Technological Understanding: On the cognitive skill involved in the design and use of technological artefacts

This paper proposes a philosophical account of "technological understanding" as a cognitive skill analogous to scientific understanding, defining it as the ability to recognize how to use or design technological artefacts to achieve practical aims, a concept illustrated through MRI and superconducting quantum computers.

The Gist

The Big Idea: What Does It Mean to "Get" Technology?

We often talk about "understanding" science. For example, a scientist understands why the sky is blue because they have a theory that explains it. But what does it mean to "understand" technology?

This paper argues that technological understanding isn't just about knowing how a machine works on the inside. It's a specific mental skill: the ability to look at a problem and know exactly how to build or use a tool to fix it.

Think of it like this:

• Science is like a Map. It helps you understand why a mountain is there and how the weather works.
• Technology is like a Hiking Boot. It doesn't explain the mountain; it helps you climb it.

"Technological understanding" is the skill of knowing exactly which boot to wear, how to lace it up, and how to step so you reach the summit without falling.

---

The Core Analogy: The Theory vs. The Tool

The authors build their idea by comparing Scientific Theories to Technological Artefacts (tools/machines).

The Scientist (The Map Maker)	The Engineer (The Boot Maker)
Goal: To explain a phenomenon (e.g., "Why does gravity pull things down?").	Goal: To solve a practical problem (e.g., "How do I get to the moon?").
Tool: A Theory (a set of ideas).	Tool: An Artefact (a physical object like a rocket).
Success: Can they use the theory to explain what happens?	Success: Can they use the tool to achieve the goal?
Understanding: Knowing how to use the theory to explain the world.	Understanding: Knowing how to use the tool to change the world.

The paper says that just as a scientist needs to "get" a theory to explain nature, an engineer needs to "get" a tool to build something useful.

---

The Three Ingredients of a Tool

To understand a tool, you have to see it as a three-part sandwich:

1. The Structure (The Hardware): The physical parts. (e.g., the metal, the wires, the chips).
2. The Phenomenon (The Magic): The physical thing that happens when you turn it on. (e.g., electricity flowing, magnets spinning, quantum particles jumping).
3. The Aim (The Goal): What you actually want to achieve. (e.g., taking a picture of a brain, calculating a drug formula).

Technological Understanding is the mental glue that holds these three together. It's the ability to say: "If I build this specific structure (1), it will create this specific magic (2), which will solve this specific problem (3)."

---

The "Intelligibility" Test: Is the Tool "Readable"?

You can't understand a tool if it's a "black box." The paper introduces a concept called Intelligibility.

Imagine you are handed a mysterious, ancient device.

• Low Intelligibility: You press a button, and a light turns on. You have no idea why. You can't predict what will happen if you press it twice. You don't understand it.
• High Intelligibility: You know that if you press the button, the light turns on. If you twist the knob, the light gets brighter. You can predict the outcome without even turning it on. You do understand it.

Technological Understanding means the tool is "intelligible" to you. You can mentally simulate how it works and predict the results.

---

The Two Examples: MRI vs. Quantum Computers

The authors use two examples to show the difference between having understanding and lacking it.

1. The MRI Machine (We Have Understanding)

• The Goal: See inside a human body without cutting it open.
• The Status: We have built these for decades.
• The Understanding: Doctors and technicians know exactly how the magnets and radio waves work together to create an image. They can tweak the settings and predict, "If I change this, the image will show a tumor."
• Verdict: We have Technological Understanding. The tool is intelligible.

2. The Superconducting Quantum Computer (We Lack Full Understanding)

• The Goal: Solve complex math problems that normal computers can't handle (like designing new medicines).
• The Status: We have the science (we understand the physics of quantum particles), but we haven't built a working, reliable machine yet.
• The Problem: We know the "magic" (quantum physics), but we can't figure out the "structure" (the hardware) that keeps the magic stable long enough to do the job. The machine is still a bit of a black box; it breaks easily, and we can't reliably predict its behavior.
• Verdict: We have Scientific Understanding (we know the physics), but we lack Technological Understanding (we can't build the tool to use that physics).

---

The Designer's Superpower

The paper concludes that the highest form of technological understanding is Design.

Designing a new technology is like being a chef who has to invent a new recipe from scratch.

• You have a Goal (a delicious meal).
• You have a Pantry (laws of physics and available materials).
• Technological Understanding is the skill of looking at the pantry and saying, "If I mix these specific ingredients in this specific way, I will create the flavor I need."

It's not just about knowing the ingredients (science); it's about knowing how to combine them to create a result (technology).

Summary

Technological Understanding is the cognitive skill of being able to look at a practical problem and knowing how to build or use a tool to solve it. It requires the tool to be "intelligible"—meaning you can predict how it works without needing to guess. When we can't build a tool yet (like a perfect quantum computer), it's not because we lack science; it's because we haven't yet achieved the technological understanding needed to turn that science into a working machine.

Technical Summary

1. Problem Statement

Despite the extensive philosophical literature on scientific understanding (specifically the ability to explain phenomena using theories), the concept of understanding in relation to technology remains underexplored. Existing accounts either focus on the knowledge required for design/use without addressing the cognitive skill of application, or they focus on "opaque" technologies (like AI) from a hermeneutic or public debate perspective.

The authors identify a critical gap: there is no comprehensive, epistemically informed philosophical account of what it means to "understand" a technology. This lack of definition renders calls for "improved technological understanding" vague and ineffective. The paper aims to fill this gap by defining technological understanding as a specific cognitive skill required for designing, reasoning about, and using technological artefacts.

2. Methodology

The authors employ a conceptual analysis and analogical reasoning approach, grounded in the philosophy of science and technology:

• Theoretical Foundation: The paper builds directly on Henk de Regt's (2017) account of scientific understanding. De Regt defines scientific understanding not merely as possessing knowledge, but as the cognitive skill to use an intelligible theory to explain phenomena.
• The Core Analogy: The authors construct a heuristic analogy between scientific theories and technological artefacts:
  • Science: Uses theories to explain natural phenomena (answering "Why?").
  • Technology: Uses artefacts to exploit phenomena to achieve practical aims (answering "How to solve?").
• Case Studies: The theoretical framework is illustrated and tested using two contrasting examples of quantum technology:
  1. Magnetic Resonance Imaging (MRI): A mature, first-generation quantum technology where the artefact is fully intelligible and functional.
  2. Superconducting Quantum Computers: A second-generation, emerging technology where the artefact is not yet fully realized, serving as a counter-example to illustrate the lack of technological understanding in design contexts.
• Conceptual Decomposition: The authors deconstruct the "technological artefact" into specific components (Physical Structure, Physical Phenomenon, Direct Aim, Ultimate Aim) to map the cognitive requirements of design.

3. Key Contributions

A. Definition of the Technological Artefact

The authors propose a tripartite definition of a technological artefact ($t$) as a functional object consisting of:

1. Physical Structure ($X$): The material construction (e.g., magnets, circuits, chips).
2. Physical Phenomenon ($P$): The functional physical effect produced by the structure (e.g., magnetic resonance, quantum entanglement).
3. Direct Aim ($a$): The specific technological response or output (e.g., generating a medical image).

• Ultimate Aim ($A$): The external practical goal the artefact serves (e.g., medical diagnosis). The authors distinguish between the direct aim (internal to the artefact) and the ultimate aim (external context), noting that the artefact is a triple $\langle X, P, a \rangle$ that approximates $A$.

B. The Concept of Technological Understanding

The paper defines Technological Understanding as the cognitive skill to recognize how a technological artefact can be used to realize a practical aim.

• Analogy to Science: Just as scientific understanding is the ability to use a theory to explain a phenomenon, technological understanding is the ability to use an artefact to achieve a goal.
• The Criterion for Technological Understanding (CTU): An aim $A$ is technologically understood if it can be realized by using a technological artefact $t$.
• The Criterion for Intelligible Technological Artefacts (CITA): An artefact is intelligible to a subject $S$ in context $C$ if $S$ can qualitatively recognize the characteristic consequences of the artefact's operations without practically performing them. This mirrors De Regt's criterion for scientific theories.

C. Typology of Understanding (Logical Options)

The authors categorize technological understanding into three logical specifications based on whether the aim and the artefact are fixed or open:

1. Minimal Account: Both aim and artefact are fixed. Understanding is the ability to operate the artefact and explain its output.
2. Maximal Account: Both aim and artefact are open. Understanding involves conceptualizing a new relationship between a need and a potential solution.
3. Via Media (Design Context): The aim is fixed, but the artefact is open. This is the focus of the paper. It involves designing an artefact to meet a specific need.

D. The Design-Specific Contribution

In the context of design, the authors highlight a crucial asymmetry between scientific and technological understanding:

• Science: The phenomenon ($P$) is given; the task is to find a theory to explain it.
• Technology: The aim ($A$) is given; the task is to select a phenomenon ($P$) and design a structure ($X$) to produce it.
• Key Insight: Technological understanding in design requires the cognitive skill to integrate $X$, $P$, and $a$ effectively. It is not just applying scientific knowledge but creatively selecting which physical phenomena to exploit to solve a problem.

4. Results and Illustrations

• MRI Example (Success): Technological understanding is present. Engineers and radiologists can qualitatively predict how adjusting magnetic fields ($X$) produces specific tissue contrasts ($P$) to achieve medical diagnosis ($A$). The artefact is intelligible; the link between structure and aim is established.
• Superconducting Quantum Computers (Failure/Incompleteness): While there is scientific understanding of quantum mechanics (superposition, entanglement), there is currently a lack of technological understanding regarding the full realization of the aim (fault-tolerant computation).
  • The "triple" $\langle X, P, a \rangle$ is not yet fully intelligible.
  • Engineers cannot yet qualitatively predict how to scale qubits ($X$) to maintain coherence ($P$) for reliable computation ($a$).
  • The paper argues this is an epistemic failure: the artefact is not yet intelligible because the consequences of its operation cannot be reliably recognized or controlled without trial-and-error.

5. Significance

• Epistemic Dimension of Technology: The paper shifts the focus of technology from purely instrumental or social constructs to an epistemic activity. It argues that designing and using technology is a cognitive skill comparable to scientific explanation.
• Context-Dependence: It establishes that "understanding" is not binary but context-dependent. One can understand how to use an MRI (minimal account) without understanding how to design one (via media account).
• Diagnostic Tool: The framework provides a way to diagnose why certain technologies fail or remain "black boxes." If a technology lacks "technological understanding," it is because the link between its physical structure and its intended aim is not yet intelligible to the relevant community (e.g., the current state of quantum computing).
• Beyond "Knowledge": The paper distinguishes between knowing facts (scientific knowledge) and understanding (the skill to apply that knowledge to realize aims). This clarifies that possessing scientific theories is insufficient for technological success; one must possess the skill to operationalize them.
• Future Research: The framework sets the stage for assessing and improving technological understanding in specific domains, moving beyond vague calls for "explainability" to concrete criteria for intelligibility in design and operation.

In summary, the paper successfully transfers the philosophy of scientific understanding into the realm of technology, defining technological understanding as the cognitive skill of intelligibility required to bridge the gap between physical structures and practical human aims.