“State of the scs union” speech by Giancarlo Guizzardi

Colleagues and friends,

We operate where formal models meet human behavior, where technical rigor collides with social reality, and where automation constantly tempts us to believe that complexity can be eliminated rather than understood.

In this context, we sustain that complexity does not disappear when ignored but it merely reappears as risk; that systems do not “understand” by themselves; that meaning is not extracted automatically from data, but it is constructed, negotiated, and contextual.

Our responsibility is not to be impressed by surface performance of trendy technologies, but to ask what assumptions are embedded, what distinctions are erased, and what categories are silently imposed. For us, taking Ontology and semantics seriously is not an academic luxury, but a defense against conceptual confusion.

Most system failures are caused by misaligned incentives, misplaced trust, and poorly understood socio-technical dependencies. Systems are not isolated artifacts, but embedded in organizations, regulations, and human practices. Security is not a property that can be added at the end, but a fragile equilibrium that must be continuously maintained.

Service-oriented systems promise flexibility, scalability, and interoperability. But without the right approach, what they often deliver is opacity: responsibility becomes distributed, accountability diluted, and failures harder to explain. Here again, Ontology and semantics are not optional. Without shared meaning, interoperability is an illusion, and automation merely accelerates misunderstanding.

Progress in science is not measured by the number of definitive answers we provide, but by the quality of the questions we are able to sustain. We continuously advance methods to clarify concepts, frameworks to reason about trust and responsibility, and models that expose hidden assumptions. This is slow work, often invisible, and increasingly countercultural in an academic environment obsessed with speed and metrics.

Education remains one of our most consequential responsibilities. We are not training students to chase technological trends, but to outlive them. The tools they learn today will be obsolete tomorrow; the habits of critical thinking, conceptual precision, and epistemic humility will not. If our graduates leave knowing how to question system boundaries, challenge simplistic claims about “intelligence,” and recognize the ethical implications of design choices, we have done our job.

We resist the temptation to simply follow the loudest narratives. We also do not reject them reflexively, but we examine them carefully, and when necessary, disappoint. We say: this does not work the way you think it does. We insist that understanding precedes automation, and that responsibility cannot be delegated to artifacts.

We are a group that insists on clarity in times of hype, on rigor in times of acceleration, and on responsibility in times of delegation. In a technological landscape increasingly driven by what can be built, we remain committed to asking what should be built, under which assumptions, and at what cost.

We commit to building systems we can understand and trust. Systems that are semantically transparent and uphold human purposes. We commit to Meaningful Computing.