"How Social Media's Giant Algorithm Shapes our Feeds."
This headline came from today's Washington Post, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his Art of Computer Programming. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result. Should we be bothered that the Post (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie? Paul Ceruzzi Tom Haigh & Paul Ceruzzi, A New History of Modern Computing (MIT Press 2021)
Dear Paul, I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers. Safiya Noble’s book blows this out even further as she argues for Algorithms of Oppression. Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook. And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks. Looking forward to further conversation. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center <http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy <http://jitpedagogy.org/> Co-Founder - NYCDH <http://nycdh.org/> E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com <http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition <https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition <https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book <http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/>
On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu> wrote:
This headline came from today's Washington Post, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his Art of Computer Programming. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result.
Should we be bothered that the Post (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie?
Paul Ceruzzi
Tom Haigh & Paul Ceruzzi, A New History of Modern Computing (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org <http://sigcis.org/>, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e=> and you can change your subscription options at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e=>
Hello, My sense is talk of when an algorithm becomes many algorithms or the like is an example of a sorites paradox (how many items make a heap, if you take one item off a heap it is still a heap yet if you take 10 items off it is not etc.). How many steps can you add to an algorithm before it becomes a heap of algorithms, a blob (or a piece of software and how many lines of code before a piece of software becomes a suite of software and so on)? My suspicion is talk of "the algorithm" may have started with Google's PageRank algorithm. My sense is that the original PageRank algorithm was a proper Knuthian algorithm of definite and limited size, but of course as they applied it to search and had to deal with various exigencies including people trying to game the algorithm there were endless additions and tinkering. So probably the scheme by which Google arranges search results is more like a heap of algorithms or the Blob than the original PageRank algorithm, but it is often called an algorithm or "the algoirthm". I am guessing the popular notion of algorithm grew from Google's PageRank to other not wholly dissimilar systems such as the method by which Facebook (and other social media sites) decides what we see on our feed or Youtube decides what videos to suggest we might want to watch and so on, On Thu, Oct 28, 2021 at 12:49 AM Kimon Keramidas <kimon.keramidas@nyu.edu> wrote:
Dear Paul,
I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers.
Safiya Noble’s book blows this out even further as she argues for *Algorithms of Oppression. *Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook.
And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks.
Looking forward to further conversation.
Cheers, Kimon
*Kimon Keramidas, Ph.D.* Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations
*Pronouns:* He/Him
*New York University* 14 University Place New York, NY 10003
*Co-Director* - ITMO University International Digital Humanities Research Center <http://dh.itmo.ru/en_about> *Co-Founder* - The Journal of Interactive Technology and Pedagogy <http://jitpedagogy.org> *Co-Founder *- NYCDH <http://nycdh.org/>
*E *kimon.keramidas@nyu.edu *W* http://kimonkeramidas.com
*The Sogdians: Influencers on the Silk Roads* Exhibition <https://www.freersackler.si.edu/sogdians>
*The Interface Experience: Forty Years of Personal Computing*Exhibition <https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience>
*The Interface Experience: A User’s Guide**Winner* of the *2016 Innovation in Print Design Award* from the *American Alliance of Museums* Buy Book <http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/>
On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu> wrote:
This headline came from today's *Washington Post*, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his *Art of Computer Programming*. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result.
Should we be bothered that the *Post* (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie?
Paul Ceruzzi
Tom Haigh & Paul Ceruzzi, *A New History of Modern Computing* (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e= and you can change your subscription options at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e=
_______________________________________________ This email is relayed from members at sigcis.org, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at http://lists.sigcis.org/pipermail/members-sigcis.org/ and you can change your subscription options at http://lists.sigcis.org/listinfo.cgi/members-sigcis.org
-- Yours Truly, Allan Olley, PhD http://individual.utoronto.ca/fofound
Hi all, It might be relevant in this context to watch the keynote video from Charles Isbell at NeurIPS 2020: https://nips.cc/virtual/2020/public/invited_16166.html I’ve posted the title and abstract below, but the talk also discusses machine learning systems as “algorithms with gaps” that are filled in by using example data. I really like this framing, because it shows us how machine learning fits into the traditional programming paradigm, and it gives you a sense of (and an opportunity to discuss) the reliability of the different stages that a computer goes through to solve the problem at hand. Best wishes, Emiel van Miltenburg —————— Invited Talk: You Can’t Escape Hyperparameters and Latent Variables: Machine Learning as a Software Engineering Enterprise Charles Isbell Tue, Dec 8th, 2020 @ 02:00 – 04:00 CET Abstract: Successful technological fields have a moment when they become pervasive, important, and noticed. They are deployed into the world and, inevitably, something goes wrong. A badly designed interface leads to an aircraft disaster. A buggy controller delivers a lethal dose of radiation to a cancer patient. The field must then choose to mature and take responsibility for avoiding the harms associated with what it is producing. Machine learning has reached this moment. In this talk, I will argue that the community needs to adopt systematic approaches for creating robust artifacts that contribute to larger systems that impact the real human world. I will share perspectives from multiple researchers in machine learning, theory, computer perception, and education; discuss with them approaches that might help us to develop more robust machine-learning systems; and explore scientifically interesting problems that result from moving beyond narrow machine-learning algorithms to complete machine-learning systems. On 28 Oct 2021, at 07:28, Allan Olley <allan.olley@alumni.utoronto.ca<mailto:allan.olley@alumni.utoronto.ca>> wrote: Hello, My sense is talk of when an algorithm becomes many algorithms or the like is an example of a sorites paradox (how many items make a heap, if you take one item off a heap it is still a heap yet if you take 10 items off it is not etc.). How many steps can you add to an algorithm before it becomes a heap of algorithms, a blob (or a piece of software and how many lines of code before a piece of software becomes a suite of software and so on)? My suspicion is talk of "the algorithm" may have started with Google's PageRank algorithm. My sense is that the original PageRank algorithm was a proper Knuthian algorithm of definite and limited size, but of course as they applied it to search and had to deal with various exigencies including people trying to game the algorithm there were endless additions and tinkering. So probably the scheme by which Google arranges search results is more like a heap of algorithms or the Blob than the original PageRank algorithm, but it is often called an algorithm or "the algoirthm". I am guessing the popular notion of algorithm grew from Google's PageRank to other not wholly dissimilar systems such as the method by which Facebook (and other social media sites) decides what we see on our feed or Youtube decides what videos to suggest we might want to watch and so on, On Thu, Oct 28, 2021 at 12:49 AM Kimon Keramidas <kimon.keramidas@nyu.edu<mailto:kimon.keramidas@nyu.edu>> wrote: Dear Paul, I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers. Safiya Noble’s book blows this out even further as she argues for Algorithms of Oppression. Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook. And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks. Looking forward to further conversation. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement<http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center<http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy<http://jitpedagogy.org/> Co-Founder - NYCDH<http://nycdh.org/> E kimon.keramidas@nyu.edu<mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com<http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition<https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition<https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book<http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/> On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu<mailto:CeruzziP@si.edu>> wrote: This headline came from today's Washington Post, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his Art of Computer Programming. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result. Should we be bothered that the Post (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie? Paul Ceruzzi Tom Haigh & Paul Ceruzzi, A New History of Modern Computing (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org<http://sigcis.org/>, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e= and you can change your subscription options at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e= _______________________________________________ This email is relayed from members at sigcis.org<http://sigcis.org/>, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at http://lists.sigcis.org/pipermail/members-sigcis.org/ and you can change your subscription options at http://lists.sigcis.org/listinfo.cgi/members-sigcis.org -- Yours Truly, Allan Olley, PhD http://individual.utoronto.ca/fofound _______________________________________________ This email is relayed from members at sigcis.org<http://sigcis.org>, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at http://lists.sigcis.org/pipermail/members-sigcis.org/ and you can change your subscription options at http://lists.sigcis.org/listinfo.cgi/members-sigcis.org
Dear All, It is not the first time the word "algorithm" has shifted in meaning, in fact, its "Knuthian" version of a well-defined sequence of a finite number of steps leading to a specific result only dates back to the late 19th century. Later, "algorithm" became a household word in computing but only after 1960, because of ALGOL and, later, Knuth. Before that time "method" is used much more frequently than "algorithm". These results come from an article Liesbeth De Mol and msyelf recently wrote on the semantic shifts happening to words like "program", "code" and "algorithm". It is due to published soon in the volume "Abstractions and Embodiments: New Histories of Computing and Society" edited by Stephanie Dick and Janet Abbate. A preprint is online: https://hal.univ-lille.fr/hal-03081203 Though we stop around 1960 in our article, the conclusion says something about the generalization of the word "algorithm" now, meaning indeed something like "complex program". Though its popular use may certainly have to do with Google, as Allan suggests, you may find such usage earlier on. In the 1970s one frequently finds "scheduling algorithm" and in IA they also talk of algorithms. These are not "Knuthian" algorithms, but rather numerical formulae with a lot of (empirical) inputs that are processed to *control* or stabilize a system, be it a multiprogramming system or an IA system. In contrast with "Knuthian" algorithms, the formulae depend on "arbitrary" parameters that are tweeked to obtain some kind of system behaviour. If one takes the example of the "Google"-algorithm, the "Knuthian" part of it is just plain matrix diagonalization/inversion, but it is how the "empirical" input is put into the matrix, and how the weights are accorded to entries of the matrix that make up the intricate interest for Google, but these are "arbitrary" parameters that constitute top layers built on the "Knuthian" matrix algorithm, these layers reflect economical and social choices. best wishes Maarten On 2021-10-28 07:28, Allan Olley wrote:
Hello,
My sense is talk of when an algorithm becomes many algorithms or the like is an example of a sorites paradox (how many items make a heap, if you take one item off a heap it is still a heap yet if you take 10 items off it is not etc.). How many steps can you add to an algorithm before it becomes a heap of algorithms, a blob (or a piece of software and how many lines of code before a piece of software becomes a suite of software and so on)?
My suspicion is talk of "the algorithm" may have started with Google's PageRank algorithm. My sense is that the original PageRank algorithm was a proper Knuthian algorithm of definite and limited size, but of course as they applied it to search and had to deal with various exigencies including people trying to game the algorithm there were endless additions and tinkering. So probably the scheme by which Google arranges search results is more like a heap of algorithms or the Blob than the original PageRank algorithm, but it is often called an algorithm or "the algoirthm".
I am guessing the popular notion of algorithm grew from Google's PageRank to other not wholly dissimilar systems such as the method by which Facebook (and other social media sites) decides what we see on our feed or Youtube decides what videos to suggest we might want to watch and so on,
On Thu, Oct 28, 2021 at 12:49 AM Kimon Keramidas <kimon.keramidas@nyu.edu> wrote:
Dear Paul,
I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers.
Safiya Noble’s book blows this out even further as she argues for _Algorithms of Oppression. _Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook.
And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks.
Looking forward to further conversation.
Cheers, Kimon
Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement [2] Affiliated Faculty, Program in International Relations
Pronouns: He/Him
New York University 14 University Place New York, NY 10003
Co-Director - ITMO University International Digital Humanities Research Center [3] Co-Founder - The Journal of Interactive Technology and Pedagogy [4] Co-Founder - NYCDH [5]
E kimon.keramidas@nyu.edu W http://kimonkeramidas.com [6]
_The Sogdians: Influencers on the Silk Roads_ Exhibition [7]
The Interface Experience: Forty Years of Personal Computing Exhibition [8]
The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book [9]
On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu> wrote:
This headline came from today's _Washington Post_, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his _Art of Computer Programming_. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result.
Should we be bothered that the _Post_ (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie?
Paul Ceruzzi
Tom Haigh & Paul Ceruzzi, _A New History of Modern Computing_ (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org [1], the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at
and you can change your subscription options at
_______________________________________________ This email is relayed from members at sigcis.org [10], the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at http://lists.sigcis.org/pipermail/members-sigcis.org/ and you can change your subscription options at http://lists.sigcis.org/listinfo.cgi/members-sigcis.org
-- Yours Truly, Allan Olley, PhD
http://individual.utoronto.ca/fofound
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Loving this discussion! Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center <http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy <http://jitpedagogy.org/> Co-Founder - NYCDH <http://nycdh.org/> E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com <http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition <https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition <https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book <http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/>
On Oct 28, 2021, at 7:02 AM, Maarten Bullynck <maarten.bullynck@kuttaka.org> wrote:
Dear All,
It is not the first time the word "algorithm" has shifted in meaning, in fact, its "Knuthian" version of a well-defined sequence of a finite number of steps leading to a specific result only dates back to the late 19th century. Later, "algorithm" became a household word in computing but only after 1960, because of ALGOL and, later, Knuth. Before that time "method" is used much more frequently than "algorithm".
These results come from an article Liesbeth De Mol and msyelf recently wrote on the semantic shifts happening to words like "program", "code" and "algorithm". It is due to published soon in the volume "Abstractions and Embodiments: New Histories of Computing and Society" edited by Stephanie Dick and Janet Abbate. A preprint is online: https://urldefense.proofpoint.com/v2/url?u=https-3A__hal.univ-2Dlille.fr_hal-2D03081203&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=ssIf8CORoTT-SDz5BKdVA2uxSd_o2K5Jqpgd6YSBfzk&e= <https://urldefense.proofpoint.com/v2/url?u=https-3A__hal.univ-2Dlille.fr_hal-2D03081203&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=ssIf8CORoTT-SDz5BKdVA2uxSd_o2K5Jqpgd6YSBfzk&e=> Though we stop around 1960 in our article, the conclusion says something about the generalization of the word "algorithm" now, meaning indeed something like "complex program". Though its popular use may certainly have to do with Google, as Allan suggests, you may find such usage earlier on. In the 1970s one frequently finds "scheduling algorithm" and in IA they also talk of algorithms. These are not "Knuthian" algorithms, but rather numerical formulae with a lot of (empirical) inputs that are processed to *control* or stabilize a system, be it a multiprogramming system or an IA system. In contrast with "Knuthian" algorithms, the formulae depend on "arbitrary" parameters that are tweeked to obtain some kind of system behaviour. If one takes the example of the "Google"-algorithm, the "Knuthian" part of it is just plain matrix diagonalization/inversion, but it is how the "empirical" input is put into the matrix, and how the weights are accorded to entries of the matrix that make up the intricate interest for Google, but these are "arbitrary" parameters that constitute top layers built on the "Knuthian" matrix algorithm, these layers reflect economical and social choices.
best wishes
Maarten
On 2021-10-28 07:28, Allan Olley wrote:
Hello, My sense is talk of when an algorithm becomes many algorithms or the like is an example of a sorites paradox (how many items make a heap, if you take one item off a heap it is still a heap yet if you take 10 items off it is not etc.). How many steps can you add to an algorithm before it becomes a heap of algorithms, a blob (or a piece of software and how many lines of code before a piece of software becomes a suite of software and so on)? My suspicion is talk of "the algorithm" may have started with Google's PageRank algorithm. My sense is that the original PageRank algorithm was a proper Knuthian algorithm of definite and limited size, but of course as they applied it to search and had to deal with various exigencies including people trying to game the algorithm there were endless additions and tinkering. So probably the scheme by which Google arranges search results is more like a heap of algorithms or the Blob than the original PageRank algorithm, but it is often called an algorithm or "the algoirthm". I am guessing the popular notion of algorithm grew from Google's PageRank to other not wholly dissimilar systems such as the method by which Facebook (and other social media sites) decides what we see on our feed or Youtube decides what videos to suggest we might want to watch and so on, On Thu, Oct 28, 2021 at 12:49 AM Kimon Keramidas <kimon.keramidas@nyu.edu> wrote:
Dear Paul, I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers. Safiya Noble’s book blows this out even further as she argues for _Algorithms of Oppression. _Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook. And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks. Looking forward to further conversation. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement [2] Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center [3] Co-Founder - The Journal of Interactive Technology and Pedagogy [4] Co-Founder - NYCDH [5] E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W https://urldefense.proofpoint.com/v2/url?u=http-3A__kimonkeramidas.com&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=tgE2ZDeam7GsgcgHLR_pU8AMmyVTpTDwLg1Vpn8dX1M&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__kimonkeramidas.com&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=tgE2ZDeam7GsgcgHLR_pU8AMmyVTpTDwLg1Vpn8dX1M&e=> [6] _The Sogdians: Influencers on the Silk Roads_ Exhibition [7] The Interface Experience: Forty Years of Personal Computing Exhibition [8] The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book [9]
On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu <mailto:CeruzziP@si.edu>> wrote: This headline came from today's _Washington Post_, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his _Art of Computer Programming_. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result. Should we be bothered that the _Post_ (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie? Paul Ceruzzi Tom Haigh & Paul Ceruzzi, _A New History of Modern Computing_ (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org <http://sigcis.org/> [1], the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e=> and you can change your subscription options at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e=>
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I’m enjoying it as well as I hope to work on a project looking at how power systems experts resolve which algorithms to use to maximize economy and control the flow of electricity on networks - a different application but relevant in terms of how to explain the process to a non-technical audience. -Julie Julie Cohn, Ph.D. Non-Resident Scholar, Center for Energy Studies Baker Institute for Public Policy, Rice University, and Research Historian, Center for Public History University of Houston email: cohnconnor@gmail.com cell: 713.516.0849 Author: The Grid: Biography of an American Technology (MIT Press, 2017) https://mitpress.mit.edu/books/grid
On Oct 28, 2021, at 7:57 AM, Kimon Keramidas <kimon.keramidas@nyu.edu> wrote:
Loving this discussion!
Cheers, Kimon
Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations
Pronouns: He/Him
New York University 14 University Place New York, NY 10003
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On Oct 28, 2021, at 7:02 AM, Maarten Bullynck <maarten.bullynck@kuttaka.org <mailto:maarten.bullynck@kuttaka.org>> wrote:
Dear All,
It is not the first time the word "algorithm" has shifted in meaning, in fact, its "Knuthian" version of a well-defined sequence of a finite number of steps leading to a specific result only dates back to the late 19th century. Later, "algorithm" became a household word in computing but only after 1960, because of ALGOL and, later, Knuth. Before that time "method" is used much more frequently than "algorithm".
These results come from an article Liesbeth De Mol and msyelf recently wrote on the semantic shifts happening to words like "program", "code" and "algorithm". It is due to published soon in the volume "Abstractions and Embodiments: New Histories of Computing and Society" edited by Stephanie Dick and Janet Abbate. A preprint is online: https://urldefense.proofpoint.com/v2/url?u=https-3A__hal.univ-2Dlille.fr_hal-2D03081203&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=ssIf8CORoTT-SDz5BKdVA2uxSd_o2K5Jqpgd6YSBfzk&e= <https://urldefense.proofpoint.com/v2/url?u=https-3A__hal.univ-2Dlille.fr_hal-2D03081203&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=ssIf8CORoTT-SDz5BKdVA2uxSd_o2K5Jqpgd6YSBfzk&e=> Though we stop around 1960 in our article, the conclusion says something about the generalization of the word "algorithm" now, meaning indeed something like "complex program". Though its popular use may certainly have to do with Google, as Allan suggests, you may find such usage earlier on. In the 1970s one frequently finds "scheduling algorithm" and in IA they also talk of algorithms. These are not "Knuthian" algorithms, but rather numerical formulae with a lot of (empirical) inputs that are processed to *control* or stabilize a system, be it a multiprogramming system or an IA system. In contrast with "Knuthian" algorithms, the formulae depend on "arbitrary" parameters that are tweeked to obtain some kind of system behaviour. If one takes the example of the "Google"-algorithm, the "Knuthian" part of it is just plain matrix diagonalization/inversion, but it is how the "empirical" input is put into the matrix, and how the weights are accorded to entries of the matrix that make up the intricate interest for Google, but these are "arbitrary" parameters that constitute top layers built on the "Knuthian" matrix algorithm, these layers reflect economical and social choices.
best wishes
Maarten
On 2021-10-28 07:28, Allan Olley wrote:
Hello, My sense is talk of when an algorithm becomes many algorithms or the like is an example of a sorites paradox (how many items make a heap, if you take one item off a heap it is still a heap yet if you take 10 items off it is not etc.). How many steps can you add to an algorithm before it becomes a heap of algorithms, a blob (or a piece of software and how many lines of code before a piece of software becomes a suite of software and so on)? My suspicion is talk of "the algorithm" may have started with Google's PageRank algorithm. My sense is that the original PageRank algorithm was a proper Knuthian algorithm of definite and limited size, but of course as they applied it to search and had to deal with various exigencies including people trying to game the algorithm there were endless additions and tinkering. So probably the scheme by which Google arranges search results is more like a heap of algorithms or the Blob than the original PageRank algorithm, but it is often called an algorithm or "the algoirthm". I am guessing the popular notion of algorithm grew from Google's PageRank to other not wholly dissimilar systems such as the method by which Facebook (and other social media sites) decides what we see on our feed or Youtube decides what videos to suggest we might want to watch and so on, On Thu, Oct 28, 2021 at 12:49 AM Kimon Keramidas <kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu>> wrote:
Dear Paul, I actually don’t think that’s an inappropriate use of the term and that term has certainly evolved in popular use to this extent. I would also say that it has grown in its uses in technical application. It may seem like a blob from one perspective but for Facebook, the system that decides a post’s position based on predictions is very much a “well-defined, finite set of steps that produces an unambiguous result.” They get exactly what they want by feeding data into that algorithm and getting a result that they can then apply to their business practices. I think that in this day and age a conception of how algorithms are conceived, executed and worked has to be more expansive as technologies are increasingly integrated into complex formulaic processes such as these. For example, I am certain that there is some level of AI built into Facebook's algorithm and therefore a level of complexity that seems “blob-like” but nonetheless is conceived and executed with the goal of unambiguous (at least from their perspective) algorithmic results by Facebook’s engineers. Safiya Noble’s book blows this out even further as she argues for _Algorithms of Oppression. _Noble highlights that embedded social biases actually integrate themselves into the construction of computer-based algorithms. They embed themselves in such a way that we could say that these biases become acceptable cultural practices that integrate themselves into those “well-defined, finite steps of steps” if we start analyzing choices made in the construction of algorithms from a sociological as well as technical outlook. And as far as whether people should consider some algorithms as something threatening. That probably wouldn’t necessarily be a bad thing at this point. I know that despite a long held skepticism towards all things Facebook even I have been shocked about some of the blatant abuses that are being revealed over the last few weeks. Looking forward to further conversation. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement [2] Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center [3] Co-Founder - The Journal of Interactive Technology and Pedagogy [4] Co-Founder - NYCDH [5] E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W https://urldefense.proofpoint.com/v2/url?u=http-3A__kimonkeramidas.com&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=tgE2ZDeam7GsgcgHLR_pU8AMmyVTpTDwLg1Vpn8dX1M&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__kimonkeramidas.com&d=DwIGaQ&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=49QsR91LxS0YGRfHDPUnMkgjTVw8FQVS4rg4ZvoDsqY&s=tgE2ZDeam7GsgcgHLR_pU8AMmyVTpTDwLg1Vpn8dX1M&e=> [6] _The Sogdians: Influencers on the Silk Roads_ Exhibition [7] The Interface Experience: Forty Years of Personal Computing Exhibition [8] The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book [9]
On Oct 27, 2021, at 7:52 PM, Ceruzzi, Paul <CeruzziP@si.edu <mailto:CeruzziP@si.edu>> wrote: This headline came from today's _Washington Post_, in a long above-the-fold article about Facebook's policies in determining what users see when they "like" a post. The article does not define the word, but describes an algorithm as "...a system that decides on a post's position on the news feed based on predictions about each user's preferences and tendencies." That sounds to me like a complex piece of software, with perhaps hundreds of lines of code, that takes in a lot of variables and produces a potentially wide range of outputs. It conjures up an image of something sinister and menacing. Not what Knuth defined as an "algorithm" in Volume One of his _Art of Computer Programming_. His definition has been refined over the years, but it retains the notion of a well-defined, finite set of steps that produces an unambiguous result. Should we be bothered that the _Post_ (and I assume other newspapers) are not using the term properly? Are people now going to think of an "algorithm" as something threatening, like "The Blob" in that famous Steve McQueen movie? Paul Ceruzzi Tom Haigh & Paul Ceruzzi, _A New History of Modern Computing_ (MIT Press 2021) _______________________________________________ This email is relayed from members at sigcis.org <http://sigcis.org/> [1], the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_pipermail_members-2Dsigcis.org_&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=3RMyQdkyVkCEDElaIzRGbRU2gLRvNdv47KpPH6ucCnY&e=> and you can change your subscription options at https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e= <https://urldefense.proofpoint.com/v2/url?u=http-3A__lists.sigcis.org_listinfo.cgi_members-2Dsigcis.org&d=DwICAg&c=slrrB7dE8n7gBJbeO0g-IQ&r=8lhfdn1CVAMK_u4AbH6K2X3Rh95e5EvJanbOcfGalCo&m=ea2IyyzGMBYqnJeWKHghD5FkVqtgxsNckj3MEVinsCQ&s=5ORNb_FCuQhU8VwTR2W2fTju2szcYKM7i-cfA7rrbnQ&e=>
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Thank you very much Paul and everyone for raising that discussion. To borrow from Paul, indeed, algorithms are in fact pieces of software, and I think the result of this rebranding is to invisibilize what a piece of software really is : much more than algorithms, and much more than lines of code. Software is compiling. More generally, its relationship to hardware is not straightforward. It is not obvious that it may run on any machine. It is not obvious that it will work consistently in different computing environments. Software is licensing. Beyond an open or proprietary dichotomy, it is not obvious how and when a piece of software may be used by whom on what terms. Especially as it's now been a long time that coding/programming is not about "writing [put an impressive number here] lines of code", but more about calling libraries that other developed, and licensed. Software is distribution. Algorithms always seem to be developed for internal (and even secret) use but people elaborating a piece of software are most of the time creating a tool that will be used by other people (even within a corporation), and this leads me to the most important point : Software is not only about developers, it is also about users. The use people make of software is not necessarily how it is meant to be used by the developers. Bernhard Rieder in Engines of Order makes the case that every developer is indeed a user of the libraries they are calling. Software is about the complex relationships between developers and users and algorithms tend to erase all this, they're seen as teleogical, and yes, threatening weapons to the point that they're now rhetorically the usual suspects when something goes wrong, the ideal culprits for all the sins of humanity. Don't get me wrong, I do believe that "algorithms" perform very mean tasks like equating gorillas with black people. Algorithms of oppression indeed. There's a very active, very timely and very welcome body of research on these topics, but I do believe that rhetorically calling a piece of software "an algorithm" tends to invibilize (or even anthropomorphize, like for example in the "algorithmic bias" phrasing) a lot of aspects of these pieces of software. -- *********************************************** Alexandre Hocquet Archives Henri Poincaré & RWTH c:o/re https://poincare.univ-lorraine.fr/fr/membre-titulaire/alexandre-hocquet https://www.humtec.rwth-aachen.de/cms/HUMTEC/Das-Projekthaus/Kaete-Hamburger... ***********************************************
This thread reminded me of Nick Seaver's take on the term algorithm, which seems more relevant than ever: Seaver N. Algorithms as culture: Some tactics for the ethnography of algorithmic systems. Big Data & Society. December 2017. https://journals.sagepub.com/doi/full/10.1177/2053951717738104 //Ed
I liked this recent tweet from Colin McMillen [1 <https://twitter.com/mcmillen/status/1449116726407401472>]: algorithms are money laundering for unethical decision-making I like Cathy O'Neil's discussion of algorithms <https://www.youtube.com/watch?v=heQzqX35c9A> (2:38), "an opinion embedded in math" and shared it with my Race, Gender, and Computing class. I also shared David Malan's more conventional definition <https://www.youtube.com/watch?v=6hfOvs8pY1k> (4:57).
Great discussion - thanks everyone! My thoughts: Wrt social media and big tech, the phrases “the algorithm” and “these algorithms” now function much like the phrase “these models” in many non-scientific discussions of climate science. They're massive generalizations, or straw figures to beat up on, or invoked as symbols of power relationships, stupid science, or human bias. The reality is more complex. As an example, O’Neil’s “an opinion embedded in math” is dead-on right for some kinds of machine learning algorithms. But it’s dead wrong for many other algorithms. An algorithm for sorting lists alphabetically or numerically is not “an opinion embedded in math” since most of the time, alphabetical and numerical order are uncontroversial, widely used standards. Yet no distinction is made. “These algorithms.” To describe usages like these, I like Malte Ziewitz’s phrase “the *figure* of the algorithm,” which is only loosely connected to what is actually going on under the hood. Ziewitz, Malte. 2017. “A not quite random walk: Experimenting with the ethnomethods of the algorithm.” Big Data & Society 4 (2): 205395171773810. doi:10.1177/2053951717738105 I see no reason to “correct” these usages most of the time – but they *can* become quite problematic when they’re really gestures at big tech, social media, human decisions leading to biased training data for ML, and so on. They obscure the complexity of how human choices and responsibilities interact with automatic activity in algorithmic systems. For many with little understanding of how computer systems work, “the algorithm” becomes a proxy for “the programmers” and often assumes intent on the part of those programmers - but today, in many case programmers don't know in advance how their code will interact with all the other code in massive online systems that also interact with *other* massive online systems, all of them constantly changing on a near-daily basis. Nor do many discourses about algorithms fully take into the account how social media algorithms are constantly adapting in the continual back-and-forth between the human users of these systems and “the algorithm.” Some ideas about all this appear in my article “We Have Been Assimilated: Some Principles for Thinking About Algorithmic Systems.” 2018. In IFIP Advances in Information and Communication Technology: Living with Monsters? Social Implications of Algorithmic Phenomena, Hybrid Agency, and the Performativity of Technology, edited by Ulrike Schultze et al., 19–27. Cham, Switzerland: Springer International Publishing. http://dx.doi.org/10.1007/978-3-030-04091-8_3 If you can’t get access directly, email me and I’ll send you a copy. Best, Paul On Oct 29, 2021, at 09:16, Ellen Spertus <spertus@mills.edu<mailto:spertus@mills.edu>> wrote: I liked this recent tweet from Colin McMillen [1<https://twitter.com/mcmillen/status/1449116726407401472>]: algorithms are money laundering for unethical decision-making I like Cathy O'Neil's discussion of algorithms<https://www.youtube.com/watch?v=heQzqX35c9A> (2:38), "an opinion embedded in math" and shared it with my Race, Gender, and Computing class. I also shared David Malan's more conventional definition<https://www.youtube.com/watch?v=6hfOvs8pY1k> (4:57). _______________________________________________ This email is relayed from members at sigcis.org<http://sigcis.org>, the email discussion list of SHOT SIGCIS. Opinions expressed here are those of the member posting and are not reviewed, edited, or endorsed by SIGCIS. The list archives are at http://lists.sigcis.org/pipermail/members-sigcis.org/ and you can change your subscription options at http://lists.sigcis.org/listinfo.cgi/members-sigcis.org ________________________ Paul N. Edwards<https://profiles.stanford.edu/paul-edwards> Director, Program on Science, Technology & Society<http://sts.stanford.edu> William J. Perry Fellow in International Security and Senior Research Scholar Center for International Security and Cooperation<http://cisac.fsi.stanford.edu/> Co-Director, Stanford Existential Risks Initiative<https://cisac.fsi.stanford.edu/stanford-existential-risks-initiative> Stanford University Professor of Information<http://www.si.umich.edu/> and History<http://www.lsa.umich.edu/history/> (Emeritus) University of Michigan
An algorithm for sorting lists alphabetically or numerically is not “an opinion embedded in math” since most of the time, alphabetical and numerical order are uncontroversial, widely used standards. Yet no distinction is made. “These algorithms.”
For many with little understanding of how computer systems work, “the algorithm” becomes a proxy for “the programmers” and often assumes intent on the part of those programmers - but today, in many case programmers don't know in advance how their code will interact with all the other code in massive online systems that also interact with *other* massive online systems, all of them constantly changing on a near-daily basis. Nor do many discourses about algorithms fully take into the account how social media algorithms are constantly adapting in the continual back-and-forth between the human users of these systems and “the algorithm.”
With regards to these two comments from your great contribution Paul. Trying to differentiate two types of algorithms perhaps allows for unintentional or even purposeful dismissal of the social situatedness of the development of any algorithm. In your first example the reason that it is uncontroversial is that the algorithm lacks a level of complexity and therefore its design is very unlikely to end up with results that are encoded with any sort of concerning cultural context as we see it. But even in this example we can postulate a fictional environment where such an algorithm could have social ramifications. Imagine a society where those people whose names start with higher letters in an alphabet by default have more power than others. Then an alphabetizing system would reinforce such a social strata, and lack of recognition by a person using that algorithm in certain instances where ramifications would come through would represent irresponsible naivete. This is not that far a reach from histories of noble and non-aristocratic names in recent Western history. You sort the names, you sort the classes. I posit this speculative/real fictional example because there is always a creator crafting an algorithm and then applying it in practice. Algorithms are culture. Sometimes their creators are programmers, sometimes they are mathematicians, sometimes they are economists, and so on and so forth. Those algorithm crafters can only ever see the world through the eyes of their personal history (the Bourdiueian habitus) and whether they do it intentionally or not the work is imprinted by that history. Which leads to what I see as a problem of your second quote. The algorithm isn’t a proxy for the programmers, because they are part of an indivisible system. You can’t have one without the other. So, if we are going to critique the algorithms we must consider the programmers. And if we are going to critique the programmers we must consider the algorithms they create. They may not have intent, but they always have agency. A few structures in contemporary society however often let programmers or the companies they work for off the hook. One is the positivistic nature of much computer science which lacks an introspective and self-critical analysis to think about just what would be the ramifications of an algorithm once it interacts with a massive online system. Just because they don’t know–as you state–doesn’t mean they shouldn’t imagine what might happen. Nor does it mean that they shouldn’t be vigilant or adaptive about sociocultural impacts, which they often are not because that does not fit their motives or the motives of the corporations they work for. This rupture is what people in the humanities in media studies, digital humanities, etc. are often trying to bring to the table, a more systemic understanding of the ramifications of these actions. Second is the continued American passion for techno-libertarianism, which has gotten us into this huge mess with Google, Facebook, etc. Many people have known for a long time that these companies, and specifically the algorithms they use to do business, are aimed towards corporate expansion and not with the public good or betterment of individuals in mind. But, as the success stories of the 21st century they have for a long time been given the benefit of the doubt by consumers, tech critics, and government. Only now has there been the beginning of a reckoning. But for the majority of their existence Facebook and Google have been companies driven by advertising sales with some alternative services (search, mail, books, scholar, apps) provided for free to entice people into their ecosystem and enhance that business model. And the main focus of their work is to create algorithms that are (to quote Paul’s paraphrase of Knuth) well-defined, finite set of steps that produce unambiguous results. And in this case those unambiguous results of their algorithmic processing is more information to improvement their systems and to ultimately increase ad sales revenue, despite potential social harm. I go to this length because I think your comments that the algorithms are constantly changing and adapting lets the corporations and programmers off the hook. They are of course completely aware of this system flux and their algorithms are complicated enough to not only recognize, but to exploit that flux. Algorithms have input and output, and we should keep a focus in critiquing our digital era on what people intend for their algorithms to do, what types of outputs they are crafting for. Looking into that, we can better determine whether they are creating public systems that are not exploit and harming people through the intentional crafting of those algorithms. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center <http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy <http://jitpedagogy.org/> Co-Founder - NYCDH <http://nycdh.org/> E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com <http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition <https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition <https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book <http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/>
On Oct 29, 2021, at 4:25 PM, Paul N. Edwards <pedwards@stanford.edu> wrote:
Kimon, thanks for this interesting reaction. I agree with a lot of what you say. With regards to these two comments from your great contribution Paul. Trying to differentiate two types of algorithms perhaps allows for unintentional or even purposeful dismissal of the social situatedness of the development of any algorithm. In your first example the reason that it is uncontroversial is that the algorithm lacks a level of complexity and therefore its design is very unlikely to end up with results that are encoded with any sort of concerning cultural context as we see it. Your emailer, word processor, spreadsheet, calculator, and a million other pieces of software in daily use are full of algorithms to do uncontroversial things. It’s not that they’re not complex, since many of them are in fact quite complex - it’s that their purposes and outcomes don’t have much ethical significance. Vast numbers of algorithms do things such as controlling machinery (your car), modeling physical processes, and a billion other things that are not about human relations with each other. Social media infrastructure is qualitatively different because it’s entirely about human relations. Further, while the algorithms making up word processors and emailers are complex, they can be understood by a person examining the code. The AI and ML cases that are so concerning today are problematic because (a) they DO concern socially and ethically significant issues, and (b) in many cases, especially ML and neural networks, no one can understand the code because it’s not produced by people at all.. It has step-by-step procedures, but human beings literally can’t understand them - only the outcomes they produce. Neural nets are a great case to look at because they’re in fact very simple - there’s almost nothing but addition, subtraction, and multiplication going on under the hood, yet tracing out the interactions of all that math won’t tell you zip about how it recognizes a signature or a face. They’re “trained,” not coded in the more traditional sense. I’m not interested in letting programmers off the hook, and sometimes I’m sure they’re at fault. Instead, I'm interested in people having a clearer picture of what they’re talking about, and I think a lot of discourse about “the algorithm” targets the wrong thing. Tech companies absolutely need to be held responsible for the terrible outcomes of software they create, but this won’t happen because their programmers wake up and act ethical (though of course they should do that.) Where we differ is that given the complexity of systems with multiple millions of lines of code and teams of hundreds of coders working simultaneously, those coders can't anticipate the interactions that may result. To me, that’s not “letting them off the hook,” it’s focusing attention on what the hook is trying to catch, which is not a few bad apples (individuals) spoiling the barrel. It’s unanticipated (and unpredictable) consequences of complex system interactions. “Move fast and break things” sure did work - a lot got broken, and usually because the companies (as we have been hearing from the recent whistleblower cases) knew they were breaking things but were making too much money to stop. Focusing on individual coders as the evildoers won’t work, because that’s not usually the level where the problems occur. A major lesson of STS, and sociology in general, is that system effects aren’t under the direct control of lower-level actors. In your reply here, you lump programmers and tech firms together. I think tech firms, especially, and government regulation are more appropriate levels of agency than coders. I’m not sure we actually disagree about most of this, except that you seem to think programmers have more agency in complex systems than I do. Read my article, or look at Jenna Burrell’s interesting "How the machine ‘thinks’: Understanding opacity in machine learning algorithms” (2016). Best, Paul But even in this example we can postulate a fictional environment where such an algorithm could have social ramifications. Imagine a society where those people whose names start with higher letters in an alphabet by default have more power than others. Then an alphabetizing system would reinforce such a social strata, and lack of recognition by a person using that algorithm in certain instances where ramifications would come through would represent irresponsible naivete. This is not that far a reach from histories of noble and non-aristocratic names in recent Western history. You sort the names, you sort the classes. I posit this speculative/real fictional example because there is always a creator crafting an algorithm and then applying it in practice. Algorithms are culture. Sometimes their creators are programmers, sometimes they are mathematicians, sometimes they are economists, and so on and so forth. Those algorithm crafters can only ever see the world through the eyes of their personal history (the Bourdiueian habitus) and whether they do it intentionally or not the work is imprinted by that history. Which leads to what I see as a problem of your second quote. The algorithm isn’t a proxy for the programmers, because they are part of an indivisible system. You can’t have one without the other. So, if we are going to critique the algorithms we must consider the programmers. And if we are going to critique the programmers we must consider the algorithms they create. They may not have intent, but they always have agency. A few structures in contemporary society however often let programmers or the companies they work for off the hook. One is the positivistic nature of much computer science which lacks an introspective and self-critical analysis to think about just what would be the ramifications of an algorithm once it interacts with a massive online system. Just because they don’t know–as you state–doesn’t mean they shouldn’t imagine what might happen. Nor does it mean that they shouldn’t be vigilant or adaptive about sociocultural impacts, which they often are not because that does not fit their motives or the motives of the corporations they work for. This rupture is what people in the humanities in media studies, digital humanities, etc. are often trying to bring to the table, a more systemic understanding of the ramifications of these actions. Second is the continued American passion for techno-libertarianism, which has gotten us into this huge mess with Google, Facebook, etc. Many people have known for a long time that these companies, and specifically the algorithms they use to do business, are aimed towards corporate expansion and not with the public good or betterment of individuals in mind. But, as the success stories of the 21st century they have for a long time been given the benefit of the doubt by consumers, tech critics, and government. Only now has there been the beginning of a reckoning. But for the majority of their existence Facebook and Google have been companies driven by advertising sales with some alternative services (search, mail, books, scholar, apps) provided for free to entice people into their ecosystem and enhance that business model. And the main focus of their work is to create algorithms that are (to quote Paul’s paraphrase of Knuth) well-defined, finite set of steps that produce unambiguous results. And in this case those unambiguous results of their algorithmic processing is more information to improvement their systems and to ultimately increase ad sales revenue, despite potential social harm. I go to this length because I think your comments that the algorithms are constantly changing and adapting lets the corporations and programmers off the hook. They are of course completely aware of this system flux and their algorithms are complicated enough to not only recognize, but to exploit that flux. Algorithms have input and output, and we should keep a focus in critiquing our digital era on what people intend for their algorithms to do, what types of outputs they are crafting for. Looking into that, we can better determine whether they are creating public systems that are not exploit and harming people through the intentional crafting of those algorithms. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement<http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center<http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy<http://jitpedagogy.org/> Co-Founder - NYCDH<http://nycdh.org/> E kimon.keramidas@nyu.edu<mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com<http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition<https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition<https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book<http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/> On Oct 29, 2021, at 4:25 PM, Paul N. Edwards <pedwards@stanford.edu<mailto:pedwards@stanford.edu>> wrote: ________________________ Paul N. Edwards<https://profiles.stanford.edu/paul-edwards> Director, Program on Science, Technology & Society<http://sts.stanford.edu> William J. Perry Fellow in International Security and Senior Research Scholar Center for International Security and Cooperation<http://cisac.fsi.stanford.edu/> Co-Director, Stanford Existential Risks Initiative<https://cisac.fsi.stanford.edu/stanford-existential-risks-initiative> Stanford University Professor of Information<http://www.si.umich.edu/> and History<http://www.lsa.umich.edu/history/> (Emeritus) University of Michigan
Paul, I agree that I am sure that we probably agree on most of this, and making sure I wasn’t being antagonistic was something I was hoping to come across with in my writing. I’m glad it’s clear we are conversing and not fighting :) No all caps probably helps with that HAHAHA. I’ve loved this conversation from all aspects, including Tom and Ramesh’s great contributions lately as well. Really great stuff. I now see that you are worried about targeting individual coders as evil doers and that kind of direct stigmatization is not what I meant so we can agree on that. But I would push back against your claim that system effects aren’t under the control of lower-level actors (direct or indirect). In a network of actors there is push and pull from all directions and as similar minded small groups of actors act together they can influence the shape of a system. I am not picking on individual programmers, but I am concerned about the culture of programmers and the the groups of individuals that tend to constitute those communities. At the firm and regulator level that you mention (and which I agree are very much the main power players here) I believe that the impetus is most likely profit driven and in some cases driven by CEO-idealism that is blind to social impact (see Zuckerberg, Musk, and Bezos). But the communities of practice that are doing the work, developing the algorithms, and creating the programs to allow those algorithms to interrelate and execute are implicated by their constitution and worldview. That is where the positivism, techno-libertarianism, and disregard for concerns of intersectionality still occurs and which will both indirectly and directly influence the development of algorithms and programs. We know that the people developing these technologies are not representative of our society and that demographics are skewed so these gaps are inevitable. We also know that these communities can be antagonistic to critique and the kinds of perspectives that STS and sociology bring to the table. Just look at the letter that the Google engineer wrote back in 2018 and that made it onto the community boards there. The fact that he felt comfortable posting that material because he was confident enough that is telling. That is really the concerning issue and a reconsideration/critique of who is culpable for inequities in algorithms and software must happen not just at the governmental and boardroom level but must engage from top to bottom in how these industries situate themselves in relation to social responsibility in the development of their products and not in just being successful and profitable. Once again really enjoying the conversation and back and forth. Cheers, Kimon Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations Pronouns: He/Him New York University 14 University Place New York, NY 10003 Co-Director - ITMO University International Digital Humanities Research Center <http://dh.itmo.ru/en_about> Co-Founder - The Journal of Interactive Technology and Pedagogy <http://jitpedagogy.org/> Co-Founder - NYCDH <http://nycdh.org/> E kimon.keramidas@nyu.edu <mailto:kimon.keramidas@nyu.edu> W http://kimonkeramidas.com <http://kimonkeramidas.com/> The Sogdians: Influencers on the Silk Roads Exhibition <https://www.freersackler.si.edu/sogdians> The Interface Experience: Forty Years of Personal Computing Exhibition <https://www.bgc.bard.edu/gallery/exhibitions/10/the-interface-experience> The Interface Experience: A User’s Guide Winner of the 2016 Innovation in Print Design Award from the American Alliance of Museums Buy Book <http://store.bgc.bard.edu/the-interface-experience-a-users-guide-by-kimon-keramidas/>
On Oct 31, 2021, at 1:35 PM, Paul N. Edwards <pedwards@stanford.edu> wrote:
Kimon, thanks for this interesting reaction. I agree with a lot of what you say.
With regards to these two comments from your great contribution Paul. Trying to differentiate two types of algorithms perhaps allows for unintentional or even purposeful dismissal of the social situatedness of the development of any algorithm. In your first example the reason that it is uncontroversial is that the algorithm lacks a level of complexity and therefore its design is very unlikely to end up with results that are encoded with any sort of concerning cultural context as we see it.
Your emailer, word processor, spreadsheet, calculator, and a million other pieces of software in daily use are full of algorithms to do uncontroversial things. It’s not that they’re not complex, since many of them are in fact quite complex - it’s that their purposes and outcomes don’t have much ethical significance. Vast numbers of algorithms do things such as controlling machinery (your car), modeling physical processes, and a billion other things that are not about human relations with each other. Social media infrastructure is qualitatively different because it’s entirely about human relations.
Further, while the algorithms making up word processors and emailers are complex, they can be understood by a person examining the code. The AI and ML cases that are so concerning today are problematic because (a) they DO concern socially and ethically significant issues, and (b) in many cases, especially ML and neural networks, no one can understand the code because it’s not produced by people at all.. It has step-by-step procedures, but human beings literally can’t understand them - only the outcomes they produce. Neural nets are a great case to look at because they’re in fact very simple - there’s almost nothing but addition, subtraction, and multiplication going on under the hood, yet tracing out the interactions of all that math won’t tell you zip about how it recognizes a signature or a face. They’re “trained,” not coded in the more traditional sense.
I’m not interested in letting programmers off the hook, and sometimes I’m sure they’re at fault. Instead, I'm interested in people having a clearer picture of what they’re talking about, and I think a lot of discourse about “the algorithm” targets the wrong thing. Tech companies absolutely need to be held responsible for the terrible outcomes of software they create, but this won’t happen because their programmers wake up and act ethical (though of course they should do that.)
Where we differ is that given the complexity of systems with multiple millions of lines of code and teams of hundreds of coders working simultaneously, those coders can't anticipate the interactions that may result. To me, that’s not “letting them off the hook,” it’s focusing attention on what the hook is trying to catch, which is not a few bad apples (individuals) spoiling the barrel. It’s unanticipated (and unpredictable) consequences of complex system interactions. “Move fast and break things” sure did work - a lot got broken, and usually because the companies (as we have been hearing from the recent whistleblower cases) knew they were breaking things but were making too much money to stop.
Focusing on individual coders as the evildoers won’t work, because that’s not usually the level where the problems occur. A major lesson of STS, and sociology in general, is that system effects aren’t under the direct control of lower-level actors. In your reply here, you lump programmers and tech firms together. I think tech firms, especially, and government regulation are more appropriate levels of agency than coders.
I’m not sure we actually disagree about most of this, except that you seem to think programmers have more agency in complex systems than I do.
Read my article, or look at Jenna Burrell’s interesting "How the machine ‘thinks’: Understanding opacity in machine learning algorithms” (2016).
Best,
Paul
But even in this example we can postulate a fictional environment where such an algorithm could have social ramifications. Imagine a society where those people whose names start with higher letters in an alphabet by default have more power than others. Then an alphabetizing system would reinforce such a social strata, and lack of recognition by a person using that algorithm in certain instances where ramifications would come through would represent irresponsible naivete. This is not that far a reach from histories of noble and non-aristocratic names in recent Western history. You sort the names, you sort the classes.
I posit this speculative/real fictional example because there is always a creator crafting an algorithm and then applying it in practice. Algorithms are culture. Sometimes their creators are programmers, sometimes they are mathematicians, sometimes they are economists, and so on and so forth. Those algorithm crafters can only ever see the world through the eyes of their personal history (the Bourdiueian habitus) and whether they do it intentionally or not the work is imprinted by that history.
Which leads to what I see as a problem of your second quote. The algorithm isn’t a proxy for the programmers, because they are part of an indivisible system. You can’t have one without the other. So, if we are going to critique the algorithms we must consider the programmers. And if we are going to critique the programmers we must consider the algorithms they create. They may not have intent, but they always have agency. A few structures in contemporary society however often let programmers or the companies they work for off the hook.
One is the positivistic nature of much computer science which lacks an introspective and self-critical analysis to think about just what would be the ramifications of an algorithm once it interacts with a massive online system. Just because they don’t know–as you state–doesn’t mean they shouldn’t imagine what might happen. Nor does it mean that they shouldn’t be vigilant or adaptive about sociocultural impacts, which they often are not because that does not fit their motives or the motives of the corporations they work for. This rupture is what people in the humanities in media studies, digital humanities, etc. are often trying to bring to the table, a more systemic understanding of the ramifications of these actions.
Second is the continued American passion for techno-libertarianism, which has gotten us into this huge mess with Google, Facebook, etc. Many people have known for a long time that these companies, and specifically the algorithms they use to do business, are aimed towards corporate expansion and not with the public good or betterment of individuals in mind. But, as the success stories of the 21st century they have for a long time been given the benefit of the doubt by consumers, tech critics, and government. Only now has there been the beginning of a reckoning. But for the majority of their existence Facebook and Google have been companies driven by advertising sales with some alternative services (search, mail, books, scholar, apps) provided for free to entice people into their ecosystem and enhance that business model. And the main focus of their work is to create algorithms that are (to quote Paul’s paraphrase of Knuth) well-defined, finite set of steps that produce unambiguous results. And in this case those unambiguous results of their algorithmic processing is more information to improvement their systems and to ultimately increase ad sales revenue, despite potential social harm.
I go to this length because I think your comments that the algorithms are constantly changing and adapting lets the corporations and programmers off the hook. They are of course completely aware of this system flux and their algorithms are complicated enough to not only recognize, but to exploit that flux. Algorithms have input and output, and we should keep a focus in critiquing our digital era on what people intend for their algorithms to do, what types of outputs they are crafting for. Looking into that, we can better determine whether they are creating public systems that are not exploit and harming people through the intentional crafting of those algorithms.
Cheers, Kimon
Kimon Keramidas, Ph.D. Clinical Associate Professor, XE: Experimental Humanities & Social Engagement <http://as.nyu.edu/xe.html> Affiliated Faculty, Program in International Relations
Pronouns: He/Him
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On Oct 29, 2021, at 4:25 PM, Paul N. Edwards <pedwards@stanford.edu <mailto:pedwards@stanford.edu>> wrote:
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participants (10)
-
Alexandre Hocquet -
Allan Olley -
Ceruzzi, Paul -
Ed Summers -
Ellen Spertus -
Emiel van Miltenburg -
Julie Cohn -
Kimon Keramidas -
Maarten Bullynck -
Paul N. Edwards