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A reflection on the growing gap between laypeople and experts.

I recently finished reading “The Death of Expertise” by Tom Nichols. The central argument of the book is both straightforward and unsettling: although the internet and modern technology have made information more accessible than ever before, they have also lowered the threshold for considering oneself an “expert.” Easy access to information is often mistaken for genuine understanding.

Nichols explores how several developments (including the rise of the internet, the commercialization of university education, and the growing obsession with attention in journalism) have widened the gap between experts and the general public. The book was published in 2017 and primarily focused on developments in the United States, but many of its observations remain highly relevant today.

In fact, some of the trends that Nichols described seem to have intensified over the past decade. The rapid rise of AI tools has further blurred the distinction between access to information and actual expertise, while ideological polarization increasingly shapes scientific and public debates. Discussions about science are often influenced by identity and ideology instead of being based on evidence and nuance. In this blog post, I will reflect on the three main themes discussed by Nichols: the internet, university education, and journalism.

Ever-increasing Dunning-Kruger Effect

The rise of the internet has amplified the Dunning-Kruger effect: a cognitive bias in which individuals with limited knowledge or competence in a domain tend to overestimate their own abilities, often because they lack the awareness to recognize their own limitations.

In online environments, there are countless examples of people confidently presenting strong opinions on topics they have little formal training in, sometimes even directly challenging experts. I have encountered this issue myself. On several occasions, individuals have attempted to explain evolutionary theory to me (often based on creationist arguments that reflect a limited understanding of evolutionary mechanisms) or have objected to taxonomic interpretations in my goose research because these did not align with their preferred species lists.

And this trend has only intensified with the rise of AI tools. People often no longer take the time to genuinely engage with concepts or arguments. Instead, they consult their preferred AI system and quickly arrive at the conclusion that they understand the topic better than experts who have spent their careers working through its complexities.

These development have also changed how I engage online. I have stepped away from participating in online discussions (especially with creationists). Instead, I now mainly use social media as a platform to share my scientific work and blog posts. I also find myself increasingly reluctant to engage with laypeople in online spaces, and I tend to prefer conversations within the scientific community. We undoubtedly need online science popularizers to help bridge the gap between experts and the general public. However, this role has become increasingly difficult (and frustrating) due to the rise of attention-driven influencers, whose primary incentive is visibility rather than accuracy or nuance.

Evaluating Education

In his book, Nichols describes how American universities and colleges have increasingly taken on the characteristics of businesses that treat students as customers. Rather than focusing on rigorous scientific training, institutions tend to adapt their courses to meet student expectations and preferences. The concern is that this dynamic contributes to a perception among students that they are already experts, whereas a university education is best understood as an entry point into a field rather than its endpoint.

I found this conclusion too harsh. It is certainly true that universities are under increasing pressure to respond to student feedback, but ultimately teachers can still offer high-quality education. At Wageningen University, for example, every course is evaluated by students, including open comment sections. Some of this feedback is genuinely valuable, such highlighting unclear instructions, workload imbalances, or organizational issues. However, other comments are more easily set aside, especially when they concern the scientific content itself. I am often surprised that some students believe they know better than the professors who are at the forefront of the field. Fortunately, these cases are the exception rather than the rule, and most students provide constructive input that genuinely improves course quality.

Ideological Influences

A more concerning development is the growing influence of ideology within education and research. There is nothing inherently wrong about being motivated by ethical concerns or social causes, but these should not compromise scientific rigor. A recent example can be found in a Wageningen University course on “Queer Biology.” While it is certainly valuable and interesting to study phenomena such as same-sex sexual behavior in animals, or the weird mating system of the White-throated Sparrow (although I would argue this species still has two sexes), it is important not to let ideological frameworks shape scientific conclusions. In this context, it is worth avoiding the naturalistic fallacy: the idea that what occurs in nature is inherently good or morally justified. Observing homosexual behavior in animals, for instance, does not by itself provide an ethical argument for human behavior. By the same logic, you could try to justify infanticide by pointing to its occurrence in lions.

A similar issue arises in the growing romanticization of indigenous knowledge (also see this blog post). This shift is partly motivated by a legitimate and necessary effort to address historical injustices, including colonialism and the marginalization of local communities, and to engage more respectfully with indigenous perspectives. However, this should not lead to an uncritical acceptance of all forms of indigenous knowledge as scientifically validated. Many such systems include local myths or context-specific explanations that may have cultural, historical, or philosophical value, but that do not necessarily translate into reliable scientific knowledge.

Addicted to Attention

Finally, Nichols turns to journalism, arguing that we need good (science) journalists to help bridge the widening gap between experts and the general public. While I definitely agree with this advice, I am increasingly concerned that the dynamics of today’s attention economy are making this task more and more difficult.

As I noted earlier, the rise of attention-driven influencers (whose primary incentive is visibility rather than accuracy or nuance) has contributed to a decline in the overall quality of popular science communication. I could easily point to numerous examples of science communicators who seem more focused on building personal brands rather than on producing high-quality content (but this is not the place for naming and shaming). Indeed, it has become more difficult to find good science journalists and communicators that produce quality content that aligns with my interests (at least in Belgium and the Netherlands). Instead, I find myself increasingly drawn back to earlier science communicators such as Carl Sagan and Stephen Jay Gould (although there are certainly excellent science writers, such as Ed Yong and Carl Zimmer).

I also notice a growing tendency for ideological framing to seep into online science communication. The YouTube channel Crash Course used to be one of my favorites, but in recent years they seem to have become more susceptible to ideological pressures. In a recent series on geology (presented by an overacting host with an annoying TikTok-vibe), the opening segment of one episode focused heavily on the idea that indigenous peoples “already knew everything all along.” One example discussed fossil trackways referred to as “Place with the Bird Tracks,” which the host interpreted as evidence that indigenous peoples already understood that birds are dinosaurs. That is obviously complete nonsense because these people had no clue of modern evolutionary biology. But I digress.

In the end, I am afraid that I cannot offer a satisfactory solution to these concerning trends. My own approach has largely been to step back from online discussions and avoid attention-driven media ecosystems. Instead, I prefer to seek out my own sources (often in book form) and focus my energy on writing blog posts about topics that genuinely interest me.

A reflection on various personal insights.

You are reading blog post #100 on this website. An ideal moment to pause and reflect on my academic journey so far. I wrote my very first blog post in February 2016, during the final year of my PhD. More than a decade later, I am now an assistant professor at Wageningen University, with two postdoctoral positions in Sweden along the way. Earlier this year, I made the transition from lecturer to assistant professor. The past ten years have been anything but linear. I have experienced countless ups and downs (some of which have been covered in other blog posts).

In this post, I want to zoom out from the day-to-day struggles and reflect on a few broader lessons. These observations are, of course, shaped by my own experiences and will not map perfectly onto everyone else’s path. Still, I hope that some of them might resonate or at least provide a useful perspective. Throughout this post I will refer to other blog posts that provide more details and additional insights.

Defining Your Purpose

During my PhD and postdoc years, I regularly struggled with motivation. I found myself questioning the bigger picture: What is the point of this research? Am I actually capable of becoming a professional scientist? (Hello, imposter syndrome!) The uncertainty of short-term contracts and the constant job insecurity didn’t exactly help.

In an attempt to deal with these issues, I turned to books on motivation and productivity (Atomic Habits is a well-known example) and started exploring philosophical perspectives such as stoicism and existentialism. Over time, these ideas helped me reframe how I think about work and purpose. As I have written in another post, I have come to identify as an “optimistic nihilist”: I don’t believe that life comes with inherent meaning, but we do have the freedom to create our own meaning and purpose. One idea that stuck with me comes from Simon Sinek, who argued that it is important to clearly define your purpose. After some reflection, I landed on a simple but guiding principle: scientific knowledge for everyone.

Having that sense of purpose made it much easier to navigate academic decisions. This perspective gave me a framework to evaluate opportunities and priorities. If my goal is to make science more accessible, then blogging, publishing papers, and teaching should be my main tasks.

A Series of Unanticipated Events

Once you have defined a sense of purpose (something that might change over time), it can be tempting to anchor yourself to a specific path. In academia, that often means following the “standard” trajectory: obtaining a PhD, a few postdocs, and eventually a tenured position. But it is worth resisting that pressure. A rigid plan can be more limiting than helpful. Flexibility and adaptability matter far more than sticking to a predefined route.

My own path is a good example. Although I eventually ended up following a fairly conventional academic trajectory (with a few detours), that was never the plan. After finishing my PhD, I considered leaving academia to become a science journalist. I even explored this option through an internship at a Dutch newspaper (which was definitely fun, but not really my cup of tea). But when I was offered a postdoc position at Uppsala University, I decided to stay in research a bit longer.

The move to Uppsala did not go smoothly. A difficult situation with a stubborn supervisor meant I had to improvise, which led to a short-term postdoc at the Karolinska Institute in Stockholm (you can find the complete story in this blog post). During my years in Uppsala, I focused primarily on genomic analyses of the bean goose complex which ultimately culminated in two papers. It was definitely interesting work, but I found myself missing teaching and the day-to-day interaction with students (which partly explained my motivational struggles).

When my postdoc contract ended, I was fortunate to find a lecturer position at Wageningen University. At the time, it felt like a deliberate shift away from the publish-or-perish culture and the constant competition for grants. I decided to focus on teaching (even stepping outside my core expertise to teach forest ecology) and I was convinced that I would never enter the tenure track system. And yet, things changed again. Wageningen University recently introduced the academic career framework (ACF) which promises more flexibility and room for personal preferences. And eventually, I switched from the lecturer to the professor track (similar to tenure track).

Looking back, the common thread is not careful planning, but a series of unanticipated turns. Most of my decisions were shaped by opportunity, constraint, or simple curiosity rather than by a long-term master plan. Ultimately, I feel that I have ended up where I am supposed to be. So, the main lessons from this section: you don’t need to have everything mapped out. Stay open, adapt when circumstances change, and trust that you will find your way to a place where you belong.

Don’t Compare Yourself to Others

After reading about someone else’s academic journey, it is almost inevitable to start comparing. But that is a trap worth avoiding. How other people present themselves is often unrealistically positive, especially on social media. Measuring yourself against that distorted version of reality rarely leads anywhere productive.

A more useful approach is to stay focused on your own trajectory. Do your own thing, in a way that aligns with your interests and values. Along the way, you will receive plenty of unsolicited advice (often well-intended), but not all of it will fit your situation. It is worth pausing every now and then to ask yourself a simple question: are your decisions truly your own, or are they being shaped by external expectations?

That doesn’t mean you should ignore the advice of other people. You can learn a lot from people that you admire, and having role models can be genuinely helpful. I have personally drawn inspiration from Charles Darwin (not just for his scientific contributions, but also for his daily routine) and from the writing style of Stephen Jay Gould. At the same time, it is important to keep that admiration in perspective. Role models can guide and motivate, but they should not become unrealistic benchmarks that you should match (also see this blog post). The goal is not to replicate someone else’s life, but to build your own.

Consistency Is Key

After these philosophical reflections, we can turn to something more practical. Academic life is inherently fragmented: teaching, supervising students, writing papers, applying for grants. And, in my case, blogging. The challenge is not just to do all these things, but to do them in a sustainable way. For me, two principles make a difference: working at a natural pace and maintaining consistency.

The idea of a “natural pace” is closely related to the philosophy of slow productivity, which I’ve discussed in earlier posts. In an achievement society that often equates success with productivity, it is easy to fall into the trap of always doing more (with an increasing risk of burnout). A more sustainable approach is to find a personal working speed. That pace will look different for everyone (so again, don’t compare yourself to others). The key is to develop a rhythm you can maintain without burning out.

That natural pace becomes very powerful when combined with a consistent work ethic. In my case, I keep a fairly structured schedule from 9 to 5 and rarely work in the evenings or on weekends (although I do make an exception for writing blog posts for my Avian Hybrids website on a quiet Sunday). I also try to align my work with my energy levels. Mornings are when I am most focused, so I reserve that time for cognitively demanding tasks such as writing papers or commenting on drafts. Afternoons, when my energy levels tend to drop, are reserved for meetings. Of course, this structure isn’t always possible (sometimes my teaching duties are fixed in the mornings), but it serves as a useful baseline.

Each day starts with a simple to-do list, which I work through at a steady pace. If I don’t have the energy to finish something, I move it to the next day rather than forcing it. That small adjustment makes the process more sustainable and, somewhat counterintuitively, more productive over time (also see this blog post). This combination of a manageable pace and consistent effort has allowed me to maintain a steady output of both blog posts and scientific papers.

Building Your Network

Although I enjoy writing papers on my own, science is ultimately a collective effort. Not only do we build on the work of those who came before us (standing on the shoulders of giants) but we also rely on others to tackle bigger questions. That is why developing a scientific network is so important. There are many ways to do this: attending conferences, engaging with colleagues online, or sharing your work on social media. Over time, these interactions can grow into meaningful collaborations. That said, networking shouldn’t feel forced. Not everyone thrives in the same environments, and it is important to find an approach that feels natural to you.

What matters just as much as building a network is how you behave within it. In collaborations, being a kind and reliable colleague already goes a long way. I have always tried to be approachable and open, but also dependable by responding to emails in a timely manner and following through on what I promised. Those small habits build trust, which is the foundation of any good collaboration.

As a side note, having a strong network can also open doors to recognition and awards. My very first blog post, for example, was about receiving a “Success of the Month” award, for which I was nominated by my supervisor. That experience also highlighted a slightly uncomfortable truth: who you know can matter as much as what you know. This is one of the reasons that I remain somewhat skeptical about the value we attach to awards in academia (also see here and here on why I don’t like awards).

The importance of a strong network is nicely illustrated by the picture below, taken at the Plant and Animal Genomics Meeting 2016 in San Diego. It shows the presenters of a session on avian genomics. Many of the people in that picture later became close collaborators, ranging from postdoc advisors to co-authors.

Don’t Forget To Have Fun

Finally, the most important lesson: have fun! That might sound obvious, but it is surprisingly easy to lose sight of this aspect. Academia can feel like a constant rat race with another paper to finish, another deadline to meet, or another item added to an ever-growing to-do list. People often forget to enjoy the process.

Toward the end of my PhD, I took a course in career planning (somewhat ironic, given my rather unplanned path described above). One of the exercises was to sketch out an ideal career, focusing not on prestige or metrics, but on what genuinely brings you joy and fulfillment. I remember that my ideal endpoint was a permanent position at an unspecified university where I would spend my time teaching, writing papers (and perhaps some books), and blogging. That is, more or less, exactly what I am doing now.

Looking back, I didn’t get here by carefully optimizing every decision or chasing a perfectly defined goal. Instead, I consistently gravitated toward the parts of academia that I enjoyed most. That simple strategy (prioritizing curiosity and enjoyment) turned out to be surprisingly effective. So, don’t forget to enjoy what you are doing. If you can find genuine satisfaction in the day-to-day work, you are more likely to end up somewhere that feels right.

A reflection on the urge to control information overload.

Have you ever finished a book, only to realize a few weeks later that you have forgotten most of it? You cannot remember some of the characters or the key points of the book. It happens to all of us. Some people try to fight this issue by holding on to everything they read (or at least the parts they consider most important). On YouTube, you will come across countless self-proclaimed productivity gurus selling elaborate note-taking systems or life hacks designed to help you remember more.

A few years ago, I have fallen into that trap myself. I became fascinated with the idea of building a digital “second brain”, which is a system to capture, organize, and connect all the information that you encounter. The inspiration of this system came from the Zettelkasten method (German for “slip box”), a note-taking system built on small, interconnected pieces of information. It is often associated with sociologist Niklas Luhmann, who used a collection of more than 90,000 index cards to support his remarkably prolific writing (see this blog post for more details). I tried to build a similar system, but ultimately, it did not work for me. What started as a helpful tool quickly turned into a source of pressure. The constant need to capture insights and create meaningful connections became overwhelming, and eventually anxiety-inducing (which I explained in this blog post).

In this blog post, I will argue that you should not try to remember everything that you read or keep elaborate notes. Of course, there are situations where careful note-taking is useful, such as studying for an exam or gathering material for a paper. But outside of those contexts, it should not become a burden that takes over your experience of reading.

The Promise of Productivity

So, where does this urge to remember everything actually come from? Many of us are naturally drawn to a wide range of topics, a curiosity-driven exploration of the world. Personally, I have broad interests and read books on various topics, from quantum mechanics and evolutionary biology to the history of the Roman empire and human behavior. But curiosity does not automatically imply a need for total recall. Trying to retain every detail from such a broad range of interests is just impossible.

A more powerful driver, however, could be the current culture we live in. In an achievement-oriented society, knowledge can easily become a way to show off. Being able to list the “classics” you have read (or casually quote a well-known author) can create the impression of intelligence and depth. Reading, in this sense, turns into social performance. In addition, there is the modern obsession with productivity. Systems like the Zettelkasten method promise more than just organization. They suggest that, if done correctly, they will lead to original insights and meaningful output. Beneath that promise of productivity again hides the achievement society, namely the desire to create something to impress other people.

I have felt that pressure myself, especially in academic settings. The expectation to generate original ideas – for papers, projects, or blogs – can quietly reinforce the idea that everything you read must be captured, stored, and made useful. However, I have decided to resist this pressure and focus on enjoying the process.

Embracing Wu Wei

So, how do I approach reading now? I try to keep it simple: I read for its own sake. Not to impress others, not to optimize my productivity, but because I enjoy it. Whether it is getting lost in a story or exploring a new idea, the focus is on the experience itself rather than what I can extract from it. However, this does not mean that I ignore everything I read. If an idea stands out (something that could grow into a blog post or a paper), I will jot it down. But I no longer feel the need to capture everything or build an elaborate system around note-taking. I trust that the truly meaningful ideas will emerge naturally.

In a way, this approach echoes the Taoist concept of Wu Wei, often translated as “non-action” or “effortless action” (also see this blog post) While I don’t follow the spiritual dimensions of this concept, I do appreciate the underlying principle: working with the natural flow of things rather than constantly trying to control and optimize everything. Applied to reading, Wu Wei means letting ideas and connections develop organically instead to trying to force them into a rigid structure.

Ultimately, I have found it more useful to focus on the experience of reading rather than trying to control what I could get out of it. Letting go of the urge to remember everything has made reading feel less like a task and more like something I can simply enjoy. And in practice, this approach often leads to interesting insights and countless ideas for blog posts and research projects. Without the pressure to produce.

A reflection on the balance between recognition of ideas and individual scientists.

This week, the Belgian news was dominated by Rosa Rademakers, a Dutch researcher at VIB and University of Antwerp, who received the Breakthrough Prize for her genetic research. Her team identified a genetic variant linked to both dementia and ALS, an important scientific advance.

The media attention left me with mixed feelings. On the one hand, it is encouraging to see science receiving recognition, even if the underlying genetics might remain inaccessible to most people. On the other hand, the focus on a single individual risks distorting how science actually works. Good science is rarely the product of one person. It is a collective effort, built on incremental contributions from countless researchers whose names never make the headlines (see this blog post). Framing discoveries around individuals can obscure this reality, which is one reason I don’t like awards in general (also see here and here).

The Role of Role Models

At the same time, I recognize the value of role models, especially for young girls and underrepresented groups. Seeing someone who resembles you succeed in science can be a powerful motivator, drawing more talented people into the field. However, there is a fine line: role models should inspire through their ideas and contributions, not become larger than their ideas.

Take Jane Goodall as an example. Her pioneering work on chimpanzee behavior transformed primatology and inspired generations of scientists and conservationists. However… This may sound like swearing in the conservation church, but I have never been a big fan of Goodall or her organization. Over time, she came to be treated as a saint, and parts of the conservation movement around her have taken on a somewhat sectarian vibe. In her later years, her increasing spiritualism – even flirting with pseudoscience like intelligent design – felt at odds with the scientific rigor you would expect from an experienced researcher. Here is a quote from an interview after she was awarded the Templeton Prize (already a huge red flag).

When more scientists are saying there’s an intelligence behind the universe, that’s basically what the Templeton Foundation is about: We don’t live in only a materialistic world. Francis Collins drove home that in every single cell in your body there’s a code of several billion instructions. Could that be chance? No. There’s no actual reason why things should be the way they are, and chance mutations couldn’t possibly lead to the complexity of life on earth.

Such misguided statements highlight the risk of elevating individuals above ideas. The suggestion that evolutionary complexity cannot arise from “chance mutations” reflects a fundamental misunderstanding of how evolution works. Evolutionary biology does not rely on chance alone: it is the interplay between random mutation and non-random natural selection that drives the emergence of complexity. When influential figures like Jane Goodall share such blatant nonsense, they risk misleading the general public about one of the most robust and well-supported frameworks in science. It is a reminder that scientific credibility should rest on the strength of ideas, not the stature of the people expressing them.

Science Communication

When I reflect on my own role models, such as Carl Sagan and Stephen Jay Gould, a different pattern emerges. What stands out is not just their scientific work, but their ability to communicate ideas clearly and thoughtfully. Carl Sagan, while not without his critics or limitations, played a pivotal role in popularizing science for a broad audience, most notably through the TV series Cosmos, where he conveyed the wonder of the universe while grounding it firmly in scientific reasoning. Stephen Jay Gould, similarly complex and not without controversy, reshaped how many people (including me) think about evolution through his essays and books, exploring concepts such as contingency and punctuated equilibria in ways that were both accessible and intellectually rigorous.

They earned my admiration not by carefully curating a personal image (even though Carl Sagan was very charismatic), but by offering compelling ways to think about science. Stephen Jay Gould, in particular, introduced me to ideas that reshaped how I understand evolution, even in cases where I ultimately disagreed with him. But that is precisely the point of this blog post: it was the ideas that inspired me, not the individuals behind them.

This contrast feels especially relevant today. Many modern science communicators seem more focused on personal branding than on the substance of the science itself. This shift risks reinforcing the very problem seen in our achievement society: an emphasis on personalities over ideas.

My take home message is not to reject recognition or role models altogether, but to strike a better balance. Science needs visibility and people need inspiration. But ultimately, ideas should take center stage, not individuals.

A reflection on the importance of problem-solving.

The decline of the indigenous population on Easter Island is often told as a cautionary tale of environmental self-destruction. According to a common narrative, the island’s inhabitants exhausted their natural resources (most notably through severe deforestation), triggering ecological collapse in an already fragile system. This interpretation, popularized by Jared Diamond, is frequently invoked as a warning for our own era of unsustainable consumption, driven by individualism and capitalism.

However, this “ecocide” story has not gone unchallenged. A growing number of scholars argue that it oversimplifies a far more complex history, pointing to alternative explanations and questioning the extent of environmental mismanagement (see Wikipedia for a overview of the criticism). One particularly thought-provoking perspective comes from David Deutsch in his book “The Beginning of Infinity“. He shifts the focus away from resource depletion and toward something more fundamental: the role of knowledge and problem-solving.

The Easter Islanders may or may not have suffered a forest-management fiasco. But, if they did, the explanation would not be about why they made mistakes – problems are inevitable – but why they failed to correct them.

Deutsch makes a distinction between dynamic and static societies. Dynamic societies embrace the creation of new knowledge, welcome criticism, and adapt their institutions accordingly. Static societies, by contrast, are bound by tradition and resistant to change. When confronted with challenges (such as environmental degradation) they struggle not because solutions are impossible, but because their culture inhibits the discovery and adoption of those solutions. From this perspective, the story of Easter Island is not about why mistakes were made, but why they were not corrected.

A History of Ideas

As Deutsch succinctly puts it: “History is the history of ideas, not of the mechanical effects of biogeography.” Resources definitely matter, but ultimately ideas drive progress. This way of thinking resonates with me. It suggests that while recognizing problems is essential, it is only the starting point. What truly matters is our ability and willingness to find solutions.

This perspective also sheds light on why some forms of climate activism fail to persuade the broader public. The emphasis is often too much on the problem. But awareness alone rarely inspires change. In some cases, it even leads to resistance. When activists disrupt sporting events or deface artworks, they may attract attention, but they do not necessarily find support (these actions even annoy me). Similarly, moralizing arguments that rely on guilt or shame are generally counterproductive, pushing people away rather than bringing them on board.

If we want meaningful change, we need to complement problem-awareness with tangible solutions. Moreover, the solutions should be presented in a way that invites participation rather than demanding compliance.

Avoiding Trees

This perspective also reminds me of a simple metaphor (unfortunately, I cannot remember the original source). Imagine skiing down a slope dotted with countless trees. If you fixate on the trees (i.e. the problems), you are almost guaranteed to hit one. But if you focus on the gaps between the trees (i.e. the solutions), you will move more smoothly and safely downhill. I notice the same effect in everyday life when I am cycling to work. If I concentrate too much on obstacles like branches on the path, I tend to overcorrect and come dangerously close to them. But when I focus on the open space, navigation becomes effortless.

I have tried to apply this mindset more broadly. Instead of dwelling on problems, I aim to direct my attention toward possible solutions. That doesn’t mean ignoring the problems, because understanding them remains important. But ultimately, progress depends on what you do next. You don’t want to end up like the inhabitants of Easter Island. Not because you faced problems, but because you failed to solve them.

And the best way to solve these problems is the scientific method (see this blog post for the details).

A reflection on the intrinsic and extrinsic factors of student motivation.

This week, I gave a lecture on the interplay between evolution and climate change to about 30 students. That might sound like a decent turnout, but it was only around 25% of the roughly 120 students enrolled in the course. My colleagues reported similar numbers, and I have heard similar stories from other courses as well. It would be easy to label the absent students as unmotivated or disengaged. Instead, I have been thinking about what might actually be behind these low attendance rates, from the process of learning how to be a student to the broader system we have built around rewards and performance.

Extrinsic Motivation

First, becoming a university student is a learning process in itself. You move from a highly structured environment in high school (where attendance is mandatory and schedules are fixed) to a setting where freedom is the default. That transition takes time. Students need to figure out which activities are essential (such as practical sessions), how to balance studying with a social life, and how to manage their time. And along the way, they will make mistakes. They might miss a session they shouldn’t have, or oversleep after a fun night out (we have all been there). But that is part of the process. Making mistakes is how you learn.

Second, there is the broader cultural obsession with efficiency and productivity. Students, like everyone else, are constantly optimizing: how can I achieve more while doing less? Why bike to campus for a lecture when you can watch it later at double speed from the comfort of your bed? Those are fair questions. However, learning often benefits from stepping outside that comfort zone. There is something uniquely engaging about being physically present in a lecture hall. When I was a student, recorded lectures were not even an option (which makes me sound older than I feel). If you missed a lecture, you relied on slides and the kindness of classmates sharing their notes.

Third, and related to this productivity mindset, we live in what has been called an achievement society. Students are encouraged (implicitly and explicitly) to maximize results in minimal time. Naturally, they start looking for the most efficient path to high grades. Our educational systems don’t exactly discourage this. At Wageningen University, like many places, courses are structured around learning outcomes. To assess those outcomes, teachers design assignments and exams with detailed rubrics for grading. The result? Students who follow the guidelines closely are rewarded with good grades. This approach makes perfect sense, but also leaves limited room for curiosity-driven exploration. Intrinsic motivation can get squeezed out by the focus on external rewards. In our current course, we are trying to create some space for that intrinsic motivation. For example, students can choose the topic of their essay (within the scope of the course). It is a small step, but it gives them the opportunity to follow their own interests.

Privileged Positions

So perhaps lecturers should think more about how to nurture that intrinsic motivation (where possible). At the same time, it is worth reminding students that they are in a privileged position. University offers a level of freedom that many only fully appreciate later, once they have entered more structured working environments. It is also an intellectually stimulating space: students are exposed to diverse ideas and novel perspectives. And they learn from lecturers who are often deeply knowledgeable (sometimes even leading figures) in their fields. Students don’t always realize how remarkable that situation is.

But the idea of privilege goes both ways. Lecturers, too, can lose sight of it. Academia has its own relentless pace, and it can be easy to get caught up in the never-ending rat race for publications, funding, and recognition. In the process, we sometimes forget how fortunate we are. We work with curious, motivated colleagues. We explore questions we genuinely care about. And we teach subjects we are passionate about.

So rather than focusing on the 75% who didn’t show up, maybe we should shift our attention to those who did. The students who are present and engaged. Even if it is just a small group. It is a privilege to teach them.

A reflection on science and the role of indigenous knowledge.

When applied properly, the scientific method has the potential to generate knowledge without limit. This is one of the central ideas in “The Beginning of Infinity” by David Deutsch. He arrives at this conclusion by combining two simple claims: “problems are inevitable” and “all problems are solvable”. Taken together, these ideas imply an open-ended process of knowledge creation.

But how does the scientific method actually work? Deutsch defines science as conjecture (i.e. an educated guess) in combination with a culture of open criticism. In other words, everyone can propose an idea which can consequently be criticized by anyone else. Authority should be distrusted (i.e. Nullius in Verba – take nobody’s word for it). Over time, bad explanations will be weeded out, whereas the best explanations will rise to the surface.

Finding Good Explanations

What makes a good explanation? According to Deutsch, good explanations share two key features: they are universal, and they are hard to vary.

A universal explanation goes beyond local or immediate appearances. Its opposite is a parochial explanation which mistakenly elevates specific, limited observations to the status of universal laws. Such explanations fail to “jump to universality” and remain tied to the narrow perspective of the observer. The belief that the Earth is flat is a classic example. It extrapolates from everyday experience (i.e. the ground appearing flat beneath our feet) and treats this observation as a fundamental truth about the world.

The second feature of a good explanation is that it is hard to vary without losing its explanatory power. Deutsch illustrates this concept with the Greek myth of Persephone, which attempts to explain the seasons. In the myth, Persephone, the daughter of Zeus and Demeter, is abducted by Hades and taken to the underworld. Demeter, the goddess of agriculture and fertility, is devastated by her daughter’s disappearance. In her grief, she neglects the Earth, causing crops to fail and the land to become barren. Facing a world on the brink of famine, Zeus intervenes and orders that Persephone be returned. However, because she has eaten pomegranate seeds while in the underworld, she is bound to return to Hades for part of each year. As a result, Persephone spends several months in the underworld (bringing winter, when Demeter mourns) and the rest of the year on Earth (bringing spring and summer, when Demeter rejoices and the land flourishes). While evocative, this is a poor explanation because it is highly flexible: its details can be altered in countless ways without affecting its basic narrative. This ease of variation reveals a lack of explanatory depth.

The reason those myths are so easily variable is that their details are barely connected to the details of the phenomena. Nothing in the problem of why winter happens is addressed by postulating specifically a marriage contract or a magic seed, or the gods Persephone, Hades and Demeter. Whenever a wide range of variant theories can account equally well for the phenomenon they are trying to explain, there is no reason to prefer one of them over the others, so advocating a particular one in preference to the others is irrational.

Indigenous Knowledge

Now that we have outlined the core of the scientific method (conjecture combined with a culture of criticism) and defined what constitutes a good explanation (one that is universal and hard to vary), we can turn to a more controversial topic: the role of indigenous knowledge.

In recent years, there has been a growing interest in incorporating indigenous knowledge into scientific research. There are indeed nice examples where such knowledge has proven valuable. For instance, a recent study in Oryx combined ethnospecies lists from local communities with scientific datasets to reveal a consistent decline in bird body mass across three continents. Approaches like this study demonstrate that local knowledge can complement scientific inquiry, particularly in data collection and long-term ecological observation.

However, indigenous knowledge is often romanticized, sometimes being portrayed as inherently superior to scientific knowledge. This tendency is partly driven by a legitimate desire to correct historical injustices (such as colonialism and the marginalization of local communities) and to show greater respect for indigenous perspectives. While this shift is clearly necessary and overdue, it should not come at the expense of critical evaluation of indigenous knowledge.

Many elements of indigenous knowledge consist of local myths or context-bound explanations. As such, they are often parochial rather than universal, and therefore do not qualify as good scientific explanations. This does not diminish their cultural, historical, or philosophical value, but it does mean they should not automatically be treated as reliable sources of scientific insight.

A River as Co-author

There appears to be growing pressure within academia to signal the recognition of indigenous knowledge, sometimes in ways that blur the distinction between cultural respect and scientific rigor. A striking example appeared in Nature, where conservationist Anne Poelina listed the Martuwarra River of Life as a co-author on her publications.

Poelina explains that “in terms of property rights, the river owns me. So, I have a duty of care and the fiduciary duty to protect this river’s right to life.” Because Poelina works with the river to produce fresh knowledge and assimilate ancient wisdom, she decided to recognize its contributions formally. In 2020, she started including the Martuwarra River of Life as the first author on her publications.

When asked why the river should be listed as first author, she responded: “Because it’s the authority. It’s where I get my authority.” This reasoning stands in direct contrast with the scientific method, which explicitly rejects appeals to authority as a basis for truth. Science operates as a culture of criticism, where ideas must withstand scrutiny regardless of their source. As physicist Richard Feynman famously put it: “If it disagrees with experiment, it’s wrong. In that simple statement is the key to science. It doesn’t make any difference how beautiful your guess is, it doesn’t matter how smart you are, who made the guess, or what his name is … If it disagrees with experiment, it’s wrong. That’s all there is to it.”

Hence, attributing authorship to a river on the grounds of authority is not just unconventional; it reflects a fundamental misunderstanding of how knowledge is evaluated in science.

Another Fallacy

A similar issue arises in arguments that emphasize the age of indigenous knowledge (or any other knowledge system). Poelina suggests that “if we have the oldest systems of thinking around science and law, shouldn’t the world be listening to what our people have to say?”. But age is not a marker of reliability. As discussed earlier, Greek myths are thousands of years old, but they obviously fail as scientific explanations because they are easily varied and lack universality.

The same principle applies more broadly: all knowledge claims (whether scientific or indigenous) must be evaluated using the same standards. Some elements of indigenous knowledge may indeed prove robust and valuable under scrutiny, while other elements may not. We still need to separate the trustworthy wheat from the superstitious chaff. And the scientific method is the best approach to do just that.

All in all, I would argue that Poelina’s justification (resting on appeals to authority and the age of a knowledge system) is fundamentally flawed. She clearly does not understand how modern science works. From this perspective, the case for including a river as a co-author is unconvincing. You might disagree with my conclusion. And that is perfectly fine. Science celebrates criticism.

Nullius in verba!

Don’t underestimate the power of curiosity.

During my postdoc at Uppsala University (2018–2020), I worked at the Evolutionary Biology Center, surrounded by colleagues tackling fundamental evolutionary questions, such as the genomics of speciation and other curiosity-driven research. Our department regularly hosted international visitors who presented their latest findings in weekly seminars. The academic atmosphere was intellectually vibrant and deeply inspiring.

When I moved to Wageningen University in 2020, I noticed a clear shift in focus. I started working as a lecturer with two ecology groups: one focused on wildlife ecology and conservation, the other centered around forest ecology and management. Ecology tends to attract people with a strong passion for nature conservation. Unsurprisingly, there was a much stronger emphasis on societal challenges, such as climate change and biodiversity loss, along with more overlap with the social sciences.

While these topics are undeniably important and timely, I personally find them less interesting. At times, I catch myself missing the intellectually stimulating and curiosity-driven environment that I experienced in Uppsala. I need the fun of fundamental science.

The Growing Emphasis on Societal Relevance

This contrast between Uppsala and Wageningen made me reflect on a broader trend in academia: the increasing emphasis on societal relevance, often at the expense of fundamental questions. Part of this shift is understandable. The current funding climate has become more competitive, with fewer opportunities for an increasing number of scientists. In such an environment, it makes sense that funding agencies prioritize research with clear societal impact. However, I sometimes feel that this emphasis has become exaggerated.

I have encountered several recent examples that illustrate this trend. During a visit from our department head to the wildlife ecology group, most of the discussion revolved around policy and political implications. There were very few curiosity-driven questions. A similar pattern regularly appears in student presentations, where societal relevance is overemphasized. Students tend to highlight specific aspects, such as the biodiversity value or contributions to local livelihoods in their study area, even when these aspects are not directly connected to their research questions. In one case, a student planning to study the migration of White Wagtails was encouraged by his fellow students to explain the societal relevance of his work, despite the fact that such relevance is not essential to the project. Finally, when I was invited to speak at a local Science Café, the organizers requested that I address the societal relevance of my research for the audience (being a stubborn scientist, I will not).

This emphasis extends beyond my immediate working environment to the broader activities at Wageningen University. Many of the seminars and events (such as those organized under Studium Generale) primarily focus on societal questions, often framed around policy, sustainability, or global challenges. While these discussions are important, they tend to leave little room for fundamental, curiosity-driven science. Occasionally, these activities even drift into non-scientific topics (dare I say, demonstrable nonsense). Apart from the Wageningen Ecology and Evolution Seminars (WEES), there seem to be relatively few platforms dedicated to fundamental research. It sometimes makes me wonder: where is the science?!

A Case for Curiosity-Driven Science

I find myself increasingly at odds with this obsession with societal relevance. Not every research question needs to be framed in terms of societal benefit. Some questions are simply interesting. And that should be reason enough to pursue them. I have discussed the broader benefits of fundamental science in a previous blog post, but my position here is simpler: there is no inherent need to justify curiosity. If a question sparks genuine interest, that is a valid foundation for research.

Science has always advanced through a combination of curiosity and application. While societal challenges certainly deserve attention, we risk losing something essential if we sideline curiosity-driven research. A question is worth pursuing simply because it is interesting. Period.

A reflection on the lack of free will.

“I am like a bar of soap. The more you push me, the more I slip away.”

This statement perfectly captures my attitude toward unsolicited advice. The moment someone tells me what to do, I feel an almost automatic urge to do the opposite. I am especially allergic to activist types who climb onto their moral high horse to tell others how to behave. It quickly creates an us-versus-them dynamic, where the person giving advice assumes a kind of moral superiority. Rather than persuading me, it mostly fuels my frustration. In the end, I just do my own thing. Obviously, everyone is entitled to their own opinion. But everyone is also entitled to make their own choices. Live and let live.

But are we really in control of our own choices? Do we actually have free will? After reading “Determined“ by Robert Sapolsky, I became convinced that free will is an illusion (although someone recommended “Free Agents“ by Kevin J. Mitchell for a different perspective). Recognizing that free will is an illusion leads to an interesting perspective on success and failure. I don’t want to give you a moral lesson (that would be hypocritical), but just share a thought-provoking idea that might keep you up at night.

What came before

Sapolsky’s argument that free will is an illusion can be understood as an infinite regress of causes: an ever-extending chain of “what came before”. Consider a simple choice, such as selecting coffee over tea. That decision arises from certain patterns of neural activity, which are shaped by your hormonal state at the time. Those hormonal levels, in turn, depend on your genetic predispositions to particular circumstances. Those genes do not operate in isolation; they are regulated by environmental influences, which themselves reflect prior conditions and experiences. Tracing this chain further back leads to the evolutionary history that shaped those genes in the first place. Once these layers are connected, it becomes increasingly difficult to identify any point at which a decision emerges independently of prior influences. As Sapolsky puts it:

“In order to prove there’s free will, you have to show that some behavior just happened out of thin air in the sense of considering all these biological precursors. It may be possible to sidestep that with some subtle philosophical arguments, but you can’t with anything known to science.”

For a more complete exploration of this argument, I encourage you to read the book. But let’s continue with the premise that free will is indeed an illusion. This conclusion leads to some interesting insights on the value of failure and success.

The graduate and the garbage collector

One passage from Sapolsky’s book that particularly resonated with me presents a thought experiment at a university graduation ceremony. He captures the scene so vividly that it is worth quoting in full, so I will include the entire section below. Take your time to read it and reflect on its implications.

“Imagine a university graduation ceremony. Almost always moving, despite the platitudes, the boilerplate, the kitsch. The happiness, the pride. The families whose sacrifices now all seem worth it. The graduates who were the first in their family to finish high school. The ones whose immigrant parents sit there glowing, their saris, dashikis, barongs broadcasting that their pride in the present isn’t at the cost of pride in their past.”

“And then you notice someone. Amid the family clusters postceremony, the new graduates posing for pictures with Grandma in her wheelchair, the bursts of hugs and laughter, you see the person way in the back, the person who is part of the grounds crew, collecting the garbage from the cans on the perimeter of the event.”

“Randomly pick any of the graduates. Do some magic so that this garbage collector started life with the graduate’s genes. Likewise for getting the womb in which nine months were spent and the lifelong epigenetic consequences of that. Get the graduate’s childhood as well—one filled with, say, piano lessons and family game nights, instead of, say, threats of going to bed hungry, becoming homeless, or being deported for lack of papers.”

“Let’s go all the way so that, in addition to the garbage collector having gotten all that of the graduate’s past, the graduate would have gotten the garbage collector’s past. Trade every factor over which they had no control, and you will switch who would be in the graduation robe and who would be hauling garbage cans. This is what I mean by determinism.”

“And why does this matter? Because we all know that the graduate and the garbage collector would switch places. And because, nevertheless, we rarely reflect on that sort of fact; we congratulate the graduate on all she’s accomplished and move out of the way of the garbage guy without glancing at him … It is the events of one second before to a million years before that determine whether your life and loves unfold next to bubbling streams or machines choking you with sooty smoke. Whether at graduation ceremonies you wear the cap and gown or bag the garbage. Whether the thing you are viewed as deserving is a long life of fulfillment or a long prison sentence.”

Beyond your control

Let me return to one particularly striking sentence: “Trade every factor over which they had no control, and you will switch who would be in the graduation robe and who would be hauling garbage cans.” It captures, in a single line, how profoundly our lives are shaped by forces beyond our control.

We are quick to praise individuals for their hard work and discipline, or to reward the “best” among us with meaningless awards (also see this blog). However, we rarely pause to consider the countless unseen factors – genetics, upbringing, and chance encounters – that have played a decisive role in their success. In the same way, we are quick to blame people for their failures or poor decisions, without reflecting on the equally powerful influences that have shaped those outcomes.

This thought experiment has fundamentally shifted how I view the world. It is tempting to feel resentment when someone succeeds undeservedly, or to complain when misfortune befalls someone who seems to deserve better. But if most outcomes are deeply contingent on factors beyond individual control, then both success and failure begin to look less like personal achievements or shortcomings, and more like the result of a vast web of interconnected circumstances.

Go with the flow

Finally, extending this perspective into the future leads to a striking – and somewhat unsettling- realization: if every event is the product of prior causes, then in a sense, everything is already determined. The present unfolds from the past, and the future follows from the present in a continuous chain of events.

But does that mean we should simply throw up our hands and surrender to chaos or apathy? Not quite. Even if free will is an illusion, the web of causes shaping our actions is so vast and intricate that it remains practically impossible to untangle it. For all practical purposes, we still experience ourselves as free agents who can make our own choices. That is why it makes sense to live as if we have free will.

For me, viewing the future as fixed (yet fundamentally unknowable) feels oddly liberating. It allows me to let go of the pressure to control everything and instead move with the flow of events, trusting that things will unfold as they must (note that I do not believe in “fate” or any mystical nonsense). Don’t worry about success or failure. Instead of striving to change the world or alter the behavior of others, there is a certain peace in engaging with life as it comes.

Sit back, relax and enjoy the ride.

Can you survive the academic rat race without a burnout?

Academia is often described as a rat race: a hypercompetitive world driven by a relentless “publish or perish” culture. Researchers are forced into a relentless cycle of producing papers and chasing funding. The consequences are no secret: burnout, mental health struggles, and quiet quitting (i.e. doing only the bare minimum to stay afloat). In its current form, the academic game is clearly unsustainable.

But there is something misleading about the metaphor of a rat race. A race implies a finish line. And I would argue that there is no clear finish line in academia. This perspective was nicely captured in a quote by James Clear (the author of Atomic Habits): “The important stuff has no finish line.” Research, mentorship, and curiosity are not tasks to complete but practices to sustain. Hence, treating academic life as a never-ending sprint is fundamentally flawed. What we need instead is a more sustainable, resilient way of working.

“Many of the best things in life are endless. Being in a great relationship. Staying fit and healthy. Doing work that fulfills you. Being a good parent, coach, or teacher. Stop worrying about accomplishing these things and instead focus on building a life where you continually practice them. The important stuff has no finish line.”

James Clear

Slow Productivity

This is where the idea of “slow productivity” enters the conversation. I have written about this philosophy in previous blog posts (see here and here). At its core, slow productivity rests on three simple but powerful principles:

1. Do fewer things
2. Work at a natural pace
3. Obsess over quality

Rather than focusing on rapid output, the goal is to maximize meaning and impact over the long term. This movement has gained traction in recent years. Books like The Slow Professor by Maggie Berg and Barbara Seeber, and Slow Productivity by Cal Newport, have challenged the assumption that faster is always better. Yet despite these ideas entering the mainstream, many researchers still feel compelled to constantly do more. A symptom of what the Korean philosopher Byung-Chul Han has described as the “achievement society” (also see this blog post).

Let’s Play a Game

To make this conversation more tangible (and a bit more playful), I decided to build a game: The Slow Professor. Using a vibe-coding approach, I created a simulator that allows players to experiment with different academic strategies. The premise is simple: navigate academia while keeping your mean stress level as low as possible.

You earn bonus points for academic rank (from Assistant Professor to Full Professor). But if you hit burnout, you lose points. Using different settings, you can explore various roles – such as field ecologist, data scientist, or dedicated lecturer – and adjust how strictly you adhere to university rules (through “mandated cards” option). Each choice affects your workload, stress, and long-term trajectory. Unfortunately, WordPress wouldn’t let me host the game directly on the blog. But you can access it through my GitHub page.

My hope is that the game will sparks some conversation and reflection. What if academic success isn’t about doing more, but about doing meaningful things in a sustainable way? After all, the important stuff has no finish line.