The Diffractive Apparatus: Ontology as the New Frontier of Healthtech 3.1

As artificial intelligence becomes ubiquitous and its infrastructure increasingly commoditized, the innovation center of gravity shifts from engineering capability to philosophical clarity. The decisive questions are no longer can we build this, but why we build it, what assumptions we encode, and which values we operationalize. Philosophy becomes the primary differentiator. The choices we make about meaning, agency, purpose, and human experience ultimately define our products far more than the technical stack beneath them.

Every product is a philosophy expressed in design.

This dynamic becomes especially consequential in health technologies, where design choices directly configure how life is sensed, interpreted, and acted upon.

Before a single measurement occurs, a system has already embedded a worldview: assumptions about what matters, which bodies become legible, and what forms of life count as intelligible. Technologies do not simply observe the body; they shape its possibilities.

In Healthtech 3.0, the defining competitive advantage is not data, algorithms, or insights—it is the ontology a company brings into being.

Borrowing from the theory of quantum physics, physicist-philosopher Karen Barad offers a useful language for this, calling the integrated arrangement of tools, models, assumptions, and interactions the apparatus. An apparatus is not merely a passive witness but an active participant in making the world it measures. Because measurement is world-making, the design of health technologies is always, consciously or not, an ontological act—one that generates the realities in which both patients and practitioners operate.

The Apparatus as World-Maker

In quantum physics, measurement does not uncover a fixed truth; it produces one. Heisenberg and Bohr showed that observer and observed are inseparable, and that observation collapses the quantum wavefunction (encapsulation the myriad of possible arrangements) into a concrete phenomenon.

Healthtech operates under a similar logic. Sensors, assays, and algorithms determine what counts as legible data, translating physiology through filters that are never neutral. What becomes measurable becomes actionable—and what becomes actionable becomes “real” within a system.

Karen Barad’s philosophical framework, agential realism, expands the quantum logic beyond the realm of the small into the fabric of everyday phenomena, showing how matter, meaning, and measurement are co-constituted across all scales. It reminds us that technologies shape the worlds of meaning and practice we inhabit. Under this lens, Healthtech 3.0—the convergence of biology, computation, and behavior—is not merely a digital extension built on top of medicine. It is a world-building engine that defines what health and sickness mean, and ultimately, how human life can unfold. We are not only quantifying life; we are programming what life can be.

The Diffractive Stack

The diffractive stack describes how coherence across the three technology layers—the scientific, infrastructural, and experiential—turns a healthtech product into a living apparatus. When insights from one layer interfere with and inform the others, the system becomes adaptive, self-correcting, and contextually alive. This is epistemic coherence: a unified, dynamic logic of health that enables scale. Many healthtech failures trace back to incoherence across layers, where biology, code, and experience diverge into incompatible worlds.

To build a diffractive apparatus, companies must align their philosophical commitments across:

• phenomenon design: defining a new, meaningful health reality
• agential infrastructure: systems that can explain themselves, and
• collaborative intra-action: giving users partial authorship of insight.

This is where the three layers emerge as the foundational building blocks of diffractive design.

The Three Layers: Scientific, Technical, Human

Any health technology spans three interlinked domains: the scientific (what becomes visible), the technical (how that visibility is encoded), and the human (how it is lived and acted upon). In practical terms, these correspond to the underlying IP/science, the coded infrastructure, and the application/user layer.

Every startup begins with a fundamental choice about what counts as signal and what counts as noise across each of these three domains. These first choices, what Barad calls ontological cuts, set the trajectory of the world the product will construct. When the cuts across scientific, technical, and human layers align, the product builds trust and coherence.  When they drift, companies fracture into incompatible internal realities, and struggle to scale.

Choices Inform New Realities

Coherence across domains is necessary, but not sufficient for disruptive and meaningful innovation. Companies choosing to build reflective systems (in Barad’s terminology), only digitize what we already believe, reflecting or mirroring an existing world-view. Calorie counters and step trackers are a good example of these systems: they mirror familiar metrics without producing new insight.

Diffractive systems, by contrast, reveal something previously invisible. They unfold a new reality by revealing new signals, linkages, or forms of health that shift how individuals and clinicians understand the body.

A few examples of healthtech diffractive systems:

QuantHealth’s simulation-based trials turn a retrospective cohort into a computational population that produces new forms of evidence.

The individualized cardiac digital twin by the Helsinki University Hospital tracks coherence across ECG, medication timing, movement, and recovery patterns, predicting deterioration through subtle signal dynamics rather than thresholds.

23andMe built a world in which health becomes probabilistic and ancestry becomes destiny. Levels built one where metabolism becomes dynamic and individualized.

Neko Health treats whole-body scanning as a continuous sensory layer rather than a periodic diagnostic check, redefining what counts as early detection and what becomes visible as ‘health’ in the first place.

Each of these companies made an ontological gamble: this is what matters; this is the body we will measure; this is the body as we will define it.

Designing for Relational Intelligence

Digitalization, integration, and personalization are necessary but not sufficient to create a diffractive system.

In fact, many new digital health platforms encode a worldview in which integration, digitalization and personalization are key elements, yet the body is understood mostly as a machine to be optimized. Scoring and gamification incentivize initial adoption, but eventually drift into loops of self-surveillance.

Diffractive systems take a different approach. They surface interdependence among signals, treat physiology and context as entangled, and prioritize patterns over prescriptions. This marks the emergence of relational intelligence: systems that not only interpret signals but evolve with users over time.

In Barad’s term, these systems embody intra-action, where human, digital, and biological agents mutually shape one another. The central design question becomes whether a system enforces a fixed worldview or adapts to the shifting world the user inhabits.

Technologies such as Omada Health and HeartMath illustrate this dynamic, allowing user input to refine and reshape algorithmic outputs.

As relational intelligence deepens, users transition from objects of measurement to participants in meaning-making. The paradox of great healthtech is that its best users eventually need it less—a sign not of disengagement, but maturation.

The Ethics of Design

Every apparatus performs a cut, deciding what falls within its field of measurement and what remains outside it. It defines whose bodies, histories, and experiences are legible to a system—and whose are effectively erased. The question, then, is not whether health technologies are neutral; it is what kind of reality they normalize.

Acknowledging this cut is not moral posturing but strategic responsibility. When the cut is too narrow—relying on limited cohorts, outdated biology, or simply narrow metrics of what health may be—the world it constructs breaks under the pressure of real diversity.

Ethics, in this context, is not an external constraint but an internal architecture: every product encodes a theory of what a body is, what counts as evidence, and what forms of life are intelligible. Different companies enact different ethical worlds, not because one is superior, but because each performs a distinct agential cut.

In biomedical intelligence, QuantHealth and Owkin model the clinical world through fundamentally different lenses: one treats the trial as a simulated and adaptive population, while the other grounds intelligence in federated observational learning.

In prevention, Neko Health frames the body as a continuously updating physiological field while Prenuvo treats tit as a high-resolution archive to be periodically examined.

Each of these companies' approach is an ethical stance about what kind of evidence should guide therapeutic decisions, how the body should appear in data, and which temporalities of health are made legible.

Seen this way, the ethics of health technology lies not in compliance checklists but in the ontological commitments that shape which lives become knowable, actionable, or supported by care. An apparatus is ethical not because it avoids harm, but because it declares, with precision, the kind of world it is bringing into being.

Healthcare 3.1 — Towards Systems that Co-Author Realities

Healthtech sits at a key inflection point. As biology, computation, and ecological instability converge, health becomes an ecological condition, distributed across bodies, environments, and infrastructures.

In this expanded terrain, companies like Cityblock Health treat care as an ecological network rather than a clinical encounter, illustrating how new ontologies reorder not just medical workflows but entire systems of relation.

The next wave of health technology will not be defined by who gathers the most data, but by who articulates the clearest stance on what counts as health. Together, these shifts highlight a deeper question: not how much data we capture, but what world our measurements bring into being.

Healthcare 3.1 builds on diffractive logic by extending coherence across layers into ongoing coordination among phenomena, infrastructure, and user agency. It stays within the ontology of HealthTech 3.0 but expresses its mature, entangled form.

In this stage, health technologies move beyond optimization toward ontological design—systems that evolve with the realities they help create. Users become co-authors of insight, data becomes a living material, and measurement becomes inseparable from meaning. The most ambitious companies will treat ontology—not computation—as their primary intellectual property, recognizing that every product is, ultimately, a philosophy rendered in code.