/things, honored people/places/things, displays of comfort (or discomfort), unconscious habits and practices, and interactions with material goods. Each of these finds its way into the ethnographic mind as ethnographers examine the sights, sounds, scents, touches, or tastes of the culture that surrounds them. A core part of this examination of cues is the ability to continually sort and prioritize levels of relevance in situ. This skill is sometimes described as context-awareness, but it also includes visual literacy, layered listening, and the ability to identify and home in on relevant details in order to explore them in more depth.

Perhaps someday LLM-driven android ethnographers will take on these tasks — infusing themselves into the very last corners of non-digitally-mediated human experiences, and ushering in a whole new set of moral and existential challenges. Who knows what the human response might be.

Photo: 2018, Soo-Young Chin and ‘friend’ in the Changi airport, Singapore

It is by now clear that the field of applied research is experiencing some very dramatic shifts. From mass layoffs, ‘silent’ re-orgs, ‘right-sizing,’ and many unknowns about the impact of AI, the pendulum for insight work has swung to an extreme I’ve never seen before. This is difficult for all of us in the industry, and is particularly challenging for anyone impacted by layoffs, or those who are in the early stages of their careers.

This post is dedicated to anyone facing these recent challenges. It’s mostly a loose collection of thoughts and insights that I might have shared with my younger self; including, most pertinently, questions I wish I’d asked of myself and others. It’s not meant to be comprehensive, and its applicability will vary depending on your circumstances. It is, however, an attempt to help you take advantage of this shift in the industry by pausing and using ethnographic thinking to re-frame your career considerations as you engage in conversations with prospective employers and your fellow travelers in life.

Let’s start with a few ways of looking at job-seeking in this field that often get overlooked. Regardless of industry, these considerations should help you steer around the hazards that could de-rail you and, worse yet, erode your confidence in a tough job market.

How does the company make their money?

This one is FAR more critical than I once realized; and it’s not about examining balance sheets or annual reports. It’s about understanding the core value of what a company does that enables it to exist. For example, a social media company doesn’t succeed unless it can offer a compelling platform for people to share content. Without that, it doesn’t make money. If people don’t come to the platform to share and enjoy content, the company has no clear way to attract either advertisers or memberships — which means they have no business model. So, their research needs encompass things like understanding what motivates people to create, share, and consume content, as well as how to best facilitate momentum for this ‘flywheel.’ If you’re talking with a company that operates in this space, ask yourself whether this is something that truly drives you to produce your best work. If yes, then great, this might just be the type of company where you’ll thrive, because this org will repeatedly look for these types of insights to help the business thrive and grow. If not, there’s no reason to think you’re deficient in some way. But it’s best to identify this early, and preferably well before you start the interview process or accept a position.

Beyond the matter of research focus, you should also consider that the core business model of most companies permeates nearly every interaction within it. When people talk about organizational culture, they often refer to things like whether the org has a ‘flat’ structure (I’ve never seen one that really does), ‘work-life balance’ (you should have your own definition of this), or even perks. These may shape a org’s culture, but they often pale in comparison to the overarching influence that the core business model has on how people prioritize, make decisions, influence change, or get rewarded. Want to know what really drives people and behavior in an org? Follow the money.

Is there room to be you?

To answer this question, you’ll want to think beyond identity categories to consider your own unique attributes and whether or not they’re a match for the org. Start with a solid understanding of what you bring to the table. Self-evaluations like Strengths Finder are one way to do this. However, what I’ve found to be even more useful over the years is to listen carefully to how others perceive your value. Ask them about what stands out in your work for them (good and bad) — maybe even propose a feedback exchange of some sort. Reflect back on things like previous performance reviews, casual conversations with colleagues at the bar, surprise compliments that stuck with you, or random comments about your work that resonated deeply for you for one reason or another. In a phrase: feedback is a gift — unwrap it.

Then, try to understand the org’s dynamics. Start with a focus on processes and practices. For example, are the org’s practices rooted in well worn orthodoxies or are they more flexible and open to change? Ask them about reporting structures and levels, operating procedures, and approval processes that will impact your work (e.g., research planning, budgeting, participant recruiting, collaboration protocols and practices, organizing workshops, reporting out, etc.), and listen for signs of flexibility or ossification. Compare their responses to your own thresholds for structure and process in your work.

You’ll also want to probe into how people are rewarded within the org. Even if you aren’t particularly career-focused, these standards will have bearing on your level of satisfaction in the role and your relationship with your peers. To get started, ask about success stories for people in roles similar to the one you’re considering. More specifically, ask them to tell you about the one thing that person did that stood out most? How were they rewarded? Listen carefully for signs of how the org positions and recognizes value, and make sure you gather as many different views as possible and take detailed notes on each.

Then, ask yourself what type of stories you heard. Are they sharing examples that focus on how this person successfully managed up?; about how they changed hearts and minds?; how brave they were?; how efficient they were? how radical they were? how they rallied colleagues?; how they systematized a practice? Each of these is an indicator of the values of the org. You may find that the greatest insights you glean are from the subtexts of these conversations. Pay close attention to these signals; they’re the interstices and the cracks where company culture actually resides. And those cracks are where you’ll be living…nearly every day. Listen for telling pauses, tone of voice, veiled judgements, elation, joy, team alignment, patterns of conflict, etc. Then, finally, look for themes across your conversations and ask yourself if you see alignment or gaps between your own values and those that you’ve seen signaled. If the latter, how big are those gaps, and are they deal-breakers?

Who’s in charge really?

There’s often a distinct difference between official org charts and actual networks of influence within orgs. Many of us have seen instances where “dotted-line reports” or “advisors” hold far more sway than those listed on formal team rosters. Informal networks will influence your experience in significant ways, since they often set the conditions and tone for how the team communicates, interacts, and makes decisions. To get past the party line, you’ll want to dig a bit deeper than a glance at the org chart. Ask about how the group identifies stakeholders, who they are in relationship to the team, and how they achieve buy-in with them (including examples of both successes and challenges). Then follow that up with “who else is critical in the decision making process” to get a more complete picture. Knowing who you’ll need to convince that your work is valuable, and where they sit in the org, is critical information for understanding where opportunities lie for the role, and whether or not the interactions needed will sync with your strengths, work style, and values. Will you be spending most of your time sharing insights and influencing decisions with designers?; product managers?; executives? Your approach to each needs to be different, and it will shape nearly everything about how you work.

In addition to reporting structure and understanding the network of stakeholders with whom you’d interact, you’ll want to get some understanding of how leadership is performing. For example, are they sending signals that indicate leadership gaps? The obvious first place to look is the job description itself. Read it carefully. Is it clear? Does it feel scoped correctly, given your experience in the field? Signs of leadership gaps are often reflected in job descriptions that are scoped too broadly (they want one person to cover a vast array of responsibilities that stretch across multiple different practices) or too narrowly (caution: micro-manager ahead). In addition, strong leaders have strategic conviction. Ask people to help you understand the top two or three strategic priorities for the year, and how they’re driven. If they give you empty platitudes instead of a strategic vision the includes at some indication of how goals will be accomplished and measured, the odds are high that you’re headed into a rudderless team.

Leadership gaps aren’t necessarily a bad thing, if there are indications that the team is open to new ways of influencing the org. This could even be an opportunity for you to help drive change and make significant impact. Listen for cues from people that demonstrate how change happens within the org. Ask about how someone in this position might shape the role once they’re in it, and whether the org is open to some early ideas you might have.

Finally, dig a bit further into the characteristics and approach of key leaders in the org. Ask about their leadership style, their tenets, what makes them unique? Probe for examples of how they affected change or drove impact, and how the org responded. Do some digging online to see if you can find interviews with those leaders, or guest appearances on podcasts, etc. Try to gather as many of these stories as possible, and then ask yourself one very important question: Given what I’ve seen and heard so far, can I imagine myself as a leader in this org? If the answer is no, this may be an indication of cultural misalignment, which could lead to feelings of indifference toward the company or even resentment. Either way, feeling like this certainly won’t inspire you.

What’s their approach to innovation?

Research is often tied closely to innovation initiatives within an org. However, there are many different ways innovation is approached and positioned within companies. I’ve had the privilege of working with some incredibly talented and experienced people in this space, and two conversations have really stuck with me.

The first conversation I want to share with you is one I had with someone who I sincerely consider a product genius. We were discussing our experiences with the different attempts we’ve seen to activate innovation insights within a company, which I’ll paraphrase here: There tend to be two main modes for integrating innovation within an org — the “looking for friends” approach, and the “shiny thing on a shelf” approach.

In the first of these, an innovation group is tasked with creating great new ideas. They might conduct exploratory research, carefully craft a set of design principles, and even cook up some prototypes. Then, they begin to look around the company to build relationships with teams that might want to take up the mantle and bring these ideas to life. If they find interested teams, they often eventually realize that those teams’ reward structures and workflows are simply not designed to ‘ingest’ thinking that’s so different from what has traditionally worked for them. The innovation teams’ insights eventually just become more work for which they won’t be rewarded. If they do find some alignment with those teams, they often come up against a game of odds: most new ideas fail, and those teams don’t want to be associated with a series of failures.

After a few attempts at this, these innovation groups will often shift to a “service model” where they begin working with another team that has some sort of mandate to innovate, and offer their skills as a means of helping them discover and develop the next big thing. Unfortunately, the objectives for this type of work are often constrained by the mental models and limitations of ‘tried and true’ practices. The team ‘contracting’ the services of the innovation team often frames goals and objectives in incremental terms that don’t align well with the riskier and more creative type of work that drives the innovation team. The result is frustration on all sides; and, often, a re-org or dissolution of the (non-revenue-tied) innovation team.

On the other hand, the “shiny thing on a shelf” approach follows a workflow much closer to that of an incubator. The innovation team is responsible not just for exploring, setting parameters or specs, and generating mock-ups, but for finding product-market-fit, and developing and testing workable prototypes in the marketplace. The idea is that once successes are clearly demonstrated in the ‘real world’ by these teams, they can more easily earn the trust of other teams in the org, who are motivated to integrate their successes and adapt them to their needs. This approach is much more difficult, requires high levels of buy-in from leadership, and often longer timelines — all things that are rare in lean times. However, I’ve seen it work first hand in the form of live model tests, pop-up stores, and new product experiments where teams develop and test offerings in real world settings. Research is critical throughout the process in this approach; and, because it sits much closer to addressing business needs in real-world settings, its value is self-evident.

The second story I want to share is from a conversation I had with a fellow researcher who’s seen his share of innovation practices come and go as a researcher within some very well-known large companies. His take?: a company that launches a dedicated innovation group in the ‘looking for friends’ model described above is likely not fostering the organic innovation that is already occurring within its product teams, and isn’t committed enough to give an innovation team a long enough leash to pursue the ‘shiny thing on a shelf’ approach. So, teams formed under these conditions often have the odds stacked against them right out of the gate.

So, where does this leave you as a researcher looking to find your next role? As you talk with prospective employers and teams, ask them how the org approaches innovation. Is it considered a speciality handled by a dedicated team, or is it an integral part of how products change and evolve? If they have a dedicated team, does that team operate as a discrete unit, a service model for other teams, or more like an incubator? What role does research play in the model they’ve deployed? What are the channels they have in place to cultivate and recognize research-driven innovative initiatives? What are their success stories?; their failures? Then, take the time to consider where your strengths would be most valuable in the context of the model they’ve chosen.

Do they prioritize humility?

This may be the most important assessment you make as you engage in conversations with prospective teams. You will make mistakes in your work. Your colleagues will too. It’s essential to understand the character of interactions within a team to determine whether you’d be entering an environment where teammates learn from those mistakes and offer one another support in the process. I’ve had two employers in the history of my career that made this a priority when recruiting. One did so explicitly (yay!); and, while the other may not have articulated it so directly, it was clear that they held people to standards that privileged authenticity, kindness, humility, and empathy.

It may be difficult to make an assessment like this with what little time you have to get to know a prospective team, but I would say that it’s a combination of gut feeling paired with some lightweight queries. When I talked with people in both of the companies referenced above, I was struck by how warm, sincere, and transparent everyone was. After seeing this across 10-12 different employees, a clear pattern emerged. In addition to looking for these qualities, you might also ask some questions that get at the matter somewhat tangentially. For example, you could inquire about how the team has responded to adversity and then listen for signs of humility, accountability, and openness to learn. Do they share stories about how people rolled up their sleeves and came together, or does their response focus more on internal politics or maybe conflict avoidance?

Another way to assess this is to explicitly demonstrate your own humility and see how they react. After talking about a project and your impact or accomplishments, wrap up with a short summary of gaps, challenges, or shortcomings. Talk about where it went wrong, and what you’d differently if you had a chance to start over. Maybe even prompt them for ideas about how they might have done things differently, just out of curiosity. Does sharing this experience seem to fall on deaf ears, or is this the moment where they engage even more with your work? Either says volumes about how they work and where they invest their energy.

What to do with responses

The job hunt can be a bit of a minefield. Managing a rapidly growing number contacts, context-switching, adapting to changing org needs, ghosting (just weird), etc. If you’ve been through a series of interviews with an org, and you’ve reached the point where you finally receive a response, I’d like to offer what I think is the healthiest response to each.

If they say ‘no,’ in whatever form, many companies aren’t in a position to share why. Feel free to ask them politely for any information they have about your candidacy, but ultimately your best reaction to a ‘no’ is to learn what you can, then let it go and move on.

If they say ‘maybe,’ prepare yourself for a ‘no,’ but try to dig for more detail. What’s delaying the decision? Is it a matter of budget? team match? waiting on a re-org? When will they know more about budget? What are their standards for a team match? How long do re-orgs typically take? Then, be sure to offer more of your time to clarify questions about your work and approach, during which you’ll want to get as much feedback as possible from them. No matter the explanation from their end, your goal is to use the ‘maybe’ response as a way to learn more about the org and their perception of your candidacy. You’ll also want to consider that a ‘maybe’ could also be a delay tactic while they court other candidates or wait from a response from someone they consider their top choice. All that sucks, of course, so try to use the ‘maybe’ as a personal learning and growth opportunity.

Finally, if you get a ‘yes’ response, congratulations, but make sure you have all the clarity you need going in. Do you have a clear understanding of expectations for the role? Have you taken the time to read between the lines of the role’s responsibilities to determine the higher order need they have? Are you seeing signs of humility and integrity among those with whom you’ll work? There’s no such thing as a perfect org, but you’ll want to ensure that you have optimized for your well-being before jumping in.

A few final thoughts

Most careers are non-linear, so give yourself a break and open your perspective to possibilities that aren’t at the top of your wishlist. In my career, I’ve run across projects, clients, and jobs that I initially felt weren’t that interesting for one reason or another, only to find out later that they included some of the greatest growth opportunities I’ve ever experienced. If you’re just getting started, this is particularly important. You may have your heart set on that dream company or job, but you may very well be limiting yourself. This is why I often recommend that younger researchers spend some time working in a consultancy, where they can get exposure to many different industries and types of clients. You’ll learn much more about your strengths and interests this way, and in a much faster timeframe.

Lastly, I realize that people have different levels of interest in, and tolerance for, playing the career ‘game,’ but I’ve never seen anyone who’s both happy and laser-focused on winning that game. In the end, you have far less control over what happens than you might think. Enjoy the ride, the destination is never what you think it’ll be.

Photo credit: Marcel Duchamp – Five-Way Self Portrait (1917)

In a relatively recent LinkedIn post, my friend and colleague Kirsten Lewis asked “Where are the thoughtful and creative product thinkers today?” In my view, they’re working at the intersection of insights across disciplines within innovation hubs. These teams typically include researchers who are driving strategic exploratory research and creative methods, designers who configure and iterate unique imaginings of product possibilities, engineers who detail the practicalities of those possibilities, marketers who determine how they might be positioned, data scientists on how they might scale, and so on. Ideally, this collaboration also takes into account the web of interactions within the systems where product is embedded—what we might call an ecological view. It’s holistic, systemic, and contextual. 

But what about the role of research more specifically? Creative and thoughtful research should ideally contribute to the collaborative process above by going beyond understanding current user/customer needs and stepping back to reflect on how historical and current contexts shape the range of product possibilities into the future—what I would call an evolutionary view. While both an ecological and evolutionary view are critical for informing product innovation, the latter is where I’d like to focus in this post, because it provides the foundation for both thoughtful and creative research as well as the opportunity for anthropological insight to inform the opportunity discovery process. 

Enter Pathfinding

Pathfinding research is a practice that identifies emerging needs and works backwards to develop products that fit, or can adapt toward, those needs. The pathfinding process typically begins with a mix of foundational, foresight, exploratory, secondary, and strategic research. Methods often include scanning for signals of change by investigating new products with growing appeal, immersion within influential niche communities, working closely with subject matter experts, listening critically to visionaries, conducting deep dives into marketplace shifts, targeted research with key segments, and other approaches. Depending on the project and the research approach, pathfinders will use an array of these and other methods. But, regardless of methodological mix, pathfinding typically requires synthesizing disparate data streams, keen pattern identification, cross-pollinating insights between different domains, and systems thinking. While many of these skills are well aligned with the strategic value of ethnographic praxis I highlight in Ethnographic Thinking, pathfinding doesn’t necessarily require enlisting social science directly. However, in this post I’d like to advocate strongly for a form of pathfinding that draws more explicitly from anthropology.

Evolutionary Pathfinding

Perhaps the most common assumption about pathfinding is that it’s about predicting the future. It’s not. And it’s especially untrue for what I’ve come to refer to as evolutionary pathfinding. Instead of chasing trends, evolutionary pathfinding focuses on understanding what’s changing through the lens of human inertia. The goal is to think beyond the current moment and aim toward lasting value and long term market advantage by building meaningful, compelling, and enduring products. This is done by identifying opportunity spaces within a trajectory of shifts from the past, to the present, and on to patterns we see among emerging signals on the horizon. Let’s look more closely at how this is accomplished and the ways that anthropology can inform it.

First, within evolutionary pathfinding, patterns of emerging signals are only considered significant indicators when they can be substantiated by cultural and/or behavioral drivers that have been proven to have clear lasting cultural impact. Pointing toward a handful of signals that happen to align with an organization’s strategic priorities (or stakeholder personal preferences) won’t cut it. In order to defend an opportunity area worthy of investment, strong substantiation of patterns of signals is critical; and it needs to come from broader social and cultural contexts.

For example, in one recent project I led, we were seeing increasing numbers of young people gravitate toward non-traditional skill-building—and away from traditional education programs. While not a majority, we knew that these were significant signals of change because our research into the broader cultural contexts of this market revealed a long history of under-funded and out-of-touch educational institutions and curricula. The pattern we identified was substantiated by these drivers that occurred (and were occurring) over the course of time in this market.

Second, patterns of emerging signals (and the drivers that catalyze them), should collectively demonstrate some alignment with at least one core human universal need that transcends things like historical or cultural specificity—things like creativity, connection, or protection. This provides some indication that they have lasting value. For example, in another project, when we started to see increased interest in crypto and fintech innovation (pattern of signals) within a market that showed clear historical and ongoing mistrust toward financial institutions (drivers), we were eventually able to situate an opportunity for new products anchored within a deeper need for fair exchange, subsistence, and asset protection.

It’s important to note that the approach to pathfinding I’m outlining here views politically-laden advocacy and utopian visions of ‘the future’ with a high degree of suspicion, since they’re largely modes of thinking intentionally designed to enact influence on shifts in cultural or behavioral phenomena over time. Their intention is to re-shape trajectories, rather than observe how they’re evolving organically. In this sense, evolutionary pathfinding is more about what doesn’t change than trying to predict what will change. 

With this foundation, we can begin to entertain more specific questions about the cadence of evolutionary change and how it influences areas of opportunity. Here, we can borrow from the concept of punctuated equilibrium to help us understand the difference between shifts that reflect incremental change, and those that are a response to high-impact social disruption. 

So, in addition to understanding cultural and/or behavioral shifts and their relevance, we should also be investigating critical cultural moments that have highly symbolic or material influence with the potential to trigger a cascade of rapid and broad-sweeping change. Recent examples of such ‘tremors’ include the spread of COVID-19 or George Floyd’s death, and the social impact of both (feelings of isolation and subsequent impact on mental health, rise of social justice movements and increasing political polarization, etc.). These are the punctuations in our social world that shake up the more common and incremental states of equilibrium. They don’t necessarily need to be the focus of pathfinding, but we should be sure to integrate their power to accelerate social or behavioral change, and in what ways.

Some Final Thoughts

When an org starts to prioritize thinking about where to invest next, it’s easy to get lost in trends or run toward the sexiest shiniest new thing. However, strategically selecting opportunity areas shouldn’t occur outside the cultural, historical, and evolutionary contexts that shape them—paired with deep thought about how they do (or don’t) align with an org’s range of current and potential capabilities. 

What evolutional pathfinding does particularly well in this context is remind us of three important things that can help orgs prioritize where to place future bets: 

  • Humans evolve slowly, but adapt rapidly to local conditions. 
  • Our behavior is rooted in evolutionary fitness, which favors collective survival (even if some traits may not be currently relevant). 
  • Accelerations in technology do not accelerate human evolution.

In short, an evolutionary approach to pathfinding helps us understand the collective pathways of our species to see how they condition future possibilities for tapping lasting human needs and values.

We were all obsessed. I know I was. My friends and I steeped ourselves in a steady media diet of alien abductions, Bigfoot and Nessi sightings, haunted houses, extra sensory perception, ‘The Bermuda Triangle,’ and a half-dozen other supernatural phenomena. None of it was particularly hard to find in the late 70’s—they popped up in everything from grocery store magazines, questionable library ‘books,’ and TV specials. Our fervor hit new heights with the release of the film Close Encounters of the Third Kind (I remember repeated viewings, and deep identification with Richard Dryfus’ character). Ripley’s Believe it or Not was our Mecca.

Most of us were old enough to know that these phenomena were at least partly fictional, but there seemed to be something within each of us that compelled us to return to these stories over and over again. In fact, we internalized them to the point where we longed for a day when we might spot a UFO on a clear night, or catch a glimpse of Bigfoot through the brush while camping. Sometimes we’d even conjure up our own evidence, like the time when we dug a hole in the yard and found a piece of plastic sheeting that we were absolutely certain must have come from a spaceship crash. What added even more allure to these tales was the notion that big government, the military, a secret society, or some other nebulous forces were engaged in conspiracies to keep us from learning ‘the truth.’

Later, after we’d all gone our separate ways, our generation’s appetite for the supernatural was satiated with productions like Unsolved Mysteries. In grad school, we took turns hosting X-Files watch parties, soaking in every moment with friends who had remarkably similar childhood preoccupations, even though we grew up in entirely different parts of the United States.

The Truth is Out There. — Agent Mulder

There are many factors that probably contributed to our shared obsession, some of which had something to do with the profit margins of the entertainment industry. After all, these narratives were the perfect mix of true stories, tall tales around the campfire, mystery, investigative journalism, and other-worldly fantasy. They opened up the imagination in ways that were connected just enough to grounded reality. They also played with the rules of nature, and toyed with logic by alternately fore-fronting and obfuscating those rules.

As consumers of these stories, we were given permission to both believe and not believe (sometimes simultaneously); and, it didn’t matter much where we landed. In fact, you could argue that this slippage between faith and skepticism was at the heart of their appeal. What seemed to matter most in these stories was the thrill of believing—an emotionally charged whirlwind of exploring partially veiled phenomena paired with the freedom of never quite knowing whether we were dealing entirely with facts.

What seemed to matter most in these stories was the thrill of believing—an emotionally charged whirlwind of exploring partially veiled phenomena paired with the freedom of never quite knowing whether we were dealing entirely with facts.


I’ve been a student of narrative and its relationship to human behavior for a very long time. Stories with ‘slippages’ between daily life and shared imaginaries are actually far more common than many people assume.

My doctoral dissertation focused on radical environmentalists at the turn of the 21st century and the ways in which they adopted (and co-opted) anthropological narratives to construct their belief systems. Some of these beliefs were inspired by the work of Marshal Sahlins, but they also included primitivist fantasies that idealized an imagined purity and egalitarianism of cultures from the Pleistocene era.

This blend of fact, fiction, and trans-historical, decontextualized cross-cultural comparisons—paired with their cell-based, leaderless structure—created a Petri dish for the rapid circulation of narratives that served as the ideological underpinning of direct action (most often property destruction). The point here is not that the beliefs of these activists were accurate or inaccurate, but that this form of narrative generation, distribution, and co-modification is so compelling that substantiating their perspective was largely irrelevant to them. Like the supernatural stories from my childhood, the whole experience of being caught up in a blurring between the real and the imaginary has an allure that outstrips logic, and is an incredibly powerful motivator to actualize beliefs.

This is a dynamic Wolfgang Iser so astutely identifies as ‘fictionalizing’ in his work The Fictive and The Imaginary:

“Just as the fictionalizing act outstrips the determinacy of the real, so it provides the imaginary with the determinacy that it would not otherwise possess…We can now see two distinct processes, which are set in motion by the act of fictionalizing. Reproduced reality is made to point to a ‘reality’ beyond itself, while the imaginary is lured into form. In each case there is a crossing of boundaries: the determinacy of reality is exceeded at the same time that the diffuseness of the imaginary is controlled and called into form.”

If this all sounds a bit heady, ask yourself where religion would be without this form of fictionalization. Religion (or even spirituality in general) engages the imagination in ways that reference both historical accounts and imagined new worlds. It’s also an incredibly powerful motivator; to the point where it can influence everything from the clothing we wear, to the buildings we live in, to the food we eat. Unprovable religious beliefs have also been so closely held historically that they’ve been the cause of countless (and sometimes deadly) conflicts.

Some argue that the role of fictionalizing (be it spiritual, supernatural, or otherwise) is hard wired into humans as a species. They would say that we’re all compelled in some way to consume and share narratives that necessarily don’t prioritize adherence to facts and physics.

Why do people believe and do weird things? Because, in the end, feeling alive is more important than telling the truth. We have evolved as living creatures to express ourselves, to be creative, to tell stories. We are instruments for feeling, faith, energy, emotion, significance, belief, but not really truth. — Louis Theroux


If you’ve made it this far, you’re probably wondering where I’m going with all this. Or maybe you’ve seen the connections I’m drawing between our common human propensity to fictionalize (and act upon the fictions we create) and our presently polarized political climate.

In the US at least, both extremes of the the political spectrum seem to think the other is delusional. What’s more, both extremes seem to be investing a great deal of energy into disproving (or dismissing) the views of the other. From “conspiracy theories” to “fake news,” dismantling the ‘fictions’ of the Other has become a core part of our (shameful) political discourse. If you think the answer to all this conflict is as simple as proving the opposing side wrong, think again.

Attempts to ‘debunk’ beliefs rooted in unsubstantiated narratives are easy to find, regardless of political position. But in many cases, these efforts often do very little to change opinions (see also this, this, and this). In fact, I would argue that most debunking projects end up being tautological exercises that simply reinforce the ‘rightness’ of the debunker, whose audience is most often people who already agree with their position. But with a broader lens it’s clear that in most cases both the debunker, and the ideologue they hope to disprove, claim that “the evidence is all around us,” and that there is, in fact, no debate to be had.

Resistance to debunking is complicated further by an array of cognitive biases, including confirmation bias and familiarity bias, among others. In addition, many people’s identities are entangled with deeply engrained belief systems, which, when working together, skew much more toward emotion than empirical evaluation. As Jonathan Rauch puts it, “believing is belonging.” He argues, “Reason can overrule our biases, but usually not when our personal prestige or group identity is at stake.” Compounding this further, numerous studies have found that falsehoods travel far faster, further, broader, and deeper than factual information, triggering outrage—especially when they are disseminated within like-minded groups.

We’re playing the wrong game if we focus on debunking, since it has, and always will, largely fall on deaf ears.


What I’d like to ask is this: What options do we have when, regardless of empirical evidence, these types of beliefs are often unlikely to shift in meaningful ways? And, more importantly, where could we be spending our energy most effectively in an effort to de-escalate conflict and de-polarize our discourse?

It may be helpful to return to the story I shared above and our childhood fascination with the supernatural. If our parents and other adult guides had spent the considerable energy it would have taken to try to convince us that our loosely-constructed ‘beliefs’ were false, would it have kept us from looking up into the night sky and hoping to see a UFO? No. And, if they’d forbidden us to watch those shows about UFO’s, or read the magazines about Bigfoot, would that have kept us from seeking out this material on our own? Certainly not. The fictive draw was simply too compelling.

Clearly there’s a difference between our currently polarized political landscape and childhood interest in supernatural fantasies, but what should we do when compelling fictions slip into the realm of politics or policy? How should we, as ‘parents’ in a room of shouting ‘children,’ respond?

  • Be wary of utopian tendencies

When narrative constructions displace opportunities to consider empirical evidence within discourse (either by flooding a platform with their messaging, shouting down others, or ‘canceling’ them, etc.), the range of irrational possibilities broadens, inviting those who wish to drive narratives toward their imagined possible futures (on either side) to more easily influence others. This opens the door for utopian ideologies to slide in undetected, as they inherently blend reality and fiction, leaning more heavily on swaying people’s emotions than their minds.

You could make a case that the United States is fertile ground for this phenomenon, given that utopian sentiment is deeply rooted in our country’s history and shared cultural imagination. From fleeing the old world and inventing a radically new form of governance, to becoming the global destination to reinvent yourself, start fresh, or build an empire, the U.S. is a particularly compelling magnet for utopian thinking (good, bad, and otherwise).

Having spent many years understanding and interpreting utopian movements, I’ve witnessed first hand how easy it can be for people to get swept up in the appeal of their narratives. But their fictionalizing ‘magic’ has tendencies to leak beyond spirit-filled inspiration to influence the realms of governance and policy. This is dangerous. The good news is that this slipperiness can be easy to spot. Most utopian movements that begin to morph from inspiring narrative into bully pulpit aren’t very successful at masking the fact that their decrees tend to become very ‘blurry’ once people begin to ask specific questions about the power dynamics they inevitably impose. They defend their positions by pointing back to their own (often loosely constructed) positions, by citing slogans or enlisting fictionalizations to abstract the issue and reinforce emotional connections to their ideology. Anyone astute enough to track an argument can spot this, from whatever end of the political spectrum it arises.

  • Situate your emotions (and your response)

I certainly don’t want to imply that all fictionalizing acts are harmful. Narrative building (and listening) is core part of who we are, and how we learn, as humans. I would say, however, that due to the challenges described above, it’s increasingly up to each of us to determine whether the narratives we’re experiencing are merely a form of entertainment (where we intentionally want our emotions to be engaged), or whether they’re overstepping their influence in critical ways.

When you’re faced with acts of fictionalization being peddled as mandates or facts (be they utopian or otherwise), ask yourself if your emotions are being triggered, or if the emotions of others are; and whether or not this appears to be the primary objective of the messenger. Truth-seeking, and fair and balanced arguments, are inherently deliberate, evaluative, and comparative. They don’t take short-cuts through the field of emotions.

I’ve found that a good response to irrational (and irrationally imposed) views is to slow down the pace of messaging and communication, gently disrupt the flow of the narrative, and, if possible, introduce interactions that open the process to include multiple checkpoints and diverse viewpoints. This deflects emotional and instinctual reactions by introducing processes that favor considered reason. If none of these are possible, speak up without reinforcing the position of an irrational ideologue, and move on. Engaging emotionally with them will go nowhere.

  • Prioritize humility, generosity, and our common human values

Begin with the premise that we aren’t all going to agree all the time, and that’s OK. Then, find a way to highlight the fact that we all have some core common needs, traits, and values as humans who are SO briefly sharing our time on this planet. We may find different paths to get there, but we all value love, security, accomplishment, freedom, honesty, creativity, pleasure, etc. in one form or another. Whenever possible, return to these universals, and make them the focus. This should help keep destructive and vengeful tendencies at bay long enough to set a baseline for constructive interactions, even if it means identifying ‘no-go’ zones.


Some final thoughts

I certainly don’t claim to have all the answers here, let alone a solution to our polarized climate. However, reflections on the role of narrative, the irresistible draw of the fictive and the imaginary, and strategies for understanding the seductive pull of both, seemed like a gap within the current discourse on this topic. There are some great writers linked above in this entry. I hope you’ll take the time to dig in and reflect on their contributions as well.

The trailer appeared one day on the lawn between the fifth and sixth grade wings. It was completely white and unmarked on the outside, with a small wooden staircase leading to the front door. No one really seemed to take much notice of it as we lined up to go to lunch or passed by on the way to P.E., but eventually a small group of us got to know it very well.

When you walked in, you entered what our adult leaders called the “gathering room“—a lounge-y space, loosely patterned after the ubiquitous conversation pits of the 1970’s, replete with burnt orange throw pillows, U-shaped built-in bench seating, and shag carpeting. This is where most of our brainstorms were held. Past this room, and down a hallway, were work rooms, each set up for a different function. One room was a sound editing ‘suite’ with tape recorders and log sheets; another had rolls of paper with art supplies and easels; another was a listening room with a record player and albums that I think were mostly recordings of classical music and spoken word, some books, and a couple of bean bag chairs.

On the first day, I remember feeling especially relieved when I saw my friend Preston there, the only other kid I knew. Most of us were from different classes or grades, and it quickly became obvious that we were a really diverse mix. Among us were kids who excelled selectively (today they might be thought of as ‘on the spectrum’), kids with learning disabilities, kids with outstanding creative skills (music, dance, art), and the academically ‘gifted’—basically a collection of anyone who stood out in one way or another. We were never told anything about how we were selected, however. I only clued in once I started thinking about why both Preston and I were there. He wasn’t particularly scholastic, but was certainly very creative. In our school talent show, he bravely performed a solo dance routine from All That Jazz, and he once invited me to play a dragon (no lines) in a play in which he starred as a knight (most of the lines).

We were all pulled out of our regular classes twice a week to gather at the trailer. Once there, we were put into small working teams and given very loosely defined assignments. These usually emerged from discussions with our teachers – two very groovy women, one of whom I remember regularly sported knit vests – and often concluded with a loose ‘brief’ that was something like “Why don’t you and Katura try and make a radio program about this topic?” From what I remember, it didn’t even seem to matter what the topic was. What did seem to matter was that the teams of two or three were always selected by our teachers, and they were always different.

On a typical day, you’d find groups of us pursuing missions we created to achieve whatever goal we decided was important. We struck out in little pods of continuous motion, darting from one room to another, heading out of the trailer to collect necessary items, staging a photo shoot, recording and documenting, drawing up plans, and occasionally consulting with our teachers because we urgently ‘needed’ something to complete our assignment. We were never stopped in the hallways by other teachers or adults as we scampered about the campus. In fact, I remember the feeling of being almost invisible.

Tempers sometimes flared within the teams, and it wasn’t unusual to hear occasional shouting matches erupt. But for the most part it was more bee hive than dog fight. Actually, a circus is probably the best metaphor. Either way, it was intense; which is appropriate, because the program itself was called (no kidding) High Intensity. Maybe elementary school education in 1970’s Florida was some sort of experimental hotbed, I don’t know. I don’t even know how aware my parents were of the program, other than they probably signed a permission slip at some point.

In any case, this combination of assignments and mix of kids made for some really colorful interactions and project outcomes that ranged from the delightful to outright puzzling. Every few weeks, we were all brought together in the gathering room and some teams were asked to share their projects with everyone. Usually, the teachers would begin by asking questions about the details of our project, and then transition to questions about how we accomplished what we did (even if the outcome was unfinished or wasn’t much of an accomplishment at all). I remember playing part of the radio show Katura and I produced using a cassette recorder to interview kids in the school about lunch menus. Other groups showed drawings, or photos, or danced, or sang a song they made up. Many projects made no sense at all, or seemed like only part of an idea.

At the end of these share-outs, our teachers would often lead us through brainstorm sessions, and give us challenges to solve. The only one I remember was something like “What invention would make life better in the home?” There were lots of ideas, most of them silly (which seemed like the goal for some); but, I distinctly recall my friend Preston saying that we should invent stronger toilet paper—which really threw me. When the teacher probed “why?,” he said that his mother often used toilet paper to quickly wipe things down in the bathroom, and that he noticed that it always fell apart. I remember thinking to myself “What a dumb idea. Why doesn’t she just use a sponge?” But the teachers ran with it. They probed the rest of the group with “How would we go about making a stronger toilet paper? How would we test it? What else could we use this product for?” My skepticism dissolved, as I was swept up into thinking about processes, features, uses, and tradeoffs; instead of judging my friend and his idea.

I won’t say that this moment changed my life, but it has stuck with me all these years. I don’t know where Preston is today, but I do know that his “dumb idea” still stands as reminder for me.


Collaboration, innovation, and culture

In a survey of over 1700 CEO’s, three out of four identified collaboration as the most important trait they are seeking in employees. That’s because collaboration introduces divergent forms of thinking and speeds up “chains” of connected ideas that trigger and accelerate creative new approaches to challenges. Both are critical for companies that need to innovate.

Most experts agree that “building a culture of collaboration” is the key to making this happen. More specifically, Evan Rosen, the author of The Culture of Collaboration, argues that providing collaborative tools alone aren’t sufficient. Instead, organizations need to dismantle traditional formal hierarchies, reduce formality, shift reward structures toward cooperative work models, and adopt more spontaneous work styles.

If your organization’s culture is command and control, the culture must shift to let collaboration happen. The expectation that team members must go through channels or move requests for decisions “up the flagpole” runs contrary to collaboration. Introducing collaborative tools into this type of culture sends mixed messages and breeds confusion. Therefore, senior leaders must first focus on reducing formality throughout the organization, because formality poisons collaboration and diminishes value…The most effective culture shift happens when senior leaders set the stage, so that people at all levels, functions, business units, and regions want to collaborate rather than internally compete. Part of the equation is changing the recognition and reward system to compensate people for collaborative rather than internally competitive behavior.

—Evan Rosen

Collaboration and Ethnography

While the conditions these experts recommend are clearly conducive to collaboration and innovation, I’m not sure they actually constitute creating a culture of collaboration. In the anthropological sense, cultures form from the shared values, priorities, behaviors, and norms that arise from patterns of interactions over time. Cultures aren’t manufactured, and people don’t typically need to be incentivized to participate in their practices.

However, even if we can’t create culture, we can navigate it. This is very different from adapting institutional structures for collaboration, advocated above. The actual practices of collaboration occur between people, and are incentivized by a very wide range of motivations, both intrinsic and extrinsic. That set of motivations may be so complex that some forms of collaboration may even be more likely to arise despite the lack of tools or structure designed to encourage collaboration. In any case, the point is this: navigating cultures is critical for fully understanding the everyday motivations and interactions that drive practices of collaboration. This understanding provides the insight into a culture that’s necessary to respond in-the-moment to support ongoing collaborative behaviors—an inherently ethnographic undertaking.

If we take a deeper dive into how ethnographers work, we can see that collaboration is actually critical to what they do on at least two levels. First, at the macro level, an understanding of the dynamics of collaboration within a culture is a critical part of how ethnographers discover how cultures develop shared meaning. It’s the analytical and interpretive space in which ethnographers identify the forms of cooperation, alliances (both obvious and uncanny), and inventive workarounds that tell the stories of how cultures develop their own unique ways to come together and form collective values, behaviors, priorities, norms and beliefs.

At a more granular level, ethnographic field research requires ethnographers to collaborate with the people who are the subjects of their work (many of whom may have very different views of the world than the ethnographer). Empathy, curiosity, flexibility, deep listening, deferring judgement, and holistic thinking, are among the core skills they use to build rapport with research participants. That rapport is essential for developing the mutual trust necessary for engaging in the intimate set of interactions needed to understand people in the context of their culture.

Given the deep familiarity ethnographers have with collaboration (both in terms of navigating field research and understanding how people come together to form cultures), they are highly qualified leaders for collaborative work. If they’re doing their jobs well, they have a deep understanding of the customer/constituent AND team dynamics AND company/organizational culture. In fact, they should always-already be collecting and analyzing the data on all these fronts (whether formally or informally) to optimize for collaboration and alignment.

How does this look? By facilitating collaborative practices on the granular level (field and team), and pairing that with an understanding the broader cooperative dynamics within cultures (company/org/nation, etc.), ethnographers are in a unique position to 1) identify synergies and tensions between these layers 2) inform effective organizational strategies to adapt accordingly, 3) ensure that teams benefit from the efficiencies of collaboration and are aiming toward productive alignments across these layers. This dynamic approach requires in-the-moment, ongoing reflection and adaptation (hence the term navigation) that I argue is far more effective than many of the remnants of assembly-line work streams we still see operating today; and organizations should be enlisting ethnographers (and their brethren) to orchestrate it more often.

Where to start?

Any experienced ethnographer will tell you that successful collaboration doesn’t mean that everyone is equal, or has an equal say. It does mean that a group is syncing up their best skills at the right time and place in an environment that prioritizes open communication, de-prioritizes ego, and always aims for the greater good. And, it takes at least one person whose senses are finely tuned for picking up on signals from different players to help usher the process.

Before tackling the bigger challenge of understanding the cooperative dynamics of a culture (organizational, national, etc.) and a group’s position within it, it’s likely easier to begin with a tighter scope. Many of the principles ethnographers use to respectfully build rapport in the field can be used to optimize for collaboration within teams. I’ve added some pointers I’ve found effective below. You may even find some techniques below that echo my teachers’ guidance from High Intensity!

  • Set expectations early: When ethnographers introduce themselves to their research participants, they often need to explain the nature of their work, which is often unfamiliar and unusual for most people. This includes letting participants know that this type of research differs from surveys or focus groups, and that their own behaviors and practices will shape the interactions and outcomes of the research. In this same way, team leads should let teams know at the outset that this will be a different working model—one that privileges collaboration and distributes responsibility. They should clearly convey the values and ways of working that will be prioritized, including roles, expectations, deliverable development, tools, and interactions.
  • Keep the lines of communication open: Ethnographers depend on the generosity of their participants, and have to establish trust with them to gain access to their perspectives. That means prioritizing open communication devoid of power games. Likewise, encouraging collaboration within a team requires that everyone recognize that information hoarding isn’t useful for the team; exposure to more ideas, and helping make critical connections between them, is. More communication is better; transparent and authentic communication is best.
  • Cross-pollinate often: Ethnographers are always looking for the unseen and unspoken connections that help them construct an interpretation of a culture. These often include things like workarounds, behavioral patterns, and distinct outliers. Transferring these skills to a team involves keeping an eye out for modes of thinking that are headed down well-trodden paths, and encouraging the integration of other perspectives. Help the team pause and reflect; and find ways to help them ask the questions that are sitting in the back of their heads but haven’t come out yet. Curiosity above all, especially when it comes to familiar processes and practices.
  • Build on trust: Deferring judgement is critical for ethnographers to understand even the most controversial feelings that most participants would never share with others who live in their culture. This requires deep listening, careful timing, and sincere interest. Similarly, in a team you’ll want to lay the groundwork so that everyone can feel comfortable expressing themselves. Anyone should be able, at any time, to respectfully ask ‘why’ and get an honest response.
  • Work it out and move on: Conflict is part of learning about cultures; and ethnographers will also find themselves in conflict with their participants from time to time. However, the most important thing for them is to learn from those conflicts and to use them as a means for forming deeper and more nuanced interpretations. Within a team, you’ll want to find ways to work through differences in ways that expand, rather than narrow, the collective understanding. Model language that conveys respect and works toward finding common ground. Ask: What hybrids might work? What analogous models might help shift the team’s thinking and reveal new opportunities? Wrap up by asking “Have we fully considered the most important factors that will help us build toward our collective goal?”

Resources

If you’d like to explore this topic more, I’ve gathered a few resources below:

I receive a lot of queries about my journey to and through anthropology, innovation, and industry; as well as requests for advice from people just getting started. I wish I had time to answer them all, but in lieu of that, I’ve decided to offer this post. I hope it’s both useful and engaging!

A circle of plastic chairs around a fiberglass table with an umbrella stuck in the middle—that was my ‘office’ for about three years. It was a very comfortable place for me; the smell of chlorine, the sound of flip flops scuffling along the pool deck, lawn sprinklers schtick-schtick-schticking in the distance. I started swimming in the first grade, and later worked as a lifeguard over summer vacations. I served as captain of my high school swim team, and continued lifeguarding as an undergraduate. I was wet—a lot.

I could usually be found at my ‘office’ between swim training sessions, entering notes into a PDA I used to keep track of client progress. On a typical day, one or two members would join me for a chat in the shade. Many of them were in the entertainment business— studio execs, actors, writers, choreographers, etc. Most had ‘hopped’ over the LA river from the row of studios where they worked in Burbank.

The people I worked with ranged from ambitious athletes looking to improve their stroke, to busy professionals who wanted to optimize the time they spent on cardio. They also included folks like the high-spirited writer looking for the next new experience, the studio exec who just needed a break in her day, and the furniture store owner with fierce dedication and sporadic progress. And then there was the Russian, who only wanted to learn how to swim as far as possible underwater. (I still think he was a spy, or maybe a method actor preparing for the role of a spy. In LA you never know.)

Anyway, this was my life during the last few years of grad school at USC. I had a dissertation writing fellowship, so my time was spent writing and swim training, swim training and writing—plus a lot of time driving back and forth along Hollywood Way between home and the pool. I loved it. My approach to training centered around helping clients build confidence and rethink their body’s relationship with the water. Much of the technique I used was derived from the total immersion method; but I quickly learned that the real key to helping people improve wasn’t teaching the mechanics of swimming. It was to understand my clients holistically, and to adapt the pace, cadence, and style of training to their individual frames of reference. The process was surprisingly ethnographic in a lot of ways, and involved getting to know clients well enough to understand their contexts, motivations, personal logics, fears, and thresholds.

Over time, many of them shared deeply personal thoughts with me as part of this process, especially when they lost concentration, or forgot something we’d covered in a previous session. They’d hang their arms over the edge of the pool, out of breath and defeated, searching for a way to rationalize their performance in their mind, “I’m just out of it today. I wish I knew how to deal with…” Of course, I wasn’t there to help solve their problems; but, I did listen.

One client liked to talk through the differences between a novel and a screenplay in an attempt to delay his first plunge into the pool. Another would run through the intricacies of business deals. But, many exchanges ran much deeper. Out of the blue, a client came out to me one day, and another broke down crying during a warm-up stretch. Eventually I realized that there was a very deep connection between helping people grow more confident with their bodies in the water and the personal transitions they were experiencing in other parts of their lives. It was truly inspirational to witness the changes they were experiencing.

I eventually finished my dissertation and graduated with a doctorate in Social Anthropology. I had no prospects for directly applying my ten years of graduate training (which encompassed both an MA and PhD), and had pretty much resigned myself to becoming some sort of ‘aquatic anthropologist.’ I was, after all, using many of the skills I’d developed in my training: facilitating conversations, listening deeply, building rapport, identifying patterns, developing interpretations, etc.

One day, a friend contacted me about an opening as adjunct professor at CalArts in their critical studies department. Within a month I was designing and teaching their visual anthropology and ethnographic methods courses. The students were great: all artists who were taking my courses because they were actually interested in anthropology (or in some cases how they might use ethnographic methods in their artwork). The bonus was that CalArts doesn’t assign grades, so I never found myself haggling over how many points someone should have received to ‘get an A.’ I even had a teaching assistant.

However, the pay was low, and it was clear that there were no real growth opportunities there. In fact, I continued to make more money swim training; but, for the time being, it seemed like the ‘logical’ thing to do with my degree. My mind began to wander, though, and I would often daydream about building a lap pool in my backyard and running training sessions from home.

About a year later, I ran across an online listing for a Research Scientist at Intel near Portland Oregon that caught my eye. I’d never seen a job description like it. They were looking for social scientists, and especially anthropologists, to develop a deep understanding of the role of technology in cultures across the world. My first reaction when I saw this was “Why has no one ever told me about using my training this way?” And then, “Why was the unstated assumption that the ultimate use of a doctorate in anthropology should be teaching at a university?”

I had some thinking to do. I’d always been drawn to anthropology precisely because of the way it requires a grounding in lived experiences, the way it necessarily privileges cultural relevance and context. This position seemed like a great way to engage that inspiration directly. But, was this worth leaving Los Angeles and my life as a swim trainer? I was certainly fulfilled, and felt a great deal of satisfaction from helping people build their confidence—both in the water and out.

Eventually, my curiosity got the best of me. I applied, was offered the position by Genevieve Bell to join her Digital Home Group, and decided to jump into an entirely new role and life. I remember saying goodbye to my clients, some of whom I’d known for years. A few of them treated me to lunch, and gave me some parting gifts. I still cherish one in particular: a DVD of Wes Anderson’s Life Aquatic.


I had no knowledge of chip architecture, use cases, or even customer segmentation when I walked into my job talk at Intel. I just focused on what I knew and what inspired me. The talk was titled “Narratives, Networks, and Cultural Landscapes”—themes that spanned across my work with Radical Faeries, the Earth Liberation Front, and the people of Jalcomulco. Those themes drove much of my work at Intel, and still do today. I learned the rest on the job.

So, when people ask me how they can transition from academia to industry, I’m often caught a bit off guard. I never considered my decision to join Intel a departure from my approach to life as an anthropologist. As I argue in Ethnographic Thinking, I believe that training in anthropology distinctly (and permanently) changes how you approach the world and your role in it. From the swimming pool to the strategic plan, thinking like an anthropologist has become inescapable for me.

That said, there are some adjustments from academia to industry I experienced that may be useful to readers of this post. For better or worse, a large portion of doctorate training in anthropology is a solitary venture. After coursework in ethnographic methods and a deep dive into the literature of the discipline, you usually define your dissertation research topic, focus on a geographic region, select a field site, and establish the theoretical grounding that will inform your work. Only then do you set out for the field, nearly always alone. While there, most budding anthropologists earnestly collect copious amounts of data (likely too much), return from the field to analyze it, alone, and begin writing their dissertation, again alone.

My experience in industry has been quite the opposite. Collaborating with peers and within interdisciplinary teams is critical to success in industry-based research roles. There’s a reason for that. As cognitive psychologist Robert Weisberg argues, collaboration introduces divergent forms of thinking within groups and speeds up “chains” of connected ideas that trigger and accelerate creative new approaches to challenges. Other dynamics that come from effective collaboration include things like building and maintaining project momentum, increased flexibility, and accelerated problem solving. With collaboration tied so closely to innovation and effective team performance, there’s little room for the maverick.

Fortunately, many of the skills ethnographers acquire in their training are actually quite useful for collaboration and supporting healthy team dynamics. In order to build rapport with participants, most ethnographers have honed skills in empathy, facilitation, and deferring judgement. All of these can be applied directly to the relationships they have with fellow team members. Time in the field also teaches ethnographers to expect the unexpected and to adapt accordingly. Flexibility in industry settings is an incredibly valuable skill, since market shifts often drive changes in strategic priorities. Fieldwork also priorities a mindset of participatory learning and the ability to function and focus in unfamiliar settings. These are incredibly valuable skills for helping teams think outside of their internal practices and priorities, and to integrate analogous models into their work. Finally, a healthy dose of reflexivity combined within a holistic understanding of the relationship between researcher and participant helps keep ethnographers working in industry focused on how they’re embedded within cultural systems they investigate, and not just as representatives of an organization or client. This kind of perspective shifting is critical to building a broader cultural understanding of an organization’s offerings.

Another important adjustment from the academy to industry is the difference in time frames. In general, the academy tends to think of research in much longer terms. This is understandable, given that research in academia often runs parallel to teaching and publishing responsibilities, most of which are the solo responsibility of the researcher. However, in industry, insights from research tend to have a much shorter shelf life. Pair that with the fact that research questions are often addressed by teams in industry settings, resources tend to be more readily available, and shifting strategic priorities change based on economic contexts, and the result is that you can easily find project durations in industry settings that span from half to a quarter (or less) of those in most academic settings.

However, this doesn’t mean that research in industry settings is necessarily less rigorous. What it does mean is that researchers need to be better prepared to think collaboratively, to delegate, to coordinate, and to synthesize and interpret data that may easily shift in terms of its relevance to the organization’s needs. It also means that it becomes more important to be able to accurately and frequently scope and scale research, to ensure that it aligns with the needs of the organization (not just your interests).

This brings me to the final major shift I see between the academy and industry settings. Within the academy, research outcomes tend to focus on contributing to a body of scientific knowledge of one sort or another. This might be an area of investigation that has lasted for years, or even decades, and its form of execution often centers around models of peer review and theoretical debate that can last just as long. In most industry settings, you will find that there can be significant value placed on cumulative knowledge-building and even some theoretical debate; but at the end of the day, the greatest value is from the impact research outcomes have for the organization under current (and near term) market conditions. In short, your insights need to be relevant to a much broader range of stakeholders than other researchers.

There are certainly more considerations to take into account when transitioning from the academy to industry, but careful attention to these should help any anthropologist or other qualitative researcher think about the primary adjustments they’d need to make.


Resources

Shifting focus to industry also means tapping a different (and broader) set of resources. Some of my favorites are listed below. This list isn’t anywhere near exhaustive, so if you have any additions, please add them in the comments below, so that all readers can benefit.

Take a break and listen to my conversation with Rita Denny! We chat about how EPIC is pivoting for their conference this year in light of COVID-related restrictions, as well as changes in ethnographic praxis overall. We also touch on the early bias toward psychology in industrial research, the illusion of the sovereign and rational decision-making customer, the advantages ethnographers have as both insiders and outsiders in their organizations, and the opportunity to observe social change as it occurs in our current disruptive moment.

A special thanks to Gerry Scullion and ThisisHCD for hosting ethnopod.

Be sure to check out some of Rita’s work below, as well as a profile by Josef Wieland on the EPIC site.

Please join me as I talk with Sam Ladner about her new book, Mixed Methods. We cover some of Sam’s critical insights, including: working in cross-functional teams, the importance of artifacts, creating psychological safety, luxuriating in the customer, and data exhaust. If you’re a current or aspiring UX Researcher, this episode is for you! (Thanks to Gerry Scullion and ThisIsHCD for hosting ethnopod.) And, if you’d like to dive deeper, check out some of these reading recommendations, including two of Sam’s books!

Anthropology and computer science go back much further than many realize; and the relationship between the two continues to evolve. Join me as I talk with Genevieve about the relationship between technology and culture, cybernetics, and the story behind the formation of 3AI at Australia National University. (Thanks to Gerry Scullion and ThisIsHCD for hosting ethnopod!) And, if you’d like to dive deeper, check out some of these reading recommendations:

My colleague, Charley Scull, has been ‘unpacking’ weirdness for a while now, and reaching some intriguing insights about its anthropological usefulness. Most recently, he presented some of his thinking in this space at the EPIC 2019 conference. For those of you who missed it, he’s captured it below, just after his introduction to the work:

Charley: In this Pecha Kucha, I use an anthropological perspective to explore the theme of weirdness. The talk begins with an observation about weirdness while doing sustainable seafood fieldwork in Indonesia with the Future of Fish organization. It then goes on to explore the meaning of the term through philosophical and marketplace lenses and makes a case for weirdness’ value as a researcher superpower!