We are amidst an explosion of artificial intelligence research, particularly around large language models (LLMs). These models have a range of applications across domains like medicine, finance, commonsense knowledge graphs, and crowdsourcing. Investigation into LLMs as part of crowdsourcing workflows remains an under-explored space. The crowdsourcing research community has produced a body of work investigating workflows and methods for managing complex tasks using hybrid human-AI methods. Within crowdsourcing, the role of LLMs can be envisioned as akin to a cog in a larger wheel of workflows. From an empirical standpoint, little is currently understood about how LLMs can improve the effectiveness of crowdsourcing workflows and how such workflows can be evaluated. In this work, we present a vision for exploring this gap from the perspectives of various stakeholders involved in the crowdsourcing paradigm -- the task requesters, crowd workers, platforms, and end-users. We identify junctures in typical crowdsourcing workflows at which the introduction of LLMs can play a beneficial role and propose means to augment existing design patterns for crowd work.
Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach
Text-to-Layout: A Generative Workflow for Drafting Architectural Floor Plans Using LLMs
Department of Civil and Environmental Engineering, University of Houston（土木与环境工程系，休斯顿大学）；Center for Transportation Research, The University of Texas at Austin（交通研究中心，德克萨斯大学奥斯汀分校）；Department of Information Science Technology, University of Houston（信息科学与技术系，休斯顿大学）
Simulating Generative Social Agents via Theory-Informed Workflow Design
Information Hub The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州）信息中心）；Department of Electronic Engineering Tsinghua University（清华大学电子工程系）
Natural Language Programming in Medicine: Administering Evidence Based Clinical Workflows with Autonomous Agents Powered by Generative Large Language Models
Icahn School of Medicine at Mount Sinai（西奈山伊坎医学院）；Mount Sinai Hospital（西奈山医院）；Boston Children’s Hospital（波士顿儿童医院）；Harvard Medical School（哈佛医学院）；University of Pittsburgh School of Medicine（匹兹堡大学医学院）
Generative AI-assisted Participatory Modeling in Socio-Environmental Planning under Deep Uncertainty
School of Computing（计算学院）；Information Systems, Faculty of Engineering（信息学院，工程学院）；Information Technology, The University of Melbourne, Parkville VIC 3010, Australia（信息科技，墨尔本大学，帕克维尔 VIC 3010, 澳大利亚）；Industrial Research Organization (CSIRO), Research Way, Clayton VIC 3168, Australia（工业研究组织（CSIRO），Research Way，克莱顿 VIC 3168, 澳大利亚）；Department of Psychiatry, The University of Melbourne, Parkville VIC 3010, Australia（精神病学系，墨尔本大学，帕克维尔 VIC 3010, 澳大利亚）
Preparing to Integrate Generative Pretrained Transformer Series 4 models into Genetic Variant Assessment Workflows: Assessing Performance, Drift, and Nondeterminism Characteristics Relative to Classifying Functional Evidence in Literature
Mass General Brigham Personalized Medicine（麻省总医院布里格姆个性化医学）；Brigham and Women’s Hospital（布莱根妇女医院）；Microsoft Corporation（微软公司）
Explanova: Automatically Discover Data Insights in N \times M Table via XAI Combined LLM Workflow
Institute for Clarity in Documentation（清晰文档研究所）；Inria Paris-Rocquencourt（巴黎-罗克Quantin 国家信息与自动化研究所）；Rajiv Gandhi University（拉吉夫·甘地大学）；Tsinghua University（清华大学）；Palmer Research Laboratories（帕尔默研究实验室）
Design tools in the 3D industry, while powerful, are still tedious and labor-intensive when it comes to bringing a creative idea for a visual effect to life. In this position paper, we discussed how an infamous generative synthetic media, deepfakes, could be of use and embedded into common sophisticated 3D workflows to reduce user workloads in areas such as 3D model editing, material design, and character animation. As a case discussion, we also prototyped a tool to address the retargeting problem in character animation. Although deepfakes themselves have received a negative public image, the …
"ChatGPT, what am I missing?": Designing AI Workflows around Professional Task Structure to Shape Analytic AI Use
AI Institute, Harvard Business School（哈佛商学院人工智能研究所）；Frontline Associates（前线协会）；Emory University School of Law（埃默里大学法学院）；Laboratory for Innovation Science at Harvard（哈佛大学创新科学实验室）；Harvard John A. Paulson School of Engineering and Applied Sciences（哈佛约翰·A·保尔森工程与应用科学学院）
Generative Design workflows have introduced alternative paradigms in the domain of computational design, allowing designers to generate large pools of valid solutions by defining a set of goals and constraints. However, analyzing and narrowing down the generated solution space, which usually consists of various high-dimensional properties, has been a major challenge in current generative workflows. By taking advantage of the interactive unbounded spatial exploration, and the visual immersion offered in virtual reality platforms, we propose V-Dream, a virtual reality generative analysis framewo…
University of Maryland, College Park（马里兰大学帕克分校）；University of Massachusetts, Amherst（马萨诸塞大学阿默斯特分校）；AWS AI Labs（亚马逊AI实验室）；MIT CSAIL（麻省理工学院计算机科学与人工智能实验室）
IT University of Copenhagen（哥本哈根信息技术大学）；University of Salzburg（萨尔茨堡大学）；University of Washington（华盛顿大学）
Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. Such technologies potentially introduce a massive disruption to creative fields. This paper presents the results of a qualitative survey ($N$ = 23) investigating how creative professionals think about generative AI. The results show that the advancement of these AI models prompts important reflections on what defines creativity and how creatives imagine using AI to support their workfl…
Not Another EHR: Reimagining Physician Information Needs with Generative AI Technology
University of Washington（华盛顿大学）；Northeastern University（东北大学）；Stanford University School of Medicine（斯坦福大学医学院）；Stanford University（斯坦福大学）；Microsoft Research（微软研究院）；Microsoft（微软）；University of Washington School of Medicine（华盛顿大学医学院）
What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safety
College of Information Sciences and Technology, The Pennsylvania State University（信息科学与技术学院，宾夕法尼亚州立大学）；Max Planck Institute for Security and Privacy（安全与隐私研究所）
