Search Results for author:
Found 5 papers, 0 papers with code
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms
This paper introduces a collaborative, human-centred taxonomy of AI, algorithmic and automation harms.
Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems
For such a novel type of algorithmic auditing to become standard practice, two main prerequisites need to be available: A lifecycle model that is tailored towards transparency and accountability, and a principled risk assessment procedure that allows the proper scoping of the audit.
Flat Latent Manifolds for Human-machine Co-creation of Music
We therefore consider a music-generating algorithm as a counterpart to a human musician, in a setting where reciprocal interplay is to lead to new experiences, both for the musician and the audience.
Active Learning based on Data Uncertainty and Model Sensitivity
It relies on the Jacobian of the likelihood to detect non-smooth transitions in the latent space, i. e., transitions that lead to abrupt changes in the movement of the robot.
Unsupervised Real-Time Control through Variational Empowerment
We introduce a methodology for efficiently computing a lower bound to empowerment, allowing it to be used as an unsupervised cost function for policy learning in real-time control.
