Immanuel Kant and the Hallucinating Tester

Quality is an illusion. That may seem like a bold statement, but there is a deeper truth to it that I will discuss in this blog. I’ll also discuss how we can approach the real.

We can think of testers as doctors, scientists, or researchers whose job is to research, explore, or examine some software, gather, analyze, and communicate factual knowledge based on observations.

But science teaches us that when we research and observe things, including software, what we “see” is not reality. At TED 2017, University of Sussex neuroscience professor Anil Seth called what we see “hallucinations”.

This gives the hopefully scientific tester some severe epistemological challenges: As she is a person, and is hallucinating, how can she (or we) trust her observations?

The problem for her is that the images that she experiences as real are a synthesis, an intuitive product of her observances based on a minimal amount of sensory data. The critical mindset is important in testing but doesn’t help by itself.

Fortunately philosophy has a solution for her (and us). Before I explain it, let me share a daily life story about intuitive illusions and assumptions.


Walking on Black Ice

I was out walking my poodle Terry a few days ago. A car came against us, but as we were on the sidewalk and the car on the road, the situation was intuitively safe.

Unfortunately, my intuition turned out to be wrong as only a moment later my foot slipped on the sidewalk and I realized that the wet road was not wet; both the road and the sidewalk were covered in black ice.

When another car approached I was aware of the danger, and made sure to keep myself and my dog safe.

There could be a moral in this story about always being cautious about cars and roads, but it might end up in over-cautiousness of the type that grandmothers sometimes impose on their grandchildren.

Instead I consider it a reminder that we don’t see things as they are: The road was wet until my foot slipped and I realized it was icy.

Already the Stoic philosophers in Rome 2000 years ago had figured this out.


Immanuel Kant’s Model of Mind

In 1781 the German philosopher Immanuel Kant published his mammoth work Critique of Pure Reason in which a key concept is the transcendental, which can be thought of as a bridge between the real and the hallucination.

Let me explain: Something that is only realized by intuition, dreams, myths etc, and which doesn’t link to experience, is transcendent. Something realized by pairing sensing and experience is transcendental.

Kant’s model is simple and straightforward, as Kant was pedantic, but it still needs some explanation:

Outside us is of course the objects which we sense. Kant calls them “the things in themselves”. It could be the road I was walking with my dog.

Kant thinks of us as rational beings who act on the basis of the thing in itself, and that has caused much debate. Skepticism will claim that the thing in itself is not available, and that there is only the subjective experience. Logical positivism will claim that the thing in itself doesn’t exist at all. Realism will doubt the subjective. We can probably all appreciate that the always rational human doesn’t exist.

But Kant’s bridge is interesting. What he says is that even though “the thing in itself” is not available to us, we can still say rational things about what we see.

So the mind is connected to the real in a way so we can gain and share experience. Does it sound weird? In a way it is, but Kant’s arguments has generally stood the test of time and critical philosophers – and even neuroscience.

So let me tie this to testing.


Belief as a Premise

There are different ways to test: In exploratory testing, we do it interactively by operating and observing the software. In automated testing we “outsource” the actions to another piece of software, and our task is then reduced to making sense of data from the tests and suggest and possible implement changes to the test-software. Scripted and chartered testing sits somewhere in-between the two “extremes”.

However,no matter how we practice testing, we need to make sense of what is observed. And since observing is subjected to sensing, the only thing we have available is our intuitive image about the thing we are testing.

James Bach is quoted as saying “Belief is a sin for testers.” I like the quote as it is an important reminder to be careful what we think: It’s not reality. The road might not only be wet. The software probably doesn’t always do what it did this time. I probably missed something. My mind is hallucinating.

So with a bit of wordplay in Kant’s home language, German, I’ll say that “die Sinne ist die Sünde.”

Our senses are the sinner, but as they are also our only hope to see some tings about reality belief is not an option. It’s a premise.

But since we know, we can establish the transcendental: Think the real rationally by testing our beliefs.

In other words: The realist approach to testing is to test the product. The transcendental approach is to test beliefs.


On Common Terms

There is something missing in the above as so far I’ve only talked about sensing, imagining, and experiencing. The brilliant part of Kant’s philosophy is that he explains how we can collect experiences.

Kant develops four categories of terms that we think by, and argues how they are given to us a priori, i.e. before we experience anything. He argues how they come from the existence of time and space. Back in his time Newton had just published his theories. Today, we’ve progressed, and it probably makes better sense to think of the terms as a result of the experience of space and time.

But what’s important is that although our experiences vary, we’re on common terms, so to speak.

This is important as it means we can think and express our knowledge about experiences generally.

Let me give some examples: I told you about the black ice on the road above, and while cannot be certain what I said is true, you can understand my experience. I can also share a testing problem, and we can imagine solutions together. I can try them out afterwards, and share experiences with you. We can even talk about testing in general, and imagine solutions to certain testing problems in general.

In other words: The terms allow us to relate, connect, discuss, collaborate, learn, reflect, prospect etc.

This makes the transcendental model of experience complete: We can sense, imagine, think, and express our thoughts into words and actions that we can share with others, who can do the same.


The Two Things I Want to Say

So what do I want to say with all this? I want to say two things:

The first is that yes, we are trapped in hallucinating minds. We might theoretically be able to escape them if we subject our testing to strict scripted procedures, make sure what we do is repetitively accurate, and only communicate what we can verifiably record and therefore objectively observe. But we’ll essentially be turning ourselves into machines and miss intuitive and tacit knowledge. And one way or another, we’re still stuck in a mess where at every and any judgement and decision made will be based on hallucinations.

But we’re not lost as we can explore the product and our intuitive ideas about it transcendentally, i.e. by realizing that both are in play when we test. Although we can’t get access to the “thing as it is”, we can experience it. Our expeirences do not have to be transcendent, i.e. disconnected from real, but can be transcendental.

And this is the second thing I’ll say: Since we are not alone in the trancendental, our roles as testers become clearer.

People are different, but I think a fundamental, perhaps even genetically coded, qualification for testers is to be sensitive people with intuitions which are easily disturbed by reality. On top of that, great testers need critical thinking skills, i.e. courage to doubt intuitive illusions, and creativity to come up with test ideas useful in the context. The rest is about interaction and communication with teams and stakeholders so that the good hallucinations about the software that we develop through our testing are shared.


Testing Transcendentally

In the spirit of Anil Seth, the neurology professor, let’s be honest: Software quality is a hallucination.

We can’t escape our minds and the apparent mess created by the hallucinations we think of as real. But we can experience quality transcendentally by testing.
To me testing is not so much an exploration of a product.

I see testing first and foremost as the transcendental practice of exploring of our own, and our team colleagues’ and stakeholders’ hallucinations about the product.



Cynefin and the Greek Square

Recently I discovered that there is a relation between Cynefin’s domains and the Greek Square, a square formed by the four fundamental human values; the true, the just, the beautiful, and the good.

This became clear to me when I was thinking about values governing and shaping our actions in the domains.

In the obvious domain, truth is the governor. What else could shape action in that domain than a desire for truth, fact, and sticking to those facts?

In the complicated, justice shapes actions, as this is where we ask others for help and seek knowledge, which always needs justification in the social. It is okay letting solutions on complicated problems rely on knowledge bases, past solutions to similar problems, and expertise.

The value that shapes my actions in complexity seems to be beauty. Dijkstra said, “beauty is our business” when he described programming. Creative and aesthetic leadership are tightly connected. Some philosophers have described the sense of beauty as a taste. In that case, the thing that keeps me going is the hope for good taste. And good taste is not just good, it is something with aesthetic value.

In chaos, we need to stay grounded, but act on our toes. A desire to do good is the only thing capable of grounding us in chaos, and this is where ultimately gut feelings (gut etymologically has the same root as good, and even God), and intuition are what I can rely on.

(I put freedom in the middle in my sketch below. This was inspired by Ole Fogh Kirkeby, who connects the four fundamental human values with human freedom. Whether it fits Cynefin, I’m not sure.)


More to come…

Introducing STPA – a new Test Analysis Technique

At the core of innovation in IT is someone getting the idea of connecting existing services and data in new ways to create new and better services. The old wisdom behind it is this:

The Whole is Greater than the Sum of its parts
– Aristotele

There is a flipside to this type of innovation that the opposite is also true: The whole can become more problematic than the negative sums of all the known risks.

My experience as a tester and test manager is that projects generally manage risks in individual subsystems and components quite well.

But I have on occasions found that we have difficulty imagining and properly taking care of things that might go wrong when a new system is connected to the infrastructure, subjected to real production data and actual business processes, and exposed to the dynamics of real users and the environment.

Safety, Accidents and Software Testing

Some years ago, I researched and came across the works of Dr. Nancy Leveson and found them very interesting. She is approaching the problem of making complex systems safe in a different way than most.

Leveson is professor of aeronautical engineering at MIT and author of Safeware (1994) and Engineering A Safer World (2011).

In the 2011 book, she describes her Systems-Theoretic Accident Model and Process – STAMP. STAMP gives up the idea that accidents are causal events and instead perceives safety as an emergent property of a system.

I read the book a while ago, but has only recently managed to begin the transformation of her ideas to software testing.

It actually took a tutorial and some conversations with both Dr. Leveson and her colleague Dr. John Thomas at the 5th European STAMP/STPA workshop in Reykjavik, Iceland in September to completely wrap my head around these ideas.

I’m now working on an actual case and an article, but have decided to write this blog as a teaser for other testers to look into Leveson’s work. There are quality resources freely available which can help testers (I list them at the end of this blog).

The part of STAMP I’m looking at is the STPA technique for hazard analysis.

According to Leveson, hazard analysis can be described as “investigating an accident before it occurs”. Hazards can be thought of as a specific type of bug, one with potentially hazardous consequences.

STPA is interesting to me as a tester for a few reasons:

  • As an analysis technique, STPA helps identify potential causes of complex problems before business, human, and societal assets are damaged.
  • One can analyze a system and figure out how individual parts need to behave for the whole system to be safe.
  • This means that we can test parts for total systems safety.
  • It works top-down and does not require access to knowledge of all implementation details.
  • Rather, it can even work on incomplete models of a system that’s in the process of being built.

To work, STPA requires a few assumptions to be made:

  • The complete system of human and automated processes can be modeled as a “control model”.
  • A control model consists of interconnected processes that issue control actions and receive feedback/input.
  • Safety is an emergent property of the actual system including users and operators, it is not something that is “hardwired” into the system.

I’d like to talk a bit about the processes and the control model. In IT we might think of the elements in the control model as user stories consisting of descriptions of actors controlling or triggering “something” which in turn produce some kind of output. The output is fed as input either to other processes or back to the actor.

The actual implementation details should be left out initially. The control structure is a mainly a model of interconnections between user stories.

Given the control model sufficiently developed, the STPA analysis itself is a two step activity where one iterates through each user story in the control structure to figure out exactly what is required from them individually to make the whole system safe. I won’t go into details here about how it works, but I can say that it’s actually surprisingly simple – once you get the hang of it.

Dr. John Thomas presented an inspiring tutorial on STPA at the conference.

Safety in IT

I have mentioned Knight Capital Group’s new trading algorithm on this blog before as it’s a good example of a “black swan project” (thanks to Bernie Berger for facilitating the discussion about it at the first WOTBLACK workshop).

Knight was one of the more aggressive investment companies in Wall Street. In 2012 they developed a new trading algorithm which was tested using a simulation engine. However, the deployment of the algorithm to the production environment turned out to be unsafe: Although only to be used in testing, the simulation engine was deployed and started in production resulting in fake data being fed to the trading algorithm. After 45 minutes of running this system on the market (without any kind of monitoring), Knight Capital Group was bankrupt. Although no persons were harmed, the losses were massive.

Commonly only some IT systems are considered “safety critical” because they have potential to cause harm to someone or something. Cases like that of Knight Capital indicate to me that we need to expand this perspective and consider safety a property of all systems that are considered critical to a business, society, the environment or individuals.

Safety is a relevant to consider whenever there are risks that significant business, environmental, human, personal or societal assets can be damaged by actions performed by a system.

STAMP/STPA and the Future of Testing

So, STPA offers a way to analyze systems. Let’s get this back to testing.

Software testing relies fundamentally on testers’ critical thinking abilities to imagine scenarios and generate test ideas using systematic and exploratory approaches.

This type of testing is challenged at the moment by

  • Growing complexity of systems
  • Limited time to test
  • Problems performing in-depth, good coverage end-to-end testing

DevOps and CD (continuous delivery) attempts to address these issues, but they also amplify the challenges.

I find we’re as professional testers more and more often finding ourselves trapped into frustrating “races against the clock” because of the innovation of new and more complex designs.

Rapid Software Testing seems the only sustainable testing methodology out there that can deal with it, but we still need to get a good grip on the complexity of the systems we’re testing.

Cynefin is a set of theories which are already helping testers embrace new levels of complexity in both projects and products. I’m actively using Cynefin myself.

STAMP is another set of theories that I think are worth looking closely at. Compared to Cynefin, STAMP embraces a systems theoretical perspective and offers processes for analyzing systems and identify component level requirements that are necessary for safety. If phrased appropriately, these requirements are direct equivalents of test ideas.

STAMP/STPA has been around for more than a decade and is already in wide use in engineering. It is solid material from one of the worlds’ leading engineering universities.

At the Vrije Universiteit in Amsterdam, the Netherlands they have people taching STPA to students in software testing.

The automobile industry is adopting STPA rapidly to manage the huge complexity of interconnected systems with millions of lines of code.

And there are many other cases.

If you are curious to know more, I suggest you take a look at the resources below. If you wish to discuss this or corporate with me on this, please write me on twitter @andersdinsen or e-mail, or join me at the second WOTBLACK workshop in New York on December 3rd, where we might find good time to talk about this and other emerging ideas.


Thanks to John Thomas and Jess Ingrassellino for reviewing drafts of this blog post. Errors you may find are mine, though.

This photo shows machinery in an Icelandic geothermal power plant. Water heated to 300 deg C by the underground magma flows up and drives turbines and produces warm water for Reykjavik.

With Cynefin, I can justify skepticism about inappropriate approaches and co-create better ones

As testers we need to better understand and be explicit about problems in testing that don’t have known, clear, or obvious solutions. Cynefin can help by transforming the way we, our teams, and our stakeholders think about testing problems.

Ben Kelly and James Christie has written very good blogs about Cynefin and testing. Liz Keogh was one of the first to write about Cynefin in development. At the bottom of this post, I have included a video with David Snowden and a link to an article I found interesting when I read it.

With this blog post I’m sharing elements of my own understanding of Cynefin and why I think it’s important. I think of Cynefin itself as a conceptual framework useful for comprehending dynamic and complex systems, but it is also a multi faceted “tool” which can help create context dependent conceptual frameworks, both tacit and explicit, so that we can better solve problems.

But before diving into that (and in particular explain what a conceptual framework is), I’d like to share something about my background.

Product design and the historic mistakes of software development

I used to study product design in university in the early 90’s. Creating new and innovative products does not follow obvious processes. Most engineering classes taught us methods and tools, but product design classes were different.

We were taught to get into the field, study real users in their real contexts, develop understandings of their problems, come up with prototypes and models of product ideas, and then try out these prototypes with the users.

Discussing an early draft of this post with James Christie, he mentioned that one of the historic mistakes of software development has been the assumption that it is a manufacturing process, whereas in reality it is far more like research and development. He finds it odd that we called it development, while at the same time refusing to believe that it really was a development activity.

SAFe, “the new black” in software delivery, is a good example of how even new methodologies in our industry are still based on paradigms rooted in knowledge about organizing manufacturing. “The Phoenix Project”, a popular novel about DevOps states on the back cover that managing IT is similar to factory management.

What I was taught back in the 90’s still help me when I try to understand why many problems remain unsolved despite hard work and many attempts on the opposite. I find that sometimes the wrong types of solutions are applied, solutions which don’t take into consideration the true nature of the issues we are trying to get rid of, or the innovations we’re trying to make.

Knight Capital Group, a testing failure

The case of Knight Capital Group is interesting from both innovation, risk and software testing perspectives, and I think it exemplifies the types of problems we get when we miss the complexity of our contexts.

Knight Capital Group was one of the more aggressive investment companies in Wall Street. In 2012 they developed a new trading algorithm. The algorithm was tested using a simulation engine, I assume to ensure to that stakeholders that the new algorithm would generate great revenues.

The testing of the algorithm was not enough to ensure revenues, however. In fact, the outcome of deploying to algorithm to production was enormous losses and the eventual bankruptcy of the company after only 45 minues of trading. What went wrong?

SEC, Securities and Exchange Commission of the U.S.A.:

[…] Knight did not have a system of risk management controls and supervisory procedures reasonably designed to manage the financial, regulatory, and other risks of market access […] Knight’s failures resulted in it accumulating an unintended multi-billion dollar portfolio of securities in approximately forty-five minutes on August 1 and, ultimately, Knight lost more than $460 million […]

But let’s assume a testing perspective.

It think it’s interesting that the technical root cause of the accident was that a component designed to be used to test the algorithm by generating artificial data was deployed into production along with the algorithm itself.

This test component created a stream of random data and was of course not supposed to run in production since it was designed to generate a stream of random data about worthless stock.

I find it strangely fascinating that the technical component that caused the accident was designed for testing.

Why didn’t someone ensure that the deployment scripts excluded the testing components?

Was it software testing that failed? It is not uncommon that software testing is entirely focused on obvious, functional and isolated performance perspectives of the system under test.

The component did it’s job: Helped test the new product. The testing strategy (probably undocumented) however, obviously did not consider possible side effects of the component.

I think Cynefin could have helped.

Cynefin transforms thinking

Let’s imagine we’re test managers at Knight and that we choose to use Cynefin to help us develop the testing strategy for the new algorithm. 

David Snowden talks about Cynefin as a ‘sensemaking tool’ and if you engage Knights’ management, financial, IT-operations, and development people in a facilitated session with a focus on risks and testing,

I’m pretty sure the outcome would be the identification of the type of risk that ended up causing the bankruptcy of the company, and either prevented it by explicitly testing the deployment process, or made sure operations and finace put the necessary “risk management controls and supervisory procedures” in place.

I think so because I have observed how Cynefin sessions with their brainstormings are great for forming strategies to deal with the problems, issues, challenges, opportunities etc that we are facing. It helps people talking seriously about the nature of problems and issues, transforming them into smaller chunks that we can work with, and to help escalate things that require escalation.

Cynefin seems to be efficient breaking the traditional domination of boxed, linear and causal thinking that prevent problem solving of anything but the simplest problems.

My interpretation of what is happening is that Cynefin helps extend the language of those participating in sessions.

Decision makers a Knight Capital did not think about possible negative outcomes of the testing software. They had a simplistic view of their business risks. Cynefin could have helped them by extending their ‘sensemaking’ to more complex risks than those they were focusing on.

In the following I’ll dive a bit more into why I understand the sensemaking part of Cynefin to be a language-extending tool.

Language and Conceptual Frameworks

Language is an every-day thing that we don’t think much about.

Yet it is the very framework which contains our thinking.

While we can know things we cannot express (tacit knowledge), we cannot actively think outside the frame language creates.

Many philosophers have thought about this, but here I’d like to refer to physicist Niels Bohr (1885-1962) who in several of his lectures, articles, and personal letters talks about the importance of language in science.

Science is in a way about sensemaking through knowledge gathering and poetically (paraphrasing from my memory) Bohr describes language as the string that suspends our knowledge above a void of endless amounts of experiences.

In “The Unity of Science”, a lecture given at Columbia University, New York in 1954, Bohr introduce language as a “conceptual framework”:

“[it] is important […] to realize that all knowledge is originally represented within a conceptual framework adapted to account for previous experience, and that any such frame may prove too narrow to comprehend new experiences.”


“When speaking of a conceptual framework, we merely refer to an unambiguous logical representation of relations between experience.”

Bohr was the father of quantum physics, which is more than new laws about nature. It introduced new and complimentary concepts like uncertainty, and non-deterministic relations between events. The extension was made for quite practical purposes, namely the comprehension of observations, but has turned out to be quite useful:

“By means of the quantum mechanical formalism, a detailed account of an immense amount of experimental evidence regarding the physical and chemical properties of matter has been achieved.”

The rest is history, so to speak.

This is relevant to software testing and Cynefin because I think that the conceptual frameworks based on the thinking developed during industrialism are far from capable of explaining what is going on in software development and therefore also in testing.

Further, Cynefin seems to be an efficient enabler to create extensions to the old thinking frameworks in the particular contexts in which we use it.

Cynefin and software testing

Software development is generally not following simple processes. Development is obviously a human, creative activity. Good software development seems to me to be much more like a series of innovations with the intention to enable someone doing things in better ways.

Testing should follows that.

But if language limits us to different types of linear and causal thinking, we will always be missing that there is generally no simple, algorithmic or even causal connection between the stages of (1) understanding a new testing problem, (2) coming up with ideas, and (3) choosing solutions which are effective, socially acceptable, possible to perform, and safe and useful.

Experienced testers know this, but knowledge is often not enough.

James Christie added in his comments to the early draft mentioned above that as testers, with Cynefin we can better justify our skepticisms about inappropriate and simplistic approaches. Cynefin can make it less likely that we will be accused of applying subjective personal judgment.

I would like to add that the extended conceptual framework which Cynefin enables with us and our teams and stakeholders further more allow us to discover new and better approaches to problem solving

David Snowden on Cynefin

This video is a very good, quick introduction to Cynefin. Listen to David Snowden himself explain it:


AI personally found this article from 2003 a very good introduction to Cynefin:

The new dynamics of strategy: Sense-making in a complex and complicated world (liked page contains a link to download the article)


Efter 15 år som freelancer tør jeg godt tvivle på mig selv

I disse dage er det 15 år siden jeg tog springet og gik freelance. Det har jeg ikke fortrudt!

Jeg er blevet hyret ind som eksperten, der skal gøre det komplicerede enkelt og løse problemer. For det meste I lange kontrakter, men altid som den frie fugl. Jeg elsker det faktisk!

Konsulentjobbet kræver masser af kærlighed: Kærlighed til problemerne, der skal løses og kærlighed til de mennesker som har problemer. Ja, og kunden. Der følger også mere kedelige ting med: Kontrakter, fakturering,… den slags. De er en del af gamet.

I gamet er også en forventning om performance: At vi hurtigt kan gå ind og “levere varen” – uden slinger i valsen.

Ydmyghed er faktisk utrolig afgørende. For, – hånden på hjertet – konsulenter er langt fra perfekte og slet ikke ufejlbarlige.

Specialistrollen og forventningen om den sikre performance må aldrig komme til at betyde, at man ender med næsen i sky. Jeg kan godt blive lidt flov, hvis jeg ind imellem møder en anden konsulent med en attitude i retning af at de er universaleksperter, der altid ved bedst.

Jeg synes jeg selv er rimeligt god til at undgå den attitude. For mig hjælper det at jeg jævnligt mindes om nogle af de fejl jeg har begået. Efter 15 år i rollen har jeg ikke længere tal på, hvor tit jeg har fejlet i en opgave. Pinligt, men sandt. Og nu har jeg sagt det!

Den klassiske pinlige situation for mig som tester er et ”bugslip”: Kunden vil gerne have testet, at systemet vi arbejder med viser netop et bestemt resultat og jeg er hyret ind til at dokumentere kvaliteten af systemet inden vi går i produktion med det.

Jeg er testekspert og har indsigt i teknikken og projektet. Jeg udfører ordren. Det ser fint ud. Vi overholder planen. Alt er godt.

Men så kommer der melding om en fejl i produktion, og endda et åbenlyst problem som jeg simpelthen overså da jeg testede.

I sådan en situation er det ikke rart, at være i mine sko. Puh, jeg husker hver eneste gang det er sket, og det er mere end en gang! Det ligger desværre i testerjobbet, at det sker. Jeg prøver, at afstemme forventningerne om det, men sjovt er det aldrig.

Den situation og andre fejl jeg har haft del i har lært mig, at nok er det ret vigtigt at bruge sin erfaring og ekspertise, men det er også vigtigt at kunne tvivle på sig selv. Ja, tvivle: At vide, at ekspertise tit er langt fra nok til at garantere succes.

Sommetider er det faktisk netop ekspertisen, der står i vejen for at man gør det godt.

En generel ting jeg har tænkt lidt over (men ikke tænkt færdig) er, at vi alle faktisk burde blive bedre til at improvisere. Altså improvisere ærligt og blive dygtige til det: Fejle kontrolleret, observere det vi kan lære – og gøre bedre, fejle lidt mindre, evaluere, gøre det meget bedre.

Altså blive bedre til at undgå at lade os blænde af tidligere gode erfaringer – og derfor misse det åbenlyse.

Jeg tror i alle tilfælde på, at det er en kvalitet, når jeg som konsulent tager tvivlen med på arbejde – som en god ven, der hjælper til at jeg gør mit bedste. Og jeg tror på, at det er en kvalitet, hvis jeg deler tvivlen på en konstruktiv måde, så vi i fællesskab kan bruge den til at gøre vores bedste.

Ekspertisen og erfaringen er stadig vigtig. Men tvivlen må vi alig glemme.

I øvrigt føler jeg mig klar til at tage 15 år mere. Måske ses vi derude! Og bliv ikke overrasket, hvis jeg er eksperten, der tvivler.