Discussions about how heuretics happen are often muddled because of vocabulary. Ideally, we would have orthogonal terms that ‘span’ the relevant information about the process of creating new things. This is an attempt to massage existing frameworks into a set of orthogonal terms.
The Quadrant Model of Scientific Research has two axes - Consideration of Use and Quest for Fundamental Understanding. “Consideration of use” is tricky because as Jason Crawford pointed out, you need to note who is considering the use - the scientist might not be considering the use but the person funding them may. There’s also the expectation that enough research that has no consideration of use will eventually lead to something valuable because of the track record of the first half of the 20th century.
BUT we may have screwed up cause and effect by thinking that all use-unconsidered research led to amazing things, while it’s actually only things in Bohr’s quadrant. The increasing number of scientists created more competition and pushed people to do research in the lower left quadrant. So while there’s lots of “No considerations of use” most of it may not actually be a quest for fundamental understanding.
According to the NSF in What is Basic Resesarch
A worker in basic scientific research is motivated by a driving curiosity about the unknown.
Basic research is performed without thought of practical ends.
The essential difference between basic and applied research lies in the freedom permitted the scientist.
In applied work his problem is defined and he looks for the best possible solution meeting these conditions.
However, according to modern NSF in a recent budget
Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts. Basic research may include activities with broad or general applications in mind, such as the study of how plant genomes change, but it should exclude research directed toward a specific application or requirement, such as the optimization of the genome of a specific crop species.
Applied research is original investigation undertaken to acquire new knowledge. Applied research is, however, directed primarily toward a specific practical aim or objective.
There’s actually three interlinked criteria here. One is “what’s motivating the researcher?” “where is the problem coming from?” And “how specific is the practical application?” Note that this last question is only introduced in the modern definition of basic/applied, and the question of where the problem is coming from is absent in the modern definition. At the end of the day, the Basic/Applied framework is intimately tied to a world where research becomes a commoditized good and the original distinction was basically between “is the scientist working for the government or not?” Now it’s become … weird and awkward.
The “specificity” axis feels especially problematic for the basic -> applied pipeline model of innovation. There are many examples in history of someone discovering a broadly applicable principle by studying some very focused problems.
The question of ‘where is the problem coming from?” is actually less clear cut than one might expect at first glance. One might be tempted to say in Basic Research the researcher “comes up with their own problem.” However, there are many clearly defined problems in fundamental physics like “Under which conditions do smooth solutions to the Naiver—Stokes equations exist?” Intuitively, someone working on that problem would still be doing basic research. So I might adjust the definition of Basic research to be that the researcher gets to choose their own problem, while in applied research someone chooses their problem for them.
So basic research secretly has three axes: motivation, specificity and intention/Considerations of Use.
Motivation is just
From The decline of unfettered research - otherwise known as curiosity-driven. Basically “work on whatever you want.” There’s an assumption that it will be unconsidered for use because that is the cloth that the physicists came from. But throughout history unfettered research has varied between considerations of use.
And then to pull out the other orthogonal axes of the Quadrant and Basic/Applied frameworks, you have
Interestingly, the “not seeking fundamental understanding” “no consideration of use” quadrant of the quadrant model is empty. The void creates the implications both that no work happens there and that work done there would be worthless. These implications are both false. There are many historical examples where people discover new phenomena just from dicking around, instead of being on a Grand Quest for Fundamental Understanding! The ability to say ‘huh that’s funny’ is important for discovering new phenomena. On the flip side, many researchers do work not to advance fundamental understanding, nor to do something useful, but to publish a paper or get a grant. The criteria there is “Novelty” which has become a Suitcase Handle Word word for what could be paradigm shifting.
I like the definitions in Cycles of Invention and Discovery :
Discovery is the Creation of new knowledge and facts about the world
Invention is the Accumulation of and creation of knolwedge that results in a new tool, device, or process that accomplishes a particular or specific purpose
I like the definitions in Cycles of Invention and Discovery :
Development is a Scheduled activity with a well-defined outcome in a specified time frame aimed at the marketplace
Research is Unscheduled quest for new knowledge and inventions whose outcome cannot be predicted
I like the definitions in Radical Abundance:
Science tries to build abstract theories through the process of inquiry.
Engineering tries to build concrete systems through a process of design and implementation.
In the framework of Cycles of Invention and Discovery, Engineering is the work to create an invention while Science is the work to create discovery.
The unintuitive part is that this does mean you can have Engineering research and scientific development. However, that completely squares with the real world - there are engineering projects that don’t have predictable outcomes and are unscheduled.
The issue actually comes back to culture - after WWII “scientist” became super sexy and “engineer” was close to “plumber.” Interestingly that trend has to some extent reversed due to Silicon Valley.
We may actually need a third orthogonal axis here: History. Historical narrative is not scientific inquiry or engineering design but it is valuable. It is possible to X is engineering, it is impossible to X is science, here is a narrative around X is history.
This one is super tricky. Many people naturally tie the evolutionary/revolutionary distinction to outcomes. Gerry Neumann argues convincingly that there is just One Process - Post and the seemingly discrete difference is just due to a mismatch between our mental lognormal models of impact and the true power-law distribution of impact. However, in The Structure of Scientific Revolutions, Kuhn equates evolutionary work to work “within a paradigm” and revolutionary work as “changing/attempting to change the paradigm.” I like this because you can look at something beforehand and ask which it is. Of course, defining Paradigms is hard but Technological paradigms and technological trajectories might have more to say about that.
Demand-pull and technology push is another axis people talk about with respect to technology motivation. However, it seems like it’s some linear combination of fettered/unfettered (“build this for me!” vs “I want to build this because it will be sweet!”) and use considered/not considered (“This will solve a problem!” vs. “this will be sweet!”) So it’s important to mention but doesn’t make it onto the list of orthogonal axes. (See Technological paradigms and technological trajectories for a good discussion of Demand-Pull and Technology-Push)
Jason Crawford pointed out that ambition is another way we think about research. Ambition could be broken apart into Risk and Scope. Scope seems indistinguishable from Breadth, so we do need to introduce a risk axis. However, in reality thinking about uncertainty is more precise than risk because many times you don’t actually know the risk distribution. Uncertainty always involves risk but risk does not always involve uncertainty. And then ambition is a linear combination of Uncertain/Certain with Broad/Specific
Colloquially, this is the “risk” associated with the activity. However, especially with research and even with development there is uncertainty on top of the risk. Uncertainty always involves risk but risk does not always involve uncertainty. This is much more of a continuous distribution than the other axes, but to keep with the convention let’s call it Uncertain/Certain.
So now we’re up to nine orthogonal axes