A minuscule fraction of the deep sea has been scientifically explored and characterized due to several constraints, including expense, inefficiency, exclusion, and the resulting inequitable access to tools and resources around the world. To meet the demand for understanding the largest biosphere on our planet, we must accelerate the pace and broaden the scope of exploration by adding low-cost, scalable tools to the traditional suite of research assets. Exploration strategies should increasingly employ collaborative, inclusive, and innovative research methods to promote inclusion, accessibility, and equity to ocean discovery globally. Here, we present an important step toward this new paradigm: a collaborative design study on technical capacity needs for equitable deep-sea exploration. The study focuses on opportunities and challenges related to low-cost, scalable tools for deep-sea data collection and artificial intelligence-driven data analysis. It was conducted in partnership with twenty marine professionals worldwide, covering a broad representation of geography, demographics, and domain knowledge within the ocean space. The results of the study include a set of technical requirements for low-cost deep-sea imaging and sensing systems and automated image and data analysis systems. As a result of the study, a camera system called Maka Niu was prototyped and is being field-tested by thirteen interviewees and an online AI-driven video analysis platform is in development. We also identified six categories of open design and implementation questions highlighting participant concerns and potential trade-offs that have not yet been addressed within the scope of the current projects but are identified as important considerations for future work. Finally, we offer recommendations for collaborative design projects related to the deep sea and outline our future work in this space.

由于若干限制因素，包括费用、效率低下、排斥以及由此导致的全球工具和资源获取不公平，深海的一小部分已被科学探索和表征。为了满足了解地球上最大的生物圈的需求，我们必须通过在传统的研究资产套件中添加低成本、可扩展的工具来加快步伐并扩大探索范围。勘探战略应越来越多地采用协作、包容和创新的研究方法，以促进全球海洋发现的包容性、可及性和公平性。在这里，我们向这一新范式迈出了重要一步：关于公平深海勘探的技术能力需求的协作设计研究。该研究侧重于与用于深海数据收集和人工智能驱动的数据分析的低成本、可扩展工具相关的机遇和挑战。它是与全球 20 名海洋专业人士合作开展的，涵盖了海洋空间内地理、人口统计和领域知识的广泛代表性。研究结果包括对低成本深海成像和传感系统以及自动化图像和数据分析系统的一系列技术要求。作为研究的结果，一个名为 Maka Niu 的摄像系统已经完成原型设计，并正在由 13 名受访者进行现场测试，并且正在开发一个在线 AI 驱动的视频分析平台。我们还确定了六类开放式设计和实施问题，突出了参与者关注的问题和潜在的权衡，这些问题尚未在当前项目的范围内得到解决，但被确定为未来工作的重要考虑因素。最后，我们为与深海相关的协作设计项目提供建议，并概述我们在这一领域的未来工作。