Metcalfe et al (1) argue that the greatest potential for human-AI partnerships lies in their application to highly complex problem spaces. Herein, we discuss three different forms of hybrid team intelligence and posit that across all three forms, the hybridization of man and machine intelligence can be effective under the right conditions. We foresee two significant research and development (R&D) challenges underlying the creation of effective hybrid intelligence. First, rapid advances in machine intelligence and/or fundamental changes in human behaviors or capabilities over time can outpace R&D. Second, the future conditions under which hybrid intelligence will operate are unknown, but unlikely to be the same as the conditions of today. Overcoming both of these challenges requires a deep understanding of multiple human-centric and machine-centric disciplines that creates a large barrier to entry into the field. Herein, we outline an open, shareable research platform that creates a form of hybrid team intelligence that functions under representative future conditions. The intent for the platform is to facilitate new forms of hybrid intelligence research allowing individuals with human-centric or machine-centric backgrounds to rapidly enter the field and initiate research. Our hope is that through open, community research on the platform, state-of-the-art advances in human and machine intelligence can quickly be communicated across what are currently different R&D communities and allow hybrid team intelligence research to stay at the forefront of scientific advancement.

翻译：Metcalfe等人（1）指出，人机协作的最大潜力在于应对高度复杂的问题空间。本文探讨了混合团队智能的三种不同形式，并认为在所有形式中，人机智能的融合在适当条件下均可发挥效用。我们预见到构建有效混合智能面临两大研发挑战：首先，机器智能的快速进步和/或人类行为与能力的根本性变化可能超越研发速度；其次，混合智能未来运行的环境条件尚不可知，且很可能与当前条件不同。克服这些挑战需要深度融合以人为中心和以机器为中心的多学科知识，这构成了该领域的高准入门槛。本文提出一个开放共享的研究平台，该平台能在具有代表性的未来条件下构建混合团队智能形态。该平台旨在促进新型混合智能研究，使具备人本导向或机器导向背景的研究者能快速进入该领域并开展研究。我们期望通过平台的开放式社区研究，人机智能领域的最新进展能在当前分散的研发社群间快速传播，推动混合团队智能研究始终处于科学发展的前沿。