Title
Responsible innovation, anticipation and responsiveness: case studies of algorithms in decision support in justice and security, and an exploration of potential, unintended, undesirable, higher‑order efects
Author
Steen, M.
Timan, T.
van de Poel, I.
Publication year
2021
Abstract
The collection and use of personal data on citizens in the design and deployment of algorithms in the domain of justice and security is a sensitive topic. Values like fairness, autonomy, privacy, accuracy, transparency and property are at stake. Negative examples of algorithms that propagate or exacerbate biases, inequalities or injustices have received ample attention, both in academia and in popular media. To supplement this view, we will discuss two positive examples of Responsible Innovation (RI): the design and deployment of algorithms in decision support, with good intentions and careful approaches. We then explore potential, unintended, undesirable, higher-order effects of algorithms—effects that may occur despite good intentions and careful approaches. We do that by engaging with anticipation and responsiveness, two key dimensions of Responsible Innovation. We close the paper with proposing a framework and a series of tentative recommendations to promote anticipation and responsiveness in the design and deployment of algorithms in decision support in the domain of justice and security.
Subject
Responsible innovation
Algorithms
Decision support
Justice and security
Higher-order effects
To reference this document use:
http://resolver.tudelft.nl/uuid:31ea3864-350f-46d9-a1db-fe941973c1f4
DOI
https://doi.org/10.1007/s43681-021-00063-2
TNO identifier
956678
Source
Ai and Ethics, 1 (1), 501-515
Document type
article