Creating design resources to scaffold the ideation of AI concepts
Advances in artificial intelligence have enabled unprecedented technical capabilities, yet
making these advances useful in the real world remains challenging. We engaged in a …
making these advances useful in the real world remains challenging. We engaged in a …
Angler: Hel** machine translation practitioners prioritize model improvements
Machine learning (ML) models can fail in unexpected ways in the real world, but not all
model failures are equal. With finite time and resources, ML practitioners are forced to …
model failures are equal. With finite time and resources, ML practitioners are forced to …
Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit
Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet
innovation teams struggle when envisioning AI concepts. Data science teams think of …
innovation teams struggle when envisioning AI concepts. Data science teams think of …
Investigating Why Clinicians Deviate from Standards of Care: Liberating Patients from Mechanical Ventilation in the ICU
N Yildirim, S Zlotnikov, A Venkat, G Chawla… - Proceedings of the CHI …, 2024 - dl.acm.org
Clinical practice guidelines, care pathways, and protocols are designed to support evidence-
based practices for clinicians; however, their adoption remains a challenge. We set out to …
based practices for clinicians; however, their adoption remains a challenge. We set out to …
Co-ML: Collaborative machine learning model building for develo** dataset design practices
Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML
systems requires significant considerations around how to design representative datasets …
systems requires significant considerations around how to design representative datasets …
Creating Design Resources to Scaffold the Ideation of AI Concepts
N Yıldırım, C Oh, D Sayar, K Brand, S Challa… - … Conference, Dis 2023, 2023 - gcris.ieu.edu.tr
Advances in artificial intelligence have enabled unprecedented technical capabilities, yet
making these advances useful in the real world remains challenging. We engaged in a …
making these advances useful in the real world remains challenging. We engaged in a …
[BUCH][B] Designing for Reliability in Algorithmic Systems
S Robertson - 2023 - search.proquest.com
As we introduce complex algorithmic systems into decision-making in high-stakes domains,
system designers need principled approaches to help people set their expectations of these …
system designers need principled approaches to help people set their expectations of these …
[PDF][PDF] Fairness-Aware Models for Generating Synthetic Data in Diverse Domains
XLYLH Zhang, Z Chen, J Wu, L Wang - researchgate.net
Large language models (LLMs) are increasingly used in various applications, yet biases in
training data can lead to unfair outcomes in model predictions. To address this challenge …
training data can lead to unfair outcomes in model predictions. To address this challenge …