Science in action: accelerating the zero-emission transition faster

The ongoing effort to accelerate the transition to zero-emission, could get even faster by a deeper understanding of Science in Action (SiA). The authority on SiA is Bruno Latour, creating theoretical knowledge about the system dynamics behind SiA. The theory can be turned into a technique to assist the acceleration, at least that is my postdoc researching in the NEON research project. In this article I will elaborate on the SiA-model and how NEON allows us to do R&D to build a SiA-technique.

Bruno Latour’s first book on the anthropology of science dates back to 1979. The most famous book actually popularized the term “Science in Action” (1987). The most influential book for me is the lesser recognized book Pandora’s Hope (1999). Probably as Latour raises a question at the start of the book: “do you believe in reality” ? Latour was clearly ahead of his time, the concept of alternative facts would only surface in 2017. The book is to me an essential scientific bridge to connect anthropology of science to cognitive research. The complicated link (on a meta-system level) has been examined in my PhD. I will not go into it now. I will focus in this article on the model from the 1999 book. Latour describes it as “the blood flow of science” by circulation of scientific facts, let me simply call it the SiA-model. The SiA-model contains five “loops”. In the book it takes many pages to elaborate these loops, I will try to improve on this by introducing some new language.

Let me start by using a metaphor to elaborate the SiA-model. Consider how stable a four legged chair is, but when you are careful a one leg chair could be enough to sit on. Metaphorically, loop 1 is this required legg and loop 5 is the seat. If you have more loops “in the loop” you gain stability, increase outreach and scale. Let me replace the general “loop” with a better term. Loop 1 is what is known as the science discipline, mobilizing the world via instruments. The science discipline is never a stand alone case, so loop 5 always exists, creating the links and knots binding the science into the social fabric. Loop 5 is what makes science interdisciplinary and creates reciprocity.

Adding the prefix inter- shows the relation between loop 1 and 5, so let me also add prefixes to elaborate the relation between loop 1 and the other loops. We do need to be careful as other scholars have been using terms with a slight different meaning. In this article the prefix will elaborate how the discipline is rooted in the social fabric. Except for loop 2, all other loops have a relationship outside academia.The prefix for loop 2 is therefore intra-disciplinarity and refers to: co-creating knowledge by colleagues to bridge disciplines. The concept of intra-disciplinarity in this paper would be expressed by other scholars as a process from intra- to transdisciplinarity. In those cases intra-disciplinarity research is referring to the same discipline and transdisciplinarity goes beyond the disciplinary perspectives. Still in this paper it would all be called intra-disciplinarity research. Let me elaborate all the loops and how they reach out, next I come back to the concept of transdisciplinarity research.

Intra-transdisciplinary, extra-transdisciplinary and com-transdisciplinary

Intra-transdisciplinarity creates new knowledge that becomes a bridge between two disciplines. For example, combining biology and chemistry into biochemistry. In hindsight the created knowledge is easy, but consider the current scientific enterprise to combine quantum mechanics and computing mechanics into the first quantum computer. Across history several such intra-disciplinarity have happened, some spontaneously, others requiring a scientific enterprise.

As a prefix for loop 3 I suggest extra-disciplinarity: explore scientific knowledge for the benefit of an organization. Extra-disciplinarity connects the science discipline not to another discipline, but towards some special interest party (i.e. allies). Extra-disciplinarity exists with all domains and it is ancient, like philosophers influencing politics. With the industrial revolution extra-disciplinarity got tight strongly to applied sciences. The past decades extra-disciplinarity research has been supported in universities by an internal organizational structure called Technology Transfer Office (TTO).

Debackere (2010) gives a historical overview of TTO. The first generation was the university’s R&D administration for contract research and IP management going back to the 1970s. The second generation TTO are the incubation centers for PhD spinoffs from the 1990s. The third generation TTO is more recent and has a focus on Public Private Partnerships (PPP), like the Eindhoven Engine (2018).

As a prefix for loop 4 I suggest com-disciplinarity: scientific cultivation and preservation of the commons. Latour does not mention the commons, but what he is pointing at with “public representation” gains more autonomy as the commons. The commons are resources accessible to all members of a society. Commons was originally provided to us by mother nature. Cultivating the world allowed us to move beyond the game of natural commons. Like the domestication of plants, animals and eventually non-living objects via technology, creating cultural commons. While loop 1 is about mobilizing the world, loop 4 is about cultivating the world. Latour has a more restrictive view with “public representation” only addressing social commons (i.e. subset of cultural commons). He notices how scientific innovation is depending on public representation to allow cultivation.

By describing loop 4 in relation to the commons we can understand how this part is about a particular self-discipline. As growth and innovation disturbes the existing balance, self-discipline is required to avoid future tragedies. It is seen in all types of evolution: natural evolution, cultural evolution and technological evolution. Growth and innovation can fracture what used to be robust, creating fragility and disbalance. The fragility can result in the tragedy of the commons. Com-disciplinarity is about antifragility to avoid future tragedies.

Com-disciplinarity is the hardest of all “loops” to understand, therefore we have to start with simple examples I call the resource cases. Consider archaeology excavating bones by brushes instead of shuffles, because of the fragility of those bones. Also later, the bones are presented in a protective way. Like glass cabinets at the museum, allowing you to see, but not to touch. The fragile resource case can be generalized to many other resources and what becomes fragile can be surprising. Consider how humans are becoming a fragile resource with new resources like dangerous chemical substances or concentrated radioactive substances. In those resource cases humanes became fragile and required protection.

If we generalize beyond resources, what becomes fragile will be increasingly hard to understand. Think about digital innovations, who could have guessed that our psychological safety would become fragile by social media? Cultivating of digital commons is one of the latest trends and doing participation research in digital communities has taught me a lot about com-disciplinarity. Like how discipline mobilizes the world, while com-disciplinarity cultivates the world. We do see only a very narrow part of the world being cultivated in the lab. In the case of resources it is an artifact. Digital artifacts are often technology as a medium, and a medium can mobilize bigger parts of the world. They are game changers.

For example social media has made the media landscape fragile, creating the turbulent war on sensemaking we currently experience. We can also see how an artifact slowly turns into a medium, like A.I. technology. It has been narrow in the past decades, but with big data it is now becoming broader and it will make our cognition even more fragile as already happened by social media. The need to become aware of com-disciplinarity is going to get increasingly more important. The challenge is to understand the weak signals in the present before they become unstoppable forces of tragedy in the future.

Com-disciplinarity can be perceived as the opposite to extra-disciplinarity. Instead of considering one special interest group, society at large is considered. Evolutionary, com-disciplinarity begins as a local consearn, but now there are global issues, like regulation on carbon-emissions and integral life cycle analyses. From the delicate activities of a scientist to the responsible policymaker, one can recognize how com-disciplinarity is about restricting oneself on short term to avoid tragedy on longer terms. The restriction comes from wisdom. It is not limiting, but a stranger action to include future values. I will give more details on those stranger actions, first an overview:

1. (no prefix) Science discipline: to mobilizing the world
2. Intra-disciplinarity: co-creating a cross-disciplines to bridge existing disciplines
3. Extra-disciplinarity: explore scientific knowledge for the benefit of an organization
4. Com-disciplinarity: scientifically cultivation and preservation of the commons
5. Inter-disciplinarity: all part of the puzzle creating reciprocity

For com-disciplinarity we need these short term restrictions to long term benefits. In an earlier article I elaborate how a technological innovation can use such a method to cross transition gaps. The article elaborates on successive groups in relation to product life cycle. Let me refine my previous article on technology innovation and use it to reason about social innovation.

The restriction to cross the transition gap relates to feedback acquired later in the life cycle of the technology that would be relevant knowledge to build the technological prototype. It is a wicked problem we can overcome by methods that have proven their relevance. The first is called pretotyping. By creating the interface as-if the technology exists, it is possible to have potential customers interacting with the tool before any prototype is built. In the second transition phase the tool exists, but now the market has to be discovered. A big organization can apply dogfooding on its innovative product to mimic an internal market and gain first hand experience by its employees. For an even later group, we would require infrastructure, now digital twins can be built to simulate a large population acting in a particular way to test the infrastructure design.

Pretotyping, dogfooding and (digital) twinning are tools to investigate the value across the life cycle of the product. Other life cycles could relate to the scarcity of the resources, the effect of the waist and the effect on mobilizing the world. For example, social media and the need for information hygiene is a very new need to conserve sense making. In contrast to past SiA (e.g. conservation of ancient bones). The recent SiA is mixing up the mobilization of the world and the cultivation of the world. To address this change let me consider three levels of interdisciplinarity.

Different levels of transdisciplinary research

Interdisciplinar as a concept has been used to refer to many things and I will also use it as a general concept. In practice three levels of interdisciplinarity can be recognized based on how rigorous they use the loops: basic (one loop), relative (tree loops) and integral (four loops) interdisciplinarity. Let me elaborate and give examples for each. Basic interdisciplinary research has trivial intra-, extra- and com-disciplinarity, but is still profound research and lately it has been expressed as transdisciplinary research. Let me express the other two levels of interdisciplinarity also with a prefix: macro-disciplinary (tree loops) and hyper-disciplinary (four loops).

Transdisciplinary are classic scientific enterprises, some going back many centuries. Like described in the stories by Jules Verne e.g. ”Around the world in 80 days” (first published in 1872). Relative interdisciplinary research can have three types with three out of four loops, we can make three possible combinations and each will be a different kind of enterprise: social enterprises (trivial intra-disciplinarity), technology enterprise (trivial com-disciplinarity) and software enterprises (trivial extra-disciplinarity). The social enterprise will be the macro version of transdisciplinarity, yet it is not the most recognized of the modern scientific enterprises. I will start with examples of technology enterprise as the most recognized macro-disciplinary research and end with software enterprise as they will bring us smoothly to hyper-disciplinary research.

In the book (Latour 1999) an example is given of transdisciplinarity research. The case is about a scientific enterprise, funded by the institute of science, to investigate if a forest or savanna is gaining ground. Each science discipline adds a part of the puzzle. A pedologist studies the composition and distribution of soils. A botanist studies the leaves in the forest. A cartographer creating altitude maps, etc. The outcomes of each research can be compared (no creation of a new domain i.e. intra-disciplinarity is trivial). No expensive or unique materials are required for the research, the funding is enough (no institution i.e. extra-disciplinarity is trivial). The scientist takes samples, but they have no impact on the resilient forest (no fragility i.e. com-disciplinarity is trivial).

The most recognizable macro-disciplinary research are technology enterprises like: the particle accelerator (e,g CERN), international space station, nuclear fusion research (e.g. ITER), gravitational wave detector (e.g LIGO), etc. Technology enterprises create new disciplines (i.e. intra-disciplinary is not trivial). Such projects would also require institutions (i.e. extra-disciplinary is not trivial). The research is still very narrow cultivating the world (i.e. com-disciplinary is still trivial). We do see the outcome being broadly spread knowledge in society, but most of these technological enterprises have a trivial impact on the population of the world. At least when the technology is Science in Action (SiA).

Once the research leaves the labs and valorisation becomes more central, the technology can have a serious impact on the world. The process takes several decades and happens after SiA. It is the cultivation of technological evolution. The other two scientific enterprises have broad cultivation and are not seen as scientific enterprises. The social enterprise because the intra-disciplinary is trivial and the software enterprise because it is a wicked and emerging thing not yet fully understood. In both cases the science develops by living labs (including common people) and not by classic labs (only for experts).

Social enterprises are the macro version of transdisciplinarity. As an example, consider how Karl Marx and colleagues in humanities created a movement with communism. They would mobilize some of the largest nations in the world. The living lab was so big, it was like not seeing the trees through the forest. The scale at work also has another significant effect on the weak signals. Often a social enterprise is created to oppose an existing culture. The weak negative signal creates this spiral of problems that develops into a tragedy. Communism has this paradox to destiablis socia structure that did work under capitalism, in a lot of cases it results into famine. Capitalism has this paradox with free-riders, inequality and sustainability.

To overcome those paradoxes requires counter-intuitive thinking. To give a simple example of counter-intuitive thinking consider how Intellectual Property (IP) law makes knowledge, which is intrinsically abundant, become scarce. IP intends to reduce the free-rider problem, but it creates more problems than it solves according to the lesson from the history of technology. Alternatives are possible, but they are challenging to accept as they go against the habitual way of thinking. To elaborate how counter-intuitive the thinking becomes, let me refer to a study I made.

By participating in an open source project I noticed open innovation and assumed the entrepreneurs took over the developers culture. Little did I know about the actual dynamics at work. After in depth interviews with a dozen entrepreneurs it became clear how the effect was not intentional, but a pragmatic spillover effect of the way they had to develop their business i.e. a culture for self-organizing innovation. The entrepreneurs understood the fragility of their business ecosystem and had the willingness to take an economical hit as a company, to protect the fragile community. The entrepreneurial culture was counter-intuitive to classic business logic. Collectively they did resolve the sustainability paradox by com-disciplinary thinking. It worked at least for a while. The entrepreneurial culture breaks down once the development enters the next transition phase. The first transition phase is closely related to research and so we can turn to universities to see how a more structured organization could ensure com-disciplinary thinking.

Current generation universities have a dedicated structure for extra-disciplinarity called TTO. We could envision a similar structure for com-disciplinarity. Let me call it the Cultural Integration Office (CIO). In contrast to TTO, which brings innovative technology to the world, the CIO would bring the world into the labs. In social enterprise we notice how a weak negative signal by strawmanning an opponent grows like a cancer to the system. To avoid the negative spiral and start a positive spiral, we need counter-intuitively steelman and opponent. Steelmanning is building the best form of the other side’s argument and then engaging in sensemaking. Sensemaking can be the cultural-capital tool for CIO, like venture-capital is the tool for TTO. The concept of cultural-capital has an unexpected relation to software development and the concept of hyper-disciplinary research.

Software evolution towards hyper-disciplinary research

The software enterprises have rigorous intra- and com-disciplinary and they exist as proprietary or open source software projects. In both cases the extra-disciplinarity is trivial, needing a basic organization (proprietary company or open source foundation). Compare it to the technology or social enterprise that requires a governing institution. The software enterprise is part of a digital evolution that is eating the world, not just mobilizing the world. The difference between eating versus cultivating the world is an essential difference, changing the game of evolution as we know it.

Humanity has hacked natural evolution by domestication, creating cultural and technological evolution. In a wicked plot twist, software evolution is now hacking humanity. It is humanity at war with itself, as we lack rigorous com-disciplinarity. Software development has been growing exponentially for decades creating some strange challenges, like the perpetual state of inexperience. The game changing dynamics the software revolution is bringing is in my opinion still not fully understood. They are more influential than the game changing dynamics of the industrial revolution. The industrial revolution was the start of labor by machines, the software revolution is the start of cognition by machines in a very unexpected way.

We use metaphors like the technological singularity and the global brain to envision what is to come. If we look at it from the perception of relative interdisciplinary research, we notice how each enterprise (technological, social and software) are converging from the already big macro-disciplinary research into hyper-disciplinary research. Each relative interdisciplinary research has one trivial loop, so they converge as all loops become rigorous. Let me shortly elaborate how each is converging.

Because of the acceleration of innovation, recent technological enterprises are having a broader effect on society (e.g. A.I., crypto technologies). The same tech can become a mediator for social enterprises. With the emerging Internet of Things (IoT) the boundaries with software and other technology enterprises are dissolving too.

The scale and speed are on a whole new level, the macro-disciplinary research involves international collaboration, the new level is global and integral, like the development of the internet. Hyper-disciplinary goes beyond mobilizing the world, it is about turning the earth into a meta-living system. In some cases the trend is expressed as Spaceship Earth. To me it seems a too strong technological focus, alternatively we can see it as the next stage of the Gaia hypothesis. The Gaia hypothesis is about the collective of all life on earth producing a kind of global homeostasis. So a meta-body seems to exist, with the Global Brain this meta-body is gaining a kind of cognitive abilities too.

Hyper-disciplinarity is currently an evolutionary phenomena, it will take decades before the effect is noticed. In this article I suggested an organizational structure in a university to support com-disciplinary research (CIO i.e. Cultural Integration Office) and it can have some effect on evolution. The first expected effect of such a structure would be the macro version of transdisciplinarity, bringing social enterprises truly in the realm of scientific enterprises. Simultaneously software enterprises are penetrating the realm of scientific enterprises via IoT and our ability to run forecast models (like digital twins). I expect TTO, CIO and IoT to stimulate the development of SiA-technique. We can actually do research on the development of a SiA-technique on a smaller scale by focusing on crossover programs, like the NEON project.

NEON (New Energy and Mobility Outlook for the Netherlands)

NEON research is humble in size, but challenging in respect to the SiA model. The team contains 33 Phd students, much smaller than a technological enterprise like CERN. The technological enterprise on zero-emission is much more distributed and NEON is but one player in a bigger emerging ecosystem. What is making NEON interesting is how many of the loops are involved in a minimum setting. As the project deploys, I expect to see a shift across all the loops, so let me go over each loop again.

For NEON, the mobilization of the world is by developing digital twins. The current digital twins forecast models use existing tech that is often outdated by the time of implementation. NEON builds simulation with state-of-the-art tech, currently still in the labs. Allowing a forecast with emerging tech that will exist in the future. The ability to forecast with emerging technology allows a just-in-time implementation for the transition.

In total NEON has ten work packages, each package has to model their particular research into a digital twin so we can run agent based simulations of possible transition scenarios. Work package ten is the integral transition model and the main work package, the other nine packages are intra-disciplinar. At first glance, it looks impossible to bridge so many disciplines simultaneously. Still we are not exactly bridging disciplines, but modeling them into software. This allows to bridge the disciplines first rudimentary and later improve the accuracy.

It is this minimum setting that has all SiA loops in a non-trivial way. This does result in a need to build our own development method for intra-disciplinary collaboration i.e. SiA-technique. The SiA-technique for intra-disciplinarity is based on agile software development, we call agile science. At the moment NEON has been running for a year and half. We expect another year and half before the agile science method is fully operational. In total NEON will run for four years. Recently we did start the development of extra-disciplinarity too and it is expected to be central in the fourth year.

Funding to develop extra-disciplinarity was provided half a year ago and current planning would lead to operational activities in half a year. So the project is in motion and R&D on both the intra- and extra-disciplinarity are assured. Extra-disciplinarity is happening for NEON thanks to the next generation of TTO (Technology Transfer Office). While earlier TTO had a strong focus on one organization, the focus on PPP is turning extra-disciplinarity into a regional enterprise. As NEON is part of the Eindhoven Engine, we have this open dialogue to do research on extra-disciplinarity.

The research in intra-disciplinarity is in active development and the research on extra-disciplinarity is in preparation. In contrast, com-disciplinarity is not enough understood to have applied research beyond the first transition phase. The R&D on the first transition phase would become relevant after extra-disciplinarity became fully operational, so it will take some years. Beyond the first transition phase we need foundational research first. In collaboration with colleagues on transition research we are combining our understanding to a more integral view on the challenge. With the lack of concrete knowledge, I turn to metaphors (see my presentation on how digital wolves change digital rivers).

The entrepreneurial culture allowed the developers community to cultivate a commons at least until the community entered the next transition phase. Internally, the habitual way of working got in the way of resolving growing tensions (for details see this section of my PhD). Externally, the incumbent organizations entered the ecosystem, creating this tragedy of the entrepreneurial culture. As a participant at the sideline, I could only witness the tragedy of the entrepreneurial culture. In NEON I have an active management role and it is focused on the partners. In this setting I can play an active governance role. The governance would be a kind of risk management for the commons during transition phases of NEON. So all together the R&D on the SiA-technique becomes:

1. Mobilizing the world via digital twins (i.e. agent based modeling)
2. Intra-disciplinarity via agile science method
3. Extra-disciplinarity via regional development by PPP (i.e. the Eindhoven Engine)
4. Com-disciplinarity via risk management for the commons during transition phases
5. Inter-disciplinarity: transdisciplinarity, macro-disciplinarity and hyper-disciplinarity

To wrap up, let me elaborate how I envision we could avoid the tragedy of the cultural commons across the transition phases. First we do need to generalize as the entrepreneurial culture happens as the novelty emerges. In the next phase the novelty is integrating and it requires the participation of incumbent organizations. The tragedy of the entrepreneurial culture happened as the habitual kicked in and the incumbent entered the ecosystem. We are implementing agile science to avoid the habitual way of working.

The breakdown as incumbents enter the ecosystem is resolved in a similar way as the transition gaps for product development. In product development it is about the tool, in community development it is about the culture, but the process can be generalized for both:

bringing future experience to the present to avoid lock-in action that could easily be avoided. For tools it was bringing customers and market experience to the moment of innovation. For culture it is about bringing incumbents experience and political experience to the moment of innovation.

The tension between incumbents and entrepreneurs was clearly experienced in previous participation research. The need to include politicians relates to the weak signal picked up during the final experiment. Let me first address how to include incumbents and next give more details on the weak signal during the final experiment.

The PhD students are the bridge, being strongly interacting with one of the partners and with the other PhD students. With NEON we do have 20 Public Private Partners (PPP) from incumbent markets (energy and mobility) involved at the beginning of the innovation. The co-creation produced by agile science is expected to create serendipity first for the PhD students and later propagate to the partners. Serendipity and spillover effects are expected based on historical cases on technology, what they are is by definition unknown. Important is to create the setting and navigate with the tension that will arise. Like the interviews with the entrepreneurs, it is currently unknown what the outcome is. The setting will provide the right way to do the research and after the agile science experiment we can report about the outcome.

The weak signal of the final experiment was about the power game. The power game was a spillover effect of the collective psychology. The experiment was set up to work with exponential propagation and it worked as designed, from a small group of innovators who helped me govern the majority of students. The IT-platform kept control over the checks and balances, while most of the educational tasks became peer-learning. The emerging dynamic at the front of the curve (innovators) was by design. Unexpectedly a similar dynamic emerged at the end of the curve, where resistance had enough critical mass to produce an opposition. The power dynamic between majority and opposition is well known from politics. It was a surprise to see the power dynamic emerge in the experiment.

While I’m now aware of the power dynamics, it is too early to work on that later transition phase. The current research is about integrating lessons learned from agile education research to enable agile science research. Between 2006–2010 I ran agile education experiments to eventually create a final experiment at scale in 2010–2011. It would be great if I could run an agile science experiment at scale after three years and learn more about the power dynamics. It appears NEON research is a good environment to develop a proof-of-concept around SiA-technique and provide us with the required insights. Including politicians could be for a follow up research. The research is only at the beginning of its journey, who knows where the path will bring us.