000 02368nam a22002057a 4500
003 OSt
005 20240416150151.0
008 240416b |||||||| |||| 00| 0 eng d
022 _a1369-118X
100 _aPrzhedetsky, Linda
_9831
245 _aMediating access:
_bunpacking the role of algorithms in digital tenancy application technologies
260 _bInformation, Communication and Society
_c2024
300 _a17 pages
500 _akeywords: PropTech; algorithms; automation; data; housing; tenancy
520 _aDigital tenancy application technologies (DTATs) are becoming the dominant means through which renters in the private rental sector (PRS) apply for housing. These PropTech tools, which claim to streamline application processes to save renters and lessors time and effort, necessitate the collection of data. Though the collection of certain data – such as income and rental history – has long been a standard part of rental application processes, DTATs now facilitate the collection of additional data including social media activity, behavioural data, and more. Increasingly, DTATs offer the ability to ‘make sense’ of this data, evaluating applicants through the use of algorithms. Drawing on lessons from banking and insurance sectors, this article outlines how DTAT algorithms can reshape individuals’ access to essential services delivered through competitive markets. It explains how algorithmic processes can introduce and exacerbate the unfair and unlawful treatment of renters, which can result in significant harms. To identify, redress, and prevent these harms, I argue that it is crucially important to use shared terminology to describe how DTATs are collecting and using data. This article introduces a framework for understanding how algorithms ‘screen’ and ‘sort’ applicants based on the data that is collected through DTATs. The process of ‘sorting’ is further broken down into three categories – ‘scoring’, ‘rating’, and ‘ranking’. The article concludes by explaining how this framework can assist researchers and policymakers to identify, analyse and prevent harms that are catalysed, or exacerbated by DTATs.
650 0 _aCommunications
_9519
650 0 _aPrivate Rental
_9501
856 _uhttps://doi.org/10.1080/1369118X.2024.2334904
_yView item on publishers website
942 _2ddc
_cA
999 _c869
_d869