Skills and Workforce Core- Ping/Watson

技能和劳动力发展：摘要（项目描述） Bridge 2AI的数据生成项目（DGP）将建立旗舰AI就绪数据集。这些将提供 建立一个基金会，为培训个人使用人工智能（AI）提供新的机会， 数据驱动的方法。然而，人们日益认识到，没有一种“一刀切”的培训办法 研究人员在这个空间，鉴于其高度跨学科的性质。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跨 学科研究。希望获得技能和技能的个人的背景和兴趣的多样性， 生物医学/行为人工智能的知识需要一种动态的、深思熟虑的方法，以最大限度地利用 DGP和拥抱所需的个体多样性，以确保生物医学/行为AI使每个人受益。 该技能和劳动力发展核心（SWDC）旨在与DGP培训模块配合使用， 促进DGP产品的使用，并为他们的理解提供无数的机会和场所， 使用.为此，它将与其他BRIDGE协调中心（CC）核心紧密集成。它将获得 来自广泛的最终用户和利益相关者的反馈，关于DGP产品如何被感知， 完善SWDC的使命有三个方面：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）在DGP中实施战略， 为不同的学习者提供一种动态的方式，以接收提供技能组合的定制课程，（实用） 知识和经验; 3）解决对生物医学数据更加多样性的迫切需求 通过利用Bridge 2AI产品的新颖参与计划，为科学创造机会， 指导和长期影响。这一使命是通过两个具体目标实现的：1）开发课程， 教育材料，以及与指导总干事的互动会议，从而解决技能发展问题;以及2） 为新的、多样化的、准备好人工智能的劳动力开发培训机会，建立基础设施和关系， 船舶，以促进劳动力的发展。计划举行一系列会议，以了解DGP数据集， 工具，从中我们可以确定共同的机会，并确定优先事项，以开发教育模块， 计划活动，包括数据大会和黑客马拉松（与标准和工具优化- 核）。在这个模块库和其他资源的基础上，我们计划创建新的方法来定制 为学习者推荐的一套课程，考虑到他们的教育背景，对AI的熟悉程度，以及 有针对性地使用技能。重要的是，所有这些发展都将以我们对公平、多样性、 和包容性（EDI），因为我们希望有意义地参与代表性不足的少数群体和弱势群体 在生物医学数据科学中，确保他们的存在和未来的声音。

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.