October 2023
Climate change and other difficult challenges facing global society are prompting a search for new ways of approaching social innovation. At a time when increasingly complex circumstances are rendering accepted wisdom and existing systems of knowledge less relevant, the concept of “natural-born intelligence” put forward by the theoretical biologist Professor Yukio-Pegio Gunji represents a potential key to overcoming a growing rigidity in societal systems and technology. How can this natural-born intelligence be put to work in a society that is in thrall to artificial intelligence? A proponent of the idea that the natural-born intelligence of human beings is the wellspring of innovation, Professor Gunji here discusses this proposition with his former student, Youichi Horry, who has been involved in a wide variety of work at Hitachi, Ltd. In this section, they focus on the platform technologies for supporting the transition to a sustainable society. Then, they look at the formulation of “problem” and “solution” and the relationship between individual intentionality and group order.
Yukio-Pegio Gunji,Ph.D.
Professor, Department of Intermedia Art and Science, Faculty of Science and Engineering, School of Fundamental Science and Engineering, Waseda University
He obtained a Ph.D. in science from the Graduate School of Science at Tohoku University in 1987. He was appointed a Professor in the Department of Earth and Planetary Science, Faculty of Science at Kobe University in 1999 and a Professor in the Faculty of Science and Engineering, School of Fundamental Science and Engineering at Waseda University and a Professor Emeritus, Faculty of Science at Kobe University in 2014.
He has published numerous works, including “Groups are Consciousness” (PHP Institute, 2013), “Life, Indomitable” (Seidosha, 2018), “Natural-born Intelligence” (Kodansha, 2019), and “Yattekuru” (Igaku-Shoin, 2020). His most recent publication is “From Whence Comes the Memory of Having Once Lived in that Game World?” (Seidosha, 2022).
I understand you have known one another for a long time?
Horry: Since 1987, it has been 36 years now. Professor Gunji came from the graduate school to teach at the Department of Earth and Planetary Sciences in the Faculty of Science where I was studying at Kobe University. While I may not be his greatest acolyte as such, I was his first. I learned all manner of things from him, whether it be how to look at things, fundamental ways of thinking, or what stance to take as a researcher.
Gunji: He still often drops in at the laboratory and offers his advice to the students. I expect it is encouraging for them to see a former student who is playing an active role in society and I am always pleased to see him. However, I have not heard much about what he has been up to recently (laughing).
In that case, Horry-san, could you start by telling us about your recent activities?
Horry: I am currently working on the development of platform technologies to support the transition to a sustainable society. One of the main things I am involved with is the social and environmental return on invested capital (hereinafter environmental ROIC) approach to quantifying total value of economic activity. Along with decarbonization, which can be thought of as a challenge for the entire world, there has been strong demand recently, especially in Europe, for making the shift to a sustainable society in ways that also take account of the circular economy, biodiversity, and human rights issues. Such measures are closely interlinked with societal systems and corporate management strategy, with people looking at making it obligatory for companies to disclose non-financial information. This has included work that went into establishing the Task Force on Climate-related Financial Disclosures (TCFD) and Taskforce on Nature-related Financial Disclosures (TNFD) as well as the Task Force on Social-related Financial Disclosures (TSFD) that also focuses on respect for human rights.
While this is to some extent a rule-making competition, creating a genuinely sustainable society will require that these issues be addressed in a comprehensive manner, instead of addressing each issue individually. We developed environmental ROIC as a decision-making support tool that will facilitate comprehensive and realistic action, one that works by quantifying the social and environmental value produced by corporate projects and other economic activity, thereby providing an insight into the benefits and outcomes of this work that takes account of society and the environment (see figure on next page).
Environmental ROIC looks at how various elements interrelate, considering the different products, technologies, and other individual components of economic activity and determining which globally recognized indicators they contribute to, such as the Sustainable Development Goals (SDGs). The total social and environmental value (V) of the economic activity is then calculated using the formula shown in the figure.
In an example application of the technique to the electrical facilities at a water treatment plant, we used carbon dioxide (CO2) emissions reduction as a yardstick for technology for reducing the power required to operate the plant. This involved calculating a contribution factor (Yk) by multiplying annual power consumption by the CO2 emission coefficient for the location, where annual power consumption (kWh) is the product of multiplying the power required to operate the plant (kW) by the annual operating hours (h). The social and environmental value V is given by summing the Yk values, weighted by the Ck coefficients, after first converting them to financial values. The environmental ROIC is then obtained by adding this calculated value of V to the financial return on the project and dividing by the amount of capital invested.
Figure — Environmental ROIC Technique for Quantifying Social and Environment Value of an Economic Activity 
Youichi Horry, Ph.D.
Chief Engineer, Corporate Strategy Division, Water & Environment Business Unit, Hitachi, Ltd.
After graduating with a degree in earth sciences from the Graduate School of Science at Kobe University, he joined Hitachi, Ltd. in 1990 at the Central Research Laboratory where he worked on research into computer music and graphics. In 1997, he took up a position as a Visiting Researcher at the Institut National Recherche en Informatique et en Automatique (INRIA) in France, began his research into human interaction in 2000, and established the Hitachi Human Interaction Laboratory (HHIL) in 2003. Since 2010, he has been working on management science for social infrastructure at a number of institutions, including Hitachi’s Advanced Research Laboratory, Central Research Laboratory, and the Matsudo Research Laboratory of Hitachi Plant Technologies, Ltd. He was appointed to his current position in 2022.
He obtained a Ph.D. in engineering from Waseda University in 2018. He was appointed a C4IRJ fellow of the World Economic Forum in 2020 and an expert at WG5 of ISO TC323 (Circular Economy) in 2022.
How do you go about determining the coefficients?
Horry: What matters most is to standardize how the Ck coefficients are determined. To explain the role that coefficients play, consider how Hitachi has operated an internal carbon pricing system since 2019. This system attaches a price of 14,000 yen/ton to reductions in CO2 emissions by newly installed equipment, the intention being to highlight the extent to which such capital investments reduce emissions. In this example, this price serves as a coefficient. That is, it is a numerical expression of what Hitachi values.
As for how coefficients are determined, one way is for the person making the decision to set the value by themselves. Alternative objective approaches are to determine a market price based on market principles or to use cost-benefit (B/C) analysis, or to calculate a value using data and an algorithm.
However, whichever method you choose, the decision will reflect your values and thinking. Moreover, economic activity will have participants on many different levels, such as companies or workplaces and local or national government, with each of these organizations having different values. That is, different organizations place weight on different elements and this will cause a lot of variability in the coefficient lists.
If meaningful comparisons are to be made between quantified values, it is essential to standardize the list of coefficients. To achieve this, we started by publishing the lists so that the participants could see what others had chosen. We hoped that this would encourage convergence as people were prompted to look at what others had come up with and make changes where their own coefficients were out of step.
Collating coefficients as lists is necessary for them to be incorporated into programs automatically and also to enable appropriate adjustments to be made to the decision-making by artificial intelligence. Having anticipated this, we are currently making environmental ROIC calculations for customers in a wide range of different industries.
Gunji: I see. That is very interesting. Speaking in fundamental terms, the typical way we think about issues, whether they relate to the environment or something else, is in terms of there being a “problem” and a “solution.” However, doubt arises as to whether the problem really is a problem. A problem is something that only becomes clear when we frame it in some way. While we don’t necessarily need to look beyond this framing to bring together the relevant factors, it is also possible, conversely, for us to choose a framework that suits our own purposes, pushing aside those aspects we prefer to ignore. This means that our ability to resolve a problem depends in many cases on whether we can choose a framework that is convenient to ourselves. As it is easy to get stuck on this way of looking at things, it may be that we also need to consider stepping away from our chosen framing.
Horry: That is right. Environmental ROIC itself is not intended as a way of defining problems. Rather, we anticipated that problems might arise from the variability of coefficient lists.
Gunji: Whether it be environmental problems or anything else, the way it often works is that someone has something they want to accomplish and science is used to achieve it. While people often talk about the importance of objectivity in science, the issue is whether objectivity and the like are present to begin with. This is because a strict insistence on objectivity risks excluding the human perspective to the extent that humans could be allowed to become extinct. In that regard, having a variety of different coefficient lists represents a form of dynamism in the sense of a jumble of different subjective perspectives. By taking advantage of this, it may be possible to deliver a more successful outcome than could be achieved by something that has been carefully designed from scratch.
Horry: Environmental ROIC works by combining elements of various different types. As the number of such elements was not stipulated from the outset, they can be added indefinitely. While this has the potential to become somewhat arbitrary, I believe it also aligns in some respects with Gunji-sensei’s own thinking.
Gunji: The concept of self-organized criticality was proposed and modeled by Per Bak, a Danish theoretical physicist. The idea is that, when the behavior of certain phenomena or materials is modeled mathematically without stipulating a framing or problem in advance, they achieve a dynamic stability on their own that is in effect a close approximation to the optimal, even in a disordered open system that is exposed to external factors. This is in complete opposition to the conventional approach to design that seeks to obtain optimal solutions under ordered conditions.
One example of self-organized criticality is the sand pile model. When grains of sand are progressively dropped from above onto a flat surface, a pile tends to accumulate up to the point where a section of the pile collapses, a process that repeats over and over again as more sand is dropped. While it is the slope of the pile that determines when such collapses will happen, this in turn depends on the physical properties of the sand (size and friction). When this sand pile model experiment is run, the collapses happen on a range of different scales such that the frequency with which a collapse of any given size occurs decreases as collapse size increases. That is, the relationship between collapse size and frequency follows a power law*1.
When phenomena follow a power law, it is impossible to predict the scale of future events based on the mean size of past events. That is, a very small change in conditions can result in a phase transition. This is why they are called critical phenomena and they occur frequently in nature, earthquakes being one example.
While Per Bak passed away in 2002, ideas of this nature are once again attracting a lot of attention. In the case of animal gait, for example, a probability distribution for step length that follows a power law is called a “Lévy walk.” Animals are known to use this to search for food efficiently. Formulated as a mathematical model, this could be used to improve efficiency when searching for something under unknown conditions. While a variety of models, our own included, have been proposed to show the mechanisms that are incorporated into the way animals walk so that they exhibit criticality, my own view is that it represents a form of natural-born intelligence.
While I will talk more about natural-born intelligence later on, in simple terms I describe it as intelligence that arises from sensing and responding to external factors. My goal is to develop a theory of this natural-born intelligence and incorporate it into an intelligence model that provides ways of responding not only to predetermined conditions, but also to unanticipated external factors.
In the case of your own environmental ROIC, you do not impose a predetermined framework on the indicators and coefficient lists. By avoiding this, it may be that environmental ROIC will evolve dynamically by incorporating not only those factors that can be anticipated in advance, but also mechanisms for dealing with the unexpected or factors that conflict with one another.
Horry: That’s right. A list that allows for the comparison of coefficient values does not yet exist. Once it does, it would become possible, for example, to make explicit numeric comparisons of the different weightings that emerging nations and developed nations place on human rights, something that currently has only an implicit expression in policies. In a certain respect, this is a case of contradictory factors coming into conflict with one another and can be expected to drive convergence.
While people tend to think of coefficients as being objective, I talked earlier about how the choice of whether to determine them objectively is in fact a subjective one, meaning that they embody people’s values and opinions. On the other hand, decision-making calls for objective theory and data. Which is to say that the realm of coefficients is one where the objective and subjective are nested within one another, making it difficult in some regards to predict whether our lists will ever successfully converge.
Gunji: Is it possible to combine the freedom of individuals, such as their subjectivity and intentionality, with orderliness in the group they collectively comprise? This is an interesting problem, one for which modelling the movements of groups of animals can provide some useful insights.
Flocks of starlings or schooling sardines move in a collective fashion despite apparent randomness. While modeling such movements is surprisingly difficult, in a model I devised myself that equips the individuals that make up the group with both reactive and autonomous movements, I found it was simple to replicate group behaviors such as how their movements sync up in a linear fashion under some conditions whereas in others they just circle about or suddenly scatter in all directions.
In terms of the mechanism involved, you can think of it as an expansion or contraction in the causes that drive the decisions of individuals. While people might think that achieving orderliness requires objective decisions based on an unchanging set of causes, it turns out that groups can exhibit synchronized and harmonious movement on the basis of varying factors whereby individuals make repeated autonomous decisions while also responding to external causes. This is a state of affairs in which orderliness and the breakdown of orderliness are controlled internally. It may be that we can build such systems and still be able to control them effectively.
Horry: This is the model you wrote about in your book “Groups are Consciousness.”
In the case of environmental ROIC, having the coefficients set in stone would equate to an unchanging set of factors. In practice, however, we have provided dynamism by allowing them to be increased or decreased. As mentioned earlier, equipping environmental ROIC with the scalability to be used by organizations of different sizes is another feature.
Gunji: Mixing things that differ in scale may well prove interesting. The model I have been telling you about that allows for variable factors was developed out of the book “Groups are Consciousness.”
