For decades, design and user experience were built around computers and screens. The discipline of Human-Computer Interaction defined the framework from which we designed, evaluated, and implemented digital systems centered on human use. Its focus was clear: creating interfaces that were efficient, understandable, and task-oriented.

But the object of design has changed: today we interact with systems that learn, anticipate, and act across digital and physical environments. Systems that not only respond to commands, but also make partial decisions and intervene in operational processes.

From this transition, is not incremental, it represents a significant expansion of the discipline. This evolution requires a new conceptual framework: Human-Machine Interaction.

Beyond Human-Computer Interaction

Human-Computer Interaction (HCI) became established as a discipline to study and design the relationship between people and interactive computer systems in a context where the computer was the dominant device. Its scope was defined by three core elements: the user, the computer, and the interface that mediated between them.

The model was stable. The system executed instructions, and design focused on making that execution and the processes involved useful, usable, efficient, and understandable. Even with the rise of mobile devices and technologies embedded in everyday life, the conceptual model did not change much. We were still designing for devices that responded.

However, the object of study has expanded. Today we do not design only for computers. We design for autonomous systems, artificial intelligence, robotics, and connected infrastructures. We design for machines in a broader sense.

When the object of study changes, the discipline is forced to evolve. The history of Human-Computer Interaction is a history of continuous adaptation. Every technological shift required expanding the scope of the discipline.

Human-Machine Interaction does not break with that dynamic. It extends it to systems that no longer only execute, but also act.

Human-Machine Interaction: a necessary expansion

Human-Computer Interaction is still valid for describing the design of interactive computational systems. But when systems stop being only tools and begin to incorporate autonomy, inference, and agency, the term computer becomes insufficient.

It is in this context that I propose using the term Human-Machine Interaction.

Not as a replacement, but as an expansion. Not as a break from tradition, but as a coherent evolution of the discipline. The machine, understood broadly, includes computers, autonomous systems, artificial intelligence, and technologies capable of acting in physical and digital environments.

Human-Machine Interaction expands the field of design and user experience toward scenarios where exchange is no longer only informational or transactional, but also behavioral and operational. Design no longer means only structuring screens and flows. It now implies, among other aspects, defining behaviors, autonomy boundaries, and supervision mechanisms.

When the system can act, design takes on a different responsibility.

Implications of Human-Machine Interaction

If we accept this new approach, the implications are not only terminological. They are strategic. And even if this were simply a language revision, that would not be a problem. Revisiting language is a natural part of how disciplines evolve.

In Human-Computer Interaction, the primary focus was optimizing tasks and improving efficiency of use, as well as improving effectiveness and human performance. In Human-Machine Interaction, that focus expands toward designing systems with higher degrees of autonomy that act and influence processes beyond the interface.

When I talk about a system, I refer to technologies that do not only execute instructions, but also interpret context and produce effects in the environment. As O'Connor and McDermott point out, these are systems that function as a whole while also exhibiting emergent properties in action.

When the machine is no longer contained within a screen and begins to act in shared spaces, the design problem changes in nature: it is no longer enough to optimize an interface; we must design how that behavior is integrated, understood, and supervised in the real world.

In February 2026, The Guardian reported how several humanoid robots performed a choreographed routine during China’s most-watched televised gala. This was not a lab demonstration, but machines acting in a shared physical environment before millions of people.

This introduces new questions:

  • How do we define the degree of autonomy of a system?
  • How do we communicate the intention of a machine that acts?
  • How do we manage human supervision and intervention?
  • Who assumes responsibility when decision-making is shared?

Designing a usable experience is no longer enough. We also need to design systemic behaviors.

At this point, a critical dimension emerges: transparency. In traditional systems, the process was relatively clear. The user knew what action they executed and what result they obtained. In systems with artificial intelligence or operational autonomy, much of the process occurs outside the user’s direct view.

This is where design must decide what to show, what to simplify, and what to explain. Absolute transparency is unfeasible, total opacity should be unacceptable. In short, designing for autonomous systems means finding a balance between technological complexity and human trust.

Impact on design, business, and user experience

The shift toward Human-Machine Interaction does not affect designers alone. It affects entire organizations.

For companies, user experience is no longer a superficial layer and becomes a structural element of how systems operate. Automation, artificial intelligence, and assisted decision-making require design that articulates autonomy and control.

For design teams, scope expands. They are no longer designing only flows or screens, but continuous interactions between people and systems with different levels of action. UX becomes mediation between technological complexity and operational clarity.

When the machine acts, design becomes a mechanism of continuous balance.

When the object of study changes, the discipline changes

Human-Computer Interaction taught us how to design systems centered on human use. It gave us principles and methods. But the context has changed in scale.

When systems incorporate autonomy and agency, design is no longer limited to facilitating tasks. It begins to define behaviors, boundaries, and forms of coexistence.

Human-Machine Interaction is not a new label for an old phenomenon. It is the recognition that the central object of study, research, and application has changed.

The focus does not abandon user experience, but expands toward system behavior and its influence on human and organizational decisions.

Design is no longer only about defining how technology is used, but about establishing the limits of its behavior.