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.
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.
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.
Do they have luck or not?
It is rare for the same team to win two Ig Nobel prizes. However, this year the jury has considered the work, and not the luck, makes Andrea Rapisarda and Alessandro Pluchino deserving of a new award in Economics.
Andrea, CSH external professor, and Alessandro, together with Alessio Biondo, insist on a new investigation that luck determines success over talent.
The authors of the study, from the University of Catania, created a mathematical model that quantifies the role of talent and luck in career success. Their model demonstrates the importance of lucky events, which is frequently underestimated, in determining individual success levels.
The study warns against “naive meritocracy”, which “fails to give honors and rewards to the most competent people, because it underestimates the role of randomness among the determinants of success.”
The Italian team is one of 10 to be recognized at this year’s Ig Nobel awards for research that “first makes you laugh, then makes you think”. The prizes, announced last Thursday, are intended to celebrate “the unusual, honor the imaginative — and spur people’s interest in science, medicine, and technology.”
Congrats, Andrea, Alessandro and Alessio!
Learn more about their new study about the role of randomness in success.
And see Andrea and his colleagues receive their Ig Nobel Prize at the (extremely fun to watch!) online ceremony (starting at 1:12:15).
Great experiences at the Complexity-GAINs Summer School
During their two-week stay in Vienna, PhD students from the US and EU learned how to integrate theory and methods from a variety of disciplines, including psychology, political science, physics and mathematics
“It has been fun to connect with people from different fields,” said Elise Koskelo, one of the 38 PhD students who attended the Complexity-GAINs International Summer School, which concluded last Friday in Vienna.
“Physics can often seem like everyone sets a silo, and only other physicists understand what you’re saying or can relate to what you’re doing. But here I think everybody has found a connection in terms of quantitative understanding of social issues. And that has been really exciting,” added Elise, who’s a PhD student in condensed matter physics at Harvard University.
Other students, who come from different backgrounds, also shared the same enthusiasm. “The summer school offers the perfect combination of knowledge. What I really like here is that everything is applicable to my research area,” said Loes Crielaard, who has been studying socioeconomic inequalities in health at the Amsterdam University Medical Centers.
“Meeting such amazing people was a great experience, and I hope to continue collaborating with them in the future,” said Alejandro Pérez Velilla, an anthropologist doing his PhD studies in cognitive science at the University of California Merced.
That’s exactly one of the goals of the summer school: to enrich and promote the diversity of the complex systems research community. “It’s crucial to learn how to talk across disciplines,” stated Mirta Galesic, one of the directors of the summer school who’s a professor at the Santa Fe Institute and external faculty at CSH.
“As a social scientist, I want to solve problems and I want to be able to say when the next world war is going to be, or how we can inform people about pandemics. Or at least come closer to that. The only way to do it is to step out of the disciplines and become more quantitative. And this is the new generation that we’re training,” concluded Mirta.
“The most important aspect is the interaction with fellow students, and learning how to do transdisciplinary research, in the sense that every research question can only be solved by different disciplines collaborating on a deeper level,” explained Henrik Olsson, external faculty at the Santa Fe Institute and director of the summer school.
The program is a partnership between the Santa Fe Institute with four leading complex systems research institutions in the EU: the Complexity Science Hub Vienna (Austria), Max Planck Institute for Mathematics in the Sciences and Hamburg University of Technology (Germany), Quantitative Life Sciences, International Center for Theoretical Physics (Italy), and Institute for Advanced Studies, University of Amsterdam (Netherlands).
This year, the program was dedicated to socio-behavioral systems. The students listened to lectures from leading researchers on the dynamics of beliefs and emotions, the role of social network structures, the influence of algorithms and institutions, and their joint influence on collective outcomes and societal robustness.
In addition, they worked on hands-on group research projects to solve real-world problems. The research projects had a diverse range of topics, from early warning signals of collapse of societies, to Roe versus Wade decisions in the US, and how monkeypox spreads between people.
“When talking to psychologists and philosophers that are in my group [in the summer school] , I feel we are asking bigger questions about how to improve society, or what’s wrong with it right now,” explained Elise, whose group project was focused on opinion dynamics in homophilic networks.
For Elise, the summer school offered her a chance to develop a network with other researchers who are interested in complex systems. For the senior scientists, this was also an opportunity for establishing new collaborations, according to Mirta.
More complexity science
The program will run over three years. 2023 and 2024 will focus on intelligent systems, and ecosystems, respectively.
The Complexity-GAINs program is made possible through the support of the National Science Foundation (US) under Grant No. 2106013 (PI David Krakauer; Santa Fe Institute), “IRES Track II: Complexity advanced studies institute – Germany, Austria, Italy, Netherlands (Complexity-GAINs)”. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the investigator(s) and do not necessarily reflect the views of the National Science Foundation.
W. Wayt Gibbs and Aleszu Bajak | Our first journalists in residence
May and June were certainly our busiest months in the past academic year. In the midst of hive-like buzzing and humming at the Hub also arrived our first two COmplex SYstems Journalists in Residence: W. Wayt Gibbs in May and Aleszu Bajak in June.
W. Wayt Gibbs: all about climate change
Wayt is a senior science writer with a 30-year career as
The project Wayt applied with—and was working on during his stay—is a book intending to present facts about the complexity of climate change and the necessary technological adaptation, facts that because of their complexity are often neglected in climate change communication.
During his whole sojourn, Wayt interviewed experts from within and outside of the CSH. “I didn’t expect to go home with so many interviews,” he said shortly before he left Vienna.
Student tutorial: What to expect from journalists?
Wayt was also highly engaged in communicating with CSH scientists.
Apart from his introductory talk, he gave a tutorial on “What to expect (or what not to expect) from interacting with (science) journalists.” A great opportunity especially for our younger scientists to learn that the only obligation and responsibility journalists have is their commitment to their readers. “Even when we write about your work, we are not your friends,” Wayt made clear. Scientists—like any interviewed person—must always be aware that a given statement is a potentially published statement. “So think well in advance of what you want to tell [or not to tell] a reporter,” he recommended.
Moderating a large panel discussion
Wayt also kindly accepted our invitation to moderate one of our big outreach events on May 30: a podium discussion with [from left to right] Luciano Pietronero, Simon DeDeo, J. Doyne Farmer, Helga Nowotny, Henriette Spyra, and Peter Klimek, reflecting on “Managing a dramatically changing world: What science can contribute.”
Not an easy task, given the large number of panelists.
Thanks a lot for your valuable contributions, Wayt—and we can’t wait to read your book! 🙂
Aleszu Bajak: Data, data, data vis!
Two days before Wayt left, our second COSY JiR flew in: Aleszu arrived in mid-June from Cleveland, USA.
Aleszu is a data journalist working in the USA TODAY investigative data team.
During his stay, he intended to “develop, select, and apply the most appropriate data science methods and social science questions to a self-collected dataset from US 2022 election candidate messaging.”
As it turned out, Aleszu knew (former) CSH scientists already: While teaching and managing the graduate programs at Northeastern University’s School of Journalism, he had met Ancsa Hannak (now CSH External Faculty) for instance, or has worked remotely with David Garcia or Anna Di Natale in the past. He reconnected with this team immediatley.
Aleszu was also participating in practically all CSH events taking place during his stay, such as Márcia’s and Fariba’s or Diego Rybski’s workshop. He climbed some Austrian mountains and connected, professionally as well as privately, with many scientists in- and outside the Hub.
“What a privilege to spend the summer in Vienna learning from network scientists, physicists and psychologists about topics as diverse as pandemics, supply chains and misinformation,” he said.
(Unfortunately he somehow managed to escape my camera. So if anybody happens to have taken pictures with Aleszu that can be shared: Send them over! 😉 ).
Tutorial on principles for good data visualization
Aleszu also was so nice to give our (younger) scientists a tutorial. He focused on storytelling with data and the principles for clear and comprehensible data visualization.
“A common mistake is to put too much information into a single visualization,” he said. “Yet, most of the time you gain a lot of clarity by leaving things away.” He summarized this procedure with the words “annotate, curate, don’t overwhelm.”
Aleszu also highlighted that any visualization task should be started with questions like:
- Who is the audience?
- What are my/our goals?
- What is our capacity, budget, timeline?
- But also: What inspires me?
After almost four densely packed weeks, Aleszu headed back home to his wife and adorable kids [he showed us pictures!] last week.
We will miss you!
The next in line: Julia Sklar
The COSY JiR program allows for up to three-month stays. Because Wayt and Aleszu only spent a month each with us, we decided to invite a third applicant from our 2022 call.
Julia Sklar, an independent journalist from Boston, will arrive in November and stay until to January 2023.
Meet ‘n’ greet at the Hub
To bring a bit of change—and pepp!—into the third meeting of scientists from Central European University (CEU) and the Hub, Vito, together with CEU’s Elisa Omodei, wanted to try a new format.
Significantly supported by our event mastermind Charlotte, they asked people to prepare little posters with a portrait and a short description of their current research that were hung up on a long roll of paper in our “admin” hallway (see pic).
After a short welcome by Janos and Stefan, the scientists mingled to get to know each other. Several rounds of re-shuffling made sure that (almost) everybody met (almost) everybody.
One could tell from the outside (and from far away…) how much fun that was. For hours, our rooms were filled with joyful chattering.
After this self-introductory part, people were invited to wander around and learn about “crazy ideas” proposed by some of the scientists: funny or puzzling questions that should be discussed—and maybe even solved—in small teams during the following hours and day.
“The idea was to have fun with maybe a little bit of research,” said Vito with his typical broad smile. “When people like it, we could think about repeating such events with other institutions in the future.”
And people did like it indeed.
To be continued! 😀
The 21st century crises, from climate change or financial crises to the Covid-19 pandemic or the war in Ukraine, demand new scientific understanding and approaches, urged leading academics and public sector representatives on Monday at a panel discussion hosted by the CSH.
To address the challenges facing society, democracy, and humanity as a whole, the six panelis called for more scientific collaboration. In addition, they stressed the importance of accepting uncertainty in science.
“Whatever we try to foresee and predict is imbibed in probabilities, and there are significant areas of uncertainty,” said Helga Nowotny, chair of the CSH Science Advisory Board. Additionally, Helga mentioned responsibility—individual, institutional, and collective—and complexity science as key concepts in dealing with the grand challenges society faces.
“How do you take responsibility for present actions whose first impacts will appear somewhere in time—and we have no idea when—and will affect different groups differently?,” questioned Helga. “Is complexity science pointing in the right direction? It has produced tools, methods, and insights. But we need to have a much stronger engagement and commitment to deal with the urgent issues of our time.”
Luciano Pietronero, CSH External Faculty and professor at the University of Rome ‘Sapienza’, also emphasized the importance of dealing with uncertainty in science. He spoke of the original project he pioneered with the Italian government in order to create “scientific startups”. “My view is that we, as scientists, are too conservative. The people investing in startups accept a failure of 90 percent, for instance,” said Luciano during the panel moderated by W. Wayt Gibbs, our current COSY Journalist in Residence.
Science can contribute in three different aspects to policy making, said Henriette Spyra, Director-General Innovation & Technology at the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation & Technology: by scrutiny, systemic approaches, and radical collaboration. “Scrutiny is not only about setting objectives but also about achieving impact. We really do need more monitoring than we do now,” stated Henriette.
“On the topic of systemic approaches, I think it’s really important to get down to the details. We need to dive deeper on the mechanics of how government, organizations, rules, and regulations work, for instance. And obviously, this calls for greater collaboration.” In addition, we should think about “radical transparency and collaboration (between science and society),” added Henriette, mentioning an article in which scientists call for a moratorium on climate change research until governments take real action.
Lessons from the pandemic
CSH’s Peter Klimek also stressed the urgency of taking a systemic approach when handling complex issues. “We can dissect a problem into one million smaller problems. None of these problems is fun to work with. In fact, all these problems are hard to work with before we can make a millimeter of progress. But, at the end of the day, that’s what we need to do as scientists.”
“This is one of the lessons learned from the pandemic. It’s not enough just to wear a mask, or just to be vaccinated. We have to solve one million little problems at the same time.”
Despite the present disruptions and changes, Henriette claims herself to be “stubbornly optimistic.” J. Doyne Farmer, CSH External Faculty and professor at the University of Oxford, shares the same optimism. “I think it’s a tremendously exciting point to be a complex system scientist because we can really solve problems now that have huge effects on the future course of the world,” he said. “We have tools that will allow us to solve these problems and create a new social science that will go far beyond what we were able to do in the past, especially due to the incredible amount of data. But we have to make this happen.
“We’re going to take many false steps, but we can change things if we start to, collectively, think about a model and understand our future and convince people to take paths that respect our human nature,” adds Doyne.
Simon DeDeo, CSH External Faculty and professor at Carnegie Mellon University, emphasized the individual’s role in managing the transition in the course of a crisis. “What we need to learn as scientists—and what we need to enable policymakers to do—, is to create better possibility machines. Not probability machines, not things that make the world more predictable in the ways we want. We may need extraordinarily imaginative thinking at the level of the individual”, stated Simon. “If, from 1950 to 2020, we were in a world of ‘good systems making good citizens,’ in this future we need to empower good citizens to make better systems.”