Categories: FAANG

Negotiating Ontological Boundaries in User-Authored Personal Sensing Systems

Designed artifacts are ontological, shaping, and at times limiting, what becomes possible or imaginable. One path toward mitigating such foreclosures is giving people power over how systems are designed and built. Despite decades of scholarship around systems that enable such authorship, these systems are often evaluated on whether or not they are usable, useful, or technically feasible, leaving questions of ontological boundary negotiation, unexamined. We design two open-ended probes that utilize a Wizard of Oz technique to enable the experience of training a personalized machine learning…

Palantir Foundry for Positive Disruption

November 6, 2022

In "FAANG"

To explore AI bias, researchers pose a question: How do you imagine a tree?

To confront bias, scientists say we must examine the ontological frameworks within large language models—and how our perceptions influence outputs.

July 30, 2025

In "AI/ML News"

Symphony: Composing Interactive Interfaces for Machine Learning

Interfaces for machine learning (ML), information and visualizations about models or data, can help practitioners build robust and responsible ML systems. Despite their benefits, recent studies of ML teams and our interviews with practitioners (n=9) showed that ML interfaces have limited adoption in practice. While existing ML interfaces are effective…

June 17, 2023

In "FAANG"

AI Generated Robotic Content