Growing interest and investment in the capabilities of foundation models has positioned such systems to impact a wide array of public services. Alongside these opportunities is the risk that these systems reify existing power imbalances and cause disproportionate harm to marginalized communities. Participatory approaches hold promise to instead lend agency and decision-making power to marginalized stakeholders. But existing approaches in participatory AI/ML are typically deeply grounded in context - how do we apply these approaches to foundation models, which are, by design, disconnected from context? Our paper interrogates this question. First, we examine existing attempts at incorporating participation into foundation models. We highlight the tension between participation and scale, demonstrating that it is intractable for impacted communities to meaningfully shape a foundation model that is intended to be universally applicable. In response, we develop a blueprint for participatory foundation models that identifies more local, application-oriented opportunities for meaningful participation. In addition to the "foundation" layer, our framework proposes the "subfloor'' layer, in which stakeholders develop shared technical infrastructure, norms and governance for a grounded domain, and the "surface'' layer, in which affected communities shape the use of a foundation model for a specific downstream task. The intermediate "subfloor'' layer scopes the range of potential harms to consider, and affords communities more concrete avenues for deliberation and intervention. At the same time, it avoids duplicative effort by scaling input across relevant use cases. Through three case studies in clinical care, financial services, and journalism, we illustrate how this multi-layer model can create more meaningful opportunities for participation than solely intervening at the foundation layer.

翻译：随着对基础模型能力日益增长的兴趣与投资，这类系统正被定位为影响广泛公共服务的关键技术。伴随这些机遇而来的是风险：这些系统可能固化现有的权力失衡，并对边缘化群体造成不成比例的伤害。参与式方法有望将决策权与能动性赋予边缘化利益相关者。然而，现有参与式AI/ML方法通常深度依赖于具体情境——我们应如何将这些方法应用于本质上脱离情境设计的基础模型？本文深入探讨了这一核心问题。首先，我们系统考察了现有将参与机制融入基础模型的尝试，揭示了"参与性"与"规模化"之间的内在张力，论证了让受影响社区有意义地塑造一个旨在普遍适用的基础模型具有理论上的不可行性。基于此，我们构建了参与式基础模型的蓝图，提出更具在地性、面向应用场景的实质性参与路径。除"基础层"外，本框架创新性地引入"基层"——利益相关者为特定领域共建共享技术基础设施、规范与治理机制；以及"应用层"——受影响社区针对具体下游任务塑造基础模型的使用方式。作为中间层的"基层"通过界定潜在危害的考量范围，为社区提供了更具体的审议与干预路径，同时避免重复劳动，实现跨相关用例的规模化意见整合。通过临床医疗、金融服务与新闻传播三大领域的案例研究，我们论证了这种多层模型相较于仅在基础层干预，能创造更具实质意义的参与机会。