#64: Complimentary Science & the Lure of Convenience with philosopher of technology Sabina Leonelli and Fotis Tsiroukis

 Sabina Leonelli (hosted live here by Fotis Tsiroukis) is a philosopher of science and technology renowned for pioneering work in the philosophy of data & open science. As a professor at the Technical University ofMunich (TUM), she directs the Ethical Data Initiative and leads the PHIL_OS project, which develops empirically grounded frameworks for open science in under-resourced research environments. Her interdisciplinary approach bridges high theory with participatory, on-the-ground research—exemplified by her ethnographic collaborations with biologists and data scientists.

In this episode, host Fotis engages in a deep and wide-ranging conversation with Sabina Leonelli. They explore the intersections between philosophy, science, and society, discussing topics like complementary science, the role of qualitative and quantitative methods in research, the challenges of interdisciplinary work, and the ethical implications of AI and data-driven technologies. Sabina urges us to not fear inconvenience—embracing complexity and discomfort in intellectual and social pursuits. The conversation touches on the necessity of love, vulnerability & collective agency in navigating the modern world, offering profound insights into how we can rethink knowledge production, technology, and politics.

Sabina Leonelli

[00:00:00] Highlights & Introduction

[00:10:41] Interview Begins

[00:11:13] Sabina's Journey

[00:14:17] Fascination with Boundary-Disrespecting Thinkers

[00:16:20] Early Influences & Education

[00:19:21] Challenges of Interdisciplinary Work

[00:20:39] Mentors & Inspirations

[00:23:54] The Approach of Complementary Science

[00:28:37] Collaborating with Scientists as a Philosopher

[00:32:26] Philosophy of Data

[00:36:00] Questions Left Out of Biology

[00:37:40] Coming to terms with Social Epistemology

[00:40:05] Choices & Assumptions in Scientific Research

[00:40:05] Willingness to Engage with the Social Nature of Science

[00:44:05] Willingness to Use Different Methods

[00:48:05] Acknowledging the Role of Quantification

[00:50:27] Knowledge Hierarchies

[00:55:00] Mixed Methods for Global Issues

[00:57:00] Limits of AI: The Case of Medical Expertise

[00:58:52] AI as Complement to Expert Knowledge

[01:02:01] Cultural Obsession with Control & Convenience

[01:03:45] Social Media & Digital Divide

[01:07:20] Regaining Agency Through Politics

[01:12:30] Collective Action & Social Relationships

[01:15:00] Need for Political Engagement

[01:17:20] Contemporary Disillusionment

[01:19:40] Love as a Teacher

[01:22:20] Vulnerability & Human Experience

[01:25:50] Caring as Leverage for Engagement

PHIL_OS Project

Ethical Data Initiative (EDI)

(Book, Open Access) 

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• 13:23 (Cont.) #64: Complimentary Science & the Lure of Convenience with philosopher of technology Sabina Leonelli and Fotis Tsiroukis

Transcript

Highlights 

Sabina Leonelli: ​ [00:00:00] I've always had a very strong fascination with people who completely disrespected what we would now think of as disciplinary boundaries.

 In-between

Sabina Leonelli: it's true that within the contemporary academic world. It's a problem because a lot of colleagues who are more humanist regard me as not a humanist, you know, because I'm too interested in the sciences to be a proper humanist. And of course on the natural science side, they would say no, because you really are a philosopher. You're not necessarily producing lots of scientific papers, so you're not a scientist. I mean, I don't particularly care about any of this

Microbes

Sabina Leonelli: Why does it matter to know that microbes play such an important role in our existence, for instance. Mm-hmm. What implications does that have for how we think about ourselves and our autonomy Yeah. As human beings

Mixed Methods

Sabina Leonelli: I have yet to see a complex issue, especially a global issue, that doesn't require mixed methods. So both are quantitative and qualitative, source of information

2 Problems

Sabina Leonelli: I think there are two big problems, in our society very generally. I, I would say probably globally at this point

 Control

Sabina Leonelli: one has to do with [00:01:00] ideal control this utopia of total control 

if you posit as the overarching goal for science and technology, that it would allow humans to fully control the environment we are doing very badly because humans are not particularly great decision makers And also because such control I think has been proven over and over again over history, it's just not possible. We are part of something bigger and it be much nicer to confront life in that way.

Convenience

Sabina Leonelli: The other problem is this lure of convenience. Life is becoming ever more complex, for humans on the planet people are trying to look for shortcuts to deal with that complexity and, unfortunately, feel that they can do things effortlessly.

Being able to achieve something very quickly without really putting work into it is in itself the goal the less effort you spend on interacting with the world, the better you're gonna be.

So a lot of AI innovation at the moment is set up along those lines that, well, you know, isn't that great that eventually machines will do everything for [00:02:00] us, so we can basically sit back and look at the sky and all be philosophers. Lots of people are actually making those kinds of arguments.

59:06 - Enganing less

Sabina Leonelli: I think the fundamental idea, the expectation that you would live better if you engage less with the world, and if you put less effort in doing that mm-hmm, it's so fundamentally wrong and so devastating to people that it will, it's making victims.

Using it as a way to avoid living or to avoid engaging, your body, your soul, uh, your cognitive capacities, in a way that allows you to progress as a human being that I think potentially is a big problem, but it's too often now seen as the utopian

So for me that combination is the dangerous one. We are having a tendency to want to control things as much as possible. So nothing unexpected happens to you.

And also you can use that control to do as little as possible.

Social Media

Sabina Leonelli: One could argue that social media, most generally, is the biggest pan, [00:03:00] strategy ever invented in human history and by parliament may refer to this the, conceptualization that Roman emperors had of the citizenship. That as long as you entertain them with a circus and you kept them happy then they wouldn't question your government. They wouldn't really get interested in politics or in, what their involvement could be or whether they could actually have a better life because they'd be disrupted basically. I think the way our geopolitics are working now seem to indicate that there is something like that going on.

1:04:54 Digital Divide - Domination

Sabina Leonelli: And that's, I think, in fact the tragedy of contemporary notions of digital divide, it's not anymore a question of who has access to technology, who hasn't, . It's a question of who is able to use the technology really to their advantage. And who instead is Just by dominated by these technologies?

1:16:00 Love as max incovenient

Sabina Leonelli: I mean, I would say it is really nice to talk about love, right? Because That is clearly something which is maximally inconvenient.

There is no love without vulnerability.

There is no love without the recognition of fragility, of being in [00:04:00] complete or not being in control.

There is no love without, recognizing that you may need something else and that you may not even be sure of what it is, 

there's no love without trust and very often literally blind trust. Ultimately is a leap of faith.

I mean, it's one of the most fundamental experiences humans can have.

So love is a wonderful, teacher. If one let's it Hello everybody. This is another episode of Love and Philosophy, once more, once again hosted by me, Fotis. You might remember me from the episode with Yogi Ger or the latest, meta commentary on podcasting. Uh, we did with Andrea. this episode is a conversation with Sabina Leonel, a philosopher of science, a philosopher of technology [00:05:00] is mostly known for establishing the field of the philosophy of data, of data philosophy, uh, and also of the philosophy of open science.

phil_os

Sabina Leonelli: And a really big part of that is the research project called Phil Os, a philosophy of open science in diverse research environments, which, aims to develop an empirically grounded philosophy of open science with a focus on more under-resourced institutions.

And part of this project is also. Uh, me and my own, PhD project where I conduct qualitative ethnographic research

with a focus on local plant science and agricultural science. And this is not a very usual kind of, research work because it's, uh, really in the interdisciplinary intersection between. High theory in the philosophy of science and very on the ground [00:06:00] participatory, uh, work, and this is the kind of approach and methodology that Sabina herself, uh, has been, promoting and advocating for very, very actively, 

CV

Sabina Leonelli: Now no brief intro can do justice to the extent and prolificness of her work, which spans various fields and mainly the intersection between humanities on the one side, uh, philosophy, history and social studies, of, uh, biology and then contemporary data intensive, biological practices. Uh, she has a 60 page cv, which you can find online.

and also it is a CV written with a super small font and no line spacing. So there is no reason for me to recapitulate her achievements. You can easily find them online,

Take-away 

Sabina Leonelli: What I think is the most important takeaway from this conversation is Sabina's, willingness to stay with the trouble [00:07:00] to really be in between the dichotomies and Sabina is a natural at that. Uh, she's has been operating between the continental analytic divide Humanities versus technologies.

Quantitative versus qualitative. detention is really present in her work. And I understood through the interview that there is an underlying quest for complementarity, in all of her, intellectual trajectory, which is driven by an impetus to not only stain the uncomfortable cosiness of critical inquiry.

But be productive and really attempt to mess around to get her hands dirty and attempt to make a change. So this attitude of getting your hands, dirty as an intellectual is what I want listeners, especially those that are more philosophically minded to keep in mind. This is what I also think the role for intellectual in the 21st century involves personally, and I also try to embody this in my own way.

Uh, which is a bit different. [00:08:00] Sabina tries to work with established structures, uh, for example, the, eu, and to move them to a better direction. I tend to aim more for, uh, facilitating and building alternative infrastructures, but we both know that given our current social ills. The response should not be to destroy or to rebel without any rhyme or reason, but to build and persevere in the face of adversity.

PSP - Approach

Sabina Leonelli: now if it helps you, you can consider this kind of research as, uh, close to this newly emerging approaches of meta science or research and research, but with a more. Humanistic, uh, affinity, closer to philosophical, inquiry.

 This idiosyncratic approach is also something that we, talk a lot about in our conversation with Sabina. This approach is often [00:09:00] called complimentary science, which is about this question of what does it mean to work closely with other scientists as a philosopher or as a humanities scholar, sometimes even as part of their same research project.

 And this opens up interesting tangents about social epistemology or knowledge essentially being a social practice, something that requires scrutiny and criticism and feedback We talked about the willingness of practicing scientists to engage, uh, with this, uh, kind of epistemological framework. We also talked about the dominant paradigms of, uh, scientific methodology, the quantitative versus qualitative divide. And what drives the impetus towards more. Quantification or more automation science with Sabina framed as this [00:10:00] need for total control.

And in the end we talked about the, necessity of love, as a driver, both for navigating human life, but also intellectual pursuits and even politics. Uh, especially given our tendency for more and more convenience with Sabina sees us missing the point about what love really is, which is something extremely inconvenient.

 So I hope you enjoy this conversation and I'm happy to hear your feedback and comments. So here is Sabina. Leon.

Interview 

Sabina Leonelli: ​Alright, uh, hello Sabina. 

Hello. 

Fotis: Uh, nice to have you here. So first of all, I want to start from, um, context setting an introductory question about yourself. how would you frame your own work and what you do? 'cause I know you, uh, just as [00:11:00] a, an important thing to mention is that Sabina is my supervisor. so I got to know you fairly well, but how would you put yourself, out there?

How would you frame that? I'm more interested. Thank you. Fat. I, 

Sabina Leonelli: very nice of course, to be invited to do this and, and to have this dialogue with you, different format than usual. So I guess the way I would introduce myself is as somebody who does philosophy and history of science. And what that means is, um, thinking about why is it.

 That. Um, we as a society tend to think about science and technologies as something that are reliable, something we can trust and which has some sort of authority in society. What makes it so, uh, how is it that scientists discover what they do and, um, how is it possible in fact that people who are limited?

You know, we are very limited in the way we perceive the world, the way we interact with it. Um, we have very diverse perspectives, [00:12:00] very different ways of thinking about the world. How is it that you can combine all of this and produce knowledge, which tends to be reliable for pretty much everybody? And how can you intervene in the system of science that sometimes can look a little bit closed or very difficult for people who don't know what it is and don't know anything about scientific methods and feel like it's all too complicated for them.

But how can you intervene and participate in it in ways that actually can help to make society better? So how do you, uh, help science to continue to serve the needs of society rather than take its own road if you want, and just keep it developing science for the sake of developing science? So that's in a nutshell, I guess, uh, why I do the job I do.

Fotis: Yeah. And it seems that it is very closely, uh, related to scientific work, to the interests and concerns of scientists, uh, rather than it being either a critical endeavor that does this from a distance, let's say. [00:13:00] Um, and that's not something usual, especially in, the broader territory of philosophy of science, or science studies, So I'm interested in how you got into that, that more hands on, let's say, or, little bit more, Active participatory approach to philosophy of science, and your motivations basically, behind that and the defining moments. So if you can trace a trajectory, let's say, if you can trace your own journey of how you were led to that direction, uh, what would you start and what would you say were one or two pivotal sifts?

Sabina Leonelli: I mean, I suppose, you know, gosh, one can be write ones history in lots of different ways, but I think for me, the thing that never changed, uh, since I was very, very small, in fact as, as far as I can remember. Was my fascination [00:14:00] with, um, figures in the history of particularly Western, um, thought because that was what I was familiar with when I was a kid.

'cause I'm Multita and Har Greek. So, uh, that was at that point there was no exposure in my education as yet as I was growing up to more global influences. Right. But, um, 

I've always had a very strong fascination with people who completely disrespected what we would now think of as disciplinary boundaries.

Sabina Leonelli: So natural philosophy. Mm-hmm. Being one. And that can range from pittas to Aristotle, from helmets to, to, Schiller, from ter to, uh Leonardo DaVinci and figures like that. Um, And so I've always been very interested in philosophical thinking, but philosophical thinking that was very strongly anchored in human experience.

Fotis: And 

Sabina Leonelli: in the human attempt to try and make some sense of the world around us and to [00:15:00] take very seriously non-human lives. 

Fotis: Yeah. 

Sabina Leonelli: Um, so, you know, it sounds a bit complicated, but it really comes down to the fact that I always had this very strong intuition. I guess some people, you know, we all have our things that we were born with.

Right. And for me it was very much the idea that we live in a world which is broadly sentient. Um our life depends and is completely interrelated with the lives of so many other different creatures, but also lots of inanimate, um, processes around us. Um, you know, from the cosmos all the way to the structure of the planet.

And, um, that if you really wanted to think philosophically about the meaning of human existence and potential purpose of human lives, um, it was impossible, at least for me to conceptualize doing that. Without considering the very long trajectory of people who really try to understand the world around them and how their understanding of [00:16:00] nature shaped their own self understanding as part of nature.

So to me it was always really pretty clear. I think even when I sometimes have a look at some of the things I was writing as a child, uh, this idea that if you're interested in understanding the human role in the world, this goes through a deep engagement, both conceptual but also empirical with trying to understand nature around you and your role in it.

That was always very strong. And in fact, I had quite a few problems with that growing up. Um because, you know, I mean, I was lucky to find a high school, which was an experimental program, so I didn't actually have to choose as you have to do in Italy, typically between a linguistic or a naturalistic or a more humanistic.

Fotis: Yeah, 

Sabina Leonelli: branch, I could do all three, which meant many more subjects, but it also meant that I managed to cover the whole spectrum. So I didn't really have to choose anything in terms of subjects until I was 18 or just turned 18. [00:17:00] It was a big problem in terms of finding, um, a university training, but that's where, as somebody who had never heard of philosophy of science, I had absolutely no idea about philosophy.

Generally. I don't come from an academic family, you know, no idea about any of that. I totally randomly stumbled across this program in philosophy, history and social studies of science in London, and I moved to London pretty much like that. Uh, with this idea that I am, you know, if I stayed in Italy, I would've probably gone to study physics, theoretical physics, 'cause that was the closest thing I could find to doing both philosophy or, you know, some very abstract conceptual thinking and some science.

Um, but yeah, I mean, I was, I'm really glad now that just, you know, by a whole series of coincidences and just randomness and the goodwill of a few people, I did manage to go to London even without knowing a lot of English at that point. And I absolutely loved that course of studies because that was [00:18:00] precisely the idea, you know, is really the old fashioned idea of natural philosophy, doing philosophy in that way where there's no boundary between your engagement with nature and trying to understand as much as possible all the latest methods and technologies used to engage with nature but don't without a abandoning that sense of having a, you know, meta view, which allows you to step back and really thinking about the meaning on some of these practices and why do we believe them in the first place, and why does it matter?

Why does it matter to know that microbes play such an important role in our existence, for instance. Mm-hmm. What implications does that have for how we think about ourselves and our autonomy Yeah. As human beings 

Sabina Leonelli: and all those kinds of things. So I think. In that sense, it's pretty consistent. It's not a very interesting story.

Fotis: I'd say the opposite, uh, because you're really trying to balance the two cultures, uh, like be, uh, between the, or let's say humanistic big picture, understanding of the world with, uh, the getting your hands dirty in the actual, [00:19:00] um, empirical, uh, practice and methods of actually doing that. Um, and I think we're missing that a lot of people, um, would say that there is, this is a mode that has gone a little bit extinct, considering 

Sabina Leonelli: I would agree.

Um, 

Fotis: yeah. 

Sabina Leonelli: Yeah. It's not, it's not the easiest thing to do, of course. And I'm, you know, I, I'm never entirely sure what it means to do this well. Mm-hmm. Uh, it works for me. I, I can't think any other way. So that's, um, you know, that's, that's the way I function. Yeah. 

It's true that within the contemporary academic world.

It's a problem because a lot of colleagues who are more humanist regard me as not a humanist, you know, because I'm too interested in the sciences to be a proper humanist. And of course on the natural science side, they would say no, because you really are a philosopher. You're not necessarily producing lots of scientific papers, so you're not a scientist.

I mean, I don't particularly care about any of this, [00:20:00] um, because I was lucky enough to find my own way and to get an academic position anyhow and to be able to do interesting work. So I basically decided a while ago that I didn't need to care too much about whether people would see me as fit or not in particular cultures.

Sabina Leonelli: Um, in a selfish way. I really like to do that kind of work and there's lots of people I found on my trajectory that helped me and that are very interested in working in this way. So, you know, that's enough for me. 

Fotis: And if you can say who was figures that's, uh. May push you to that direction without you having to worry.

Uh, who would you credit for that? 

Sabina Leonelli: Uh, you mean, I mean in terms of, um, I mean, before I went to university, certainly my more humanist teachers, so especially literature were fantastic. For me that was really important because I'm a huge, uh, literature buff and I read a lot. Um, I mean, outside of work like novels and so and so.

Mm-hmm. For me, that was very, [00:21:00] very important. Uh, the fact that I spent quite a bit of my early education, um, in basically a lot of my social life revolved around the parish, uh, within a Catholic kind of upbringing, not really within my family, but more in a social sense, which meant I did a lot of theology.

Interesting. And that was very useful because it was really the only thing I could find at that point. In Italy when I was about 14, 15, 16, that was actually the closest to philosophy, abstract, systematic argument. That gets you to particular position that you can defend and actually is meaningful to you.

Right? Because philosophy wasn't done like that in Italy at that point. And so the only thing you could quote was through theology. So I definitely think I would credit a lot of people that I was lucky enough to hear about. I'm not sure I would share their moral views now, but it was very, very useful for me to pick on their conceptual Yeah.

Way of, of understanding the world that was useful. So including priests and, [00:22:00] and, and people that were training at the higher level, uh, theologians at that point. And I was lucky to meet. And at university, well of course the world changed quite a bit at that point. Um, definitely for me, one of the big influences was Aok Chang, uh, who is, um, well-known philosopher, historian of science that I was lucky to meet even before I started university because he was the person who interviewed me, uh, to determine whether I would be selected to be part of the program at University College London, where I went to study.

And he continues to be a close friend and I. Important influence in, in my thinking in a variety of ways. And, uh, yeah, the idea that he has of doing, he equals it complimentary science. So he mostly thinks historically for the work that he does, of course, I, I do slightly more contemporary work. But, uh, the way he thinks about it is history itself can also become a compliment to contemporary science, because ultimately it also is trying to understand the world better.

But in azos worlds, um, words that would mean also by [00:23:00] considering paths not taken right counterfactual. So situations where there may have been five or six very interesting research programs, say at the beginning of the 19th century in a particular subject, a few of them that got lost, sometimes not for the most rational reasons, just because, you know, people die or they don't get funding or they're not popular at that point, or, you know, a World War happens or, or something like that.

And then. You know, but some of those ideas are still valuable, right? And so doing history that we can help the sciences. So it was one, and certainly, um, and, and many people that I met at UCL at that point, Joe Keen introduced me to the philosophy, history of biology, basically converted me, I would say It took me about two lessons and I was totally sold to abandoning my Ian.

Well, I didn't abandon my fascination for the physical sciences, but I just decided I would devote the back of my interest to biology and environmental sciences. Was there something 

Fotis: specific during this lecture, during this interactions? Yeah. I 

Sabina Leonelli: mean, [00:24:00] like, I don't think it took him, it took him much more than just mentioning the fact that so many people have insisted on theoretical physics being the place where you do big thinking while in fact in biology there's just so many, um, other, and potentially, you know, at least as equally complex issues.

Mm-hmm. That you find that people have been thinking, in fact, less about in a philosophical sense. Um, and this was in the context of, you know, very beginning philosophy biology course, I think it was even our first year, and thinking about things like evolutionary synthesis. But I, I was sold within 10 minutes.

I think it didn't take long for me to consider this and say is absolutely right. So it wasn't a long moment. I mean, talking about people who of course influenced me, another person who ended up having a huge influence but was already having it at the time in writing with John d Pray, who ended up being a very, very close friend and my colleague for many, many years.

I was very lucky in that respect at [00:25:00] the University of et cetera, where I was before, but before actually meeting him in person and discovering he was also amazing, wonderful person. Um, I met him in his writing and this was one of the philosophers of science, um, in the 19, you know, 1990s, um, that was really influential because you could think about very big.

Philosophical questions about reference, about what exists and doesn't, how do we classify the world? Things like that. Mm-hmm. But do it on the basis of very deep engagement in biological knowledge. So that really exemplified the kind of thing that I thought, yeah, it's, it's exactly the way I would like to do things.

Um, so, so that was also a big influence then, um, and later on I was very, very lucky to work with Mary Morgan, who is, um, very, very important philosopher and eastern of economics. And she like passed on to me or certainly reinforced my in, in interest in the social sciences. And, [00:26:00] um, she at least gave me the sense of just how much I don't understand about economics and just how important this would be, which I'm always gonna be grateful for.

And then I spent a period in Amster, Nando was also very, very formative for me, uh, working with AM and Direct and Hans rather. Totally different way of thinking about these issues. Much less Americanized than my education was until then. And so I'm very grateful for that period too, because it was a way to go back to my continental roots, but in a kind of northern European context, um, which was also influential.

Well, I mean, let's just say certainly in the Netherlands, uh, at the beginning of two thousands when I started my PhD there, there was more openness to, uh, tracing links between the continental philosophical tradition, both actually actually philosophical and also, um, naturalistic and what was going on [00:27:00] at the time in philosophy of science.

And this was at a moment where in places like the Runo School of Economics, where I was doing my training before in London, this was not only unheard of, but very strongly opposed. So there will be a sense that you wouldn't really be a proper philosophy of science, uh, philosopher of science if you thought in those terms.

And this is exactly the kind of boundary setting in that I absolutely detest. So I didn't like it there and I left, um, in, at that moment. Um, but that was where the Netherlands really gave me much more freedom because there was a much, you know, much more openness indeed towards the approach I liked, which was to try and engage with scientific practices as a philosopher and somebody who was interested also in the history of science.

And at the same time, not to be too rigid about which philosophical tradition you would getting your insights from. I mean, I still consider myself to be in the more analytic and American tradition, but I've taken a [00:28:00] lot of ideas and insights also from continental philosophy. I'm very grateful to come from that, uh, tradition.

So that divide is also something I'm not very happy about. 

Fotis: So. It is, especially the approach of complementary science, I guess not many people are, uh, aware of. And I guess, uh, you took steps towards that, um, early on, uh, in your career and wondering how this looks in from your case, what kind of work you do, um, in that kind of approach.

Um, and what other ways are to name your approach and also in, in the way my mind since I'm work, uh, working in, uh, your approach with has, uh, um, a little bit of that, let's say. So, um, yeah, like how, how did this [00:29:00] start off and where has it led to now? You don't need to go, uh, too much into this, but if you can, um.

Say a little bit of what inspired you first and what are the current problems that you are working on? Uh, will be really 

Sabina Leonelli: I'll, I'll, I'll pick up a few things I guess. So, um, one of the early things I got very interested in was why is it that people, like, you know, a lot of biologists, so many biologists, probably the vast majority of biologists work on organisms that don't seem to have any obvious relation to humans, like little weeds or, you know, little worms or zebra fish or water fleas, you know, and they think that they can acquire insights by modeling those creatures. Mm-hmm. That will be directly relevant for us to understand the whole of biology, our whole evolutionary history and also ourselves.

Fotis: Mm-hmm. 

Sabina Leonelli: And so, um, that's a situation where [00:30:00] I ended up, uh, over time collaborating with Rachel Ankeny, um, who is, um, my closest colleague and, uh, with whom we've been doing a lot of work on the history and the philosophy of the use of organisms in research, particularly biological research. And I think that's an example where, um, we have been digging into the history of how these organisms came to be so popular, so widely adopted, what the implications of that adoption have been for biology as a whole, for better or worse, uh, how this is now evolving and quite a bit of that work, um, I think has ended up being recognized as useful by scientists.

Uh, many of the sciences that actually work on these organisms and. Are curious about their history or are curious about how do we tell a story about the credibility, right? Especially to people who are not technicians or not, you know, used to that way of thinking, why would somebody [00:31:00] who doesn't work in the warm community?

'cause there is such a thing, um, would believe that you can study worms and understand the development of human brains, right? What, how would you make that leap? And so, so that's been very nice because that showed me early on also by looking at what Rachel was already doing when I started my PhD. And she was already a full fledged academic.

That in fact is perfectly possible to collaborate with scientists offering a different set of skills and insights from the ones that they are developing, but in ways that is very complimentary, that is very collaborative and can be in fact productive towards pushing the field in one way or another.

Right? So maybe sitting on committees where you. Say, you know, which organism should be developed next, or mm-hmm. You know, how should organism work be developed in the future? You know, and this has implications for really a lot of our general understanding of nature, uh, because these are techniques and methods that look very technical, but actually they very much [00:32:00] determine what you find in biology textbooks, even the ones that my daughter uses now in, at the beginning of high school.

Right? So, so these things, I, I, it showed me early on that this was in fact not only possible, but very useful and very interesting for me to do. And then another bit where it became, uh, very important, very quickly, I got interested in these questions around the use of data and supposedly data driven approaches to research.

So this idea that, oh, now we have all this data and so on. Research is completely determined by the data. As long as you have lots of data, then eventually we'll get to a world. And of course that takes us now to current ai, right? Artificial intelligence. World where all you need to do is to feed lots of data to a machine and then the machine will become smart enough, uh, you know, it will have intelligence so that it will just produce discoveries, one after the other.

And, you know, there's no need for science anymore because all you need to do is to find good automated ways of analyzing data. And that facilitated me very early on. And so I [00:33:00] devoted a lot of time over the last 20 years trying to think about that. Uh, what actually are data? Can we even think about data analysis working in this way?

The answer is absolutely not, uh, by the way. Um, what implications does do philosophy of data really have on data practices and which actually, of which there are many, uh, because, you know, I think over the course of the years, I did show, even, for instance, during the pandemic. That certain approaches to just, you know, reading the data and pretending that there was one unical obvious way to interpret them was really a really big problem.

And anybody who had that expectation ended up not going, not doing very well. Let's put it this way, with their predictions and the models that they proposed. So, I mean, this philosophical ideas, I think in that realm too, of this old data world, uh, that also showed me that it made sense to do what I do and it does make a difference.

Uh, though of course a lot of people wouldn't, you know, consider that kind of work, who wouldn't know about it. But with the [00:34:00] people I collaborated with, it made a difference. And of course, that brings us to some of the things that we are working on together, which are broader questions around how do we even communicate and collaborate in science, uh, if it's not just by means of throwing data around or just sharing methods and, you know, with expectation that other people can just pick them up and run with them.

And that's how science works. If that's not quite how science work, then how do we tell that story? How do we think about what's the point of science being an open, um, an open activity? In which sense is it open? How do people in fact collaborate? How do people learn from each other? What is the role of so-called tacit knowledge?

Mm-hmm. You know, knowhow in scientific research. What is it that we cannot quite formalize through algorithms, for instance, what implications are designed for today? And these are the kind of questions I think, that we are dealing with now. 

Fotis: So yeah, it seems like in a way it is a different set of questions [00:35:00] that what the technician, uh, or the practicing research scientist would do both in the case of biology.

And I would be very interested in actually knowing the difference in terms of the questions being asked, uh, between these two different ways of approaching the, the target mother, like the worms in, uh, one case. Uh, and I guess data, um, driven inquiry in the other. Um, um, when you are dealing with collaborations, uh, either with, uh, uh, biologists or, uh, mathematicians and computer scientists or data scientists, um,

I mean, you've already went into how they view you in a way, uh, but I'm really wonder interested in this interaction and, um, what kind of questions you see [00:36:00] not being asked. I guess also in the case of biology, because in the case of data science, you've also already went into that, all these aspects of how is there only one interpretation?

What cannot be formalized? So first of all, I'll be interested in the biological, going back to the biological case, what. Questions are completely left out. And especially now because we have this inter intersection between data-driven, uh, methods with biology, genomics, bioinformatics, all kinds of s uh, and all kinds of chime in the disciplinary chime in medicine and biology.

Uh, what kind of questions do you see being left out, uh, uh, repeatedly, let's say? 

Sabina Leonelli: Hmm. So yeah, that's a very nice question. Um, I would say very often collaborations really start from funding common questions maybe that, um, people will be asking themselves, maybe [00:37:00] not formulating them in exactly the same way, but, um, you know, I, the vast majority of cases, I had a collaboration with biologists especially, but also data scientists.

Uh, people were asking questions that actually were similar to mine. 

Fotis: Mm-hmm. 

Sabina Leonelli: But, um, didn't really have time to pursue them at that level because of course I took it on with their work, which is, uh, in a sense technical and, and very specific in terms of deliverables and also didn't have sometimes the instruments and the skills to pursue them because of general.

Um, it does help to have a ground in philosophy and history. Yeah. It does help to devote a lot of time reading literature that, that deals with these issues, which most of scientists don't really have the time to do. Mm-hmm. And don't have the training to do. Um, so I suppose the most difficult conversations, um, happen with scientists that have been educated to not even want to consider the extent to which science really is [00:38:00] ultimately a human in social activity.

Mm-hmm. 

Fotis: And 

Sabina Leonelli: there are people who think in those terms, right? There are scientists and I respect their work. It just that. That's a very hard premise to, to go past, right? Um, who really are in that game are in the game of science because for them it's a way to reach objective knowledge, which is totally a contextual where context doesn't matter at all.

Values, interest play, no role. All you are doing is producing reliable data and then reading knowledge out of the data. And that's how you, you know, produce water tide neutral objective knowledge. Now, if you're the kind of scientist who's in it for that, and I've met both biology statisticians for instance, who have been strongly on that side, it's actually a bit hard to collaborate and ask similar questions because many of the questions I would ask are questions that start from almost [00:39:00] the.

Uh, premise and the observation that science, um, requires lots of choices and lots of, um, judgments, and many of those are linked to the specific situations. Uh, scientists are in the interests. They have the goals, they have the constraints. They work under the institutions they work for, the type of funding that they have, all of those things, uh, which doesn't make size less legitimate or, worse, but it simply means that, you then really think about scientific developments and the direction of research and some of the outcomes and the content of research also by taking these elements into account.

Fotis: Yeah. Um, 

Sabina Leonelli: now if you're the kind of scientist who really doesn't want to do that because you believe that the moment you do that, science becomes a completely relativistic endeavor and you lose any trace or objectivity, then it becomes difficult. Then there's lots of questions you will not ask, because you will not want to engage with those questions in the [00:40:00] first place. Right? So if you're the kind of data modeler that thinks that, um, if you get to the perfect model, eventually that will be a model that is completely comprehensive. So it doesn't require any choice. It doesn't require you to have a vision about what those results may mean in the future.

It doesn't require you to make any big conceptual assumption. It's just a model of what there is. 

Fotis: Hmm. 

Sabina Leonelli: Um, then there's no space for me for the kind of questions I ask because my questions are about, with a acronym in the model you're not using in, in the, uh, in the results you're now producing, what are actually the assumptions?

Could there have been different assumptions? Um, why you choosing certain methods other than not? Why are you consulting certain experts rather than others? You know, what impact do all those choices have on your work? Where, um, there is much more space to have common ground and to ask common questions is where people are willing to consider that.

And to [00:41:00] see the fact, at least for me to be honest, it is a fact. That's why it's so difficult to get past it. Um, that science is affected by all of those human factors. And actually it's the strength of science to be effective by those human factors, that they direct your attention, that they give you a particular objective or goal to work towards.

During the pandemic, there was a real global emergency. It was recognized to be a global emergency, which is rare. We have lots of global emergencies. Very often, you know, they're not acknowledged to be such by politicians and by private citizens. Right. But in the pandemic, I think pretty much everybody around the globe recognized that this was a rather difficult moment.

And so there was also consensus in the scientific community to all work towards that. And that actually made in many cases for better science for. Science that was better integrated where people were more willing to talk to each other and exchange results. 

Fotis: Mm-hmm. 

Sabina Leonelli: And that came out of the acknowledgement, the fact that now there is a specific need and we're gonna work towards that [00:42:00] for visions, which have all to do with humans and, you know, and at demand the society has at the moment, rather than simply because we want to know more about viruses.

Fotis: Yeah. Right. 

Sabina Leonelli: And so I think, you know, once you recognize this historical nature of how we're thinking about scientific developments, then the kind of questions I ask become feasible. And they are of that sort, right? Mm-hmm. So why do we choose the conceptual commitments that we choose? What could be the alternatives?

Um, what would be the implications of thinking about certain research domains differently? What would happen in biology if um, people were maybe a little bit less obsessed with genetics? Uh, which have been for a long time and thought a bit more about development, for instance, and how, um, genetic gene expression and genetic pathways actually manifest themselves in, uh, [00:43:00] development, not just in, in evolution by selection.

And actually, how does that affect, uh, the way in which organisms, um, grow, reproduce and how we think as humans? Mm-hmm. Um, you know, there's, there's many questions you can ask once you recognize that science is made of very hard work, great achievements and understanding, but there is a degree of serendipity and there is a degree of subjectivity to which research directions people take, what they decide to focus on a particular moment, what concepts they really decide to explore, and which ones they leave behind.

Fotis: Mm-hmm. And 

Sabina Leonelli: so for me, it's never a question of, um, critiquing. Biologists I need because I feel that their research is pointless. Right. That's very, very, very rarely the case. I mean, but sometimes what may happen is I encourage them to think about, well, you're making all of these assumptions in your work.

What happened if you were to think a little bit [00:44:00] outside of your own box? 

Fotis: Mm-hmm. 

Sabina Leonelli: And consider maybe other ways of, of going to the same problem, would that make a difference to what you do or not? It doesn't take absolutely anything away from their discoveries, uh, but may help to try and contextualize them, uh, a little bit more broadly and to think maybe be more systematically about the broader implications.

Right. So, I mean, the thing that I think a lot of philosophers of biology constantly get annoyed by is this, um, big social belief, uh, which are auto scientists unfortunately have, have pushed about the. Um, linguistic nature of the genetic code. Like, it's like a language that we can read better and better.

And once we can read it, we can program people and, uh, other creatures, you know, and that's something that annoys a lot of us because this is like packing up so many problematic metaphors around how biology actually works, uh, that we don't think is [00:45:00] particularly useful. We think it has been useful in, in some ways.

I mean, certainly thinking about gene sequencing as reading a code has been of course foundational. I mean, a lot of our discoveries in genetics, the value way in which we can now modify organisms both in medical terms and in terms of, you know, modifying them for food purposes for instance, or for defense.

Mm-hmm. Um, all of this come from that particular way of thinking. It certainly has been effective. But,. I would also think it's very limited, you know, and there's other ways of thinking about the role of genes in development in evolution that are potentially, you know, if not richer, certainly just as useful.

Hmm. And particularly at the moment where, um, you know, we seem to be going down this path of, um, trying to automate reality as much as possible in a way that is very ideological and sometimes rather ineffective, [00:46:00] considering other ways of thinking may be useful. Right. Yeah. So, yeah, at least that's a beginning answer, I guess.

Fotis: Yeah. I mean, to contextualize it, uh, a bit. It seems that there is, we could call it wave, an intellectual new wave of, various, thinkers, various scientists who are addressing that. Uh, had the conversation the other time with Johanne Seger Yogi, who's also from his own approach and also from his, uh, experience in biology trying to address these issues of how subjectivity or social conducts have been, are being left out.

especially in applied, uh, research settings, like these questions are not being asked at all. Then there's, uh, Evan Thompson's, uh, blind spot who, which has been kind of hot, let's say, this kind of, area for people who are interested in this kind of questions of like, how can we do science differently given this past, [00:47:00] um, issues.

However, there's still from. My experience and from my end, uh, I always see these conversations as lacking a little bit, , in terms of the more suggestive part of how these different environments look like, how these different settings look like. And also, I dunno from your case too, can you find some sort of virtue in this kind of unwillingness sometimes to engage with the social, uh, questions.

I am playing devil's advocate here, for example. all of these problems that we're talking about, about the social context being excluded, about judgment being excluded, about the subjectivity being excluded sometimes after the conversation. Um, for example, when it comes to dealing with.

The division between quantitative and qualitative research and data. Um, it, it is the case that [00:48:00] we talk about qualitative research more, more as a compliment or that's something that comes afterwards to contextualize quantitative data. Um, but do you think this is an issue of culture, an issue of underlying, uh, philosophical stance that leads to that?

Or is it something about, uh, this sort of methodologies, uh, that is actually very powerful that we should also be taking into account that yes, quantitative data maybe are actually very important to look at and to have like better methods and to have all of these aspects of efficiency or optimization, maybe they are very important.

So what do you position yourself when it comes to that? And I guess this is also a question that goes into the techno optimism, techno pessimism kind of, um, stances towards science, uh, [00:49:00] scientific practice. just to compress a little bit that, uh, question,

What is bad about quantitative? Purely quantitative? 

Sabina Leonelli: Well, I never said that there's something bad about purely quantitative, by the way. Yeah. I'm over exaggerating just to, and that's not what I, in any way. What I think is a problem sometimes is not, you know, science is a modular affair and it's got to be, um, research and inquiry generally.

I mean, our experience with the world has got to be modularized and we can't think about everything all at the same time. Right. So specializing, focusing. Is absolutely fundamental to human experience in any of these forms. We cannot always all do all the same thing. We would never learn anything. We would never be able to move on in life.

I mean, so one of the, one of the things that makes humans so interesting as an organism is this ability to modularize your experience and to choose a focus of attention for long enough that you [00:50:00] can actually really build a whole set of experiences on it and you can build methods to analyze the experiences and actually really get advanced knowledge on that particular aspect of reality.

So science obviously is the ultimate manifestation of that way, of, of, of doing inquiry more generally. Right? So there's nothing wrong with that. In fact, that's, that's a very, very, very powerful thing and that's very clear from the history of science and technology. Where it becomes very dangerous is where there are, um, entrenched hierarchies.

Among these, if you want different modules of knowledge 

Fotis: mm-hmm. 

Sabina Leonelli: That become so entrenched, so absolutely untouchable that people are not even able to question or see that hierarchy anymore. So if you're in a situation where doing computational analysis mm-hmm. It seemed to be the absolute gold standard for how you do research and doing qualitative research, [00:51:00] say in graphic study or anthropological study of some sort, or a survey, it seemed to be, oh, kind of iffy, eh, not great knowledge, kind of subjective, not, you know, you don't learn much from it.

Um, that way of, you know, putting up a hierarchy around methods about, around different domains of knowledge without, in fact, looking at the content of the particular research without looking at what kind of knowledge you need for any particular purpose. Uh, that is extremely dangerous because it gives you a situation where instead of thinking for any.

Question you pose any problem you have. What is the best combination of insights, types of expertise that are right now at our disposal to address this? You instead go to this hierarchy no matter what, you know, and just think, okay, for instance, during the pandemic, I picked up the example because people have it still in their mind.

I guess the immediate, uh, reaction of a lot of governments was, well, we're gonna take financial modelers and people who do [00:52:00] statistics have them churn through data that come from hospitals, and then we give, give us answers around the rate of transmissions of this disease and we are gonna be able to predict where it goes and stop it.

Right now. That was very much, instead of really sitting down and thinking, what kind of knowledges do we need? What, what is around here? There was a very standardized assumption that, well, here what we need to do is to do some sort of complex modeling. The more mathematical the better, and it will give us accurate answers that everybody can trust.

Which basically by the way, takes responsibility away from governments, from making decisions because then the government, like the UK kids can just say, oh, science told us what to do, so we just did it right. Like, no decision making, um, responsibility whatsoever. Now that worked probably, um, because what should have happened at that moment, and I think many people recognize this is to a much better sense and consultations around.

Okay. What kind of expertise are around? Sure. Modern is very important. [00:53:00] Virology is very important. Biomedical knowledge is very important. But the experience of people who are, um, experiencing public health is also very important. The experience of frontline doctors is extremely important because they were the ones to see first, for instance, the symptoms of long covid.

Fotis: Mm-hmm. 

Sabina Leonelli: Uh, the, the experience of patient families and groups is extremely important because these people, again, are on the frontline. They're seeing the disease as it emerges and it manifests. Not taking those forms of knowledge into account was a big mistake. 

Fotis: Yeah. 

Sabina Leonelli: It produced knowledge that was not as good as it would've been overall as an integrated whole if one had made rather unfortunate assumptions at the very beginning about what is best.

Right. So I absolutely, you know, a lot of my research is on qu quantitative methods, and I'm very used, I'm very happy to use them when I can in collaboration with people who are better than me in that respect. But, um, the message is really don't make assumptions about what [00:54:00] methods or what combination of methods or expertise would be the best to address your problem. 

Fotis: Yeah. 

Sabina Leonelli: Until you really thought about it. Uh, there's no magic formula here. For different problems that present themselves to the world. There's gonna be a need for different tools. I have to say in all of this, 

I have yet to see a complex issue, especially a global issue, 

Sabina Leonelli: systematic issue 

that doesn't require mixed methods. So both are quantitative and qualitative, 

Sabina Leonelli: uh, 

source of information, 

Fotis: So would you say this is an issue of trust in the end because there's uh, when it comes to some benchmarks and gold standards, uh, that are there in, when it comes to statistical, uh, measurements to now with Bayesian modeling now now with ai there is a lot of talk about standards. There's a lot of, like, at least the way I would put it from my own perspective, it's a lot of trust in the method itself. Yeah. As a method, which takes subjectivity away, which takes, um, and in [00:55:00] certain ways in science, it's considered a good thing the fact that it takes the subjectivity, uh, as much as possible.

Sabina Leonelli: I mean, 

I think it's a perfectly understandable mechanism, especially when science is supposed to be the grounding, the evidence for lots of very, very important decisions that governments and corporations and public administrations and, you know, people take every day. Um, but the fact is, I really don't see, a way out of the problem of trust.

Fotis: Mm-hmm. 

Sabina Leonelli: Ultimately, whether we are looking at methods, models, data systems, or at the knowhow of particular scientists, 

Fotis: um, 

Sabina Leonelli: you are always gonna find situations where certain choices have been made and judgment have be made and they're opaque. Right. Because not everybody can be an expert in everything to understand these things in depth.

Yeah. So we live in a system which is a trust system where we hope that we have institutions and mechanisms which are good enough that, uh, we are gonna be [00:56:00] able to filter out what is the most reliable knowledge. Whether you're a scientist or not, that's still gonna be true. I mean, most scientists I work with, of course there are specialists in their own area, but for everything else, they have to trust other scientists, you know, to be reliable, to tell them the truth some way, somehow, or the best possible, the closest possible version of reality that we have right now, closest to the truth.

And so there's no getting out of having to trust others, right? Like appealing to a particular method is not gonna save you because that method typically to be applied also requires people making choices and adding a certain know-how and a level of expertise. Yeah, 

Fotis: I mean the, the knowledge of a neurosurgeon, um, and the trust that you have to give for a operation to perform on you, which is not mathematically formalized, knowledge that there is some discourse around ai being able to formalize that.

But I'm not, uh, very, uh, convinced. But 

Sabina Leonelli: that's a very good example. It's a very good example because of course a surgeon. [00:57:00] Or many medical practitioners with a perfect example of people that constantly combine highly technical knowledge, a very high level of training, consultations with other specialists, with subjective understanding of the patient of their history, being able to put it in a particular context, being able to think for this particular person in this situation, given their own experience as a physician, what is best, right?

And particularly with surgery, a lot of decisions need to be made right on the spot. Like you open somebody's brain, uh, try to, um, understand how to intervene. Very often you only see how you can intervene as a surgeon once you open somebody up, uh, because there's, there's a limit to the imaging that we have.

So the issue of course, is with ai and with the combination of AI and robotics, we have made really very important progress in the accuracy. Of surgeries for sure. I mean, especially in situations like surgery on the eye, for instance, or very particular [00:58:00] parts of the brain where, you know, precision is gonna make all the difference in the life of the patient going forward.

is incredible to see how much we have managed to program robots through very particular rules, very particular algorithms to help out. But this is constantly complimentary with the exercise of this know-how and expertise and judgment, right? So, typically these robots help physicians understand how to intervene, all these systems work best when they are, you know, they human in the loop to put it in.

people would put it like, so the artificial intelligence is set up to compliment in very important ways. 

Fotis: Yeah. 

Sabina Leonelli: The type of judgment call that a physician would make, I think that's really a good example because it shows you. That we can make huge amounts of progress in technological terms and in terms of innovation and a lot of quantitative and kind of algorithmic knowledge.

But, it works at its [00:59:00] best, but it continues to be complimentary, supplementing, augmenting, like the kind of judgment and experience that humans bring to particular jobs. 

Fotis: So it's a collaboration with a non-human, the way I hear you put it, uh, which is, a much more reasonable way to approach this because the discourse is either, oh, this thing is competing as an entity of its own.

or it is, uh, totally our own control. It's just like we're just, uh, pre-programming and this goes like that from my end. This seems to be lacking a lot. even if there's more awareness, for example, with LS, that they are essentially assistive tools or collaborative tools, it seems so easy to regress back to, uh, this kind of polarity of, either this is just like merely a, mindless tool of its own or just like something that is trying to take my job, uh, or trying to get all of the expertise that [01:00:00] I've gained throughout the years that this is, uh, now competing with me and I have to compete with it.

so I'm wondering, is there a way to lead the conversation towards this appreciation of this collaborative element?

Difficulties with a collaborative view of AI

Sabina Leonelli: Well, you know, I mean, 

I think there are two big problems, 

Sabina Leonelli: um, 

in our society very generally. I, I would say probably globally at this point 

Sabina Leonelli: in, in trying to have that set up, uh, 

one has to do with ideal control 

Sabina Leonelli: that you just mentioned.

Mm-hmm. I think unfortunately, this ghost of the aspiration to control, control our lives, control how people react to us, control the way society works, control our machines, interact with us, mm-hmm. Um, 

this utopia of total control 

Fotis: mm-hmm. 

Sabina Leonelli: has a very specific historical lineage. I think feminist scholars and most adequately, uh, described some of these issues, but is incredibly damaging, because 

if you posit as the overarching goal for science and technology, that it would [01:01:00] allow humans to fully control the environment we are doing very badly because humans are not particularly great decision makers 

Sabina Leonelli: for one thing. 

And also because such control I think has been proven over and over again over history, it's just not possible. We are part of something bigger and it be much nicer to confront life in that way.

Fotis: Complexity you say, rather than a well planned, well engineered kind of. 

Sabina Leonelli: Exactly.

Convenience AI

The other problem is this lure of convenience. 

Sabina Leonelli: The fact that, 

life is becoming ever more complex, for humans on the planet 

Sabina Leonelli: in a variety of different ways.

People are trying to look for shortcuts to deal with that complexity and, unfortunately, 

Sabina Leonelli: the shortcuts that become most easily available to people that are marketed very heavily to people are the ones where, again, people may. 

Feel that they can do things 

Sabina Leonelli: easily, 

effortlessly. 

Sabina Leonelli: Right. Like that, the lack of effort, 

being able to achieve something very quickly without [01:02:00] really putting work into it is in itself the goal 

Sabina Leonelli: and that 

the less effort you spend 

Sabina Leonelli: on living 

on interacting with the world, the better you're gonna be. 

Sabina Leonelli: Right. 

So a lot of AI innovation at the moment is set up along those lines that, well, you know, isn't that great that eventually machines will do everything for us, so we can basically sit back and look at the sky and all be philosophers.

Sabina Leonelli: Right. 

Lots of people are actually making those kinds of arguments. 

Fotis: Department of government efficiency. 

Sabina Leonelli: Exactly. Exactly. 

Lots of novels written about this. Like, there's, , I'm sure people who are listening will have their own references for all of that.

Now, 

I think the fundamental idea, the expectation that you would live better if you engage less with the world, and if you put less effort in doing that mm-hmm, it's so fundamentally wrong and so devastating to people that it will, it's making victims. 

Sabina Leonelli: Right. So the fact that you don't, you know, using a collaboration with machines [01:03:00] or different types of knowledges as a way to live better is one thing. 

Fotis: Yeah. 

Using it as a way to avoid living 

Sabina Leonelli: for, for a, you know, for a lack of a better word, 

or to avoid engaging, your body, your soul, uh, your cognitive capacities, 

Sabina Leonelli: uh, your abilities 

in a way that allows you to progress as a human being to kind of, um, develop yourself to learn new things, to solve problems for yourself, that I think potentially is a big problem, but it's too often now seen as the utopian, 

Sabina Leonelli: or I have too many friends now that instead of engaging in reading a book. Just ask ChatGPT to summarize it for them. For some books that may even be an adequate treatment, maybe depending on what you want to do with them. But it does take away the experience of engaging in a focused way with a long piece of writing. Right there, there are skills you're missing there. There, there's things that have been lost.

So for me that combination is the dangerous one. 

Sabina Leonelli: At this [01:04:00] moment in time, 

we are having a tendency to want to control things as much as possible. So nothing unexpected happens to you. 

Sabina Leonelli: You can just control your environment as fully as you can. 

Fotis: Mm-hmm. 

And also you can use that control to do as little as possible, 

Sabina Leonelli: engage only with very limited like that again, are gonna be predictable, are gonna be easy. They're not gonna challenge you. 

Fotis: Is that the case though? 'Cause that's what I'm wondering because where would do we draw the line? Uh, in fact, because it is a moving target

the, the thing is that, like these advancements, uh, let's say technological or otherwise, that, reduce the work that is needed to be done, can free up space and free up attention and free up time for other stuff is what you've said before about like we will, all be philosophers once, AGI, uh, is, uh, fully out of the box. Uh, but in many ways we are surrounded and scaffolded by our technologically [01:05:00] enhanced environments in a way that, we don't have to rely on that stuff. Like when was the last time we used the map to, and, and navigate in a different country? I'm like, I'm wondering also, if this line is always shifting, we're shifting with it and we're developing with it.

Sabina Leonelli: that's certainly the case. And of course, I'm not saying that, um, this kind of innovations haven't helped in many ways to forge new ways of human life. Of course, that's, that's what happens all the time. I mean, that, that's history that we are, we are, are constantly, uh, moving target and things are always evolving in their own way.

But, um, I think there's a fair amount of technological innovation that actually has not at all created more space for people. Mm-hmm. In fact, I think there is no argument to be made, and many people have made it that, um, technologies have ended up being yet another set of distractions from things that potentially may be said to matter.

Uh, one could [01:06:00] argue that social media, most generally, uh is basically is the biggest pan, strategy ever invented in human history and by parliament may refer to this is the Latin term, indicating the, conceptualization that Roman emperors had of the citizenship. That as long as you entertain them with a circus and you kept them happy and you gave them bread and entertainment, then they wouldn't question your government. They wouldn't really get interested in politics or in, 

you know, 

what their involvement could be or whether they could actually have a better life because they'd be disrupted basically. I think the way our geopolitics are working now seem to indicate 

Sabina Leonelli: potentially 

that there is something like that going on.

Sabina Leonelli: Uh, that there is a huge amount of confusion and frustration at the diversity of information people are bombarded with at the different platforms they can go to, to try and understand how the world works and diversity of voices they may encounter. And ultimately, it's [01:07:00] becoming so confusing that, in fact it becomes, all of, it becomes a huge destruction, because it becomes much more random who we end up trusting. It becomes more random who we end up talking with. And these are smaller, smaller circles like this called eco chambers. Uh, there's in fact less communication going on. And a lot of people, whichever age end up being, taken in by looking at endless Instagram loops or TikTok videos or you name it, um, of course engineered by companies and by a type of knowledge which is specifically designed to distract you and to distract you as much as humanly possible because that's basically the business model.

So in the kind of reality, which I think, in my perception is that's actually the reality that the vast majority of people are experiencing at the moment. So there was have access to mobile, mobile phone. 

Fotis: Yeah. 

Sabina Leonelli: the idea of, you know, the technological utopia of this wonderful world where AI, for instance, is coming in, saving us all this work and allowing us to think [01:08:00] about more important, um, things or things that actually matter more for our life, or be able to read books or to get more information or to learn new things.

Mm-hmm. I mean, I don't see that happening. Um, in fact, almost at all. It seems to be a very, very elitist way of understanding the impact of some of these technologies. For the vast majority of people, I don't see that happening at all. 

And that's, I think, in fact the tragedy of contemporary notions of digital divide, 

Fotis: right?

It's not anymore a question of who has access to technology, who hasn't, . It's a question of who is 

Sabina Leonelli: be, is 

able to use the technology really to their advantage. And who instead is Just by dominated by these technologies? 

Fotis: Yeah. 

Sabina Leonelli: And their life is just completely taken over one way or the other, and they lose a sense of agency and then is a vicious cycle because the war you feel you losing agency.

The more it becomes difficult to counter, uh, that sense that actually is very often right, like the sense that people are losing agency. Yeah. But then how do you counter it in a world that so totally appropriated and dominated by technologies you can't [01:09:00] control? 

Fotis: I mean, there's this wave of people ditching their phones again.

Uh, it happens once in a while. Um, and she like, okay, now I have time to read. Which was supposed to be the premise of what this was supposed to bring you. Anyway. On, on the other hand, this, there's some assumptions. This one specific one that I want to question about this being designed from the get go like that because I remember,

in early Facebook, for example, was not designed to, uh, in terms of user engagement to have like a, uh, algorithm that can have this. Analytics that can show it. Very clearly the, the engagement of the users. And then this feedback loop started, uh, with a business model sifting to advertisers in, in fact, the feed was not there, , from its first designs. And there was, uh, when the feed was introduced as a feature, there were so many Facebook groups that was, that were going against it and like, the feed is gonna kill the platform. We don't want this. [01:10:00] In the end they weren't heard. So, I'm wondering like, I don't want this to be, to seem as if it is only a matter of the agency of some powerful people, but also all kinds of incentives, uh, complex incentives that are , involved. And that, because I've seen also the aspect of capture of how, developers, uh, or all kinds of very creative, individuals and end up being captured by the broader incentive structures, even though the motivations were. 

Sabina Leonelli: Sure. 

That's the system we live in. It's called, you know, system of capitalism. That's exactly what it does. And, there are a few winners and, but it's not, the story is not about the winners.

I mean, well, you know, it, it really is about the system. Mm. And the wake up you, so I agree with you, but that's why many people talk about the death of the dream of the internet, right? I mean, of course he was born with a completely different set of [01:11:00] assumptions and understandings about the opportunity would open up in terms of communication, in terms of freedom and openness.

And um, and then it ended up being gobbled up by the global capitalist system, which is no longer global actually right. As of today. Um, but it still is a complex and. Um, at, at the type of market where there's gonna be only a few winners and there's gonna be winners by using a particular kind of business model.

Um, and so the people who adopt that right at this moment continue to win. Uh, which unfortunately is what engenders this incredible situation of corporate domination of, uh, the internet, social media, and much of AI at the moment. 

Fotis: So, uh, I'm wondering how to regain agency in that kind of respect and with that kind of perspective, because I guess for somebody, um, who hears that it might lead to a kind of techno optimism, it's hard to get out of, um, and[01:12:00] 

Sabina Leonelli: or pessimism.

Fotis: What did I say?

Sabina Leonelli: You said techno-optimism

Fotis: Well, well, tech optimism is also hard to get out of. Uh, that's the reality of it. Yeah. It's, it's a techno pessimism that is hard to get out of, invokes a bit of, uh, helplessness. Yeah, especially , I'm wondering about the engagement of that somebody in that moment has to do with technology and with methods, uh, in order to, deal with this issue. And from your perspective, have you see, how do you see that relationship and how do we gain agency? 

Sabina Leonelli: I think first of all, acknowledging these feelings of hopelessness is really important, uh, because it's exactly the same thing when you look at technology as it is when you look at climate change, right? I think, and there are, there are good reasons to feel hopeless in that respect because in both cases, well, of course we are looking at very interrelated phenomena, uh, first of all, but you're looking at extremely complex systemic phenomena.[01:13:00] 

The kinda thing that you can't as an individual think, okay, you know what? I will change the world that will make a difference in this. It's just not gonna be possible. It's not. The kind of thinking that that will only get you down, right? Because it's gonna become so clear, so very, very quickly that the one individual can do nothing against this kind of overarching, very ingrained systems that we are living in.

But that's where I think, um, two things become extremely important. Um, one is recognizing the power of collective agency and social relationships. Um, I think the myth of the lone hacker or the lone technologies that can, you know, keep up the world through, goodwill and, and, and good intentions. I mean, it never really was there because whatever good has come from that community has always come from collective action.

But even as a myth should die, right? I mean, it's very, very important for people to recognize that the only way to [01:14:00] counter, uh, this very, very strong trends we are all suffering from is to. Kind of seek like-minded people and think about collective ways of reacting, right? 

Mm-hmm. 

And that brings me to the second point, which is good old fashioned politics.

Unfortunately, politics as a space has gone out of fashion, uh, especially among young people, partly because of the huge amount of disillusion and disappointment in the contemporary, uh, political landscape, the lack of inspiring figures and so on and so forth. The fact that it's so hard to fight against the system that we are living in, but ultimately, uh, politics and, uh, the nation states remain an incredibly powerful force on the world stage.

Fotis: Mm-hmm. 

Sabina Leonelli: Something like European Commission with all of these problems remains an incredibly important site where different cultures, different perspectives, meet and try at least to have a dialogue, right? [01:15:00] Transnational agreements, transnational venues, and meeting organizations. All of this, the very existence is a moment of hope because it means that there is something like the potential to bring together a variety of different people to engender the kind of collective actions, specific ones that may in fact make a difference structurally, rather than just being, you know, something that gets left on the wayside.

And of course, the Trump administration has a perfect exemplification of this. This is an administration predicated on the total mistrust and almost denial of the power of the state. That government should have any role in society. But as soon as the guy into government that they're basically, well, you know, I would say destroying, but certainly affecting society and not just within the US but globally, right?

Fotis: Mm-hmm. 

Sabina Leonelli: So I would say one of the big recipes, and that's something that I'm, I feel very strongly about and I really want to devote a lot of time also in my work doing in the next few years, is for people [01:16:00] to see the importance of engaging with politics. In a way that actually allows you to exercise your learning in science and technology and engaging with society in a broader sense to, to bring together different expertise, but bring them to the political stage too.

Because otherwise we end up with a whole set of people, a whole, in fact, not just one generation, but at least two or three by now. Mm-hmm. Completely disillusioned, who are all amazing people. I meet them all the time, who have the most incredible ideas, have the right motivations, really want to do good for the world, but they're so disillusioned by politics that they don't transfer all of that knowledge, expertise, capabilities, and goodwill into making a difference from society as a whole in a structural level.

And that's a huge issue. If you're that kind of person, you don't vote. It's a huge issue because ultimately, even if you may not have the best choices in front of you, you're not even engaging. You know, with that, with that. [01:17:00] Set up. But ultimately, this is one of the most powerful ones that we still have. I mean, either you go and work for one of the big corporations, you become a CEO, but by the time you get to a leadership position, you can't have that to absorb the business logic of it.

So it's not necessarily the most successful way of changing the world, and it's been tried and tested. I don't really see this working very well. Um, or you actually engage with politics in a way that's a bit more substantive and, and try and, um, canvas and get active and make sure that your intellectual and social ideas also translate into a political reality that you may be happier with.

Fotis: Yeah. I guess people's, uh, concern, and maybe we can wrap this up when it comes to the, this point specific, which is also very irritant, is the kind of, um, irony or the a realization that. Usual ways of doing politics do not work. Protests do not [01:18:00] work anymore. Um, this, um, uh, this is at least like the what is on people's minds and, um, it is way too pervasive.

Um, so maybe this is where the theme of love may come in because there is a, um, maybe we intellectualize politics a little bit too much the same way we over intellectualize science or philosophy. Uh, and, uh, the motivating factors or the stakes, uh, that are involved, uh, are being left out. And I think we are in a way, way too comfortable talking about this aspect of, uh, things, uh, this convenience, uh, and this broader context of convenience.

Maybe were too much in that. And we forget that, caring is hard [01:19:00] won. So I'm, I'm wondering like from your case, um, how would you see, how, how could we, I mean it sounds too patronizing to say like get people to care about things that are important, but I think this is maybe what we have to do and maybe the frustration and guilt that, uh, uh, comes out when I'm talking about these things is part of that.

So Absolutely. Uh, from your end, 

I mean, I would say it is really nice to talk about love, right? Because especially when one thinks about romantic love as a starting point. Mm-hmm. Because that's obviously something that many people will have, hopefully have had some experience of or be familiar with, um, that is clearly something which is maximally inconvenient.

Sabina Leonelli: Right. I mean, there is no love without vulnerability. 

Fotis: Mm-hmm. 

There is no love without the recognition of fragility, of being in complete or not being in control. 

Fotis: Yeah. Yeah. And 

there is no love without, [01:20:00] um, recognizing that you may need something else and that you may not even be sure of what it is, but you may need something else.

There's no love without trust and very often literally blind trust. I mean, you may have some reasons to trust somebody, but really ultimately is a leap of faith. Um, but at the very same time, romantic love, um, is one of the pillars of human existence. I mean, it's one of the most fundamental experiences humans can have.

Sabina Leonelli: Mm-hmm.

Um, and, you know, is very widely recognized to be very difficult, very often leading to enormous tragedy and just heartbreak. Actually always pretty much, uh, because even for people who are very happily together for many, many years, if that's what you like, um, you know, eventually one of them dies.

So. Mm-hmm. Um, but it is is also ultimately such a fundamental recognition of the nature of human life, I think, which is limited, is [01:21:00] fallible. It's, uh, constrained. It ends, it has all sorts of biological constraints in terms of what we can and cannot do. You know, even when we're in our twenties and those of us who are able bodied by most intent and purposes, and living in.

Um, democracies where we can exercise all sorts of different, uh, rights and, and abilities. I mean, even in those moments, there's lots of things you cannot do. You have the body, you have, you have the mind, you have, you have the background, you have. Um, so all of this is a constant lesson into how you can't quite control your environment.

You can't quite predict what's gonna happen. You, you can't, you know, control other people's behavior. 

So love is a wonderful, teacher. 

Fotis: Mm-hmm. 

If one let's it 

Sabina Leonelli: right. 

Fotis: Mm-hmm. 

Sabina Leonelli: It's no surprise that so many people, especially among younger generations now are so alienated, right. In a Marxist sense, from the world because it becomes so difficult to open [01:22:00] yourself up and make yourself vulnerable in a situation where you feel fragility all around you. Right? And you feel like you have to kind of put up a face and a front, because otherwise you're gonna be gobbled up by all these powers to be that are all around you don't quite understand. But they seem to. Just give you no sense of agency. Right. And so I think in that sense,

like, you know, about being in situations where, uh, you're supported.

Fotis: Mm-hmm.

Sabina Leonelli: Especially as younger people in making a direct connection. That's something a philosophy is good at.

Fotis: Mm-hmm.

Sabina Leonelli: A direct connection between your lived experience as a human being who has family relationships, um, who has love affairs, who has engagements at the social level, but also as a human being who's intellectually engaged, who is asking questions, who is recognizing that you don't know things, you know, so you're making yourself vulnerable intellectually and therefore looking for answers in the sciences, in technology, in this kind of things.

And also as a biological [01:23:00] being, which is pled with not being able to breathe well because your city's incredibly polluted, not having good access to medical care because there's serious problems with medical assistance in many countries. Um, not being able to take advantage of green spaces because they're taken over by uncontrolled urbanism, you know, and not being able to access, mountains or, or

mm-hmm.

The coast because too far away is so expensive and all of those kinds of things. I mean, all of that, and of course being subject to climate emergencies of all types, which by now is, is becoming a common experience for almost everybody on the planet. I mean, all of these identities and all of these different kinds of vulnerabilities really are all interrelated.

Fotis: Mm-hmm. 

Sabina Leonelli: Right. And I think that's what is creating so many problems that, um, is almost like people think that you can acknowledge your vulnerability as, you know, a scorned lover 

Fotis: mm-hmm. 

Sabina Leonelli: And find solutions for [01:24:00] that vulnerability in technology, for instance. Right?

Mm.

Or you can acknowledge your vulnerability as somebody who suffered the flooding or a wildfire.

Yeah.

And find solutions for that, again, in technology or innovation. Right? Well, in fact, knowledge and understanding science is also a type of vulnerability. You're opening yourself up to a different way of knowing, and, and it's a question of engaging with it in an open way, rather than just saying, oh, I have a problem in a part of my life and I'm gonna go and look for easy solutions somewhere else.

And if they don't work, then I'm gonna get upset. Right. I mean, it's, it's, it's having a more organic view of the fact that, um, you know, if you feel like you have a problem, it means that you care. You care about yourself, you care about somebody else, and that's the leverage. That's what you need to use. To then foster your engagement in, in all those opportunities we have to learn and to, and to do things in society, uh, rather than the other way around.

So I suppose caring, [01:25:00] you know, it sounds very abstract, but for me it works in my own life also. I mean, caring starts from acknowledging the fact that you have needs and, and you have things that you're unhappy with and you have problems. And using that to engender forms of care in all the aspects of your life.

Fotis: Yeah, yeah, yeah. So we have, uh, some wonderful, things to take home from this. Uh, we can have control in this complex natural world that we're in, that we're embedded in, things are transient, do with it, um, that you never work alone. And we need to feel inconvenient, I guess, In this, uh, context of convenience, so, exactly.

Thank you so much for having, giving this space to have a, a different kind of conversation. 

Sabina Leonelli: Well, thanks a much to you, Fotis I mean, collaborating with you is one of the joys of the job, so thank you.