Contestability and Professionals: From Explanations to Engagement with Algorithmic Systems

By Daniel N Kluttz, Nitin Kohli, Deirdre K. Mulligan. 2018

15 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Informatics, Safety Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Flávio du Pin Calmon
2. Charles Marx
3. Berk Ustun
4. Deirdre K. Mulligan
5. Cynthia Rudin
6. Lalitha Sankar
7. R. Caruana

In Safety Research

1. Flávio du Pin Calmon
2. K. G. Karahalios
3. Berk Ustun
4. Deirdre K. Mulligan
5. Cynthia Rudin

Citations in the corpus

• Predictive Multiplicity in Classification (2019, background): “In this way, problems that exhibit predictive multiplicity can be handled on a case-by-case basis, and in a way that allows for input from stakeholders [as per the principles of contestable design; see e.g., 20, 26].”
• Contestability in Algorithmic Systems (2019, background): “Further, while most work has focused on experts [5, 7], contestability can also serve important functions for decision subjects.”