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S3 Ep 12 - Sabina Leonelli on 'The Philosophy of Open Science'

Episode Transcript

Hello, Samara Greenwood here, and can I say a warm welcome to our final episode of The HPS Podcast for season three. For today's episode, I have the pleasure of bringing you a wonderful conversation with another one of our leading scholars in HPS, Professor of Philosophy and History of Science at the University of Exeter, Sabina Leonelli.

Sabina has such an extensive list of accomplishments that I don't quite know where to start, so I'll simply say that from September this year, Sabina will hold the Chair of Philosophy and History of Science and Technology at the Technical University of Munich, where she will co-direct a new public science lab and the Ethical Data Initiative.

Sabina also recently released a book in the Cambridge Elements Philosophy of Science series on the philosophy of open science. In this book, Sabina offers a stimulating perspective on open science, discussing both its strengths and some of its unintended downsides, including constraining academic diversity and worsening epistemic injustices in some cases.

Today, Sabina talks about her own wide-ranging experience with open science initiatives and the shift in perspective she would like to see across the open science movement towards ensuring more effective and responsible research outcomes. As Sabina covers so much fascinating ground, we decided to break our usual rule of ‘all episodes should be around 30 minutes’ to bring you this slightly longer conversation.

Samara Greenwood: Thank you so much, Sabina, for being on the podcast.

Sabina Leonelli: Thanks so much to you for having me.

Samara Greenwood: Before we discuss the philosophy of open science, I'd love if you could tell us a little bit about your background. So how did you end up in philosophy of science?

Sabina Leonelli: I am half Italian, half Greek by origin and I did most of my schooling in Italy. When I was already a high school student, I was very interested both in philosophy and in the sciences. I had absolutely no idea that such a thing as philosophy of science existed. But I was lucky enough to be admitted in University College London for my undergraduate. I ended up moving to London when I was very young, and just really by chance ended up in the history and philosophy of science department, it was kind of a science studies department, because it attracted my attention, it looked like something I'd be very interested in. And indeed, I got hooked on the subject then ended up staying in that field as I progressed through studies and my career. So, it was relatively easy, or at least it looks easy.


Samara Greenwood: Wonderful. So today we are going to talk about your rich work on the philosophy of open science, as you've outlined in your Cambridge Elements book of the same name. I was hoping you could start by telling us first, as a bit of background, your understanding of what the open science movement is all about.

Sabina Leonelli: Open science may be a relatively new label, but the underpinning idea, of course, has been with us throughout the history of science. The idea that what makes scientific research is the fact that it's not dogmatic and it's not dogmatic insofar as it's ‘open’ to input from whoever may be interested in understanding how that knowledge is produced and wants to provide feedback and scrutinize what is happening.

One can say that the concept of openness, in the sense of being receptive to scrutiny and willing to engage with otherness of any sort, is really the constitutional part of what differentiates scientific knowledge from other types of knowledge.

In that sense, the idea is very old. Of course, in the last 50 years especially, we've seen strong emphasis on the Open Science Movement. That has come about as a reaction to what has been an increasing commercialization and commodification of academic research, in particular. Also, of research happening in the private sphere, where people have started to realize that because of all the different ways in which we end up publishing in academia, many of which are governed by commercial publishers, it makes it difficult for people to access those publications and those results outside of very restricted circles. Also, the ways in which research has been commercialized more generally, where we have a lot of industry that sponsors excellent research, but very often does it in a way that is not open to the public. It is not clear, not only exactly what knowledge they're producing, but even on which topic they're working, right?

There has been this growing perception that science is not at all as open as we would wish it to be. And, this is having repercussions on the quality of the research that is produced and on its public legitimacy: the extent to which people actually trust the processes used to produce science, the methods, the procedures, and also the interest and the values that are at the heart of science. So, the open science movement has been born out of the wish to try and rescue research from this situation and make sure that this idea of openness is really placed back into the core of everything that we do as researchers, as well as the role that science has within society more at large.


Samara Greenwood: Then in your book, you discuss some key challenges you see for open science. Could you briefly tell us about some of these challenges?

Sabina Leonelli: One of the main challenges that many people now are very critical about, and rightly so, is the fact that the open science movement, with all its very good intentions as I described them, has arrived in a very crowded institutional arena.

Science already is institutionalized in very particular ways, through very specific academic setups, which respond to rankings and evaluation with very specific systems of publishing, which are already very fixed in place and very, very strong lobbies.

Also the particular ways in which we as academics have ended up managing our workday, the ways in which scholarly societies are set up, dependencies that exist between private money and commercial money coming from publishers and what is actually happening in the world of publicly sponsored research.

With open science arriving in such an arena, unavoidably, the ways in which it gets itself institutionalized, as it gets picked up by policy and made into specific regulations and guidelines, is affected by this setup. So, there is now quite a big gap between the ideals of open science, the intentions, the motivations, what people would like to achieve through the open science movement, and the way in which it is sometimes instantiated.

On the one hand, it's great that many governments, many science organizations, many national foundations have picked up on the idea of open science and tried to implement it, for instance, through open access mandates and open data mandates. On the other hand, because it has been institutionalized in a situation where commercial publishers are still pretty much ruling the ways in which they're thinking about scholarly publishing, and there are all sorts of tensions coming out of the financial pressure on scientific institutions and academic institutions.

This creates tension between what the values are of openness and open science and what the practice and implementation looks like.

For instance, there is a strong desire to try and make methods, data and models, and code even, open and openly accessible. But to do that just by putting everything online is very problematic. We know that takes a lot of work and a lot of time and a lot of skills, especially now that we are living in a very large digital transformation of research. Everything needs to be done through computers and through the ability to have access to those infrastructures and also know how to use them. In a situation where the world is already split in what we usually call ‘the digital divide’, some people have access to high-level cutting-edge infrastructures, others do not, some locations can work with those infrastructures, others do not.

Just telling people, ‘Well, to do science better, you should just put everything online and how you do that is pretty much your problem’ is not really going to resolve the issues of open science. If anything, it risks exasperating issues of inequity and issues of discrimination and lack of capacity to do some of this work that already exists in the field.


Samara Greenwood: You discuss some of these unintended consequences in your book, particularly of large-scale open science initiatives, in the way they might disrupt, dismiss, or even dismantle valuable research practices that have developed in differing locations and even across different scientific disciplines. Could you tell us a little bit more about that?

Sabina Leonelli: Philosophers of science will be very aware that to be able to work together, to collaborate, to exchange materials, we need a minimal number of standards; things that we agree on that serve as common ground, common background knowledge, common classifications, keywords, things that people can recognize around the world and use as a platform to exchange information and scrutinize each other's work. This is where some of the most fascinating work starts for open science because it's really a question of delving deep into scientific practices and thinking about, what is the common ground? Do we have some common criteria for what may count as best practice in different fields? Do we have some data formats or data classifications that may actually work for the whole of science? This is all absolutely fascinating for us in terms of thinking about, can there be even something like a general underpinning epistemology of science, right? It's such an important question for political science at the moment.

At the same time, we also know, and we know from history, that this constant attempt at trying to standardize, trying to provide this common background, also risks trumping system specific knowledge that is developed in particular locations, in relation to particular problems, particular goals, and particular materials that people may have available to them. If you throw into this mix the question of power differentials, when some locations have the resources to set up amazing infrastructures and wonderful standards that work for them, and very often with very good intentions, try and provide the resources also to others, there may still be a mismatch between what say, Harvard or Cambridge decide maybe the best standard for a particular subject, a particular domain and what people in very different locations, who don't have as much visibility and don't often have the opportunity to sit at the same table to try and make the decision together, may think those standards are.

So, the big issue at the moment is trying to think about what the sweet spot is between having a minimum level of standards that can work for people around the world, that can enable the setup of this wonderful infrastructure we could have, and in some cases do have, to exchange information adequately. But at the same time, do it in a way that takes account of the reality of a variety of different ways of working within the sciences.

This is what we usually call epistemic diversity, or sometimes pluralism, within the sciences. Also, the variety of different kinds of expertise and knowledges that are useful to scientific research, often produced by expert citizens, people who work in agriculture, people work in forestry, people who work in nature conservation, for instance, who have a lot to offer to scientific research, very often are involved in scientific projects, but are even more distant from the making of these very specialized technical infrastructures.

A good example of all of this is the situation in Europe, where there's been a lot of investment by the European Commission and various national governments in providing infrastructure that can really work for everybody, not just made for the one community in France or in Poland or in the UK, but actually accessible and usable and providing help and support to people around the world, which is very important. In a sense, one could argue this is exactly what rich places, which have the capability to build this infrastructure, should be doing. At the same time, as you can imagine, because it's so difficult to make these infrastructures, it's so hard to try and deal with the standardization problems, there is a tendency to, even when you do consultations, even when you try and put them together with a lot of different inputs, ultimately make decisions within very particular circles of people who have the time, the opportunity, the ability, the skills to participate in those discussions.

So again, we see a situation where there is a strong tendency, which is completely understandable, to trump local knowledge and disregard the reality of minority people involved in science or parts of science that maybe are not that visible or not that popular right at the moment, in favour of trying to support research that is perceived right now by some actors in the field to be the most important thing. In biology anything to do with molecular biology, for instance, and to disregard a few that are a bit more difficult to deal with. Partly also because their materials and their knowledge is more complex, for instance, in developmental biology or work in physiology. Because the idea is, ‘we have to start from somewhere and then we start to build up these infrastructures and then pick up feedback’.

But I think, for philosophers of science, because we have done so much work in understanding how important it is to provide an equal voice at the table, at the very least, to various perspectives and different ways to understand and make knowledge within the sciences, this does create a tension and a problem.

The more we standardize, the more we accelerate the process of making it possible for people within certain domains to communicate their knowledge, the more we potentially push away participation by people who are using different types of data formats, for instance, or maybe are not as digitalized and not using as cutting-edge technology as others.


Samara Greenwood: It really is such a challenging situation, isn't it? Do you have any further examples or case studies that might help our audience understand your critique in some more concrete ways?

Sabina Leonelli: For instance, one of the areas that I'm mostly busy with is thinking about plant science, crop science, and research that has to do with agriculture more generally.

This is a typical situation where there are wonderful efforts that I've been involved in and engaged with for many years now, such as the so-called ‘crop ontology’, which is a group of people who bring together various communities - a community of practice - from data science, from plant science, from crop science, but also from policy organizations, from representatives of farming organizations, also from smallholders and industry to try and think about what the best ways are to classify nomenclature around the traits of plants. So, how do you describe a leek? How do you describe the colour of a flower? How do you describe, for instance, the taste of a particular fruit or a particular vegetable in a way that is both useful to continue to study those varieties of plants and to understand how best they can be grown? This is particularly important, especially now that we are living through a huge moment of climate change.

So, it's very, very crucial that we try and use scientific research to support an agriculture that can adapt to a variety of different environments and rapidly changing environments around the world. This effort is then done by trying to really bring together voices from the different territories that are affected. People who have expertise that come from perhaps centuries of their families and their communities being involved in cultivating particular plant varieties, into actually thinking about these classifications.

This effort is wonderful because it's really meant to flank and support and complement more traditional taxonomies. Like the Linnean taxonomy, which is very much grown through a tradition which maybe takes less account, certainly in the last 200 years, of local knowledges and indigenous knowledges, and instead thinks about parameters that could be used straightforwardly by say, evolutionary biology to try and think about the conservation of particular traits or to feed into discussions around the use of genetic modifications to develop plants. That is fully understandable, but it is great to also have classifications that are developed in a way that's different.

At the same time, what is happening, even in efforts that are so well made and really trying to be inclusive, is that ultimately, they provide a platform through which all of these different organizations can donate more data, more information that is privy to their own community and their own ways of working. So, we have a situation where farmers offer up a lot of data around their cultivations and their fields, which can feed the effort to try and understand better how plants are grown locally. Organizations on the ground, NGOs, civil organizations also provide information around the conditions under which plants are grown, also the market conditions. Scientists working on the ground offer their expertise in local entomology and local climatic conditions, and all of this then gets complemented and added to what we already know coming from molecular analysis of the plants, analysis of the so-called genetic resources, which are extracted from these locations and so on and so forth.

Once all that material is online, the fact that it's been done in a way that's very inclusive can actually become a double-edged sword, because then the question becomes, ‘okay, so who has the capacity to benefit from all of that knowledge?’

Who can go into the databases that we produce and then use it to produce new varieties and products that can be of use to farmers and can actually help to realize this vision of agroecological agriculture that we have underpinning this effort? This is where the problems arise, right?

Because ultimately, we look around and we realize that there's only certain companies and institutions in the world that tend to have an almost monopoly on the ways in which agricultural innovations are developed. And they tend to be the ones that benefit the most from these kinds of infrastructure.

This is partly because of the way in which data systems end up being set up and it's partly because of the power dynamic and the commercialization of research and the neoliberal market environment we are living in. So, this is a practical example of how an open science effort, which I've also been involved in, which is hitting all the right boxes in terms of what we may regard as a constructive inclusive pluralism from the get-go, actually may end up being instrumentalized in ways that don't serve the communities that have participated in them to start with.

So the big effort, I think, for open science developments at the moment is to try and tackle examples like this and think, ‘how do we set up these infrastructures, the classification systems, the ways in which we think about methods, in a way that actually valorises the contributions of the people who have actually provided knowledge that can be used to that effect? But also provide a better way to govern these processes so that we can decide what the best use is for this material, what kind of research actually serves the public interest?'

There needs to be a more democratic discussion about what that public interest looks like, rather than leaving it in the hands of the private sector or this kind of mixture of public and private partnerships that always end up driving towards the commercialization of particular innovations.

I hope that's a little bit clearer with this example.


Samara Greenwood: Yes, that's a fantastic example, taking us through the whole process where you can see at the start, those real efforts coming from the best place, being inclusive, incorporating multiple perspectives, but still the end result can end up being not what we would hope.

Sabina Leonelli: Another quick example that people would be very familiar with is talking about COVID 19. We've all gone through sadly, the pandemic. I think everybody will be aware there has been a huge effort, and also one of the things that really pushed the open science movement, to share data around the mutants of the virus.  So, we have a sharing of the genetic sequences coming from mutants collected all over the world, which is really important to try and track a mutation that was dangerous. Also, it was really important to try and produce some of the responses, not least the vaccines that now everybody has used to defend themselves against COVID 19 in its more virulent forms.

At the very beginning of doing this research, these open science efforts were accompanied by a series of agreements, which were very much in principle agreements, around the world to try and make sure that the innovation that would come out of the vaccines would in fact be shared back with the different countries that actually offered information and results towards those efforts. As people will be aware, this just did not happen.

The moment in which the vaccines were appropriated and produced by big companies it ended up being very big business and many of the promises made to then distribute these vaccines in a way that was equitable, to make sure different locations in the world had access to the same types of vaccines, absolutely did not work. Many places were stuck either with very little access to vaccines because they couldn't afford it or access to not the best choice of vaccines, let's put it that way.

That is an example of how, as research goes through the cycles of commercialization, the ideals of open science can become disruptive.


Samara Greenwood: In your book, you then offer an alternative philosophical approach to open science to help address some of these concerns. Could you tell us some key features of this different philosophical standpoint on open science?

Sabina Leonelli: So my idea, based on many years of following up on these initiatives and seeing what works, what doesn't work, what works so-so, is to try and direct attention away from the idea that being transparent and making science amenable to scrutiny simply means putting everything online, making sure that everybody can access absolutely all the information that's produced about science at any moment; from the beginning, from the research design, all the way through its realization, and then its use, and then we're done. Because there is a lot of open science that operates almost on this premise. The fact that you share things, you make it available to others, but it's up to others to see whether they want to pick up on that information, do something with it. Basically, you've done your job, now your science is open, and you can rest assured that good things will come of that.

My argument has been that this is really not working because, ultimately, what really makes a difference in terms of people giving each other proper scrutiny and helping each other out to strengthen scientific research and make it more reliable is forming connections between different groups. This is sometimes very long standing, very often based on trust and understanding of each other's methods and each other's materials. This then allows you to scrutinize properly what somebody else is doing, but also with some understanding of what is actually happening there and how those efforts can be best interpreted, and then maybe redeployed elsewhere.

For a lot of the Open Science Initiatives I have been following which work like this, what has happened is that you end up building a relationship between, say, a particular set of infrastructures, a particular set of researchers, a particular set of communities that are interested in using the information to produce knowledge, and out of those relationships, you actually get a very meaningful result, which is the production of robust and inclusive knowledge. But when those relationships are absent, where you don't put effort into building up links and bridges between humans involved in all those efforts, then you end up in trouble because, sooner rather than later, you get in a situation where the information you're trying to share becomes completely useless, decontextualized, and it becomes almost impossible to assess its quality, to assess its meaning, and to try and recontextualize it in a way that makes sense, given your research purposes.

So, what I've been recommending is to reform an idea of open science around what I call judicious connections. This means putting the human at the centre, thinking about what kind of relationships you want to build, between which groups and for which purposes. Asking who is actually being favoured by building those relationships and by building those capacities and who is being discriminated against? Accept the fact that there's always going to be discrimination in the system. You are always going to be prioritizing some communities over others and so you might as well really think it through and be explicit about who you're favouring and who you aren't and do it in a way that is judicial.

Take account of those discriminations, take account of those rankings of priority, and really be explicit about those so that we can build a system which is directly geared towards building trust between particular actors in the system, and where sharing and decisions about what to share and when, come out of those relationships and those interactions, rather than being the starting point on which those relationships are supposed to be built.

Very often, the very act of sharing will actually alienate some potential users and some communities involved in those efforts, as we've seen again with the COVID 19 pandemic. There has been some researchers that became very wary of sharing their results on the global stage because they were worried that those results would then be picked up without any recognition, used by others, and potentially even used in a way that would be damaging to their own community.

So that is why I am trying to push for an idea of open science which is based on this very, very basic understanding of openness as a relationship. Everything else, policies around reproducibility, policies around minimal standard for quality, all of that needs to follow from building those relationships rather than being the starting point for building relationships in the first place.


Samara Greenwood: That's excellent. Did you have any examples of those cases where they are working well?

Sabina Leonelli: For instance, we have situations where there has been work over many years, especially in epidemiology, where people have tried to collect medical information, to do it for discovery, but to do it also in relation to groups of patients and medical workers and people working on the front line of medicine in hospitals. This is not actually normally done in biomedicine. A lot of research is done beyond engagement with those communities, but in some cases, it has been happening.

For instance, in rheumatology we see a lot of examples where there have been efforts to try and bring patient groups into discussions around what kind of research was being done, what were the best directions to take for research, what kind of data should be used and how should it be interpreted. Once you have those relationships in place and you have venues and platforms and infrastructures that allow you to continue to have those consultations regularly, they can become extremely fruitful.

At the moment when the pandemic hit, for instance, rheumatology was one of the first fields that actually managed to bring together patient communities to try and investigate the effects of long COVID and try and think more strategically about not just what do we do in the first few months of the pandemic, but how is this potentially going to affect our patient communities going forward? What are the kinds of treatment that we should be thinking about developing so that we can address those problems of the immediate to longer term future? How do we collect feedback from patients, from the people who are impacted directly by the pandemic, so that we make our medicine better?

So, there are examples of this happening, and there always have been in the sciences. Unfortunately, they don't always tend to be the examples that are best rewarded because we still live within a system of scientific incentives that doesn't necessarily recognize community effort, doesn't necessarily recognize service, and engagement activity, as being integral to cutting edge research.

If you live in a system where the only thing that's rewarded is impact factors and publishing a lot of papers in the highest-ranking journals, then all of those efforts to build up communities, build up relationships, don't necessarily get recognized or valued.


Samara Greenwood: How do you see this alternative approach to open science working in practice, and perhaps both at a small scale and at a large scale as well?

Sabina Leonelli: Yes, it needs to be implemented at a variety of different scales all at the same time because of course, we are looking at an extremely complex system, which is one and the same with the general market system that we see ruling the world at the moment, and of course, the political situation is also extremely important and very tense. So you need to work at a variety of scales.

What we are doing with my group is we are working with policy, so at the very macro, high level scale, both at the international and the national level. We participate in consultations around transnational agreements, around data governance, for instance, and around the implementation of open science.

We participated in the consultation around what then became the UNESCO Recommendation for Open Science, which is very important because it provides policy guidelines for everybody around the world and is now being really set to look at inclusivity and diversity in the open science landscape as one of the things that needs to be put at the centre of open science activities, which I think was a big victory in terms of thinking about this transnational level.

You need to work at the national level of policy also because, ultimately, this is where policies are implemented. At a transnational level, they give you guidelines and give you directives, which hopefully make a difference, but really, the game is played at the national and regional level. So, lots of consultations with national governments, which we have also been doing with the European Commission and lots of specific national governments in Belgium, in Canada, in the U. S., and so on, to make them think through what different strategies could be for open science activities, both in terms of how the research system is funded, and so thinking about the structure of funding agencies, but also the ways in which the research system is assessed and rewarded. Thinking, for instance, in the UK about the shape of the so-called Research Excellence Framework, which is the exercise that we use in the UK to evaluate research every six years or so, and then give money to universities according to how well they've done in the previous period.

This is the macro level. Then, what's even maybe more important for me, especially given what I believe in, in terms of judicious connections, is working with particular communities at the micro level, really thinking through specifically for this particular domain, for this particular set of materials, how do we think about sharing criteria. How do we think about ways of getting other people to interact with that knowledge and benefit from that knowledge without, at the same time, undermining the very research efforts that are being carried out?

As part of my project, we have various different case studies. We are working with people mostly working in the plant / agricultural research, but also some case studies in medicine and citizen science. We are working with very particular communities on the ground and exploring through qualitative methods, what are their challenges? What is the situation on the ground for them? What do they want to achieve scientifically and how can we support and give voice to those concerns so that they're heard beyond those particular locations?

Making them more visible at this kind of higher scale of work where people are looking for case studies to think about how can one think about open science differently.

So, all of those things need to be put together at the same time all the different stages.


Samara Greenwood: One aspect of your work that really stood out to me was your emphasis on understanding that the goal of research is not only to produce effective knowledge (so knowledge we can do something with) but also responsible knowledge, knowledge that works for the benefit of all, not just the individual. It then follows that the epistemic and ethical components of scientific practice should always be considered together.

I was really struck by this point. It just hit at the heart of something that I've long felt and really enjoyed about what the HPS perspective brings, but really struggled to articulate. I was hoping you might tell us a bit more about this aspect of your thinking.

Sabina Leonelli: Yes, thank you. For me, that is really a basic tenet of everything I do.

I see it all the time, that keeping considerations that people may associate with ethics or with social implications of science and technology separate from thinking about questions of methodology, research practice, and how do we actually get to the truth, to do good scientific work, is not only problematic but downright dangerous for the fabric of science.

In most of the cases I'm working with, it's very, very hard to disentangle what it means to do responsible research from what it means to do reliable research. So arguably, if we want to have a good grip on how to understand agroecology and understand the ecology of particular territories so that we can tackle climate change, then making sure that we have different types of perspectives and different types of knowledges included in a conversation is absolutely crucial.

If I go to a particular location in Ghana and I look at the territory, I look at the landscape and the soil, the plants that are cultivated there, I take samples, and then all I do in terms of producing knowledge is I sequence those samples and produce molecular information about the chemical composition of what is happening there, the organic and non-organic components of it, that's just partial knowledge. It will give me something. It will allow me to produce some innovations. Maybe I can produce a novel type of fertilizer that actually is inspired by the particular chemical compounds that are found on the ground. Or maybe I can use it for pharmaceutical purposes. I can find another plant compound that actually has therapeutic uses.

But it doesn't necessarily give me all the information, the kinds of knowledge, that I need to understand the ecology of the territory better. I need more types of knowledge for that. I need other disciplinary approaches, and I need information that also comes from outside the scientific environment itself.

Now, many people would regard those kinds of inclusive practices as something which belongs to the realm of ethics. ‘We're going to think about that when we have time, but really what we want to do is to get on with the science and make sure that we apply our scientific methods well.’ The message that certainly comes from my research, and I think many of our colleagues are saying very similar things, is:

No, actually, if you want to produce the best possible, most reliable knowledge you can have about all sorts of different domains, questions of inclusivity are absolutely at the core of that. They are not just an ethical afterthought; they are not just context for the work that you are doing. They are actually seeping through what you're doing through and through.

Samara Greenwood: My final question was, I was wondering what kind of further research you would like to see in this area. So where would you like to see philosophical work on open science hitting in the future?

Sabina Leonelli: I think it would be great is to have people who get more interested in what kind of science is being done, in domains that maybe are less visible or less popular.

A lot of the work in philosophy of science is now slowly changing, but a lot of the work has been on research that takes place within very well-equipped labs, with a very particular idea of what may constitute best practice within those domains. Partly also because we are funded by the same scientific system, of course, so there is a tendency to do investigations on very cutting-edge fields and technologies, which tend to be hyped at a particular moment. We've seen this happen with genomics in the past. Now we see this happening very clearly with artificial intelligence, where there's so much money being thrown at that field. So, a lot of philosophers of science are looking at what is happening with machine learning. What are the latest opportunities with neural networks and so on and so forth.

Now, of course, I'm not saying that this is not important work, but it would be very useful, for those of us who can, to flank that kind of work with research that looks at different domains. Domains that may not be as digitalized, may not be so dependent (or not yet anyhow) on AI developments, but actually also provide very important knowledge and maybe a different reference point for what scientific research is supposed to look like in the first place. Things like community efforts, things like interdisciplinary research.

These are much more difficult environments for us to look at, but what I would like to see is much more effort from us, as a community, to think with those different cases and really try and bring together a different vocabulary, a different set of terminologies and philosophical tools, so that we can properly highlight and discuss this type of research.

I think this is also very important for the rest of society because very often I find myself giving presentations to a variety of different audiences. It can be a little community in one of the villages next to my parents’ house in Italy, or it can be the European Commission, or it can be the National Science Foundation in the US, and the question that I often get asked as a philosopher is, but how do we discuss these questions about inclusivity, about data intensive methods, about open science, in a way that doesn't get as limited and constrained by the framework that we've used and developed over the years to do this, which we know is problematic?

I think, as philosophers, it would be great if we can create a community that can provide some of those answers, or at least provide some support to think about how we use language and how we reason through the huge diversity of ways of doing research, which needs to be recognized and valued by institutions.

Samara Greenwood: That's a great place to finish. Thank you so much Sabina for being on the podcast. It has been a real honour to hear you talk about this topic that's so important and so fascinating too.

Sabina Leonelli: Thanks so much to you.

Thank you to everyone who has tuned in for Season Three of the HPS podcast.

That was the final episode for this season, but we will return later in the year with Season Four. In the meantime, if you're interested in the detail of today's conversation, you can access the transcript on our website at You can also stay connected with us on social media, including BlueSky for updates, extras, and further discussion.

We would also like to thank the School of Historical and Philosophical Studies at the University of Melbourne for their much-appreciated ongoing support.

And thank you for joining us in the wonderful world of HPS once again.

We look forward to having you back again next time.


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