- Sponsor:
- sigchi
No abstract available.
AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making
In this article, we propose a conceptual and methodological framework for measuring the impact of the introduction of AI systems in decision settings, based on the concept of technological dominance, i.e. the influence that an AI system can exert on ...
Co-Writing Screenplays and Theatre Scripts with Language Models: Evaluation by Industry Professionals
Language models are increasingly attracting interest from writers. However, such models lack long-range semantic coherence, limiting their usefulness for longform creative writing. We address this limitation by applying language models hierarchically, ...
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 available to ease some of these challenges. However, little research ...
Modeling Touch-based Menu Selection Performance of Blind Users via Reinforcement Learning
Although menu selection has been extensively studied in HCI, most existing studies have focused on sighted users, leaving blind users’ menu selection under-studied. In this paper, we propose a computational model that can simulate blind users’ menu ...
User Preference and Performance using Tagging and Browsing for Image Labeling
Visual content must be labeled to facilitate navigation and retrieval, or provide ground truth data for supervised machine learning approaches. The efficiency of labeling techniques is crucial to produce numerous qualitative labels, but existing ...
What is Human-Centered about Human-Centered AI? A Map of the Research Landscape
The application of Artificial Intelligence (AI) across a wide range of domains comes with both high expectations of its benefits and dire predictions of misuse. While AI systems have largely been driven by a technology-centered design approach, the ...
Cited By
- Yamanaka S, Usuba H, Oba Y, Kinoshita T, Tomihari R, Kasahara N and Miyashita H (2024). Verifying Finger-Fitts Models for Normalizing Subjective Speed-Accuracy Biases, Proceedings of the ACM on Human-Computer Interaction, 8:MHCI, (1-24), Online publication date: 24-Sep-2024.
- Chang Y, Wang Y, Chang C, Tan W, Hsu Y, Chen Y and Chen M (2024). Experience from Designing Augmented Reality Browsing Interfaces for Real-world Walking Scenarios, Proceedings of the ACM on Human-Computer Interaction, 8:MHCI, (1-26), Online publication date: 24-Sep-2024.
- Ji K, Hettiachchi D, Salim F, Scholer F and Spina D Characterizing Information Seeking Processes with Multiple Physiological Signals Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, (1006-1017)
- Seraji M, Piray P, Zahednejad V and Stuerzlinger W (2024). Analyzing User Behaviour Patterns in a Cross-Virtuality Immersive Analytics System, IEEE Transactions on Visualization and Computer Graphics, 30:5, (2613-2623), Online publication date: 1-May-2024.
-
Benda N, Desai P, Reza Z, Zheng A, Kumar S, Harkins S, Hermann A, Zhang Y, Joly R, Kim J, Pathak J and Reading Turchioe M (2024). Patient Perspectives on AI for Mental Health Care: With Great [Computing] Power, Comes Great Responsibility (Preprint), JMIR Mental Health, 10.2196/58462
- Cabric F, Bjarnadóttir M, Ling M, Rafnsdóttir G and Isenberg P (2023). Eleven Years of Gender Data Visualization: A Step Towards More Inclusive Gender Representation, IEEE Transactions on Visualization and Computer Graphics, 30:1, (316-326), Online publication date: 1-Jan-2024.
Index Terms
- Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
CHI '19 | 2,958 | 703 | 24% |
CHI '18 | 2,590 | 666 | 26% |
CHI '17 | 2,400 | 600 | 25% |
CHI '16 | 2,435 | 565 | 23% |
CHI '15 | 2,120 | 486 | 23% |
CHI '14 | 2,043 | 465 | 23% |
CHI '13 | 1,963 | 392 | 20% |
CHI '11 | 1,532 | 410 | 27% |
CHI '09 | 1,130 | 277 | 25% |
CHI '08 | 714 | 157 | 22% |
CHI '07 | 840 | 182 | 22% |
CHI '05 | 372 | 93 | 25% |
CHI '03 | 468 | 75 | 16% |
CHI '02 | 414 | 61 | 15% |
CHI '01 | 352 | 69 | 20% |
CHI '00 | 336 | 72 | 21% |
CHI '99 | 312 | 78 | 25% |
CHI '98 | 351 | 81 | 23% |
CHI '97 | 234 | 55 | 24% |
CHI '96 | 256 | 55 | 21% |
CHI '94 | 263 | 70 | 27% |
CHI '93 | 330 | 62 | 19% |
CHI '92 | 216 | 67 | 31% |
CHI '91 | 240 | 56 | 23% |
CHI '90 | 260 | 47 | 18% |
CHI '89 | 199 | 54 | 27% |
CHI '88 | 187 | 39 | 21% |
CHI '87 | 166 | 46 | 28% |
CHI '86 | 122 | 47 | 39% |
CHI '85 | 170 | 35 | 21% |
CHI '83 | 176 | 59 | 34% |
CHI '82 | 165 | 75 | 45% |
Overall | 26,314 | 6,199 | 24% |