FIELD NOTES
Published September 2026
Donnerskirchen, Austria
When will I ever need this?
With the start of the school year, a question returns that has probably been asked for generations, especially in the higher grades: When will I ever need this?
In maths it comes up particularly often. Why solve equations if you may never use them again in your future job? Why bother with derivatives or integrals if you don’t want to become a mathematician, engineer or scientist?
The question is perfectly fair. Much of what we learn at school we will indeed never need again directly. Even so, it could be a mistake to measure the value of knowledge solely by whether we already know what we will use it for later.
I have worked in banking for many years. There, economic relationships, financing, figures, contracts and business administration mattered. Chemistry played practically no role in my working life. Nor did botany. And I certainly never had to deal with genetics. Back then, there would have been little reason to assume that many years later I would voluntarily and quite intensively engage with exactly these subjects.
Today I am training to become a skilled beekeeper at the beekeeping school in Warth – and suddenly I need all of it!
To really understand bees, it is not enough to know when to add a super or how to extract honey. Bee health and honey quality quickly lead you to chemistry. If you want to understand how traits are inherited, why the mating of a queen is biologically so special or what breeding can actually achieve, you need genetics. If you want to understand what the bees find outside their hive, when nectar flows begin and why certain plants are particularly valuable to them, you need botany. And then business administration reappears – this time not in banking, but in investments, costs, contribution margins and the question of how a small beekeeping business can be run sensibly.
Subjects that are neatly separated on a timetable suddenly meet again at the bee colony.
In a now well-known experiment, buff-tailed bumblebees were set a rather strange task. They had to move a small ball to a particular spot and were rewarded with sugar water. There is no real equivalent to this in a bumblebee’s natural world. No flower requires it to roll a plastic ball across a surface. No bumblebee ancestor had to solve this task in order to reproduce.
Nevertheless, the animals were able to learn what to do. What was particularly remarkable was that bumblebees could learn from other bumblebees. After watching another bee solve the task, they later often even chose a ball that was closer to the goal instead of simply copying the movement they had observed. In other words, they were able to choose a more efficient option.
Another experiment by the same research group worked in a similar way. An artificial flower containing sugar water lay under a transparent plate. The bumblebee could see it but could not reach it. Only by pulling on a string could it move the flower out.
Most inexperienced bees did not find this solution spontaneously. After step-by-step training, however, they were able to learn the task. Other bumblebees acquired the behaviour by watching an experienced bee. In the experimental colonies, this new technique could then spread from bee to bee.
The interesting insight here is not that bumblebees can perform tricks. The ball and the string are only experimental set-ups. They make visible something that would be harder to study in natural behaviour: a relatively small but extremely densely connected nervous system can grasp a completely new situation, draw on experience and change its behaviour accordingly.
According to current research, bees have existed for around 120 million years. Genomic and fossil data suggest that their early lineages arose in the early Cretaceous. Since then, they have spread across large parts of the earth together with an ever-changing plant world. Of course, this does not mean that 120 million years of evolution taught a bumblebee to roll a ball just in case. Evolution does not plan ahead. It cannot know which problem will arise in a future environment.
That is precisely why the ability to learn is so interesting.
An animal cannot possibly have its own innate programme for every new flower shape, every landscape and every change in its environment. Flexible learning, on the other hand, makes it possible to apply existing abilities in new contexts. The specific task need never have occurred in its evolutionary history at all.
The bumblebee was not selected to roll a ball. But it has perception and learning mechanisms that allow it to recognise the relationship between action and outcome. In the experiment, this gives rise to a behaviour its ancestors never needed.
I find this idea more interesting for education than the notion that everything we learn must later be applied in exactly the same way.
A child solving a mathematical equation today may never face exactly that equation in working life. Someone who learns integral calculus may indeed never calculate a single integral again.
That does not make the question of why we learn something superfluous. Teaching may be questioned too. And it would be scientifically too simplistic to claim that every mathematical exercise automatically increases general intelligence or problem-solving ability.
But there is another point:
In the past, I would have had no reason to consider genetics particularly important for my working life. Today it helps me to better understand the biology of a bee colony. Botany was irrelevant to my work in a bank. Today I look at a meadow, a woodland edge or a forage plant differently, because I want to understand what is actually happening there for the bees. Chemistry used to be a school subject. Today I come across it again in honey, wax and bee health.
Business administration is the counter-example. It has been with me for a long time, but in beekeeping it takes on a new context. A contribution margin for a jar of honey is something different from a financing calculation, and yet both draw on ways of thinking I already know.
Perhaps that is exactly the value of occasionally learning beyond one’s own horizon. Knowledge does not automatically disappear just because we do not need it right now. Some of it remains unused, some is forgotten. And some resurfaces years later in a context no one could have foreseen while learning it.
In beekeeping, this difference quickly becomes visible. Many tasks can be learned as fixed routines: inspect at a certain time, carry out a certain measure, use a certain tool. As long as the situation matches the instructions, that works.
Weather, forage, colony strength, the age and genetics of the queen, pathogens, parasites and location all act at the same time. A colony can develop differently than expected, even though seemingly the same measures were taken as the year before.
That is when knowledge that goes beyond instructions becomes interesting.
The more I learn at the beekeeping school, the less I am satisfied with the question of what a beekeeper does. I want to understand why they do it. Why a treatment works. Why it might not work under other conditions. Why a colony shows a certain behaviour. Why plants provide nectar at different times and under different conditions. Why genetic relationships matter for breeding and vitality.
Some of this I will probably never need in practice for my own beekeeping, such as forest honey flows. That bothers me less these days. Because nobody knows what problem will be waiting at a beehive tomorrow.
And nobody at the age of ten or fifteen knows which knowledge will suddenly become important again thirty years later.
Perhaps that is a better answer to the question of why we learn things whose immediate use we cannot yet see. Not all knowledge needs a concrete purpose at the moment we learn it. A changing world does not only reward ready-made answers. It also demands the ability to recognise new connections and to use what we have already learned in different ways.
Loukola, O. J., Solvi, C., Coscos, L. & Chittka, L. (2017): Bumblebees show cognitive flexibility by improving on an observed complex behavior. Science 355, 833–836.
Alem, S. et al. (2016): Associative Mechanisms Allow for Social Learning and Cultural Transmission of String Pulling in an Insect. PLOS Biology 14, e1002564.
Almeida, E. A. B. et al. (2023): The evolutionary history of bees in time and space. Current Biology 33, 3409–3422.
Chittka, Lars: Im Cockpit der Biene. (2025) Verlag Folio.
