N. 003       OCTOBER 2020

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How can research impact society?

Beatrice Conte

Digitalization, global change, and sustainability are key words very popular in academia as well as industry. What are the challenges we need to overcome to bridge the two fields? We discussed it with Matteo Tarantino.

(Image: Markus Spiske)

Interview

Digital transformation is a hot topic both in research and in practice. While our society is undergoing a sweeping integration of digital technologies into all organizations and businesses, it must also address broader environmental sustainability issues. This combination results in a series of economic, political, and administrative challenges. The role of research is to investigate the causes and possible solutions of those challenges, to inform policy-makers and stakeholders at every level through the processes of change. Matteo Tarantino works as an assistant professor at the Università Cattolica in Milan. He is a lecturer at the University of Geneva. His research addresses the themes of digitalization and data management, answering the questions of how people and institutions interact, use and interpret data on environmental sustainability (strictly speaking, data on environmental sustainability are data related to the impact of human activities on the natural environment: for instance, data on air pollution in cities). Professor Tarantino and I met for the first time in mid-2019 when I attended the summer school he organized at the University of Geneva on Sustainability Transitions: Design, Diplomacy, and Data. At the time, we discussed the role of digital transformation in the transition towards a more sustainable society. More recently, the two of us met again to continue our discussion. In the interview below, we dug deeper into Tarantino's work. We explored the prospects of being an "atypical researcher," moving seamlessly between academia and collaborations with companies, agencies, NGOs, and governments. Beatrice Conte: Let's start to form the basics. What do you do as a researcher in the field of digital transformation for sustainability? And how did you get to your research topic? Matteo Tarantino: In short, my research focuses on practices, motivations, and imagery related to the acquisition and usage of urban and environmental data. To give you a practical example, I am currently working on a project looking at how public institutions in eight different countries collect and use social housing data. The goal is to identify how information available becomes digital data, how those data are extracted at first, how they later circulate within the system, and finally how they are used as indicators of, for instance, the quality of social housing infrastructures. In general, I study data management's entire process to identify potential problems that would make the data difficult to handle, ambiguous to interpret, or misleading. Based on my findings, I provide policy-makers and stakeholders with suggestions on how to optimize the way people in institutions handle digital data relative to sustainability themes. It is a bit like a diagnosis and treatment sequence, but with data-related processes. My background is in sociology and computer science, and my research reflects these two major interests of mine. I am very fascinated by the human component of the digital transformation processes, so I started from there. I first tackled data coming from cities and then from housing systems. Later, I began to integrate those topics with concepts of environmental sustainability. A successful digital transformation implies that the high-level technologies available to institutions and organizations become part of the individuals' practices and habits asked to operate them. Imagine the case where a central government has the best software available to track social housing data. Still, employees at the local level are unwilling to learn how to use it, for instance, because it is too difficult to grasp. This is the paradox where a top-down change clashes with the reality of the people who must implement the change. In the context of digital transformation, this situation is much more common than you think. As dealing with challenges such as climate change asks for a globally unified and efficient data culture, we need to identify the sources of the problem to bridge the gap between technology and every user.

"Either we accept that the new data ecosystem creates the conditions for controversial movements as an unavoidable collateral effect, or we need to find new ways to communicate science and regain trust as a scientific community among the general public."

Matteo Tarantino

In this respect, what is your vision for the future of digital transformation? When do you think we will be able to reach a more fluid and standardized data culture? Data culture implies two types of key learnings. On the one hand, you must acquire the practical skills needed to use the required technological tools. On the other hand, you have to understand the importance of the appropriate use of data and correct data management. I have noted, quite paradoxically, that the new generations are putting effort into the latter goal. However, we are still way behind with regard to the former. For this reason, I am not so optimistic that we will be able to reach a more fluid and globalized data culture in the near future. Nevertheless, the real problem does not concern young people who are very reactive to technology. Instead, it affects more the older generations, those who work in public institutions right now, and are not familiar with the latest technologies and digital cultures. How do we convince them not only to learn something new but also to feel motivated and involved? This is the main issue for me. It holds particularly true in emerging countries, where the technological change is often perceived as an imposition from above. Consider also the psychological perspective: the development of new technologies goes much faster than human adaptation to change. I see the permeation of data culture as a natural process that will require its time - probably quite a long one - to unfold. I am very interested in the psychological perspective that you just mentioned. How do you think we can integrate psychology concepts into the discussion on data culture and digital transformation? Motivation is a key factor in the context of digital change. People must feel motivated to participate in the change actively and comply with it in the long term. My research team and I often observe that individuals raise barriers that hinder the change, sometimes unconsciously and sometimes deliberately. Understanding these resistances from a psychological perspective, looking at the single agent or person that is asked to ultimately enact the change, is an exciting direction to pursue. So, the keywords that summarize your research could be digitalization, global change, and sustainability. These are all words that became part of a shared cultural language only relatively recently. It seems like you invented an entirely new area of research. How did it go? The interest in research for digital transformation arose when the so-called data science, that is, everything that has to do with data and data management, became popular. In particular, my research originated when a UN agency for housing asked me for evidence-based insights for policy-making. I have been one of the first people to delve into this area of research. However, today there is an entire literature on "Science and Technology Studies" that deals with the sociological approach to digital transformation. What is still missing is something else: the dimension of sustainability. This is the real innovation that I, together with my research team, have been striving to bring to the scientific community. The close collaboration between academia and private or public organizations represents a still-too-unusual approach to research that you have successfully integrated into your work. You not only have to deal with papers and students but also with companies, agencies, NGOs, governments. How is it to be such an "atypical" researcher? Well, sometimes, it feels like being a fish out of water. One of the biggest problems that I face in my research is that I constantly need to learn the data practices and languages of the specific organization with which I am collaborating at a particular moment. Every organization has its own peculiar data culture, processes, and needs. I usually need to start from scratch and build a new chunk of knowledge that I will employ only within that organization. All the hours that I dedicate to creating this knowledge are not expendable in academia. In other words, it is a bit difficult to publish papers on the specific databases conventions of a particular organization that I learned in the context of a collaboration. Nevertheless, I genuinely believe that for academic research to be concretely relevant in the real world, researchers need to know deeply about the procedures put in place by practitioners. It is a continuous challenge, but in this sense, one of my goals is to act as a bridge between academia and practice. Speaking about the impact of science on the "real world" issues: in the last year, several anti-scientific movements have seemed to gain ground, from no-vax groups to climate change deniers to Covid-19 negationists. As a scientist, what is your stand about misinformation, fake news, and mistrust in science? Negationism in not necessarily anti-scientific, and this is one of the biggest problems of our era. Of course, negationism can be anti-scientific, but more often, movements such as anti-vax, climate change denial, or Covid-19 negationism are the result of a significant misinterpretation of scientific data available. What I observe in my work is an interesting if worrying phenomenon: the surge in data availability is producing a proportional decrease in the public's trust in those same data. Every person can find almost any kind of information online, supporting any hypotheses and theories. This is how confirmation bias works: you have an idea, you look for scientific evidence that confirms your view, and once you find something that might resemble that evidence, you convince yourself that your idea is right. This is how these controversial movements strengthen through time. In this case, people miss real familiarity with the scientific method and how science works as a cumulative process. Still, the information they rely on cannot strictly be called anti-scientific. I am a big supporter of open data in science. Still, at the same time, I realize that open data in this sense does not help in terms of science communication to the general public. The options on how to deal with this are two: either we accept that the new data ecosystem creates the conditions for controversial movements as an unavoidable collateral effect, or we need to find new ways to communicate science and regain trust as a scientific community among the general public. Finding ways to maintain the liberal circulation of information while avoiding crystallization of anti-scientism is a matter of imagination. At the moment, we cannot see the solution yet.

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Digital transformation is a hot topic both in research and in practice. While our society is undergoing a sweeping integration of digital technologies into all organizations and businesses, it must also address broader environmental sustainability issues. This combination results in a series of economic, political, and administrative challenges. The role of research is to investigate the causes and possible solutions of those challenges, to inform policy-makers and stakeholders at every level through the processes of change. Matteo Tarantino works as an assistant professor at the Università Cattolica in Milan. He is a lecturer at the University of Geneva. His research addresses the themes of digitalization and data management, answering the questions of how people and institutions interact, use and interpret data on environmental sustainability (strictly speaking, data on environmental sustainability are data related to the impact of human activities on the natural environment: for instance, data on air pollution in cities). Professor Tarantino and I met for the first time in mid-2019 when I attended the summer school he organized at the University of Geneva on Sustainability Transitions: Design, Diplomacy, and Data. At the time, we discussed the role of digital transformation in the transition towards a more sustainable society. More recently, the two of us met again to continue our discussion. In the interview below, we dug deeper into Tarantino's work. We explored the prospects of being an "atypical researcher," moving seamlessly between academia and collaborations with companies, agencies, NGOs, and governments. Beatrice Conte: Let's start to form the basics. What do you do as a researcher in the field of digital transformation for sustainability? And how did you get to your research topic? Matteo Tarantino: In short, my research focuses on practices, motivations, and imagery related to the acquisition and usage of urban and environmental data. To give you a practical example, I am currently working on a project looking at how public institutions in eight different countries collect and use social housing data. The goal is to identify how information available becomes digital data, how those data are extracted at first, how they later circulate within the system, and finally how they are used as indicators of, for instance, the quality of social housing infrastructures. In general, I study data management's entire process to identify potential problems that would make the data difficult to handle, ambiguous to interpret, or misleading. Based on my findings, I provide policy-makers and stakeholders with suggestions on how to optimize the way people in institutions handle digital data relative to sustainability themes. It is a bit like a diagnosis and treatment sequence, but with data-related processes. My background is in sociology and computer science, and my research reflects these two major interests of mine. I am very fascinated by the human component of the digital transformation processes, so I started from there. I first tackled data coming from cities and then from housing systems. Later, I began to integrate those topics with concepts of environmental sustainability. A successful digital transformation implies that the high-level technologies available to institutions and organizations become part of the individuals' practices and habits asked to operate them. Imagine the case where a central government has the best software available to track social housing data. Still, employees at the local level are unwilling to learn how to use it, for instance, because it is too difficult to grasp. This is the paradox where a top-down change clashes with the reality of the people who must implement the change. In the context of digital transformation, this situation is much more common than you think. As dealing with challenges such as climate change asks for a globally unified and efficient data culture, we need to identify the sources of the problem to bridge the gap between technology and every user.
In this respect, what is your vision for the future of digital transformation? When do you think we will be able to reach a more fluid and standardized data culture? Data culture implies two types of key learnings. On the one hand, you must acquire the practical skills needed to use the required technological tools. On the other hand, you have to understand the importance of the appropriate use of data and correct data management. I have noted, quite paradoxically, that the new generations are putting effort into the latter goal. However, we are still way behind with regard to the former. For this reason, I am not so optimistic that we will be able to reach a more fluid and globalized data culture in the near future. Nevertheless, the real problem does not concern young people who are very reactive to technology. Instead, it affects more the older generations, those who work in public institutions right now, and are not familiar with the latest technologies and digital cultures. How do we convince them not only to learn something new but also to feel motivated and involved? This is the main issue for me. It holds particularly true in emerging countries, where the technological change is often perceived as an imposition from above. Consider also the psychological perspective: the development of new technologies goes much faster than human adaptation to change. I see the permeation of data culture as a natural process that will require its time - probably quite a long one - to unfold. I am very interested in the psychological perspective that you just mentioned. How do you think we can integrate psychology concepts into the discussion on data culture and digital transformation? Motivation is a key factor in the context of digital change. People must feel motivated to participate in the change actively and comply with it in the long term. My research team and I often observe that individuals raise barriers that hinder the change, sometimes unconsciously and sometimes deliberately. Understanding these resistances from a psychological perspective, looking at the single agent or person that is asked to ultimately enact the change, is an exciting direction to pursue. So, the keywords that summarize your research could be digitalization, global change, and sustainability. These are all words that became part of a shared cultural language only relatively recently. It seems like you invented an entirely new area of research. How did it go? The interest in research for digital transformation arose when the so-called data science, that is, everything that has to do with data and data management, became popular. In particular, my research originated when a UN agency for housing asked me for evidence-based insights for policy-making. I have been one of the first people to delve into this area of research. However, today there is an entire literature on "Science and Technology Studies" that deals with the sociological approach to digital transformation. What is still missing is something else: the dimension of sustainability. This is the real innovation that I, together with my research team, have been striving to bring to the scientific community. The close collaboration between academia and private or public organizations represents a still-too-unusual approach to research that you have successfully integrated into your work. You not only have to deal with papers and students but also with companies, agencies, NGOs, governments. How is it to be such an "atypical" researcher? Well, sometimes, it feels like being a fish out of water. One of the biggest problems that I face in my research is that I constantly need to learn the data practices and languages of the specific organization with which I am collaborating at a particular moment. Every organization has its own peculiar data culture, processes, and needs. I usually need to start from scratch and build a new chunk of knowledge that I will employ only within that organization. All the hours that I dedicate to creating this knowledge are not expendable in academia. In other words, it is a bit difficult to publish papers on the specific databases conventions of a particular organization that I learned in the context of a collaboration. Nevertheless, I genuinely believe that for academic research to be concretely relevant in the real world, researchers need to know deeply about the procedures put in place by practitioners. It is a continuous challenge, but in this sense, one of my goals is to act as a bridge between academia and practice. Speaking about the impact of science on the "real world" issues: in the last year, several anti-scientific movements have seemed to gain ground, from no-vax groups to climate change deniers to Covid-19 negationists. As a scientist, what is your stand about misinformation, fake news, and mistrust in science? Negationism in not necessarily anti-scientific, and this is one of the biggest problems of our era. Of course, negationism can be anti-scientific, but more often, movements such as anti-vax, climate change denial, or Covid-19 negationism are the result of a significant misinterpretation of scientific data available. What I observe in my work is an interesting if worrying phenomenon: the surge in data availability is producing a proportional decrease in the public's trust in those same data. Every person can find almost any kind of information online, supporting any hypotheses and theories. This is how confirmation bias works: you have an idea, you look for scientific evidence that confirms your view, and once you find something that might resemble that evidence, you convince yourself that your idea is right. This is how these controversial movements strengthen through time. In this case, people miss real familiarity with the scientific method and how science works as a cumulative process. Still, the information they rely on cannot strictly be called anti-scientific. I am a big supporter of open data in science. Still, at the same time, I realize that open data in this sense does not help in terms of science communication to the general public. The options on how to deal with this are two: either we accept that the new data ecosystem creates the conditions for controversial movements as an unavoidable collateral effect, or we need to find new ways to communicate science and regain trust as a scientific community among the general public. Finding ways to maintain the liberal circulation of information while avoiding crystallization of anti-scientism is a matter of imagination. At the moment, we cannot see the solution yet.
Digital transformation is a hot topic both in research and in practice. While our society is undergoing a sweeping integration of digital technologies into all organizations and businesses, it must also address broader environmental sustainability issues. This combination results in a series of economic, political, and administrative challenges. The role of research is to investigate the causes and possible solutions of those challenges, to inform policy-makers and stakeholders at every level through the processes of change. Matteo Tarantino works as an assistant professor at the Università Cattolica in Milan. He is a lecturer at the University of Geneva. His research addresses the themes of digitalization and data management, answering the questions of how people and institutions interact, use and interpret data on environmental sustainability (strictly speaking, data on environmental sustainability are data related to the impact of human activities on the natural environment: for instance, data on air pollution in cities). Professor Tarantino and I met for the first time in mid-2019 when I attended the summer school he organized at the University of Geneva on Sustainability Transitions: Design, Diplomacy, and Data. At the time, we discussed the role of digital transformation in the transition towards a more sustainable society. More recently, the two of us met again to continue our discussion. In the interview below, we dug deeper into Tarantino's work. We explored the prospects of being an "atypical researcher," moving seamlessly between academia and collaborations with companies, agencies, NGOs, and governments. Beatrice Conte: Let's start to form the basics. What do you do as a researcher in the field of digital transformation for sustainability? And how did you get to your research topic? Matteo Tarantino: In short, my research focuses on practices, motivations, and imagery related to the acquisition and usage of urban and environmental data. To give you a practical example, I am currently working on a project looking at how public institutions in eight different countries collect and use social housing data. The goal is to identify how information available becomes digital data, how those data are extracted at first, how they later circulate within the system, and finally how they are used as indicators of, for instance, the quality of social housing infrastructures. In general, I study data management's entire process to identify potential problems that would make the data difficult to handle, ambiguous to interpret, or misleading. Based on my findings, I provide policy-makers and stakeholders with suggestions on how to optimize the way people in institutions handle digital data relative to sustainability themes. It is a bit like a diagnosis and treatment sequence, but with data-related processes. My background is in sociology and computer science, and my research reflects these two major interests of mine. I am very fascinated by the human component of the digital transformation processes, so I started from there. I first tackled data coming from cities and then from housing systems. Later, I began to integrate those topics with concepts of environmental sustainability. A successful digital transformation implies that the high-level technologies available to institutions and organizations become part of the individuals' practices and habits asked to operate them. Imagine the case where a central government has the best software available to track social housing data. Still, employees at the local level are unwilling to learn how to use it, for instance, because it is too difficult to grasp. This is the paradox where a top-down change clashes with the reality of the people who must implement the change. In the context of digital transformation, this situation is much more common than you think. As dealing with challenges such as climate change asks for a globally unified and efficient data culture, we need to identify the sources of the problem to bridge the gap between technology and every user.
In this respect, what is your vision for the future of digital transformation? When do you think we will be able to reach a more fluid and standardized data culture? Data culture implies two types of key learnings. On the one hand, you must acquire the practical skills needed to use the required technological tools. On the other hand, you have to understand the importance of the appropriate use of data and correct data management. I have noted, quite paradoxically, that the new generations are putting effort into the latter goal. However, we are still way behind with regard to the former. For this reason, I am not so optimistic that we will be able to reach a more fluid and globalized data culture in the near future. Nevertheless, the real problem does not concern young people who are very reactive to technology. Instead, it affects more the older generations, those who work in public institutions right now, and are not familiar with the latest technologies and digital cultures. How do we convince them not only to learn something new but also to feel motivated and involved? This is the main issue for me. It holds particularly true in emerging countries, where the technological change is often perceived as an imposition from above. Consider also the psychological perspective: the development of new technologies goes much faster than human adaptation to change. I see the permeation of data culture as a natural process that will require its time - probably quite a long one - to unfold. I am very interested in the psychological perspective that you just mentioned. How do you think we can integrate psychology concepts into the discussion on data culture and digital transformation? Motivation is a key factor in the context of digital change. People must feel motivated to participate in the change actively and comply with it in the long term. My research team and I often observe that individuals raise barriers that hinder the change, sometimes unconsciously and sometimes deliberately. Understanding these resistances from a psychological perspective, looking at the single agent or person that is asked to ultimately enact the change, is an exciting direction to pursue. So, the keywords that summarize your research could be digitalization, global change, and sustainability. These are all words that became part of a shared cultural language only relatively recently. It seems like you invented an entirely new area of research. How did it go? The interest in research for digital transformation arose when the so-called data science, that is, everything that has to do with data and data management, became popular. In particular, my research originated when a UN agency for housing asked me for evidence-based insights for policy-making. I have been one of the first people to delve into this area of research. However, today there is an entire literature on "Science and Technology Studies" that deals with the sociological approach to digital transformation. What is still missing is something else: the dimension of sustainability. This is the real innovation that I, together with my research team, have been striving to bring to the scientific community. The close collaboration between academia and private or public organizations represents a still-too-unusual approach to research that you have successfully integrated into your work. You not only have to deal with papers and students but also with companies, agencies, NGOs, governments. How is it to be such an "atypical" researcher? Well, sometimes, it feels like being a fish out of water. One of the biggest problems that I face in my research is that I constantly need to learn the data practices and languages of the specific organization with which I am collaborating at a particular moment. Every organization has its own peculiar data culture, processes, and needs. I usually need to start from scratch and build a new chunk of knowledge that I will employ only within that organization. All the hours that I dedicate to creating this knowledge are not expendable in academia. In other words, it is a bit difficult to publish papers on the specific databases conventions of a particular organization that I learned in the context of a collaboration. Nevertheless, I genuinely believe that for academic research to be concretely relevant in the real world, researchers need to know deeply about the procedures put in place by practitioners. It is a continuous challenge, but in this sense, one of my goals is to act as a bridge between academia and practice. Speaking about the impact of science on the "real world" issues: in the last year, several anti-scientific movements have seemed to gain ground, from no-vax groups to climate change deniers to Covid-19 negationists. As a scientist, what is your stand about misinformation, fake news, and mistrust in science? Negationism in not necessarily anti-scientific, and this is one of the biggest problems of our era. Of course, negationism can be anti-scientific, but more often, movements such as anti-vax, climate change denial, or Covid-19 negationism are the result of a significant misinterpretation of scientific data available. What I observe in my work is an interesting if worrying phenomenon: the surge in data availability is producing a proportional decrease in the public's trust in those same data. Every person can find almost any kind of information online, supporting any hypotheses and theories. This is how confirmation bias works: you have an idea, you look for scientific evidence that confirms your view, and once you find something that might resemble that evidence, you convince yourself that your idea is right. This is how these controversial movements strengthen through time. In this case, people miss real familiarity with the scientific method and how science works as a cumulative process. Still, the information they rely on cannot strictly be called anti-scientific. I am a big supporter of open data in science. Still, at the same time, I realize that open data in this sense does not help in terms of science communication to the general public. The options on how to deal with this are two: either we accept that the new data ecosystem creates the conditions for controversial movements as an unavoidable collateral effect, or we need to find new ways to communicate science and regain trust as a scientific community among the general public. Finding ways to maintain the liberal circulation of information while avoiding crystallization of anti-scientism is a matter of imagination. At the moment, we cannot see the solution yet.