Conference on Human-Centered Approaches to Artificial Intelligence Literacy in Informal Learning

纽约科学馆(NYSCI)将召开一次为期两天的参与性设计会议，以确定在非正式环境中支持人工智能(AI)扫盲的研究和教育机会，特别是针对那些社区受到某些人工智能过程中的偏见影响的多样化和服务不足的青年。人工智能使用模拟人类智能的计算机系统。人工智能系统几乎影响到日常生活的方方面面，执行导航应用、面部识别、电子支付和社交媒体背后的任务。人工智能可能会在整个文化中延续不平等和有偏见的结果。会议将探讨如何在年轻人中促进参与和概念性学习，了解人工智能是如何工作的，以及批判性地使用和应用人工智能需要哪些技能。会议还将探讨如何支持多元化和服务不足的儿童和青年在塑造人工智能和加入日益增长的STEM劳动力队伍方面的利益，这些劳动力将在他们的职业中使用人工智能。会议将确定人工智能扫盲的关键特征和需求，并探讨非正式学习在促进不同社区和服务不足社区年轻人的人工智能扫盲方面可以发挥的具体作用。与会者将包括设计师、学习型科学家、研究人员、非正式和正式的教育工作者，以及科学中心的专业人员。与会者将在不同的团队和小组中工作，探索和批评现有的人工智能工具和学习框架，讨论从前景看好的人工智能扫盲计划中吸取的教训，并确定设计原则和未来的研究方向。将特别关注非正式参与机制、有前途的网络和研究-实践伙伴关系，这些机制利用非正式学习和社区服务的独特负担来加快历史上被排斥的青年的人工智能扫盲。从这项工作中获得的见解将导致非正式机构以文化响应的方式促进人工智能扫盲的一套研究和方案优先事项。由此出版的指南和社区活动将广泛传播这次会议产生的优先事项和设计原则，以帮助非正式学习机构和社区学习组织确定资产和优先事项，以解决与人工智能扫盲有关的多样性、公平、获取和包容性问题。本研究项目由推进非正式STEM学习计划(AISL)资助，该计划旨在：(A)促进对非正式环境中STEM学习设计和开发的新方法和基于证据的理解；(B)为扩大获得和参与STEM学习体验提供多种途径；(C)推进对非正式环境中STEM学习的创新研究和评估；以及(D)让所有年龄段的公众在非正式环境中学习STEM。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The New York Hall of Science (NYSCI) will convene a two-day participatory design conference of to identify research and education opportunities in informal settings for supporting literacy concerning Artificial Intelligence (AI), especially for diverse and underserved youth whose communities are impacted by the bias in some AI processes. AI uses computer systems that simulate human intelligence. AI systems impact nearly every aspect of daily living, performing tasks underlying navigation apps, facial recognition, e-payments, and social media. AI can perpetuate inequities and biased outcomes in the culture at large. The conference will explore how to promote engagement and conceptual learning among youth about how AI works and what skills are needed to critically use and apply AI. The conference will also explore ways to support the interests of diverse and underserved children and youth in shaping AI and joining the growing STEM workforce that will use AI in their professions. The conference will identify key features and needs with respect to AI literacy and explore the specific roles that informal learning can play in advancing AI literacy for youth in diverse and underserved communities. Participants in the conference will include designers, learning scientists, researchers, informal and formal educators, and science center professionals. Attendees will work in separate teams and as a group to explore and critique existing AI tools and learning frameworks, discuss lessons learned from promising AI literacy programs, and identify design principles and future directions for research. Specific attention will be paid to informal mechanisms of engagement, promising networks, and research-practice partnerships that take advantage of the unique affordances of informal learning and community services to accelerate AI literacy for historically excluded youth. The insights gained from this work will result in a set of research and programmatic priorities for informal institutions to promote AI literacy in culturally responsive ways. The resulting published guide and community events will broadly disseminate priorities and design principles generated by this convening to help informal learning institutions and community learning organizations identify both assets and priorities for addressing diversity, equity, access, and inclusion issues related to AI literacy. This research project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to (a) advance new approaches to and evidence-based understanding of the design and development of STEM learning in informal environments; (b) provide multiple pathways for broadening access to and engagement in STEM learning experiences; (c) advance innovative research on and assessment of STEM learning in informal environments; and (d) engage the public of all ages in learning STEM in informal environments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.