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Understanding practices, challenges, and opportunities for user-engaged algorithm auditing in industry practice
Recent years have seen growing interest among both researchers and practitioners in user-
engaged approaches to algorithm auditing, which directly engage users in detecting …
engaged approaches to algorithm auditing, which directly engage users in detecting …
Design principles for generative AI applications
Generative AI applications present unique design challenges. As generative AI technologies
are increasingly being incorporated into mainstream applications, there is an urgent need …
are increasingly being incorporated into mainstream applications, there is an urgent need …
Investigating how practitioners use human-ai guidelines: A case study on the people+ ai guidebook
Artificial intelligence (AI) presents new challenges for the user experience (UX) of products
and services. Recently, practitioner-facing resources and design guidelines have become …
and services. Recently, practitioner-facing resources and design guidelines have become …
Designerly understanding: Information needs for model transparency to support design ideation for AI-powered user experience
Despite the widespread use of artificial intelligence (AI), designing user experiences (UX) for
AI-powered systems remains challenging. UX designers face hurdles understanding AI …
AI-powered systems remains challenging. UX designers face hurdles understanding AI …
Designing responsible ai: Adaptations of ux practice to meet responsible ai challenges
Technology companies continue to invest in efforts to incorporate responsibility in their
Artificial Intelligence (AI) advancements, while efforts to audit and regulate AI systems …
Artificial Intelligence (AI) advancements, while efforts to audit and regulate AI systems …
Ai robustness: a human-centered perspective on technological challenges and opportunities
Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness
remains elusive and constitutes a key issue that impedes large-scale adoption. Besides …
remains elusive and constitutes a key issue that impedes large-scale adoption. Besides …
Towards AI accountability infrastructure: Gaps and opportunities in AI audit tooling
Audits are critical mechanisms for identifying the risks and limitations of deployed artificial
intelligence (AI) systems. However, the effective execution of AI audits remains incredibly …
intelligence (AI) systems. However, the effective execution of AI audits remains incredibly …
Investigating practices and opportunities for cross-functional collaboration around AI fairness in industry practice
An emerging body of research indicates that ineffective cross-functional collaboration–the
interdisciplinary work done by industry practitioners across roles–represents a major barrier …
interdisciplinary work done by industry practitioners across roles–represents a major barrier …
A hunt for the snark: Annotator diversity in data practices
Diversity in datasets is a key component to building responsible AI/ML. Despite this
recognition, we know little about the diversity among the annotators involved in data …
recognition, we know little about the diversity among the annotators involved in data …
Zeno: An interactive framework for behavioral evaluation of machine learning
Machine learning models with high accuracy on test data can still produce systematic
failures, such as harmful biases and safety issues, when deployed in the real world. To …
failures, such as harmful biases and safety issues, when deployed in the real world. To …