Waymo is now paying DoorDash drivers to walk around Atlanta closing car doors on its autonomous taxis. The news emerged this week as the company scales its robotaxi service, revealing an unexpected coordination failure: passengers frequently exit the vehicles without closing the doors, leaving the cars unable to proceed to their next pickup. The solution? Human workers dispatched through a gig platform to perform a task that takes approximately three seconds.

This is not a minor operational hiccup. It exposes a fundamental problem in how autonomous systems handle the boundary between algorithmic and embodied coordination. Waymo's vehicles can navigate complex traffic patterns and respond to unpredictable road conditions, but they cannot manage the most basic element of the service transaction: ensuring the physical handoff is complete before the next coordination cycle begins.

The Coordination Handoff Problem

Classical coordination theory distinguishes between different governance mechanisms (markets, hierarchies, networks) based on how they manage interdependence between actors (Malone & Crowston, 1994). Platform coordination adds algorithmic mediation to this taxonomy, creating new forms of interdependence management (Kellogg et al., 2020). But Waymo's door problem reveals something more fundamental: autonomous systems create coordination gaps at the interface between algorithmic and physical action.

The vehicle's algorithm can coordinate with other vehicles, with traffic infrastructure, and with dispatch systems. But it cannot coordinate the embodied action of a passenger closing a door. This is not a technical limitation that better sensors can solve. The door remains open because passengers have no schema for understanding their role in the coordination sequence. In a traditional taxi, the driver provides implicit coordination cues: waiting, watching the mirror, sometimes explicitly requesting door closure. The autonomous vehicle provides none of these.

What makes this particularly instructive is Waymo's solution. Rather than redesigning the vehicle interface or attempting to train passengers, the company introduced a third coordination layer: gig workers who serve as physical coordination mediators. This is application layer communication in reverse. Instead of algorithms mediating between humans, humans now mediate between algorithms and physical reality.

The Schema Absence Problem

Platform workers face the awareness-capability gap: they know algorithms govern their work but cannot translate this awareness into effective action (Kellogg et al., 2020). Waymo passengers face the inverse problem. They have no awareness that their physical actions are part of an algorithmic coordination sequence. The vehicle appears autonomous, suggesting it will handle all aspects of the service interaction. This folk theory (that autonomous means fully self-sufficient) creates the coordination failure.

The distinction between topology and topography becomes relevant here. Passengers understand the topography (how to exit a vehicle, how doors work), but they lack understanding of the topological structure: that the service transaction has a defined endpoint requiring their participation. In traditional taxi coordination, this structure is obvious because the driver is physically present. In autonomous coordination, the structure is invisible.

Why Training Cannot Solve This

Waymo could theoretically train passengers through in-vehicle messaging or app notifications. But this assumes passengers would develop procedural memory for a low-frequency action (most users take occasional rides, not daily ones). The cognitive load required to maintain this procedural knowledge exceeds its functional value to the passenger. They have no incentive to internalize the coordination schema because the consequence of failure (an open door) does not affect their immediate experience. They have already exited.

This is why Waymo's solution involves human intermediaries rather than user training. The company recognized that the coordination gap cannot be closed through awareness alone. It requires active intervention by an actor who understands the structural requirement and has both the capability and incentive to fulfill it.

The Implication for Autonomous Service Design

As autonomous systems expand into service contexts, designers face a choice: build systems that can handle all coordination requirements internally, or make coordination structures legible to users. Waymo initially chose the former and discovered its limits. The door problem suggests that truly autonomous service coordination may require either complete physical enclosure of the interaction (automated doors) or explicit schema induction that makes users aware of their role in the coordination sequence.

The current solution, gig workers as coordination mediators, represents a third path: human labor inserted at the precise point where algorithmic coordination fails. This is not a temporary inefficiency. It may be the steady state for autonomous services that interface with unstructured human behavior. The question is whether we recognize these workers as performing genuine coordination labor, or whether we continue to frame door-closing as a minor task rather than the resolution of a structural coordination gap.