Systems of categorization and classification have played important roles throughout history, from ancient religious texts organizing moral codes to modern scientific frameworks. Among these is the modern digital data system, which encompasses information from personal details and online interactions to scientific measurements and business transactions. However, concerns have been raised about what information is being tracked, the purposes behind such tracking, and who ultimately controls and has access to this data.
To unpack these questions, I spoke with Cristina Alaimo and Jannis Kallinikos, co-authors of Data Rules: Reinventing the Market Economy. Cristina is an assistant professor in digital economy and society at Luiss Guido Carli University, in Rome, Italy and Jannis is a full professor of information systems at Luiss Business School.
Below is a lightly edited and abridged transcript of our discussion. You can listen to this and other episodes of Explain to Shane on AEI.org and subscribe via your preferred listening platform. If you enjoyed this episode, leave us a review, and tell your friends and colleagues to tune in.
Shane Tews: You talk about how the role of data in society has evolved, even though it’s always existed. But in the ancient days, we used to use clay tokens, and now we’re using a modern digitalization version of that. Explain what that means.
Cristina Alaimo: We all tend to think about data and digital data as shiny new things. And very rarely do we think that they are actually part of a very long history. So in the book, we look back to learn how to see what digital data changed and what remained a continuity with this long history of data.
And we start with clay tokens, really little things made of clay that were used as tools for exchange. You would get one chip for one day of work, and they were passed from one end to the other. They were the beginning of data use to represent something very abstract, such as an exchange.
Because of those tokens, the concept of exchange became something that could be thought of, something that could be used to build institutions like the institution of taxation.
Shane Tews: So, it’s more than the creation of currency. You were actually conveying information when you handed somebody one of these clay tokens.
You’ve also written several papers on how institutions change along with the creation and use of data categories that they create. Let’s talk about that.
Jannis Kallinikos: Categories and classification systems have always been important to humans—they preceded the age of digital data. But digital data changed the way we represent and group and classify things.
We’ve analyzed this in a range of contexts, including music streaming platforms. In particular, the way streaming platforms classify artistic creations and make them available to users for consumption. Users themselves react to these classification subcategories, because they provide a tool to navigate the complexity of the things that are represented.
Cristina Alaimo: We studied one of the first music streaming platforms to understand the difference between a data-based categorization versus older forms of categorizing music such as those that come from the social practice of listening to music, or those that come from a genre like classical music, or jazz, or whatever.
So, we confront a data-driven categorization and what that means for music production and consumption. This affects music labels and distributors, but also raises questions: How do we consume music? How do we like music? How do we learn and experience music? And what was that before? Were our habits different when we didn’t have masses of data coming from behavior of users tracked in real time in real time?
Shane Tews: There are also social objectives that are created from data. How are these metrics constantly evolving with new data inputs, and in what ways do they affect people’s lives more than they might realize?
Cristina Alaimo: One sector we all deal with is the hospitality industry. Think about how traveling today is different from how it was before. There used to be expert guides writing up recommendations. These were people going around and actually visiting hotels and ranking food or even restaurant style. Certain criteria needed to be observed by these guides.
Today if we travel, we have location services activated, we can receive real-time recommendations, or see if nearby hotels or restaurants are a good fit. Within this category crunch, there is a huge number of data points like real-time availability of rooms, real-time price updates, Location Services, GPS, or, as we turn on our device or our browsing history. This is all possible because of our data.
Shane Tews: There are concerns about the government or institutions having too much data on individuals, but you suggest we need to look past that because there are so many opportunities associated with digital data generation.
Jannis Kallinikos: We recognize that this is a serious problem in our society. Surveillance exists. We can do small things like have rules about how information is being accessed, who owns it, and who uses it. But, the production of information and data on individuals will continue and expand.
The problem of surveillance in this respect is intrinsic. Because of this, we have to recognize that all types of regulation will affect how we live and how our freedoms are exercised. This is a complex game. We are not against regulation. But at the same time, we see the subtlety and complexity of these issues and we don’t want simplifications here because simplifications never work.
Cristina Alaimo: We want to exit from this deadlock mindset that there is a watcher and someone being watched, because reality is a little bit more complex. There are practices, not just regulation, that can make a difference, like data literacy or expanding the scope of discourse around data. We need to be very careful when we regulate this space, because sometimes if we simplify too much, we risk the cure being worse than the illness.
I do not want to discount concerns, but the current discourse on Big Brother is a little bit too simplified. As a society, we need to move forward with technology, not against technology.
Shane Tews: I don’t think the EU’s Digital Markets Act intended to do this, but they’ve broken down security guard rails. I’ve had this conversation with multiple people in the US government who say data concerns are the problem of the digital manufacturer when in reality, it’s the government’s job to put the rules in place. The challenge seems to lie in balancing economic benefits with creating a secure environment for data. It seems like there’s a lack of understanding these complex data economics in the regulatory space, especially in Europe.
Cristina Alaimo: When we say data is complex, we don’t want to discount the fact that it can be regulated and can be governed, but we need to do it by looking at this complexity. There’s a trade-off between shareability and safety that’s intrinsic to how you work with data. So in order to really handle regulation and governance of data property, you need to really be sure what you’re talking about.
There are a couple of points on this. The first is to look at the data not just as output or technical items, but to acknowledge that the data has a life cycle, so the data must be treated differently, depending on which stage of the life cycle you want to regulate. That’s a fundamental point: treating data as a monolith is a mistake, and it’s a costly one.
So for instance, there may need some regulation and governance when the data is produced, there may be another stage when it is aggregated and forms a more complex digital object, such as a user profile. In this case, the data gets stored, and it may need a different kind of regulation.
Jannis Kallinikos: The bottom line is the data are the outcome of people’s complex interactions with digital material. But the data very often is treated as a simple thing. The debates over regulation are predominantly legal or economic. Both fields are important, but also inadequate to deal with the social and interactive complexity of data. We have been appalled by the simplicity by which these complex things are being debated for reasons, sometimes political for others, that we don’t know.
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