Skills and Workforce Core- Ping/Watson

技能和劳动力发展：摘要(项目说明) Bridge2AI的数据生成项目(DGPS)将建立旗舰的AI就绪数据集。这些将提供 建立一个基金会，建立新的机会，培训个人使用人工智能(AI)和 数据驱动的方法。然而，越来越多的人认识到，培训并不是“一刀切”的方法 鉴于其高度跨学科的性质，这一领域的研究人员。有些人对算法感兴趣 改进；其他人专注于人工智能的社会技术影响；还有一些人积极参与 纪律研究。想要获得技能和兴趣的个人的背景和兴趣的异质性 了解生物医学/行为人工智能需要一种动态的、深思熟虑的方法，使 DGPS并支持所需的个体多样性，以确保生物医学/行为人工智能惠及每个人。 此技能和劳动力发展核心(SWDC)旨在与DGP培训模块配合使用，并 促进DGP产品的使用，并提供无数机会和场所让他们了解和 使用。为此，它将与其他桥梁协调中心(CC)核心紧密结合。它将会获得 来自各种终端用户和利益相关方的反馈，了解DGP产品的认知情况以及 要有所改进。SWDC的使命有三个：1)围绕DGP开发教育模块和活动 数据集和工具，说明当代人工智能中的关键概念，涵盖技术概念和问题 围绕道德和值得信赖的人工智能(EtaI，具有道德核心)；2)跨DGPS实施战略，以 为不同的学习者提供一种动态的方式来接收提供技能集的定制课程，(实用) 所需的知识和经验；以及3)解决生物医学数据更加多样化的迫切需求 通过利用Bridge2AI产品的新颖参与计划实现科学，为 良师益友和长期影响。这一使命是通过两个具体目标实现的：1)制定课程， 教育材料和与全球定位系统的互动会议，从而解决技能发展问题；和2) 为新的、多样化的、支持人工智能的员工队伍开发培训机会，建设基础设施和关系- 船舶，以实现劳动力发展。计划举行一系列会议，以了解DGPS数据集和 工具，我们可以从中确定共同的机会并设置优先事项，以开发教育模块和 计划活动，包括数据大会和黑客松(与标准和工具优化- TION核)。在这个模板库和其他资源库的基础上，我们计划创建新的方法来定制 为学习者提供的一套推荐课程，考虑到他们声明的教育背景，对人工智能的熟悉程度，以及 有针对性地使用技能。重要的是，所有这些发展都将受到我们对公平、多样性、 和包容性(EDI)，因为我们希望有意义地接触代表不足的少数群体和处境不利的个人 在生物医学数据科学方面，确保他们在未来的存在和声音。

SKILLS & WORKFORCE DEVELOPMENT: ABSTRACT (PROJECT DESCRIPTION) Bridge2AI’s Data Generation Projects (DGPs) will be establishing flagship AI-ready datasets. These will provide a foundation to establish new opportunities to train individuals in about the use of artificial intelligence (AI) and data-driven methods. Yet there is increasing recognition that there is not a “one-size-fits-all” approach to training researchers in this space, given its highly interdisciplinary nature. Some individuals are interested in algorithmic improvements; others are focused on the sociotechnical implications of AI; still others actively engage with inter- disciplinary research. The heterogeneity of backgrounds and interests of individuals wanting to gain skills and knowledge in biomedical/behavioral AI requires a dynamic, thoughtful approach that maximizes the utility of the DGPs and embraces the diversity of individuals needed to ensure biomedical/behavioral AI benefits everyone. This Skills & Workforce Development Core (SWDC) is designed to work with the DGP Training Modules and to facilitate the use of DGP products and providing myriad opportunities and venues for their understanding and use. To do so, it will be closely integrated with the other BRIDGE Coordination Center (CC) Cores. It will garner feedback from a broad variety of end users and stakeholders as to how DGP products are perceived and can be improved. The SWDC’s mission is threefold: 1) developing educational modules and activities around DGP datasets and tools, illustrating key concepts in contemporary AI, covering both technical concepts and issues around ethical and trustworthy AI (ETAI, with the Ethics Core); 2) implementing strategies across the DGPs to provide a dynamic way for different learners to receive a customized curricula that provides the skillset, (practical) knowledge, and experience that is desired; and 3) tackling the urgent need for more diversity in biomedical data science through novel engagement programs that leverage the Bridge2AI products, creating opportunities for mentorship and long-term impact. This mission is realized across two specific aims: 1) to develop curricula, educational materials, and interactive sessions with the DGPs, thereby addressing skills development; and 2) to develop training opportunities for a new, diverse, and AI-ready workforce, building infrastructure and relation- ships to enable workforce development. A series of meetings are planned to understand the DGPs datasets and tools, from which we can identify common opportunities and set priorities to develop educational modules and plan activities, including data jamborees and hackathons (in conjunction with the Standards and Tool Optimiza- tion Cores). Building atop this library of modules and other resources, we plan to create novel methods to tailor a set of recommended courses for a learner, given their stated educational background, familiarity with AI, and targeted use of skills. Importantly, all these developments will be informed by our commitment to equity, diversity, and inclusion (EDI) as we look to meaningfully engage underrepresented minorities and disadvantage individuals in biomedical data science, ensuring their presences and voices in its future.