Algorithms that assess the risk of citizens becoming unemployed are currently being tested in a number of Danish municipalities. But according to a new study, gaining employment is not the only relevant goal for those out of work — nor should it be for an algorithm.
Together with two colleagues from the Computer Science department at the University of Copenhagen, Professor Thomas Hildebrandt and Professor Irina Shklovski, Naja Holten Møller has explored possible alternatives to using algorithms that predict job readiness for unemployed individuals as well as the ethical aspects that may arise.
An employment framework is able to output assessments made by an algorithm that, via data on the citizen’s gender, age, residence, education, income, ethnicity, history of illness, etc., spits out an estimate of how long the person — compared to other people from similar backgrounds — is expected to remain in the system and receive benefits. The researchers aim to challenge the misconceptions related to unemployment that raise ethical concerns.
One important finding from the paper tells us that “not all struggles come from personal failings and that the structures within which we operate are often just as implicated. Caseworkers clearly recognized their own limitations and that they sometimes might act from a place of bias or carelessness in their work, but there was no clear route for an algorithmic system to mitigate these issues. Instead, caseworkers pointed to the unnecessary problems that the institution of job placement itself created.”
Holten Møller, N., Shklovski, I. and Hildebrandt, T.T., 2020, October. Shifting concepts of value: Designing algorithmic decision-support systems for public services. In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society (pp. 1-12).