When people today hear the word “map”, most imagine a tool that keeps them from getting lost. In your work, however, you show that maps can also determine what we see, where we go, and whom we pay attention to. Do you remember the exact moment when you first realized that a map not only describes the world, but actively shapes it as well?
It definitely wasn’t a single “aha moment,” but rather a gradual realization. I do remember one moment, though, that first motivated me to start writing my piece about Google Maps. I was looking for a restaurant that I knew was somewhere around there, but I couldn’t find it on Google Maps. I realized that most of what Google Maps shows us is shaped more by algorithms than by the physical space itself. The decision about what you see there is essentially made for you, and as a user you don’t have much influence over it. Even when it comes to navigation, you don’t actually know whether the route selected is really the fastest one, or whether it’s been optimized according to some other criteria. It’s incredibly difficult for an individual to verify this, so we generally all rely on these simplified maps. And that led me to start asking myself just how far this power of algorithms reaches and what consequences it has for the physical reality we inhabit.
So, as always: It all started with a pub.
As these things tend to go…
In your work on London restaurants, you argue that Google Maps aren’t merely a directory, but also a “market maker.” Who, in your view, is the true cartographer of the digital world? Is it programmers, platforms, users, data owners – or rather a combination of all these actors, in which it is no longer easy to determine who is responsible for the resulting picture?
I think it’s the latter. In the end, we all play a role in it. As consumers, we hand over our data, and to a large extent we want platforms to use it, because it allows them to optimize outcomes more effectively, which we then benefit from as individuals. Then there are the programmers who make the decisions – but a significant part of those decisions is actually made for them in advance as well, and they simply carry out their task, the ultimate goal of which remains the same: to maximize profit.
Data owners also make a great many micro-decisions, each of which is rational in itself, but over time and in such enormous quantities they accumulate and have major consequences for public space. Take navigation again as an example: a long series of small, rational steps within an algorithm can lead to some streets becoming much more congested than others because of the app. And this is precisely where we encounter consequences for which these “market makers” should be held accountable.
What should they primarily be held accountable for?
The first necessary step on their part has to be transparency about what goes into their decisions. That creates room not only for operator accountability, but also for collective action. This imbalance of power between the actors lies at the root of the problem, because as individuals there is very little we can do about it.
“…it’s hard to blame an individual who starts renting out their apartment on Airbnb due to the dire state of housing in cities. From their perspective, it can make sense in many ways.”
So, to sum it up: For a property owner, putting an apartment on Airbnb may be a rational decision, just as it’s natural for a visitor to a city to rely on Google Maps reviews. But when thousands of similar decisions become concentrated in a single neighborhood, they can fundamentally transform local housing, businesses, and everyday life. What do maps allow us to understand about the collective consequences of decisions that may seem harmless when considered individually?
In the case of Airbnb, it’s clear: it’s hard to blame an individual who starts renting out their apartment on Airbnb due to the dire state of housing in cities. From their perspective, it can make sense in many ways. So the first thing we need to focus on is broader housing policy; when it’s dysfunctional or completely absent, it creates the conditions in cities that make these individual steps appear rational. Airbnb itself can’t be blamed for the fact that housing in large cities is becoming unaffordable. It’s more of a consequence. The process in which more and more people want to visit and live in large cities would have happened naturally even without Airbnb. We simply need bigger political decisions. The boom in short-term rentals is a symptom of failing housing policy.
Your work often focuses on what remains outside the frame: businesses without reviews, places without data, and communities that the algorithm can’t properly classify. How can we map absence – and how do we know whether something genuinely doesn’t exist or whether we simply can’t see it?
Working with digital data offers many advantages in terms of categorization, but it also has its downsides. Many phenomena, places, and institutions, for example, don’t have websites or a sufficiently high-quality or modern digital footprint for digital mapping to capture them. Beyond the online world, there’s still a fairly vast one offline, which is difficult to grasp in any meaningful way today. That’s why I’m convinced that digital work needs to be accompanied by fieldwork. You simply have to go to the pub.
Well, that doesn’t sound so bad.
Right? There simply is no magic tool that would allow you to avoid this journey. And I don’t just mean the pub, of course. I mean going outside, being around people, in the community, and in these places.
Perhaps that could be a universal recipe in today’s world for a number of other areas that are beginning to face the consequences of rapid digitalization.
And maybe, in the end, it’s also a nicer way. Leaving your computer behind.
„The more cities across the continent are shaped by the identical logic of identical algorithms, the more similar they will become.”
The distribution of visibility is also an issue. Through your work on restaurants, Airbnb, and urban neighborhoods, you show that visibility is distributed unequally. What happens to a city and its inhabitants when visibility becomes a condition of economic – and sometimes social – survival?
Cities are becoming standardized. London, Paris, Amsterdam – increasingly large parts of European capitals are becoming indistinguishable from their counterparts in other cities. The same trends, the same spaces, the same products.
I mostly travel between Brno, Prague, Berlin, and Brussels, and I’ve been noticing this for quite some time...
More and more people are noticing it. And it’s a natural consequence of the mechanisms we’re talking about. The more cities across the continent are shaped by the identical logic of identical algorithms, the more similar they’ll become.
And where does this all end?
When all cities are completely identical and the ideal of European unification has finally been achieved, right? I’m joking, of course – that’s precisely the opposite of what people actually want. That’s why I believe we can expect a backlash at some point. We can already see signs of it today. Unique, distinctive, overlooked places are becoming increasingly trendy. Consumers’ desire to buy products directly from farmers is also motivated by a desire to bypass the influence of algorithms, whose criteria for quality or availability are actually alien to us because they follow their own economic logic.
I believe this resistance will grow, and we’ll gradually return to appreciating individual characteristics, distinctiveness, and uniqueness. I believe we’ll recall what made Europe so unique – the fact that you could travel across it and, within a geographically small space, discover completely distinctive histories, flavours, communities, traditions, and so on.
Your maps often reveal boundaries and inequalities that we’ve grown accustomed to seeing as natural. But how do you distinguish between a boundary that the data has genuinely revealed and one created by the model itself, the categories you’ve chosen, or the original question posed by the researcher?
That’s another good but also complicated question. The decision about which algorithm to use for data analysis and machine learning ultimately always has to be made by the researcher. My approach is to try to be completely transparent about that choice (which, incidentally, is the main thing we should demand from the algorithms used by these platforms). In addition, I always try to use several different variants. I try to question myself throughout the entire process. From the outset, I try to avoid intuitively prioritizing a certain structure that begins to emerge from the research. I remind myself that it can be misleading, that it may be just one of more possible paths. Every structure like this can teach us a great deal, but we mustn’t deify it. It’s still just one model among many.
Would you consider yourself more of a data analyst or a storyteller, or has it been a mixture of both from the very beginning? Are we witnessing the birth of a new scientific-journalistic field?
I would lean toward the latter. Part of our work overlaps with that of data scientists; I then add narratives to the research, and ultimately I try to tell stories that analysts don’t necessarily see within the research. I try to see farther into the distance. My work is still grounded in data, and certain “pipelines” then emerge from it. I use these to uncover contexts and inquire into what they mean. And above all, I do this within a historical and social context.
So, as a reader of your work, I’m effectively becoming a researcher myself, because you’re teaching me to understand how the data works.
Exactly. I think it’s important for people to know how machine learning can be used in practice.
“I’ve also come across research that has noticed a connection between the decline of ‘third places’ and the rise of the far right in certain areas.”
In your writing, you focus on pubs, cafés, clubs, and other “third places,” as you call them – spaces where people meet and which are neither their homes nor their workplaces. You also focus on the decline of these places. Britain has a tradition of places like these – an entire “pub culture” similar to the one in the Czech Republic, and the tradition is facing a similar problem as these places disappear. What does their disappearance or transformation tell us about the state of society, trust between people, and our ability to live alongside people we did not choose ourselves?
That’s a philosophical question. I’m convinced this is connected to the deepening divisions within society. Places for everyone are disappearing, or they’re transforming into places that are only for a particular group. I’ve also come across research that has noticed a connection between the decline of “third places” and the rise of the far right in certain areas.
So “pubs against fascism”?
Yes, that would be my slogan.
Your research into areas such as grant programs shows that inequality often stems not only from a lack of money, but also from inequalities in the ability to understand the rules, use the right language, and navigate institutions. What would a society look like if it didn’t exclusively help only those who are capable of obtaining the “right map” of the system?
The fundamental purpose of grants is to help certain beneficial institutions compete with stronger ones. My research in Florence, however, focused on another broader trend – namely that these grants were deepening inequalities and creating new ones. What would the next step be? Well, if we managed to solve this dilemma, we would essentially solve inequality itself. We might consider making certain institutions accountable for distributing grants, but for now that idea is very distant.
At this point, we need to focus on changing the grant system so that it allocates those resources better, and, to some extent, of course, also on educating recipients about how to access those resources.
And what would be the first step in doing that?
The first step is raising awareness that this problem exists at all.
Well, there you have it – exactly what the two of us are doing right now!
Pretty much.
So we’re something like pioneers of the revolution.
Exactly. We’ll take this first step, and the rest will be up to everyone else.
“My dream map would be able to zoom all the way into the essence of tiny social interactions.”
My final question will traditionally be the most philosophical one. I want to engage the imagination a bit. With every personality we bring here to the Inspiration Forum, I try to encourage them at the end of the interview to let their imagination run wild and envision a better world. Imagine you could create a map of something we can’t yet measure or precisely name. What would you want it to show us – not only to help us navigate the world better, but perhaps also to understand what kind of world is worth creating together?
I have this basic impulse of a data scientist in me. I’d like to collect as much data as is humanly possible. My dream map would be able to zoom all the way into the essence of tiny social interactions. Everything we encounter from the moment we wake up through our journey to work, everything and everyone that shapes our judgments and reactions along the way, and how all of that shapes who we really are.
That sounds great – we could finally and definitively rid ourselves of responsibility for the consequences of our actions. Or…
Or we could start building a better world without hatred.
Lauren, thank you for the interview. And if you ever need a recommendation for a good pub in Jihlava, come to us at the Inspiration Forum instead of Google Maps. We’ll have a few tips for you.
Excellent, I’ll be looking forward to it.
The interview was published in Deník N.
