The Noxious Datafication of the Housing Market

Alexandre Petticlerc, David Eliot / Jun 29, 2024

This essay is part of a symposium on the promise and perils of human rights for governing digital platforms. Read more from the series here; new posts will appear between June 18 - June 30, 2024.

Joahna Kuiper / Better Images of AI / Little data houses (square) / CC-BY 4.0

In much of Canada and the United States, the housing market has become what philosopher Debra Satz refers to as a noxious market. A market is noxious when it is morally concerning or harmful due to the types of goods or services being traded, the conditions under which trade takes place, or the consequences of such trade. In the case of housing, the noxiousness of the market is symptomatic of increased inequality in the power dynamic between tenants and landlords, difficult access to homeownership for first-buyers, high levels of homelessness, and lack of supply. In attempts to address the problems surrounding the housing market, local and national governments have proposed numerous policy solutions. However, there has been minimal attention paid to a socio-technical development that has created many of the conditions that have exacerbated the negative effects of the housing markets: datafication.

Datafication occurs when a subject is surveilled and recorded. The perceived fact that is recorded is what is referred to as data—an abstraction of the material world. Housing data is recorded information produced from the surveillance of the housing ecosystem. It is not inherently bad, as this data can be leveraged for numerous positive purposes, such as better distribution of community resources. However, in recent years, due to a general trend of increased datafication due to the internet revolution, housing data has been leveraged not to build stronger communities, but to produce economic profit. Thus, the increase in housing data has created a bifurcation of the housing market. Traditionally, from a buyer's perspective, the housing market is mainly a means to acquire shelter. We propose that increased datafication creates—and is enforcing—a shift in the market where housing is becoming increasingly noxious for those seeking lodging, as the practices of the market migrate to the financialized conception of the housing market.

To become a financial good, a subject must become calculable, meaning that it can be calculated into economic formulas. This is achieved through datafication. Research conducted in Australia by Megan Nethercote draws specific attention to the role of house appraisers in the financialization of the Australian housing market. Appraisers translate the physical structure of the home, as well as its social position (i.e neighborhood), into a calculable economic value. Notably, in recent years it has become much easier to value one's home, as data about home sales and values has become more readily available, making it possible to easily estimate any home's value using an algorithm, instead of a trained human appraiser. As noted by Don Layton, former CEO of Fannie May, the digitization and democratization of housing data —produced by increased ease of access to housing data and financing information—resulted in individual market actors being able to visualize their housing as a financial instrument. The ability to visualize one's home as a financial asset and frictionlessly obtain valuations creates the conditions for treating homes like financial objects, and makes one more conscious of rising values and financial options such as mortgaging. Treating housing as a mere commodity encourages individuals (and investors) to act in such a way as to maximize return on investment rather than focusing on the well-being of individuals living in the homes or apartments.

The financialization of housing, driven by increased information about home values, has led to the phenomenon of housing platformization. Platformization has taken place in two major ways. First is the platformization of housing itself, and second the platformization of the housing market. The platformization of housing can be observed via the rising trend of renting in the global north over traditional home ownership. The housing stock is increasingly owned by agents other than the tenants, who then become contractual clients of the owners. This effect is amplified by the previously explored ease of mortgaging homes made possible by the increasing availability of housing data. It is now common practice to leverage investment properties in order to grow one's portfolio.

The rental market for housing itself is also being platformized by services such as Airbnb. Airbnb is a strong example of how a certain use of platforms can have detrimental effects on the housing market and on relational equality. The housing market has further been platformized through the development of platforms to act as middlemen in the real estate market. Companies such as Zillow and realtors.com act as digital listing agents that connect home sellers with buyers. Through this process, these platforms can accumulate massive amounts of information, via listings posted to the platforms, not just on the market itself,, but also on other market forces that can be derived via the analysis of user behaviors and actions. This creates an unequal market, since one party has a significant advantage in terms of information.

Recently, a related phenomenon has emerged in the housing platform space called iBuying. iBuying describes companies that work as true market middlemen. These companies collect data on the housing market which they use to fuel algorithms in order to value homes and predict future values. As such, they then buy homes with the intention of flipping them for a profit. Among the leaders in this space is the American-based company Opendoor. Opendoor provides convenience to home buyers, as it offers quick and ‘painless’ cash offers for a seller's home instantly, based on the information provided by the seller. The offer amount is algorithmically determined, based on Opendoor’s predictions regarding the potential to flip the property. The model for iBuying is notably similar to the virtual stockbroker model (i.e Robinhood), which seeks to make it easier for the average person to trade financial assets in the stock market. It is a powerful representation of how increased housing data creates the environment for housing to be increasingly treated like a financial asset and thus limits the potential for individuals to interact as equals within (and around) that market.

Although governments do recognize the detrimental effects of platforms such as Airbnb, it is our position that they are not adequately addressing the underlying cause. The datafication of housing. Further, current legislative/regulatory approaches for addressing the social harms caused by datafication are not appropriate for dealing with the harms observed in the housing market like tenant rights being disregarded or, to some extent, gentrification. Specifically, the two dominant approaches for data regulation are currently algorithmic regulation, and privacy regulation. The latter, represented by legislation such as Europe's General Data Protection Regulation (GDPR) does little to address the type of housing data explored in this article, as it is focused on protecting citizens against the abuse of their personal data. This is why algorithmic legislation is vital, as it can be a potent tool for ensuring that algorithms running on housing data do not exacerbate specific social problems such as race-based discrimination in housing. However, such laws do little to address the social effects created by the intended application of the algorithms themselves. Algorithms such as those used by iBuying companies, even those attempting to act in a completely just manner, create negative effects on the market, detracting from its social purpose of providing housing.

Although we do not yet have specific solutions to offer, we draw attention to the fact that broad data protection policies are not adequate to shield citizens from the harms of datafication. The datafication of different subjects produces uniquely different results. The datafication of housing is reshaping the housing market in a way that makes it noxious for citizens searching for lodging as it intensifies housing’s treatment as a financial good. As such, we believe that data policy must also take a targeted approach, with bespoke solutions that address individual societal harms produced by the phenomenon of datafication. Along with measures to favor non-profit housing and implement stronger protection for tenants, other solutions should focus on the underlying causes of the housing crisis: concentration of wealth, rent-seeking, and, eventually, the idea of homeownership as the solution to all problems.


Alexandre Petticlerc
Alexandre Petitclerc is a PhD candidate in philosophy at Université de Montréal in Canada.
David Eliot
David Eliot is a PhD student at the University of Ottawa where he is a Graduate Student Affiliate with the Center for Law Technology and Society and a 2022 Pierre Elliott Trudeau Foundation Scholar.