Counterfactual explanations and algorithmic recourses for machine learning: A review

S Verma, V Boonsanong, M Hoang, K Hines… - ACM Computing …, 2024 - dl.acm.org
Machine learning plays a role in many deployed decision systems, often in ways that are
difficult or impossible to understand by human stakeholders. Explaining, in a human …

Explainable and interpretable machine learning and data mining

M Atzmueller, J Fürnkranz, T Kliegr… - Data Mining and …, 2024 - Springer
The growing number of applications of machine learning and data mining in many domains—
from agriculture to business, education, industrial manufacturing, and medicine—gave rise …

On the path to the future: mapping the notion of transparency in the EU regulatory framework for AI

I Varošanec - International Review of Law, Computers & …, 2022 - Taylor & Francis
Transparency is the currency of trust. It offers clarity and certainty. This is essential when
dealing with intelligent systems which are increasingly making impactful decisions. Such …

Legal dispositionism and artificially-intelligent attributions

J Soh - Legal Studies, 2023 - cambridge.org
It is conventionally argued that because an artificially-intelligent (AI) system acts
autonomously, its makers cannot easily be held liable should the system's actions harm …

Interpretable multiple instance learning

JA Early - 2024 - eprints.soton.ac.uk
With the rising use of Artificial Intelligence (AI) and Machine Learning (ML) methods, there
comes an increasing need to understand how automated systems make decisions …