In the dynamic world of complexity science, we’re excited to recognize the achievements of two of our exceptional researchers at the Complexity Science Hub.

Two awards won by CSH researchers Jan Bachmann & Jan Korbel © ÖAW:Natascha Unkart & CSH

Jan Bachmann has been named one of the DOC fellows of the Austrian Academy of Sciences (ÖAW), securing 24 months of funding for his project, “Network Inequality and its impact on the glass ceiling phenomenon.” This recognition is a testament to Jan’s dedication and the quality of his research.


Jan Korbel‘s paper, ‘Homophily-Based Social Group Formation in a Spin Glass Self-Assembly Framework,’ published in Physical Review Letters, has earned him the first prize at the Dora Brücke-Teleky Award. This award, presented by esteemed institutions, highlights his outstanding contributions to the field.

We celebrate the achievements of Jan Bachmann and Jan Korbel and anticipate the impact of their continued work in complexity science. Congratulations to both for their remarkable accomplishments!

CSH researcher Rudolf Hanel writes a letter to his friend and fellow scientist Constantino Tsallis on the occasion of his 80th birthday

Dear Constantino,


Today, I will speak about a somewhat unusual topic among scientists, and that topic would be magic. However, it befits the occasion since I believe that the man we celebrate today deserves the honorary title magus for a life’s work that falls nothing short of what one might call an opus magnum.


But what constitutes a work of epic dimensions, an opus magnum, and what is it that is magic about it? For that, we, first of all, have to recognize that magic at all times has been the “art of making things happen.”


Traditionally, the magic woven with words and symbols has often been considered the loftiest type one can perform. Some words spoken or some symbols written, and the world changes for good. To achieve this means opus magnum for the mage. And I will have no hard time convincing you that who I am talking about here has without question performed such a feat.


Other wise men


In fact, the history of science knows many persons we could identify as magi by their magna opera. Most prominently, we, for instance, had Kepler and Galileo, who, with some tools fashioned, some words spoken, and some symbols written, changed a world that before held the earth at the center of the Universe (at least in medieval Europe) to one where we inhabit the third planet orbiting our sun. Like them, Einstein and Lorentz (and consorts), with some words spoken and some symbols written, obliterated a Universe to build a new one. Followed by the other, maybe even more mysterious magic of the quantum that, with some symbols written and some words spoken, obliterated another center. The center of certainty itself.


Where the first ones, together with Newton, obliterated the center of the Universe — so that henceforth anywhere and nowhere would we find this center, for each grain of dust to claim to be its own center — the latter performed a secrete marriage between light, space, matter and time itself. The grain of dust now is not only its own center but also its own path, and, with it, its passage of time and space becomes its very own. The price we paid for this magic of gaining certainty — that light moves at the same speed for anyone and anything—is that anything that travels slower than light can never quite reach light speed.


It’s a very egalitarian thing, one might say. However, while the first two magic acts made us more egalitarian and individual, the third one, that of the quantum, not only has given us unprecedented technological progress, it also has entangled us in Janus-faced interaction as both observers and observed in ways that yet remain to be fully understood (as Garry Larson might put it). Ripples on a pond. Thoughts and symbols that transcend time and space. A ripple of which Euclid was as much part as Kopernikus, Newton, and Einstein were. An opus magnum is not a singular act. It participates in deeper and darker currents of our collective thought excitations, and yet it is a focal point at which ripple scatters, gets amplified, modulated, and changes direction.


Beyond physics


Of course, not only physics knew its magi. There are the likes of Darwin who, similarly, obliterated a world of constancy. He obliterated a world in which everything was made the way it happened to be since the beginning of time — even our Universe was still static, neither expanding nor contracting. Now, with some symbols written and some words spoken, species that always have been the way they were, unchanging, were propelled into a world where our, or anybody’s, lineage traces back to the proverbial primordial soup for which earth, our milk-mother, turned out to be the right cauldron to cook up life.


Now, many opus magnum is more subtle. They start tiny, maybe as a seemingly harmless question, such as: If observations of a phenomenon are distributed following power laws and not exponential laws, then could it be that the process underlying the phenomenon is subject to a notion of entropy that differs from what we have learned that entropy is? What do we maximize in order to predict the typical, most likely distribution of observed events? Some words spoken and some symbols written, and another ripple — a ripple of statistical thinking — that excited the brains of other magi, such as Bayes, Boltzmann, Gibbs, von Neumann, or Shannon, found itself another focal point in the person we celebrate here today.


And again, it is a world of constancy and equilibrium that some words spoken and some symbols written are obliterated. The gravitational body of our Universe is fundamentally out — of equilibrium. If it were not like that, no eyes would ever have evolved to see it and no ears to hear it. We are children of gravity. Darwin realized it in the evolution of species, Einstein in the geometry of space-time, and now — through the new focal point — it has been realized in the statistical description of complex processes and systems that entropy is key to.


A life of its own


It is one of the characteristics of an opus magnum that it takes on a life of its own and, in the end, outgrows the spell-caster, who in the process becomes the director of the ripple rather than its origin. Origins of events always lose themselves in the historical process that led up to them, making us conduits that transform ripples that already were there. Another characteristic of an opus magnum is its irreversibility. It is a Jinni that will not go back into its bottle to promiscuously go out into the world and excite other brains to spawn offspring and evolve into ecosystems of ideas and concepts that typically are much richer than originally anticipated.


Nonetheless, as biological life forms inherit genes from their ancestors, also ideas, as they ripple away on a pond of brains, they also always inherit some of their directors agenswhich identifies as the body of event trails that originate from a person and persist while mingling with the world. The main characteristics of an opus magnum, however, rest in its subversiveness that identifies a prison we unwittingly keep ourselves in and in its power to corrode the chains that shackle us. The question it begins with becomes a cry for freedom, the freedom to see the world anew from a heretical perspective.


Thank you


Dear Constantino, it is this I want to thank you for from the bottom of my heart; you asked the pivotal question that challenged the ways we looked upon entropy. You became the heretic who recognized a prison of mind, and Tsallis entropy became the acid that corroded the shackles of equilibrium thinking and the subversion that directed the ripples that took us all along a ride that I incredibly enjoyed and keep enjoying. You have set the Jinni of entropy free, and Tsallis entropy went out into the world and promiscuously spawned offspring that all probe the ecosystem of possibilities to understand what we can mean when we say entropy. The spell you cast, i.e., the story you initiated, has already taken on a life of its own and has already outgrown not only you but all of us who were lucky enough to participate in this journey. Wouldn’t you agree that, therefore, your work shows all hallmarks of an opus magnum and accept that, in the best of senses, you are a mage?


Constantino, you have touched the lives of countless people, not only with your work but with your big heart and your generosity that we were allowed to enjoy, for instance, when we visited you in Rio. Therefore, I want to end my musings with a recollection of what Murray Gell-Mann once, in one of our conversations at the Santa Fe Institute, had to say about his own fascination with entropy in particular and complexity science in general. Murray said that the time reminded him of the early days of Quantum Mechanics when things were not yet fully settled (meaning, as settled as a scientific theory can ever be), and one could enjoy the freedom of thought that one can only experience when a revolutionary process is still in its infancy, and everything is still filled with youthly potential. That we were allowed to participate in such times is the greatest gift of all.


Dear Constantino,


Thank you, and all the best heartfelt wishes for your 80th birthday.



Constantino Tsallis is a pioneer in the applications of statistical physics to complex systems. He is best known for introducing Tsallis entropy and Tsallis statistics, and for shaping views on power laws in complex systems. Tsallis is an external faculty member at CSH and emeritus professor at the Centro Brasileiro de Pesquisas Físicas in Rio de Janeiro, Brazil. 


A number of events are being held to commemorate Tsallis’ 80th birthday. The conference “Statistical Mechanics for Complexity” takes place between November 6 and 10 in Rio. The journal Entropy has a special issue dedicated to Tsallis: “Nonadditive Entropies and Nonextensive Statistical Mechanics”. 

In May, freelance science writer Sachin Rawat visited the Complexity Science Hub to meet with our resident scientists.


“Visiting the CSH was like going to a gold mine of ideas for me as a journalist covering complexity research,” Rawat says. “CSH’s research excited me, and I believed I could gather a lot of ideas there – and I did.” 


Rawat met with CSH researchers, including the institution’s president Stefan Thurner, during his visit. “We talked about their work, how it intersects with other fields and society, and where news coverage of complexity research is lacking,” Rawat adds. 


Rawat plans to write feature stories based on his conversations with CSH scientists when he returns to India. He’s an independent journalist based in Bangalore. His work has appeared in Big Think, The Progress Network, and the Asian Scientist Magazine, among other things. Find him on Twitter @sachinxr.

What leads to political turbulence and social breakdown? In what ways do elites maintain their dominance? And why do the ruling classes sometimes lose power suddenly? In this article, CSH team leader Peter Turchin presents his groundbreaking theory of how society works and introduces us to his upcoming book, End Times: Elites, Counter-Elites, and the Path of Political Disintegration. The book will be published on June 13.

“History is not just one damn thing after another,” British historian Arnold Toynbee once quipped in response to a critic. For a long time, Toynbee’s opinion was in the minority. Historians and philosophers vehemently insisted that a science of history was impossible. I hope that End Times will convince you that this view is wrong. A science of history is not only possible, it is useful: it helps us anticipate how the collective choices we make in the present can bring us a better future.


Over the past quarter-century, my colleagues and I have built out a flourishing field, known as Cliodynamics (from Clio, the muse of history, and dynamics, the science of change). We discovered that there are important recurring patterns, which can be observed throughout the sweep of human history over the past 10,000 years. Remarkably, despite the myriad of differences, at base complex human societies, on some abstract level, are organized according to the same general principles.

(c) Penguin Random House

From the beginning, my colleagues and I in this new field focused on cycles of political integration and disintegration. This is the area where our field’s findings are arguably the most robust—and arguably the most disturbing. It became clear to us through quantitative historical analysis that complex societies everywhere are affected by recurrent and, to a certain degree, predictable waves of political instability, brought about by the same basic set of forces, operating across the thousands of years of human history. It dawned on me some years ago that, assuming the pattern held, we were heading into the teeth of another storm. In 2010, the scientific journal Nature asked specialists from different fields to look ten years into the future, and I made this case in clear terms, positing that judging from the pattern of US history, we were due for another sharp instability spike by the early 2020s.


What, then, is the model on which this forecast was based? When a state, such as the United States, has stagnating or declining real wages, a growing gap between rich and poor, overproduction of young graduates with advanced degrees, declining public trust, and exploding public debt, these seemingly disparate social indicators are actually related to each other dynamically. Historically, such developments have served as leading indicators of looming political instability. In the United States, all of these factors started to turn in an ominous direction in the 1970s. The data pointed to the years around 2020 when the confluence of these trends was expected to trigger a spike in political instability.


Sadly, nothing about my model has been disproved in the intervening years. End Times is my best effort to explain this model in accessible, which is to say non-mathematical, terms. It builds on an enormous amount of important work in a variety of different fields; I make no claims for radical originality. What I will say is that we should all take heart from the fact that societies have arrived at this same crossroads before, and while sometimes (even most of the time) the road has led to great loss of life and societal breakdown, at other times it has led to a far happier resolution for most people involved.

Peter Turchin

CSH researcher Stefan Kitzler has been awarded the 2023 SUERF/UniCredit Foundation Research Prize for his paper “Disentangling Decentralized Finance (DeFi) Compositions ”. CSH researchers Pietro Saggese and Bernhard Haslhofer, as well as Friedhelm Victor, from the Technical University of Berlin, co-authored the study.

Kitzler presented the paper on Thursday, March 30th, in a ceremony held at the Vienna University of Economics and Business. 


Learn more about the study:

About the prize

This year, the prize was awarded to two outstanding papers on the topic “Crypto assets and decentralized finance – what way forward? What implications for traditional finance? How to regulate and supervise?”. The award, promoted by SUERF – The European Money and Finance Forum and the UniCredit Foundation, is open to authors and co-authors who are citizens or residents/students in the EEA, Switzerland, and other countries in which UniCredit is present and born after 30 September 1982. 

Sándor Juhász is the first Marie Sklodowska Curie postdoctoral fellow at the Complexity Science Hub (CSH). In the next 20 months, Juhász will be delving into tax data. His goal is to find new ways of supporting local economic development.

You define yourself as “an economist interested in data magic, networks, innovation and (economic) geography.” Is it possible to perform magic with data?

Of course. Raw data files are messy and sometimes even unstructured. If you can turn it into very attractive and easy-to-understand figures at the end, the message is delivered quickly. To be able to do this with a single figure? I think this is magic.

Can you tell me what magic tricks you are going to perform at CSH?

Until now, value-added tax (VAT) information [a general tax that, in principle, is applied to all goods and services] has been used to study, for instance, economic shock propagation and supply chain resilience at the national level. However, few people have used this data for testing classic economic geographic topics or supporting local economic development policies.


I will focus on the geographical aspect of VAT networks during my stay. It is my aim to use tax data to develop tools or services where people can understand how a particular industry in a particular region depends on other industries and regions in the country, for example. It could be used to monitor the local economic environment and connections. By understanding the economic connections better, I hope we can turn this data into a tool that can support local economic development strategies. 

What made you choose CSH as your host institution for the fellowship?

The main reason is that my entire project revolves around Hungarian VAT data. And I believe CSH has a good know-how about the supply chain economy and how VAT data can be transferred into meaningful projects. 


My supervisor, Frank Neffke, was another factor that drew me to CSH. We work on similar projects and he is the kind of mentor a Marie Curie fellow needs: an experienced senior researcher. Having the opportunity to work in Vienna, which is close to my hometown of Budapest, was also a plus.

While at CSH, what are your plans?

I plan to write two research papers during the project. In addition, I plan to create an intuitive visualization site where people can check, for instance, the connections of an industry in a specific city in Hungary. This will enable them to find out who are its main suppliers and buyers. For that, I believe that CSH is the right place to be. I am looking forward to collaborating with Liuhuaying Yang and others and learning about data visualization practices. My goal is to learn as much as I can during my stay.


This visualization site could be especially useful for policymakers, as it intends to provide an overview of the local structure of the economy. It will show how flows occur across the country, and across industries. It will give a new geographic perspective on the economy, in my opinion.

Any other magic tricks? 

I am interested in two main areas of research. One is socio-economic networks, i.e. supply chains and the economic interactions between agents. The other is urban data science, namely how people move around a city and how locations are organized in cities. 


My future plan is to combine both areas and conduct very fine grain, city level studies that incorporate social interactions as well. I find that challenging, but also fun!

Would you mind giving me an example?

I am interested in studying how industries collocate in regions. We believe that they collocate in a specific region because certain channels, like input-output resources and skilled labor, or accumulated knowledge, are present there. Therefore we assume industries collocate there because they get to use the pool of resources and this reinforces spatial concentration. In the future, I would like to examine whether similar channels and reasons are important for certain shops, amenities, services, or firms to collocate inside urban neighborhoods. I am very interested in understanding how things are located at the micro level inside cities. 

Spätestens seit der Pandemie, traten die globalen Wissenslücken über Liefernetzwerke deutlich zutage. Durch das neue Forschungsinstitut ASCII gegründet vom Complexity Science Hub, der FH OÖ, dem VNL und dem WIFO, sollen diese nun geschlossen werden. Österreich wird dadurch eine internationale Vorreiterrolle einnehmen. Peter Klimek, ASCII-Direktor und Forscher am Complexity Science Hub, dazu im Gespräch – über die Entstehung des ASCII, globale Zusammenhänge und seine persönliche Vision.

Peter Klimek at the Complexity Science Hub © EugenieSophie

Aus welchem Grund wurde das ASCII gegründet? Und warum gerade jetzt?

Peter Klimek: Erstens, um zu frühzeitig erkennen zu können, dass es zu Engpässen in einer Lieferkette kommt und somit noch bevor eine tatsächliche Versorgungsknappheit eintritt. Zweitens wollen wir diese Wertschöpfungsketten nicht nur resilienter, robuster und sicherer machen, sondern auch eine evidenzbasierte Grundlage für Entscheidungträger:innen bereitstellen und proaktiv aufzeigen, wie wir sie optimal umbauen können, sodass in Zukunft ein nachhaltigeres und effizientes Wirtschaftssystem entsteht.

Könntest du das näher ausführen?

Zu erstens: Wir wollen dazu beitragen künftig die Versorgungssicherheit zu gewährleisten. Das ASCII ist eine notwendige Konsequenz aus den Erfahrungen der letzten Jahre, wo wir multiple Krisen erlebt haben und deren Auswirkungen auf die Lieferketten und Produktionsnetzwerke deutlich spürten.


Wir konnten sehen, dass Dinge, die wir davor als gegeben gesehen haben, plötzlich nicht mehr funktionierten – zum Beispiel, dass es zu Lebensmittelknappheiten kam, dass Autoteile nicht lieferbar waren und vieles mehr. Wer gerade nach Großbritannien schaut, kann diese Konsequenzen in den Supermärkten unmittelbar sehen. Bislang hat man erst bemerkt, dass es Probleme in den Versorgungsnetzwerken gibt, wenn die Sachen „plötzlich“ nicht mehr verfügbar waren. Es gab keine Möglichkeit, eine Knappheit vorherzusehen.


Wir konnten zudem beobachten, dass Lieferketten sehr anfällig sind und enorm weitreichende kaskadierende Effekte haben. Einzelne Ereignisse wie eine Schiffshavarie können beispielsweise zu globalen Störungen in Wirtschaftskreisläufen führen. Wenn in diesen sogenannten „Flaschenhälsen“ der Liefernetzwerke Störungen auftreten, betrifft das in weiterer Folge die Versorgung von sehr vielen Ländern.

“Technologiewechsel braucht Anpassung”

Zu zweitens: Viele Zukunftsthemen hängen direkt mit Liefernetzwerken zusammen. Zum Beispiel: Wie schaffen wir es Emissionen zu reduzieren? Wie entsteht ein nachhaltigeres Wirtschaftssystem? Wie können wir eine klimaneutrale Mobilität garantieren? Wenn wir zum Beispiel vermehrt auf E-Mobilität setzen möchten, müssen wir die Industriestrukturen entsprechend umstellen.


Ein Technologiewechsel bedingt immer, dass sich auch die Produktionsnetzwerke daran anpassen müssen. In vielen Bereichen wissen wir derzeit jedoch noch nicht, wo wir hier an Limitationen stoßen – etwa wie sehr man neue Technologien nach oben skalieren kann, um eine ähnliche Effizienz zu erzielen.

“Viele ungelöste Fragen”

Das heißt, würden wir beispielsweise apodiktisch von oben entscheiden, dass es nur noch E-Autos geben soll, würde sich das im Hinblick auf die notwendige Infrastruktur überhaupt ausgehen? Dies sind bislang größtenteils ungelöste Fragen, da wir gar nicht wissen, wie diese Produktionsnetzwerke aktuell im Detail aussehen.


Wir könnten beispielsweise Maßnahmen ergreifen, um in Österreich weniger Emissionen in der Lebensmittelproduktion zu erzeugen. Wenn wir zum Ausgleich dann aber Lebensmittel importieren und nicht wissen wie diese produziert worden sind, wissen wir auch nicht, was sich in der globalen Bilanz ändert. Deshalb müssen wir zuerst ermitteln, wie diese globalen Kreisläufe funktionieren.

Wie sah die Lieferkettenforschung bislang aus?

Peter Klimek: Ein Großteil der Forschung über Logistik und Lieferketten geschah bislang aus Unternehmensperspektive. Einzelne Unternehmen, die ihre Kundenzahl, Zulieferer, Infrastruktur und Lieferketten optimieren wollen.


Auf Systemebene, also wie ein optimales Netzwerk auf globaler Ebene aussieht, dazu gibt es bislang wenige Forschungserkenntnisse. Die Gründe dafür: Einerseits gibt es die Daten dazu gar nicht. Und zweitens wurde bisher häufig aus der Perspektive eines einzelnen Unternehmens geforscht, ohne auf die Makroperspektive einzugehen. Das wollen wir nun am ASCII ändern.

Und was macht das ASCII anders?

Peter Klimek: Die Forschung auf Makroebene braucht einen Mix an Disziplinen, die jetzt am ASCII (Anm.: durch die Gründungsmitglieder Complexity Science Hub, Logistikum of FH OÖ, Verein Netzwerk Logistik GmbH (VNL) und WIFO) zusammenarbeiten. Denn wir müssen die Netzwerke und Logistik kennen, wir müssen mit Systemen umgehen können, die sehr komplex und verflochten sind und wir müssen all das in einen wirtschaftspolitischen Kontext setzen können – schließlich erfüllen diese Netzwerke eine ökonomische Funktion.


Die Expertise des Complexity Science Hub auf Datenebene wird dabei eine zentrale Rolle spielen, um aus dieser enormen Menge von Daten evidenzbasierte Erkenntnisse ableiten zu können. Darüber hinaus bringen wir am Complexity Science Hub bereits einen großen Erfahrungsschatz im interdisziplinären Arbeiten mit und sind es gewohnt datengetriebene Ergebnisse in verschiedenen Kontexten so aufbereiten, dass sie als Grundlage für fundierte Entscheidungen dienen können.

Wieso kam es scheinbar plötzlich zu diesen Lieferkettenausfällen in der letzten Zeit?

Peter Klimek:  Viele Expert:innen in den einzelnen Bereichen kannten auch davor die Schwachstellen. Doch einerseits wurden sie durch diese multiplen Krisen erst jetzt ins öffentliche Scheinwerferlicht gerückt. Denn durch die Globalisierung fand in vielen Fällen hauptsächlich eine Konzentrierung der Produktionsprozesse statt, was Liefernetzwerke natürlich anfälliger macht. Wie anfällig, aber tatsächlich, das ist jetzt deutlich geworden.


So wusste man beispielsweise schon seit Jahren, dass es zu einer immer stärkeren Konzentration der Medikamentenproduktion in bestimmte Länder kommt. Schlagend werden diese Dinge allerdings häufig erst, wenn tatsächlich etwas passiert, wie es in der Pandemie der Fall war.


Andererseits gibt es Expert:innen in bestimmten Feldern, aber ein systematisches Monitoring über eine Vielzahl von Wirtschaftsbereichen und eine gezielte Aufbereitung dieser Informationen fehlt.

Was werden die großen Herausforderungen für ASCII sein?

Peter Klimek: Wir müssen die Produktions- und Wertschöpfungsnetzwerke besser kennenlernen. Da es dazu keine vollständigen Daten gibt, werden wir sie aus vielen unterschiedlichen Quellen mühsam zusammensammeln müssen. Außerdem müssen wir, um die Abhängigkeiten von Österreich zu kennen, diese Netzwerke von Anfang an auf europäischer und in Wahrheit globaler Ebene denken.


In nächster Instanz wollen wir verstehen, wie sie sich verändern, wie anfällig sie für Schocks sind und wie wir sie so gestalten können, dass sie sicherer und nachhaltiger werden, ohne dabei Effizienz einbüßen zu müssen.

Wie kam es zur Gründung des ASCII?

Peter Klimek: Während der Pandemie rückte das Thema Versorgungssicherheit immer stärker in den Fokus, sodass entsprechende Krisenstäbe des Ministeriums eingerichtet wurden, in denen unter anderem auch der Complexity Science Hub vertreten war.


Schnell haben wir dort gemeinsam festgestellt, dass die „Intelligence“ – im Sinne einer übergreifenden Aufklärungskompetenz – in Österreich fehlt, um frühzeitig drohende Engpässe erkennen zu können. Auf Basis dieser Erfahrungen entstanden einzelne Projekte und schließlich die Idee eines Institutes, das alle notwendigen Kompetenzen in sich vereint.

Wie sieht die Vision für das ASCII aus?

Peter Klimek: Meine Vision ist, dass wir ein weltweit führendes Forschungsinstitut werden, das sich mit lieferkettenbezogenen Fragestellungen datenbezogen auseinandersetzt und dadurch Nutzen für die Bevölkerung entsteht.


Neben der evidenzbasierten Politikberatung wollen wir aber auch im Bereich der Wirtschaft ein Ansprechpartner für Unternehmen sein. Im Bereich der Forschung möchten wir die fehlende Datenlandschaft ergänzen und für die internationale Forschungsgemeinschaft aufbauen, weil natürlich viele Kolleg:innen vor dem gleichen Problem stehen. Durch die Gründung des ASCII haben wir die Gelegenheit eine internationale Vorreiterrolle einzunehmen. Diese möchten wir in den nächsten fünf Jahren durch wissenschaftlich exzellente Arbeit ausfüllen.

Global knowledge loopholes about supply networks have emerged since the pandemic. The Supply Chain Intelligence Institute Austria (ASCII) should now be able to close these gaps. In an interview, ASCII director and complexity researcher Peter Klimek discusses the origins of the new institute, global connections, and his personal vision.

Peter Klimek at the Complexity Science Hub © EugenieSophie

What was the reason for the foundation of ASCII? And why now in particular?

Peter Klimek: First of all, to be able to recognize early on that there will be bottlenecks in a supply chain and thus before an actual supply shortage occurs. Secondly, we want to make these value chains not only more resilient, robust and secure, but also provide an evidence-based foundation for decision-makers and show proactively how we can optimally transform them to create a more sustainable and efficient economic system in the future.

Would it be possible for you to elaborate on that further?

Peter Klimek: Regarding the first point, we want to help ensure future supply security. ASCII is a necessary consequence of the lessons learned in recent years, where we have experienced multiple crises and clearly felt their impact on supply chains and production networks. Suddenly, things we took for granted before stopped working — food shortages, car parts not being available, etc.


Right now, you can see these consequences directly in the supermarkets in the UK. Prior to this, people hadn’t realized there were problems in supply networks until things “suddenly” became unavailable. There was no way to predict a shortage.


We also observed that supply chains are very fragile and have enormously far-reaching cascading effects. Single events such as a shipwreck, for example, can lead to global disruptions in economic cycles. If disruptions occur in these so-called “bottlenecks” of the supply networks, this subsequently affects the supply of many countries.

“Many largely unresolved questions”

Regarding the second point: many future issues will be directly linked to supply networks. How can we reduce emissions, for example? How do we create a more sustainable economic system? What can we do to ensure carbon-neutral mobility? We have to change industrial structures if we want to rely more on e-mobility, for instance.


As technology changes, production networks must also adapt. We do not yet know where we will run into limitations in many sectors. An example would be how many new technologies can be scaled up to achieve similar efficiency levels.


In other words, would a top-down decision that only e-cars be allowed even be possible in terms of the necessary infrastructure? These are largely unresolved questions so far because we don’t even know what these production networks currently look like in detail. Austria could take measures to produce fewer emissions in food production, for example.


However, if we import food to compensate and do not know how the food was produced, we also would not understand how the global balance would change. Therefore, we must first find out how these global cycles work.

What has supply chain research been so far?

Peter Klimek: Most logistics and supply chain research has been conducted from a corporate perspective. Companies strive to optimize their customer base, suppliers, infrastructure, and supply chains. There has been only limited research at the system level, i.e., what an optimal network looks like globally. The reasons for this are, firstly, that the data doesn’t exist. Secondly, research has often been conducted from the perspective of a single company, without taking a macro perspective. At ASCII, we now want to change that.

What does ASCII do differently?

Peter Klimek: A mix of disciplines is needed for macro level research, and ASCII is bringing those disciplines together (note: through the founding members Complexity Science Hub, Logistikum of FH OÖ, the Verein Netzwerk Logistik GmbH (VNL) and WIFO). Because we need to know the networks and logistics, we need to be able to deal with systems that are very complex and intertwined, and we need to be able to put all this into an economic policy context – after all, these networks serve an economic function.


The Complexity Science Hub’s expertise at the data level will play a central role in deriving evidence-based findings from this enormous amount of data. In addition, we at the Complexity Science Hub already bring a wealth of interdisciplinary experience and are used to analyzing data-driven results in a variety of contexts so that they can serve as the foundation for well-grounded decisions.

Why did supply chain failures occur so suddenly?

Peter Klimek: Many experts in the specific areas were fully aware of the weaknesses beforehand. On the other hand, these multiple crises have only now brought them into the spotlight. Often, globalization has mainly led to a concentration of production processes, making supply networks more vulnerable. The extent of their vulnerability, however, has now become apparent.


For example, it has been known for years that there is an increasing concentration of the production of prescription drugs in certain countries. As in the pandemic, these things are often only noticeable when they occur.


While there are experts in certain fields, systematic monitoring across a wide range of economic sectors and targeted processing of information are lacking.

What will be ASCII’s major challenges?

Peter Klimek: We need to better understand the production and value networks. The data on this will need to be painstakingly gathered from many different sources since there is no complete set. Additionally, in order to understand Austria’s dependencies, we must think of these networks on a European and, in fact, global level.

How did ASCII come about?

Peter Klimek: During the pandemic, the issue of supply security came increasingly into focus, so corresponding crisis teams were set up at the ministry, in which the Complexity Science Hub was also represented, among others. There, we quickly realized together that Austria lacked the “intelligence”— in the sense of an overarching intelligence competence — to be able to recognize impending bottlenecks at an early stage. Based on these experiences, individual projects were developed, and finally the idea of an institute that combines all the necessary competencies.

What is the vision for ASCII?

Peter Klimek: My vision is that we will become a world-class research institute that addresses supply chain-related issues in a data-driven manner and thereby creates benefits for the population.


As well as providing evidence-based policy guidance, however, we also want to be a point of contact for companies in the business sector. Specifically, we want to build up the missing data landscape for the international research community, since many colleagues are facing the same challenge. We have the opportunity to play a pioneering role on the international stage by founding ASCII. In the next five years, we hope to fill this role through scientifically excellent work.

The award is given by the German Physical Society, the oldest physics society in the world, to recognize outstanding original contributions that use physical methods to develop a better understanding of socioeconomic issues


CSH scientist Fariba Karimi has won the prestigious socio- and econophysics prize for her research on inequality in complex networks.


Karimi leads the Hub’s computational social science group. Her current research focuses on computational and network approaches to address pressing societal issues, including gender disparities, visibility of minorities, and algorithmic biases. Last year, her study on gender disparities in STEM (science, technology, engineering, and mathematics) fields, published in the journal Communications Physics, was featured both in Nature and Science magazines.


In addition, by using mathematical models, digital traces, and online experiments, Karimi studies the emergence of culture in Wikipedia, spreading of information and norms, and perception biases.


The award will be presented at the German Physical Society’s spring meeting in Dresden from March 26 to March 31. Karimi, who is also an assistant professor at TU Wien, will give a talk on marginalization in society and algorithms.


An enthusiastic researcher, a senior scientist at Zalando, and an “algorithmic justice consultant”. Meike Zehlike can wear multiple hats and apply her multidisciplinary skills to academia and industry. During her four-month visit to the Complexity Science Hub Vienna (CSH), Zehlike will be working with Fariba Karimi and her team to investigate ethical values and their possible effects on network structures.


What are your plans during your stay at CSH?


The plan is to combine my knowledge of ethical artificial intelligence (AI) and algorithmic fairness with CSH’s knowledge of network inequality and try to come up with an understanding of what it needs for networks to have certain definitions of fairness. At the moment, we’re analyzing different effects in network structures and seeing whether we can associate these different effects with different ethical values. At first, we’ll do the analysis, and later we want to run experiments.


You’ve got a foot in academia and a foot in the private sector.

Scientists still rarely do this. How did this happen?


This is the first time in my life – and I have never thought I would ever say that about a job – that I am in love with working with ethical reasoning in AI. I love it with all my heart! Because I believed there would be no other jobs for me [outside of universities or research institutes], I believed I had to be in academia to work in this field.


Then, after I finished my PhD, a job at [the German online fashion giant] Zalando opened up. This is a research position in algorithmic fairness, and an entire team is dedicated to it. At first, I wasn’t sure. However, I became more and more fond of it during the interview process. It turns out to be a really nice job. It’s a different way of working [compared to academia], and the field of ethical AI is younger in industry than it is in academia, and there are still a lot of unanswered questions.


From your private sector experience, what lessons have you learned?


I learned that if you want more women in academia, you need to change the structure. The way academia works is extremely discriminating against women for different reasons. One of the reasons is what Fariba has showed [in her recent study].


And that is something that the private sector is actually doing better. My experience is that big tech companies, as compared to the “old industries”, are much better at understanding how to have a more diverse workforce. Talent dropout is a crucial point [for academia]: focusing only on 50 percent of the population will result in a large amount of talent being lost to industry.


In addition, I was surprised to observe – at least at Zalando – the high level of happiness in comparison with academia, where publish or perish is the dogma. It goes without saying that [in industry] you have to deliver and receive performance evaluations. Also, industry seems to be more flexible regarding career paths and supports industry-academia exchange.


Could this be a new model for innovation (the exchange between

academia and the private, public and non-governmental sectors)?




Journalists, NGOs, academics have asked lots of questions about ethical AI, and it has taken a while for the industry to say “Okay, we need to address this problem.” This is a very positive development.


I won’t be able to apply what I’ll learn at CSH to Zalando now since Zalando is not a social network. However, it might be a potential feature for them in the future. Industry can benefit from understanding the current debate in academia and the questions being addressed. Additionally, I believe that researchers who work in industry also enjoy some academic freedom, since they don’t worry about publishing their work.


Could industry offer academic freedom as well?


Yes, in the sense that you don’t need to worry about your job. However, you do not have academic freedom in the sense of choosing whatever topic you want to work on. Business needs will still exist. You’ll likely be very business-driven depending on your type of company.


In this field, which is so young, it’s crucial that researchers can move between academia and industry. Furthermore, interdisciplinary research is the future: more and more we want to solve real world problems collaboratively. We see this in ethical AI: if you come up with efficiency optimizing algorithms and put them out there to society without consulting social scientists, something terrible may result. This is something we don’t want.


This approach to interdisciplinarity should be embraced more in a variety of ways, including from the perspective of industry and academia.



You describe yourself as an “Algorithmic Justice Consultant.”

What does it mean?


As a consultant, I provide ethical guidance on algorithms. One example is my work with IG Metal [the metalworkers’ union in Germany, which is the largest industrial union in Europe]. It’s mostly about raising awareness with works councils, and educating them about what’s happening in ethical AI, and what the problems are with AI systems, particularly when it comes to people analytics.


People analytics are being pushed more and more in companies, with the goal of improving (and reducing discrimination, for example) and becoming more efficient (in hiring process). Many of the tools being proposed at the moment make very questionable assumptions about what a good candidate should look like. To educate works councils about that situation, I show examples of what doesn’t work well and why.