Orchestrate all the Things - Data Rules: From interoperability to commensurability. Featuring "Data Rules" author Jannis Kallinikos

Episode Date: July 1, 2024

"Data Rules" is a book about data, but not just about big data crunching. A book about the relationship of data with economic institutions and society, but also about the interplay with data technologies by which data are being generated and processed. A book that is critical, but not ideological. This is how Jannis Kallinikos describes "Data Rules: Reinventing the Market Economy", a book co-authored by himself and Cristina Alaimo and recently published by The MIT Press. Jannis Kallinikos is Full Professor of Organization Studies and the CISCO Chair in Digital Transformation and Data Driven Innovation at LUISS University, Rome. This is where we met to talk about the key concepts in "Data Rules": Understanding data generation and useHow data is breaking boundariesPlatforms and choiceThe illusion of objectivityAlgorithms, agency and surveillanceFrom market and design rules to data rules Article published on Orchestrate all the Things: https://linkeddataorchestration.com/2024/07/01/data-rules-from-interoperability-to-commensurability/

Καλώς ήρθατε στο Αρχιστήριο των Πορταγών. Είμαι ο Γιώργος Ανατιώτης και θα συνεχίσουμε τα πράγματα μαζί. Στοιχεία για τεχνολογία, δίδα, AI και ΜΕΔΙΑ και πώς μπλούν σε έναν άλλο, σχετικά με τις αυτοδοχές μας. Data Rules είναι ένα βιβλίο για δίδα, αλλά όχι μόνο για τα μεγάλα κράντζα δίδα. Ένα βιβλίο για τη σχέση των δίδας με οικονομικές εταιρίες και κοινότητα, αλλά επίσης για το αντιπροσωπικό με τα τεχνολογικά δίδααια από τα οποία τα δίκαια γεννιέται και διαδικασίζονται. Ένα βιβλίο που είναι κριτικό, αλλά όχι ιδεολογικό. Αυτό είναι το πώς ο Ioannis Kalinikos σχεδιάζει τα δίκαια,

αναπτύχοντας την οικονομική του μάρκετ, ένα βιβλίο που συνέχισε από τον εαυτό του και την Christina Aleimo και που πριν έφερε στην πλατεία της MIT. Ο Ioannis Kalinikos είναι ου professor of organization studies and the Cisco Chair in Digital Transformation and Data-Driven Innovation at Lewis University, Rome. This is where we met to talk about the key concept in data rules. I hope you will enjoy this. If you like my work and orchestrate all the things, you can subscribe to my podcast,

available on all major platforms, my self-published newsletter, also syndicated on Substack, HackerNin, Medium, and Dzone, or follow Orchestrate All the Things on your social media of choice. I'm a professor here now in Louis, the last four years of my life, where I teach and do research on matters related to technology, the connection of technology with society and with economic institutions. But this line of research goes back many years when I was professor at the LSU from the year 2001 to 2021, roughly, where I resigned to get this position here at Lewis, and where I have done a lot of work, research. Several of these matters published a number of articles,

that's what we academics usually do, and these articles are articles in scientific journals, in other particular. I've written several books and participated to some degree or another in public debates. So my predominant orientation has been contribution to what we may call scientific discourse. This is a short story of mine. I was born in Greece, in a liberal town of Greece. It's called Preveza. It's a nice place to be. Where I grew up, I went into the high school and then I studied in Athens before I moved και μεταφέρασα στην Αθήνα, πριν μεταφέρασα στην Σουηδία, όπου καταφέρασα την ΠΑΤ από την ΙΟΠΣΑΛΑ,

το οποίο οι Σκανδιναίοι ονομάζουν το Cambridge της Σκανδιναίας. Είναι το πιο παλαιότερο και πολύ προστατευτικό σημείο για το μάθημα. Θα πω ότι η ευκαιρία για την συζήτηση του σήμερα είναι η πραγματικότητα ότι μόλις έφερα το βιβλίο, the occasion for having this conversation today is the fact that you just published the book, which in many ways touches upon what has been the main theme for this podcast as well. So data and by extension everything that people do with data and for data. The book is called Data Rules. It has just been published by MIT Press, if I remember correctly. Yes, that's correct. And would you like to just share a few words about what actually drove you to write this book? When did it start? Your co-author, because I know you didn't write it on your own. What

has been the process that led to...? It's important to point out that this is a book co-authored with Christina Lyman. It has its own history to some degree, an offspring of some of the things I've done in my life previously and some of the things also Christine. We started writing of this book with no clear idea of where we should go. We wrote thoughts around the importance of data and the way data impregnates social and economic relationships. How they shape them, how they are the outcome of these relationships, economic and social, and how they fit back on these relationships and change it. And we thought that one of the reasons we felt

that we drove us to write this book was that we were a bit unsatisfied with the ways these things have been debated in the literature and in the public discourses. Sometimes simplified, sometimes polarized, like the issues of surveillance, for instance, and privacy, sometimes without really taking the time to dig in into the particular details of how this society of ours and the technology we use work. One example is, for instance, the work of algorithms, which is used in abundance.

But God knows what people mean by this thing. I have a very clear idea. We write also in the book, juxtapow's Data to Algorithms, and we're probably going to speak about it, but it's just one example of how uncritically many of the trends that are characteristic of our society, how uncritically they have been picked up and been used and reproduced, and this was a kind of dissatisfaction that drove us to writing this book. We had the idea of presenting a book in which the idea of data was not just big data crunching,

the relationship of big data not only with economic institutions but also with the wider society and describe some of these relations that we thought are very closely associated with the work on data the technologies for which data are being generated and processed and some of these changes i hope we're going to speak, but just let me mention for your audience, have to do partly with the emergence of platforms as a particular types of economic entities and also the separation of private life and the home from the wider institutional life. They come now back together in a way that deserves particular attention. These were some of the broader motives.

There was a history, to summarize, there was a history on how these things have been approached by me and by my co-author, Christina Lairo, but also in some dissatisfaction that we thought we had the knowledge to at least clarify in some words. Okay, so it sounds like if I were to pick one word out of everything you said to characterize the essence of the book, that would probably be critical. You take a critical viewpoint on the use and on the origins of this whole data culture, let's say. I would agree, George, with one

reservation. We are not ideological, we are critical. The two things are separate. There's a lot of writing against this trend, which has a very heavy ideological mark. I am not an ideologist. I'm a social scientist. The critical one, still, I understand, is to present reasons to show the people that είναι να παρουσιάσουμε λόγους για να σκεφτούμε από τους ανθρώπους που θέλουν να μάθουν για αυτό, πώς είναι τα πράγματα όπως είναι. Κάποιες από αυτές οι λόγες είναι συνδέοντα με τις πριβολές, αλλά όχι όλες. Είναι μια κατασκευή που είναι ικανή να κάνω, γιατί καταλαβαίνω ότι το όνομα «πριβολές» έχει κάποιες συμφωνίες,

να πούμε, που μπορούν να οδηγήσουν ταθρώπινα να πιστεύουν αλλιώς. Είναι σημαντικό να το καταλαβαίνεις. Ευχαριστούμε. Η ερώτησή μου είναι ποιος θα βοηθήσει το πιο πολύ από αυτό το βιβλίο και ποιος είναι ο πρωτοβουλίος σου με αυτό το βιβλίο. Αυτό είναι το όνομα των Αμερικανών, το 1 διπλόμιο ερωτήματα. audience with this problem? That's what the Americans call the one billion question. Yeah, I think the primary audience should be academics across the fields of management, sociology, organizational sociology, social psychology, media and communications, information systems, and presumably some of these fields we call data science and statistics.

So about the latter, I don't believe so much. So this would be the audience. Academics spread all over these fields but we also intend to address all people that are educated and have an interest in understanding where this society is going. How can all these changes be understood, summoned into a framework, analyzed and understood. So, and that is something that goes beyond academia and I think embraces people with some level of course of education, but which are widespread in society and do not need to be academics and they aren't academics.

This is a second audience which we hope to reach. For this reason, some of the writers of this style of writing is still an academic one, but it's simpler than articles we publish in academic journals because it has this A. Now, I can also say some of the people that can benefit from such can also be leaders in critical positions, whether in governments or in particular in economic organizations, because they are obviously leaders too. To understand what's the role of day, how technology makes the production process itself? What is changing here if they are to make informed decisions for themselves and by extension for society, for economy and society? I think you just summarized what I would gather as the approach of, the intended approach of the book in terms of making an impact because at the end of the day, in my mind at least, whoever writes a book, the primary result of writing the book will be making an impact. that would probably be what some people call influence the influencers so you're not aiming

directly for the man on the street or the woman on the street but mostly for academics and let's say opinion makers vote leaders whatever you want i think it's a good description of wow yeah of the audience of the book yeah It's a very large audience. It's an international global audience of, I would say, millions. All right, so let's start getting to the core of the book, but in fact, I think before we do that, I think it would be good to read some of the core ideas of your work, because in my mind mind they probably underline they form like a foundation for everything else you've laid on top in this group so i'm not going to lie i wasn't familiar with your work previously the little research i did have the chance to do two

key concepts came out one was the information gravity and information habitat and the other was the theory of digital objects. You are the best person to summarize those for us so I will... This is this both of these concepts are recycled in the book. Some of them also have been expanded by the work of Christina separately from me, in particular the concept of data objects. But they are important, but they are not the core of the book. We draw very much on them, but the core of the book is to understand the forces of society και να κατανοήσουν τις δυνάμεις της κοινωνίας και της οικονομίας που γεννιέται αυτές τις μεσαιστές εμπειρίες. Χρησιμοποιούν αυτές τις μεσαιστές εμπειρίες

και χρησιμοποιούν να κάνουν όλα από χρήματα μέχρι να κάνουν πίσω την τράπεζα της τρόπης που οι άνθρωποι σκέφτονται και συμπεριλαμβάνουν. way people think and behave and act. So this is the primary purpose of the book. We start with three basic chapters. We trace the history of data. And the immediate and alternate take of our indication data is that data are not statistical entities, are not what statisticians and data scientists call simply data points. They are obviously these. We can pile them up and calculate them. But they are more than that. We call them cultural records. They have been used much before the digital age to do a number of things, to structure exchanges of economic goods, to monitor them, to record them in terms of accounting and other kind of recording systems. And in this quality as cultural records, data does do more than just provide

the elements or the inputs to standard calculations that are now performed by big data analytics, by algorithms, by data science, and by statistics. So this was a primary and fundamental reason for laying the foundations of data in the book in three chapters, then tracing the difference between data as cultural records prior to the digital revolution and analyzing and showing what the digital revolution brought into all the records humans, organizations, institutions used to monitor their lives, their productions, and their whereabouts. We make this contrast by drawing on fundamental information science concepts. This science has been led down by such pioneers as John von Neumann and Claude Shannon, mathematical theory of communicates, and we try to make the contrast

between prior forms of data and digital data. And out of this, to understand what digital data do that other data didn't do, but also understand that digital data are data nonetheless. This, we felt, has never been done by anyone. And this is one fundamental aim of the book. It's called Foundations and comprises chapters 2, 3 και 4. Θα δημιουργήσουμε την ιστορία των δίκτυων και την ρεβολουσία που έγινε με την διεθνή διεθνή δραστηριότητα και μετά την πέραση της συνεργασίας που έγινε

με το ίντερνετ και τα κοινωνικά μεδιά και την εποχή που ζούμε μαζί. Και το ίντερνετ των πραγματικών και ό,τι υπάρχει μετά. Όλος αυτής. Απλώς. we live together. And the Internet of Things and everything that's coming after that. All of this. Yeah, absolutely. One of the things that I liked about this book was that it started right away with stating very clearly the primary objective. And I'm going to quote here.

So the primary objective, as stated in the opening sentence actually, is to analyze the forces that install data at the center of contemporary life and reinforce the functions that they perform in the economy and society. This is very clear. At the same time, it's also a rather hard opinion. I was wondering, I just laid out how you started. Yes. How would, and you also mentioned previously that the primary audience is academics and opinion makers, thought leaders. How would anyone else besides these people be able to follow your argumentation? I don't know, to be honest, George. I'm proud to respond to your question. It may need some help, perhaps from you guides, that are able to take some of these complex ideas and make them more digestible for a broader audience. This is one way.

The other way is, and it's mostly a hope or perhaps an illusion you may say that even the educated woman or man would find it interesting to spend some time and get a little bit of a headache if i may say so to go through the book that's another interesting quote that caught my attention. You state that well-established boundaries of modern societies, such as those between work and private life or between the economic and the social spheres, are less clearly demarcated than one another in the data age. So that statement made me think a bit. I would tend to agree with that and I think probably many people would also tend to agree.

However, since we're talking about, especially since we're talking about academic discourse, and for that matter, you know, data and data science and data-driven arguments and so on, για τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δεδομένα και τα δε this in the book but let me start first from the intuition and this general idea that you say it looks like a credible argument and then see what we can think about metrics if you take facebook or tick tock what you see is that your life your private life your interactions with friends and colleagues is the center from which money has been made by Facebook and TikTok to mention just the two beasts that dominate our lives, the Arabs, the Goguryeans. So the money here is not made by producing a product in a secluded organizational setting, the factory, or any other kind of setting,

the bank, for instance, the insurance office, that is being made out in the open by crunching data that comes from our life. This is the most conspicuous fact that what once was a relatively, because it was always relatively insulated, never absolutely, but what was relatively separate before, your private life and the economic institutional life, they come together. So this is what grounds our own observation. We have seen this growing and growing and growing. Even communal life that was then in the square or in the market is now being recycled into these kinds of forms through data and interactions that record what people do on the internet or record what

people do with their devices, the internet of things that you mentioned before, and take all this data and produce either services or recommendations and other kinds of prompts that really come back and shape what people do and what choices they commit. These I think are clear evidence of the importance of data. Another one is obviously that the modern home has become a data center really. It's a variety of devices, most of them powered by the Internet of Things-based solutions and now by AI. And what's going on in the little and included spaces of the house is now public good or good for the company. It is another fundamental, so to say, inspiration or a kind of evidence that

shows how the private domestic life that was once relatively apart from the institutional and economic life becomes intermixed, how the two become intermeshed. Now, metrics, what metrics you can find of this? I believe you can have a lot of metrics that relate to the use of utilities, for instance, which are all powered by smart meters and internet-based solutions, could provide an idea about, for for instance how you measure the exposure of homes into institutional processes. There may be others as well. I don't have any direct solution at this time to this problem but that was our idea and this idea okay, you can provide a metric, but that's not the most important thing.

All the discussions then we have about privacy is based on this fundamental change. Even though quite a few people from the legal or economic fields, they do not reflect about the structural changes underneath that have made privacy a major problem. What we say, and this is chapter 5 in our book, we call it an excursus into privacy and surveillance, the phantoms of the modern problem of surveillance and privacy is the fact that this separation is not anymore what it was once. And therefore the channels for interaction between people, private lives, domestic lives, intimate even lives, and the wider world is permeable, is porous. και η διάρκεια της διάρκειας είναι θερμιακή, σπόρος. Τα πέρασαν κάθε μέρα χιλιάδες φορές. Υπάρχουν μερικά ενδιαφέροντικά σημεία που πρέπει να κάνουμε σε αυτή την επίθεση.

Νομίζω ότι ένας πραγματικός σημείο είναι ότι, καθώς και αυτό συμβαίνει, δεν υπάρχει κανένα συζήτημα για αυτό που συμβαίνει, point is that, well, it does happen. There's no, there's no debating on that, that this is taking place. But the interesting thing is that it seems to be happening actually voluntarily. Yeah, yeah, yeah. And I say, I emphasize it seems because if you start digging a little bit, you may actually unlearn that it's not entirely voluntary. I mean, it's 2024. I mean, by now people are actually born into this whole culture of having devices everywhere,

of having mobiles everywhere, of everything being recorded and somehow processed and all these things so in fact it takes a very very strong will and you have to be very inventive and very decisive to step away and say like wait this first you need to realize that this is happening and in some ways it's like asking for fish to realize that they're sitting in water. So first you have to realize that this is happening and then you have to come up with ways to actually go about in life without being embedded in this whole phenomenon. And this is not as simple as it seems. No, it's not. And as you say, it's partly voluntarily and partly not. Look, what mobile to choose is your own choice. But the use of mobile is not the choice in the world.

That's the point. What computer you will have, laptop or a small tablet, is your own choice. Whether you will have a laptop, I don't think is the choice in the world. You need to have. So you go with the flow, as the English say. But then we think this going with the flow, you can make one or another choice. And it's important to understand these differences. You can also decide that you don't want a community, that the 95% of people will not go for this choice. And that's also important to understand the numbers we're

speaking about. The majority of the people will go with the flow. Only a small part may want to have another kind of life. Just understand that. But these 95 that go with the flow, they don't make really a decision whether to go with the flow. They make smaller decisions once they decide that they go with the flow. What computer to buy or what car, if you like, to buy. So this is...sometimes we mix these different levels of reality and it's not clear how we speak about them. Interestingly, in the MIT series under which your own book was published, the previous book is in some ways precisely about that.

It's called Virtual Amish, and it's a study on the way that the Amish use technology. And I didn't read the book, but it just caught my attention that I kind of quickly browsed through it and it studies how it basically says even the Amish nowadays to some extent at least despite you know their beliefs and cultural and value system to some extent they actually have to have some level of interaction with technology because for example well they need to sell their products to the market and in order to do that They need a laptop, they need a web store and so they realize that they cannot insulate themselves as they did before Yeah, but what they do is that they are very they try to limit their Exported technology as much as possible and to us few people

Yeah, yeah, I think it's a good example. Unfortunately, I don't know this book, though I know quite a few books from the series. But this one has escaped my attention, but it may work for having a look at it. Thank you for bringing it to my attention. It's in my reading list as well. Let's see, there was a reference in your book about the interlocking of data with socio-economic institutions,

and in that context you mentioned Chandler's theory, the emergence of modern corporations in the first half of the 20th century, to the systematic generation of a variety of internal records, and that reminded me of something else which I read in another book, another reference in fact. That book was a book written by someone called Michel Bowens. The book is called The Peer-to-Peer Manifesto and it makes a number of interesting points and references. But the particular one that drove me to establish this connection was that at some point we examined the origins of the double bookkeeping system and they also claimed that this has played a fundamental role in shaping today's socio-economical

institutions. Do you agree with that? I agree, I agree, but you are referring to the work of Stomberg, Werner Stomberg, who has been more or less contemporaneous with Max Weber. He has been an economist, Max Weber is a sociologist. He's less well-known than Weber, but he made a number of points about how double entry bookkeeping was essential for the foundations of middle and then late capitalism. We don't enter in particular detail this argument. I have respect for Stomberg, though I believe that some of his arguments are controversial.

And one of the arguments, for instance, that I would distinguish ourselves and the book from this kind of thinking is the fact that double-entry bookkeeping is not a superior technology in terms of supporting profit generation. This could have done even without double entry bookkeeping. That is an important point. It's difficult to understand, but what double entry bookkeeping is doing is to pierce down the various moments and activities of the firm or the corporation, track the amount of resources and money spent in different activities, in different times, make comparison between one side here and another side there, and see

why this side is more profitable than the other. In this respect, double entry has been an essential eye, a foundation for laying, building up big corporations and businesses. And this is the idea of challenge. This idea we adopted, and I don't think for this you need an argument about capitalism or non-capitalism. It's an idea that says that the practices of management, the large corporations, would have been impossible without the data produced by double entry bookkeeping. We take this idea further, we build on it, we make comparisons with digital data, what digital data change here, and then we continue by, as I mentioned before, the discussion about privacy and surveillance and what comes into the second part of the book, the emergence

of platforms and digital ecosystems as other ways of organizing economic life. I find bookkeeping an interesting area of focus because it's something that to some extent at least everyone can relate to, everyone is familiar with. Okay, not everyone is an accountant obviously but even if not you know still manages their personal finances. So they can understand the concept of expenses, incoming and outgoing, and all of that stuff. So I think it's also interesting to relate this idea to the concept of externalities because to me that's a very good example of highlighting the fact that data is not as objective let's say absolutely it's absolutely yeah as it's supposed to be absolutely absolutely let me take first the opportunity to make this note that the small preface that has

been written in our book is written by Mike Power, who is a force and a professor of accounting at the London School of Economics and is very well known. And so she has written a three pages preface into this. So he comes from this tradition. Absolutely. The fact, and here we can enter a critical or even if you like, even ideological debate, so being critical is enough for I think. And approach accounting and how accounting institutionally and over time has chosen to record economic activities and their outcomes and see what problems it has not tackled.

The externality has not been dealt with. For instance, the pollution of the environment is being done by the firms. But there's nowhere to be found in accounting books. These costs have been offloaded to society and been dealt with tax money procured by everybody, not by the firms. This is a critique, and this is how what some of my friends may call capitalism works.

It's not the general rule, though. But going back into your observation, this shows exactly that even this data that may at first seem hard data, they are really the outcome of several assumptions, predilections, interests, and I would say also unintentional bias. Not all is calculated.

And it's important to say this is one of the fundamental ideas we pursue heavily in the book to claim that data are not objective entities in the sense that many people think of them. They have, of course, arrived. They are not hallucinations. entities in the sense that many people think of them. They have of course a life, they are not hallucinations, they are not objective in a sense, impartial. They are produced by society, the dominant relationships we have by what we know and the way what we know is involved in the production of value, goods and all this kind of stuff.

I would also add to this conversation about data not being objective, a somewhat technical observation or point of view. Even in the profession of data modeler, data modeler is someone whose job is to study a domain and come up with a model that accurately describes this domain for the purpose, typically, of creating an application that will serve an organization working in this domain. So, interestingly, typically, when you get, for example, two different people modeling the same domain,

they will not come up with the exact same model. And that already tells you something. It's- Yeah, absolutely, yeah. Yeah, the element of choice is an assumption is creeping in at any moment. I would agree with this. Yeah?

There's another point that you make that caught my attention. So in the analysis of data technology, you discussed the interplay of the technological nature of digital data and the formalized operations devoted in the software systems and devices by which they're produced. And that made me think, because when we talk about algorithms in general, it's a broad category. I would very roughly say that there are basically two types of algorithms, let's say. One type of algorithms that are deterministic,

in the sense that they somehow, let's say, are similar to mathematical equations like x plus y equals z, but there are also non-deterministic algorithms, in the sense that of statistical learning and machine learning and AI or whatever it is you want to call it. Do you think that there is a qualitative difference to be made that is important in how these two types of algorithms interact with the environment and with organizations? Yeah, that's a very complex question. I think some of these issues we already touched upon indirectly,

George. Let me take the opportunity of your questions and say the following. Let's resist the common parlance. Algorithm has not been invented yesterday. It's a word that has 1,000 years of history.

If we speak about algorithms as important today, it's because these algorithms are non-deterministic. They are able to do something which all the procedures of calculation, fixed procedures of calculation, fixed procedures of calculation, a number of steps we call algorithms, could not do. And this is what sends us at the center of modern computing and cognitive psychology. Because what this, and artificial intelligence, because what this non-deterministic algorithm can do

is to use neural networks to incorporate lessons from data, revise simply their answers, and in the next step produce something which didn't have in the previous step and do this mostly on their own in this respect well now to simplify this is a very complex discussion but this is why we speak of algorithms now because they have a force and if you like an agency as been called, the capacity to act, which deterministic forms of algorithms never had. I would argue that algorithms by themselves have zero agency. What gives them agency is people's decision to trust their outcome, or not trust their outcome or not trust their outcome but you know for example if you if you are an organization that chooses to screen job applications by applying some kind of algorithm as far as the law is concerned it doesn't matter what type of algorithm you choose to apply

what matters is that the algorithm has to be transparent it has to be explainable so you τι είδους αλγόριθμους επιλέγεις να επιλέγεις, τι σημαίνει είναι ότι ο αλγόριθμος πρέπει να είναι πραγματικό, πρέπει να είναι εξακολουθημένος. Έτσι, πρέπει να μπορείς να εξακολουθείς τις ανθρώπινες αξίες, «Αυτό είναι γιατί επιλέγω αυτήν την άτομα ή αυτήν την άτομα» ή «Αυτές είναι οι κριτήρια που έγιναν σε αυτήν την εξήγηση». Συμφωνώ, αν καταλάβεις καλά, συμφωνώ με αυτό, may be arrived at this decision. I agree, if I understand you well, I agree with this, that algorithms can have some agency, let me say some agency, in the sense that they have automated procedures for act and react,

something which previous technologies didn't have. In this respect, there is a difference. Now, whether you want to call it agency or not, capacity to act or just an automated calculation is a matter of preference, I believe. But I think the majority of the discussion we have about the importance of algorithms at some point, and even if it's never explained

very clearly, assumes that these algorithms have a space of calculation that are enacted internally by this algorithm or its interaction with other algorithms and critically with the data that are being fed into the algorithm, because algorithms without data are nothing, and make therefore decisions that those deterministic algorithms of the past could never have made. This is a fundamental difference. So now if you expand that space, and it seems that this space is expanding more and more and more and more with artificial intelligence. You are justified to worry about what the general outcome would be for companies, for governments, but also for people.

Their works and the way they live daily. Who will make these decisions? How transparent will they be? On what ethical grounds they will be made? Ποιοι θα κάνουν αυτές τις αποφάσεις, πόσο αδιαφερόντια θα είναι, σε ποιους αθλητικούς γραμμούς θα γίνονται, αυτές οι αδικαίες προκλήσεις, ακόμα και πολύ συχνά, δεν έχουν αρκετά πληροφορία με αρκετή σαφή καλότητα στις δημοσιογραφικές συζήτησεις. Συμφωνώ, νομίζω ότι αυτή η συζήτηση

στις δημοσιογραφικές συζήτησες I agree. I think this conversation in public discourse has only now begun to grow, to gain visibility. ότι αυτό το χώρο είναι διευθυντήτως από πολλούς παίκτες είναι πολύ μεγαλύτερο από το τόσο μεγάλο που μπορεί να συμβαίνει μια εκπαίδευση και να συμβαίνουν εμπνευσμοί. Απλώς, ναι. Τα πράγματα προχωρούν πολύ γρήγορα. Ήρθες να μιλήσεις για τις πρώτες τρεις κεφάλαιες του βιβλίου. Θα ήθελα να μας πηγαίνετε γρήγορα μέσα στον υπόλοιπο κεφάλαιο. Ναι, έχουμε ένα κεφάλαιο μετά από τα τρία, το οποίο είναι το ένα για την προστασία και την επισκευή. Θα πάμε για ένα κριτικό κοινό για αυτές τις διαδικασίες για την προστασία και την επισκευή. Το κεφάλαιο ονομάζεται «Εξκούρσεις για την επισκευή» γιατί είναι ένας διαδικασίος σε κάποιες τρόπες. and privacy in surveillance. The chapter is called Excursus on Surveillance because it's

detour in some ways, but one that we felt was substantial. We reject the straightforward understanding of surveillance as evil. We think it's a much more complex concept. The social processes described are much more ambiguous and complex. We draw on what we feel is the original understanding by Foucault of surveillance. Michel Foucault is a French philosopher and a professor in the history of ideas with a big, 30 years ago or 40 years ago, we take on his idea of surveillance. We expanded by using another prominent philosopher of our time. He also did now Ian Hacking and a few other people to build up the idea that surveillance construct persons, not only subjugate them. And try to understand how this diffusion of data and the way data enables surveillance also enables a number of positive things. They are not only expressions

of the will to subjugate others, as George Orwell, for instance, the concept of surveillance of George Orwell, which is very precise. You have the big brother is watching you, he wants to subjugate you. The concept of surveillance a la Foucault is more elaborate and more complex. Schools surveil its students, but they build up experts. To give you an example. The outcome is not negative only. It has negative aspects but it's much more complex and together with the negative it has also many positive aspects and therefore how data to come to today, how data impregnate the life of people do have certain negative outcomes but it has a lot of positive outcomes as well you and i george are to some degree persons that have been saved by this development and by by the way, Google and Facebook is surveilling us, if you want to.

And the way we use them to build up our capacities, not only to become subjects of their abolition, passive objects of exploitation. We reject this idea. We think that surveillance is a much more complex concept. Unfortunately, a very close friend of mine and someone who admired for a long time, Susanna

Zuboff, has taken this idea to very negative and limited directions. You're talking about the famous surveillance capitalism. I am one of the first that have read this book when Susanna wrote it. And it was just a manuscript. I'm very close friend with her. I love her but on this I disagree. I think it took some real fans of society but gave them proportion too many too big people we are not puppets of Google for God's sake all of us and not puppets of Facebook oh I think it's beyond debate the fact that surveillance is happening, whether it's a good thing or whether this is purely evil or it has some good sides to it, or whether it's entirely one-sided or not, that may be up for debate.

So this is chapter 2345, it's called an excursus on surveillance. It's a critical re-approach on surveillance and privacy, because by the end of this chapter, we take up the issue of how social relationships become economic transactions. And the difference we talked earlier before, the difference between social and economic life personal and institutional life economy and society become increasingly blurred or attenuated if you want me to use a less strong word after that the book enters a much more economic or managerial domain, if you like, though we see it mostly as chapters in the history of economic sociology. But some people may read them more narrowly.

It's an attempt to understand what happened in production of goods and the generation of value at the core of the economy as data now become the most pervasive component of value generation and data as you see in tick tock and facebook and google are being produced not in a particular corner of society, the shop floor of the factory, the factory or the office, are produced into the open world. And what does that change? This is another expression of the difference between work and private life, economy and society. And how these beasts that are being generated, and we call platforms, digital platforms better, that are the most conspicuous beasts, economic organizations that operate in this world, and everybody wants to become a platform now even caterpillar Siemens and all others build up industrial platform to

work on data not on the machines that once produced these are important but they become secondary insignificance no matter how important they are. So we discuss therefore the idea of digital platforms, from where these ideas come, how they have been manipulated, how they reflect the changes in society, and the concept of digital ecosystem, which we exemplify with some hard empirical work that Cristina has done on something which is called programmatic advertising, how automatic systems now allocate basically adverts in a scale that is beyond imagination,

in a second, into the online spaces in digital media. So we discussed this concept of ecosystem, and this is also the, give me one more minute to say this, George, because this is the title of the book also, Data Rule. Taking all these things together, we say that the diffusion of the book also, Data Rules. Taking all these things together, we say that the diffusion

of data and the way they need to be available, processed, cranced, and produced to produce value impose a system of new rules that are juxtaposed on those of the traditional market που είναι τεκστικοί σε αυτά των τραγικών και σχέσεων με το κοινό ή κατάσταση που συνδέεται με άλλες πολύ δημοσιογράφικες τεχνολογίες, για παράδειγμα, ο Καρλής Μπάλδουιν από το Harvard, στο σχέδιο της τεχνολογίας. Άρα υπήρχαν δύο πραγματικά διαφόρματα. Ένας, ο οποίος είναι ο επαναλήφιος οικονομικός διαφόρματος, There were therefore two fundamental discourses. One which is the standard economic discourse that you have market, you have competition, you have prices. So what's going on is the exchange of these things.

What Carly Spalding has done with Clark and a few other major economists is to say that many of these things are being increasingly saved. είναι να πούμε ότι πολλές από αυτές τις πράξεις βρίσκονται με αυτοκίνηση για να δείξουν πώς οι τεχνολογίες χρησιμοποιούνται για να δημιουργήσουν ή στήνουν διαφορές μεταξύ περιοχών της ζωής. Οι αρχιτεκτορίες, πώς τα τεχνολογίες παραδείγματονται, τι για παράδειγμα είναι

software και τι είναι software άλλο τρόπο, πώς μια τεχνολογία What, for instance, is software of a particular kind and what is software of another kind? How one technology is being linked to another, this is a question of architecture. They call this book, they publish design rules to show that technology and the traditional market logics, they come together. And how the technology passes the world, for instance, between different types of goods, cars here, electronics there, or other kinds of things there, they impact divisions in the world that shape how the economy performs. Do you get me?

So we take therefore these market rules, the traditional market rules, and these design rules which are very much Belvederean and say that what we have analyzed in the previous pages of the book bring forth an evidence that there is a third system of rules that have to do how data generated, how available, who has availability and accessibility on them, under which terms, and how are these data being Και πώς αυτά τα δεδομένα προσέγγιζαν και έγιναν καταστροφές. Αυτές οι κατάστασεις, όπως λέμε, έδωσαν ένα τρίτο σημείο από ευθύνες και δυσκολίες, που είναι αξιωτικά να αναφέρεται. Αυτή είναι η τέτοια στιγμή που τελείωσε το βιβλίο.

Ένα παράδειγμα που έρχεται στο μυαλό σας, για να αποτελεί το παραλληλό που έδωσες μεταξύ δεδομένων και καταστολών. An example comes to mind to potentially showcase this parallel that you drew between design rules and data rules. So you mentioned how design rules refers to the way technology may throw boundaries on the market side of things. Absolutely. The example that sort of immediately popped to my mind was, well, let's take mobile phones and the standards for mobile phone chargers. As you may know, up until recently, there was actually not a standard in the EU. Absolutely.

Yeah. And it was only recently that the standard has been... That the standard has been exposed. Exactly. This is a very good example of how the standards, other issues that easily come to mind is, και αυτό το στάνταρτ έχει εξακολουθεί. Αυτό είναι ένα πολύ καλό παράδειγμα. Υπάρχουν άλλα στάνταρτ, άλλα προβλήματα που εύκολα έρχονται στην μάθη μας. Για παράδειγμα, πώς οι μορφές ασφάλειες συνεχίζονται με άλλα είδους ασφάλειες. Χρειάζεται κάποια, βασικά, αρχιτεκτική λύση για αυτό. Αυτό είναι αυτό που ο Βάλδρυν και ο Κλάικς έλεγαν από τη δημιουργία.

Οπότε, κάποια από αυτά τα πράγματα... Στην δασκέδα των δίκαιων, το συμβαίνοντας σε αυτό θα είναι πραγματικά πράγματα που πριν μιλήσαμε για τη διευθυνσία δίκαιων. Πράγματα όπως η επιλογή της διευθυνσίας δίκαιων σε σχέση, αλλά και, στο δεύτερο επίπεδο,

η επιλογή των κόνσεπτων για να διευθυνσούν και πώς να τα διευθυνσούν ακριβώς. Αυτό στρέφει την αντιμετωπιότητα level, the choice of concepts to model and how to model them exactly. This saves interoperability of platforms. Absolutely. Without this interoperability, the platform would not really have existed. In fact, there are cases, not just cases, I would even go as far as to argue that it's the de facto, let's say, situation is one in which different organizations working on different platforms go out of their way to avoid being interoperable in order to have their to lock

in their audience, their users, and to maximize their reach. Absolutely, these are one of the tricks for gaining significance here. But when we say this thing, George, I think it's important to make some distinctions here. I think this is a great observation of yours. But still, the concept of interoperability is a concept of design. It falls well within what Baldwin and Clark, Henderson and a few other economists call architecture. The idea of data does something more. And I think the concept here that we need is not interoperability but commensurability. Because data, for instance, from private life are taken up to produce, for instance, credit

scores for individuals. Looking at with whom you interact, they may produce credit scores. This is something which you can't understand as interoperability. You can only understand it as commensurability. Which means interoperability would apply to the technical level of how you get data out Είναι μια κομμανισμότητα. Η υπερουπεραμπητικότητα θα εξασφαλίσει με την τεχνική εμπειρία για το πώς να πάρεις τα δίκτυα από ένα συστήμα, από το εγγυητικό σου, από το Facebook ή κάτι άλλο, στον εμπιστήμιο, το συστήμα. Αυτό είναι η τεχνική εμπειρία.

Είναι σημαντικό. Είναι σημαντικό όμως και ως ενανάπημα. Ναι, είναι σ Yeah, it's important. But it's important also to understand that the data brings different worlds together. When you have data on Facebook interaction with credit scores, we'll give just one simple example, there are thousands of these things happening. You bring together two different

worlds. This is what we think the concept of commensurability which is part of the data rules not the design rule makes sense. I think this is a great even though perhaps alarming... There are alarming things here, undeniably, but also some good things. Great, even though perhaps alarming way to also wrap up, bring this conversation to an end, and just ask you as the final, as the epilogue to this, so what are your hopes and your plans for this book going forward? και θα σας ρωτήσω ως επιλογή αυτό, ποιες είναι οι σκοτές και οι σχέσεις για αυτό το βιβλίο. Οι βιβλίες, όταν τα έβλεπε και τα έφερε η Ευρωβουλευτή, πήραν τη ζωή τους. Ελπίζουμε να δημιουργήσουμε έναν διεθνή συμφωνία μεταξύ των κοινωνικών σχέσεων

και επίσης σε διεθνές σεκτορές της κοινωνικής μας κοινωνίας. the discourse across the social sciences, and also in discourse across sectors of our society. The one you and I have is an example of this. And I imagine that also your podcast will be a further example of this. That's hopefully, yeah, that's our hope is, we will instigate or drive people to rethink some of things, also provide people, both academics and normal people, if I may say so, or educated people, provide them with some fundamental insights and even if you like, analytic tools for approaching the complexities of our society and our economy.

If we could make a contribution into this, it would be fantastic. I would say that's a noble aspiration. I wish you the best of luck. Thank you. Thank you very much. Let's see what will happen. Thanks for sticking around. For more stories like this, check the link in bio and follow Link Data Orchestration.