Not so Autonomous, Very Human Decisions in Machine Learning. AAAI Spring Symposium on UX for ML: Designing the User Experience of Machine Learning Systems.


Until the machines are fully autonomous and generate themselves, human design decisions affect Machine Learning outcomes every step of the way. This position paper outlines multiple stages at which design decisions affect machine learning outcomes, and how they interact. This includes: dataset curation and data pipelines, selection of optimization targets, and the designed dialogue with end-users with its implicit and explicit feedback mechanisms. We specifically also call out another user group that appears somewhat overlooked in the research literature – the data curators and editors often involved in selecting and annotating the data that machines learns from.


June 2023 | ICASSP

Contrastive Learning-based Audio to Lyrics Alignment for Multiple Languages

Simon Durand, Daniel Stoller, Sebastian Ewert

May 2023 | CHI

Minimizing change aversion through mixed methods research: a case study of redesigning Spotify’s Your Library

Ingrid Pettersson, Carl Fredriksson, Raha Dadgar, John Richardson, Lisa Shields, Duncan McKenzie

March 2023 | CLeaR - Causal Learning and Reasoning

Non-parametric identifiability and sensitivity analysis of synthetic control models

Jakob Zeitler, Athanasios Vlontzos, Ciarán Mark Gilligan-Lee