Homo Cyberneticus: The Era of Human-AI Integration
This article is submitted and accepted as ACM UIST 2019 Visions. UIST Visions is a venue for forward thinking ideas to inspire the community. The goal is not to report research but to project and propose new research directions. This article, entitled "Homo Cyberneticus: The Era of Human-AI Integration", proposes HCI research directions, namely human-augmentation and human-AI-integration.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
When ChatGPT is gone: Creativity reverts and homogeneity persists
ChatGPT has been evidenced to enhance human performance in creative tasks. Yet, it is still unclear if this boosting effect sustains with and without ChatGPT. In a pre-registered seven-day lab experiment and a follow-up …
AI Mathematician as a Partner in Advancing Mathematical Discovery -- A Case Study in Homogenization Theory
Artificial intelligence (AI) has demonstrated impressive progress in mathematical reasoning, yet its integration into the practice of mathematical research remains limited. In this study, we investigate how the AI Mathem…
Mathematical ReasoningCross-Species Data Integration for Enhanced Layer Segmentation in Kidney Pathology
Accurate delineation of the boundaries between the renal cortex and medulla is crucial for subsequent functional structural analysis and disease diagnosis. Training high-quality deep-learning models for layer segmentatio…
Data IntegrationDomain GeneralizationSemantic SegmentationDetection of bromochloro alkanes in indoor dust using a novel CP-Seeker data integration tool
Bromochloro alkanes (BCAs) have been manufactured for use as flame retardants for decades and preliminary environmental risk screening suggests they are likely to behave similarly to polychlorinated alkanes (PCAs), subcl…
Data IntegrationHeterogeneous graph attention network improves cancer multiomics integration
The increase in high-dimensional multiomics data demands advanced integration models to capture the complexity of human diseases. Graph-based deep learning integration models, despite their promise, struggle with small p…
feature selectionGraph Attention