Today (20 Jan 2026), I find it valuable to reflect on a point raised by Elon Musk in his three-hour interview on the Moonshots podcast. I was particularly intrigued by his explanation of why he believes he has grown more effective as a problem-solver over the past decade. At around 1:50:17 in the conversation, Elon argues that this growth stems from repeatedly tackling complex problems across different fields. According to him, working in multiple arenas facilitates a cross-fertilization of problem-solving approaches, such that techniques that are routine in one domain can become exceptionally powerful when transferred to another.
Here are his original quotes (Musk et al., 2026):
“Well, I’ve had to solve a lot of problems in a lot of different arenas, which you get this cross fertilization of knowledge of problem solving. And if you solve problems in a lot of different arenas, then like, what is easy in one arena is trivial in…It is like, what is trivial in one arena is a superpower in another arena. it’s sort of like Planet Krypton — you came from planet Krypton everything, so you know planet Krypton, you just be normal. But if you come to earth, you’re a superman. So, if I take volume manufacturing of complex objects in the automotive industry (I have to work on solving that), when translated to the space industry it’s like be a superman. Because rockets are made in very small numbers. If you apply automotive manufacturing technology to satellites and rockets, it’s like being Superman. Then if you take advanced material science from rockets, and you apply that to the automotive industry, you get Superman again. Yeah, that’s came from planet Krypton, back in planet Krypton this is normal.
This idea of cross-fertilization across fields is deeply compelling to me. In my own case, I want to explore whether the different “pillars” of my daily intellectual interests can foster a similarly cross-fertilizing way of working—more specifically, how different disciplines can strengthen one another by contributing their distinctive advantages. My work and intellectual interests revolve around three interconnected domains: (1) behavioral psychology, which forms the core of my PhD research; (2) design, which I developed through my bachelor’s and master’s education; and (3) philosophy, which shapes how I approach and think about things more broadly. The following text outlines how I currently understand the underlying logic of each domain and how they can mutually benefit one another.
First, I see behavioral psychology as grounded in a disciplined causal logic, with experimental research as its most rigorous expression. The experimental research mindset begins with constructs (in my own research, this can refer to perceived novelty about things), then operationalize them into measurable variables, then design manipulations that produce treatment variance while eliminating or balancing confound variance and finally minimizing error variance through reliable measurement and standardized procedures. The ideal is not merely to observe patterns, but to make the most credible claim about causality by engineering a situation where alternative explanations are systematically weakened (random assignment, control groups, manipulation checks, counterbalancing, blinding, when possible, pre-registered analyses, and careful attention to demand characteristics). This logic also forces precision about moderation and mediation (under what conditions an effect occurs, and through which mechanism, etc.). Crucially, if something cannot be manipulated or measured in a defensible way, it should not be asserted as the driver of an effect.
Design, by contrast, is not primarily about isolating causes; it is about constructing possibilities under constraints. Rather than asking “what caused what?”, design asks “what could be made possible here?” Its intelligence (as well as creativity) lies in generating, shaping, and selecting options that are both novel and workable. Where experimental research deliberately simplify reality to constructs, design must resynthesize complexity into solutions that can function in real life. In that sense, design reasoning is both abductive and generative: it moves from observations of use (and perhaps user frustration) to a plausible design hypothesis about what kinds of design/interaction might improve user experience (e.g., a feature that reopens attention, reorganizes meaning, or invites exploration). It then iterates, not to isolate one causal factor, but to build an integrated experience in which many elements must cohere (timing, feedback, aesthetics, friction, and affordance). What looks “messy” through an experimental lens is often essential to design, because real experience is often much more complicated than variable-by-variable. The output is not only a claim nor an argument, but an artifact (or intervention) that makes a new way of acting possible.
Adding to that, although philosophy is not my formal discipline but a personal interest, it adds another kind of rigor: conceptual and normative accountability in a broad sense. It pushes me to ask what my key terms mean, what distinctions I rely on, what assumptions are hidden, and whether my inferences are valid. In my research, philosophical thinking helps sharpen arguments not by testing them empirically, but by clarifying conceptual boundaries and strengthening the logic of reasoning. For example, it supports concept formation by identifying necessary and sufficient conditions and by drawing boundaries (such as distinguishing novelty as mere stimulation from novelty that genuinely triggers curiosity). It also encourages explicit reasoning about levels of explanation, making tensions visible rather than hiding it inside in vague language. In that sense, philosophy helps clarify the “architecture of reasons”: what follows from what, and what one is entitled to claim.
The cross-fertilization between behavioral psychology and design becomes most evident when each is seen as addressing the other’s hardest problems. A limitation of behavioral psychology is that it can yield clean causal insights that remain under-specified as interventions. For instance, an experimental study may demonstrate that novelty cues play a role in helping us re-engage with our existing products. However, it rarely provides insights into how these cues should manifest in a real-world interface. Design provides the missing translation layer by turning mechanisms into concrete forms that people can actually encounter. Conversely, a limitation of design is that it can produce compelling artifacts whose success is causally opaque: even if users are intrigued by a prototype, it is often unclear which feature drove the response, which mechanism was activated, or whether the effect would persist over time. Experimental logic provides the missing sieve by isolating components, testing mechanisms, identifying moderators, and preventing design from mistaking a persuasive story for a robust effect.
Now let’s map the pairwise cross-fertilizations between behavioral psychology and philosophy. Philosophy has a potential to fertilize behavioral psychology by clarifying what exactly is being studied and what kind of claim is being made. Many disputes in psychology are not only empirical; they are conceptual (for example: whether a measure captures curiosity or merely information seeking, whether the notion of “value” is subjective appraisal or normative endorsement). In this sense, philosophical thinking could benefit the field of behavioral psychology by avoiding conceptual ambiguity and reducing chaos in the process of reasoning. Conversely, behavioral psychology could also fertilize philosophy by constraining it with reality. Philosophical distinctions about concepts (such as motivation, autonomy, meaning, or well-being) become sharper when confronted with empirical findings about boundary conditions. In this regard, this appear to be a powerful loop: philosophy sharpens the questions and concepts; experiments test which parts survive contact with human behavior; the results then feed back into better conceptual refinement (rather than leaving “value” or “meaning” as untouchable abstractions).
Finally, consider the relationship between design and philosophy. I do not yet have a fully settled account of how these two domains fertilize one another, and an in-depth treatment would go beyond the scope of this text. Still, the connection is well established, and many scholars explicitly work at the intersection of design and philosophy (e.g., Parsons, 2015; Secomandi & Verbeek, 2026). From my current understanding, philosophy contributes to design primarily by interrogating and justifying the assumptions embedded in design decisions. Design choices often function like implicit arguments, for example: “If we make the interface frictionless, users will do X, and that is better because Y.” Philosophy pushes this reasoning one step further by asking what “better” means, for whom it is better, and what trade-offs that improvement implies. This helps explain why design philosophy frequently focuses on issues such as technology ethics, (de)colonial critiques of technology, and inclusive design. It is less intuitive for me to specify how design contributes back to philosophy, but one promising route is speculative design. Speculative design can make abstract philosophical positions concrete by embodying them in artifacts. When a philosophical stance is being materialized in a prototype, it becomes possible to examine what it enables, what it constrains, what harms it might introduce, and what it reveals about lived experience. In this sense, design does not merely argue about the world; it stages an argument as a tangible possibility, often to provoke reflection and discussion rather than to deliver an immediately “optimal” solution.
The cross-fertilization emerges most clearly when we treat these three fields as distinct yet complementary modes of thinking that jointly sharpen our thinking. Philosophy strengthens the conceptual core: it clarifies what we mean by introducing new concepts, makes hidden assumptions explicit, and forces rigor in the inferential steps from premises to conclusions (including what trade-offs are acceptable, and what forms of manipulation are out of bounds). Design strengthens the constructive core: it translates abstract concepts and mechanisms into concrete, experienceable forms, and it can also function speculatively by materializing a stance in an artifact to provoke reflection on what a “better” relation to technology/society/future could be. Behavioral psychology, guided by experimental logic, strengthens the evidential core: it tests which design features and mechanisms actually produce the intended psychological shifts, under what boundary conditions, etc.
Reference:
- Musk, E., Diamandis, P. H., & Blundin, D. [Moonshots]. (2026, 01). Elon Musk on AGI Timeline, US vs China, Job Markets, Clean Energy & Humanoid Robots [Video]. YouTube. https://youtu.be/RSNuB9pj9P8?t=6702
- Parsons, G. (2015). The Philosophy of Design. John Wiley & Sons.
- Secomandi, F., & Verbeek, P.-P. (2026). Design Philosophy after the Technology Turn. Bloomsbury Publishing.
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