Technologies in the workplace have been a major focus of CSCW, including studies that investigate technologies for collaborative work, explore new work environments, and address the importance of political and organizational aspects of technologies in workplaces. Emerging technologies, such as AI and robotics, have been deployed in various workplaces, and their proliferation is rapidly expanding. These technologies have not only changed the nature of work but also reinforced power and social dynamics within workplaces, requiring us to rethink the legitimate relationship between emerging technologies and human workers. It will be critical to the development of equitable future work arrangements to identify how these emerging technologies will develop relationships with human workers who have limited power and voice in their workplaces. How can these emerging technologies develop mutually beneficial partnerships with human workers? In this one-day workshop, we seek to illustrate the meaning of human-machine partnerships (HMP) by highlighting that how we define HMP may shape the design of future robots at work. By incorporating interdisciplinary perspectives, we aim to develop a taxonomy of HMP by which we can broaden our relationship with embodied agents but also evaluate and reconsider existing theoretical, methodological, and epistemological challenges in HMP research. 
                        more » 
                        « less   
                    
                            
                            Human Computation, Equitable, and Innovative Future of Work AI Tools
                        
                    
    
            As we enter an era where the synergy between AI technologies and human effort is paramount, the Future of Work is undergoing a radical transformation. Emerging AI tools will profoundly influence how we work, the tools we use, and the very nature of work itself. The ’Human Computation, Equitable, and Innovative Future of Work AI Tools’ workshop at HCOMP’24 aims to explore groundbreaking solutions for developing fair and inclusive AI tools that shape how we will work. This workshop will delve into the collaborative potential of human computation and artificial intelligence in crafting equitable Future of Work AI tools. Participants will critically examine the current challenges in designing fair and innovative AI systems for the evolving workplace, as well as strategies for effectively integrating human insights into these tools. The primary objective is to foster a rich discourse on scalable, sustainable solutions that promote equitable Future of Work tools for all, with a particular focus on empowering marginalized communities. By bringing together experts from diverse fields, we aim to catalyze ideas that bridge the gap between technological advancement and social equity. 
        more » 
        « less   
        
    
                            - Award ID(s):
- 2339443
- PAR ID:
- 10590884
- Publisher / Repository:
- AAAI
- Date Published:
- Journal Name:
- Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
- Volume:
- 12
- ISSN:
- 2769-1330
- Page Range / eLocation ID:
- 155 to 156
- Subject(s) / Keyword(s):
- workshop HCOMP gig workers
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
- 
            
- 
            Collective action by gig knowledge workers is a potent method for enhancing labor conditions on platforms like Upwork, Amazon Mechanical Turk, and Toloka. However, this type of collective action is still rare today. Existing systems for supporting collective action are inadequate for workers to identify and understand their different workplace problems, plan effective solutions, and put the solutions into action. This talk will discuss how with my research lab we are creating worker-centric AI enhanced technologies that enable collective action among gig knowledge workers. Building solid AI enhanced technologies to enable gig worker collective action will pave the way for a fair and ethical gig economy—one with fair wages, humane working conditions, and increased job security. I will discuss how my proposed approach involves first integrating "sousveillance," a concept by Foucault, into the technologies. Sousveillance involves individuals or groups using surveillance tools to monitor and record those in positions of power. In this case, the technologies enable gig workers to monitor their workplace and their algorithmic bosses, giving them access to their own workplace data for the first time. This facilitates the first stage of collective action: problem identification. I will then discuss how we combine this data with Large-Language-Models (LLMs) and social theories to create intelligent assistants that guide workers to complete collective action via sensemaking and solution implementation. The talk will present a set of case studies to showcase this vision of designing data driven AI technologies to power gig worker collective action. In particular, I will present the systems: 1) GigSousveillance which allows workers to monitor and collect their own job-related data, facilitating quantification of workplace problems; 2) GigSense equips workers with an AI assistant that facilitates sensemaking of their work problems, helping workers to strategically devise solutions to their challenges; 3) GigAction is an AI assistant that guides workers to implement their proposed solutions. I will discuss how we are designing and implementing these systems by adopting a participatory design approach with workers, while also conducting experiments and longitudinal deployments in the real world. I conclude by presenting a research agenda for transforming and rethinking the role of A.I. in our workplaces; and researching effective socio-technical solutions in favor of a worker-centric future and countering technoauthoritarianismmore » « less
- 
            The spread of infectious diseases is a highly complex spatiotemporal process, difficult to understand, predict, and effectively respond to. Machine learning and artificial intelligence (AI) have achieved impressive results in other learning and prediction tasks; however, while many AI solutions are developed for disease prediction, only a few of them are adopted by decision-makers to support policy interventions. Among several issues preventing their uptake, AI methods are known to amplify the bias in the data they are trained on. This is especially problematic for infectious disease models that typically leverage large, open, and inherently biased spatiotemporal data. These biases may propagate through the modeling pipeline to decision-making, resulting in inequitable policy interventions. Therefore, there is a need to gain an understanding of how the AI disease modeling pipeline can mitigate biased input data, in-processing models, and biased outputs. Specifically, our vision is to develop a large-scale micro-simulation of individuals from which human mobility, population, and disease ground-truth data can be obtained. From this complete dataset—which may not reflect the real world—we can sample and inject different types of bias. By using the sampled data in which bias is known (as it is given as the simulation parameter), we can explore how existing solutions for fairness in AI can mitigate and correct these biases and investigate novel AI fairness solutions. Achieving this vision would result in improved trust in such models for informing fair and equitable policy interventions.more » « less
- 
            Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often interrupting them and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives, including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, and society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our learnings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in driving progress in this domain.more » « less
- 
            Artificial intelligence (AI) underpins virtually every experience that we have—from search and social media to generative AI and immersive social virtual reality (SVR). For Generation Z, there is no before AI. As adults, we must humble ourselves to the notion that AI is shaping youths’ world in ways that we don’t understand and we need to listen to them about their lived experiences. We invite researchers from academia and industry to participate in a workshop with youth activists to set the agenda for research into how AI-driven emerging technologies affect youth and how to address these challenges. This reflective workshop will amplify youth voices and empower youth and researchers to set an agenda. As part of the workshop, youth activists will participate in a panel and steer the conversation around the agenda for future research. All will participate in group research agenda setting activities to reflect on their experiences with AI technologies and consider ways to tackle these challenges.more » « less
 An official website of the United States government
An official website of the United States government 
				
			 
					 
					
 
                                    