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#digital-labor — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #digital-labor, aggregated by home.social.

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  1. The Social Codes of Tech Workers: Class Identity in Digital Capitalism

    Robert Dorschel

    (MIT Press, 2026)

    "Digital technologies shape nearly every aspect of our lives. Yet little attention has been paid to the tech workers who design and program these technologies. Instead, the spotlight often falls on two extremes: the elite class of tech entrepreneurs and the precarious digital proletariat of gig and crowd workers. This narrow focus has left a critical gap in understanding the middle-class professionals operating behind the scenes of digital capitalism.

    Drawing on over 50 original interviews and discourse analytical research conducted in the US and Germany, The Social Codes of Tech Workers takes readers deep into their hearts and minds. Robert Dorschel demonstrates how tech workers’ subjectivity is structured by a return of social critique, hybrid professional roles, and distinctive lifestyles. The book identifies tech workers as a contradictory class formation, oscillating between a spirit of emancipation and yet another spirit of capitalism. This work will appeal to scholars across disciplines concerned with digital labor, identity, and class, as well as to the broader public interested in the culture of the tech industry and the evolving future of work."

    mitpress.mit.edu/9780262553537

    #Capitalism #Class #DigitalCapitalism #Sociology #DigitalLabor #Programming #Coding

  2. The Social Codes of Tech Workers: Class Identity in Digital Capitalism

    Robert Dorschel

    (MIT Press, 2026)

    "Digital technologies shape nearly every aspect of our lives. Yet little attention has been paid to the tech workers who design and program these technologies. Instead, the spotlight often falls on two extremes: the elite class of tech entrepreneurs and the precarious digital proletariat of gig and crowd workers. This narrow focus has left a critical gap in understanding the middle-class professionals operating behind the scenes of digital capitalism.

    Drawing on over 50 original interviews and discourse analytical research conducted in the US and Germany, The Social Codes of Tech Workers takes readers deep into their hearts and minds. Robert Dorschel demonstrates how tech workers’ subjectivity is structured by a return of social critique, hybrid professional roles, and distinctive lifestyles. The book identifies tech workers as a contradictory class formation, oscillating between a spirit of emancipation and yet another spirit of capitalism. This work will appeal to scholars across disciplines concerned with digital labor, identity, and class, as well as to the broader public interested in the culture of the tech industry and the evolving future of work."

    mitpress.mit.edu/9780262553537

    #Capitalism #Class #DigitalCapitalism #Sociology #DigitalLabor #Programming #Coding

  3. The Social Codes of Tech Workers: Class Identity in Digital Capitalism

    Robert Dorschel

    (MIT Press, 2026)

    "Digital technologies shape nearly every aspect of our lives. Yet little attention has been paid to the tech workers who design and program these technologies. Instead, the spotlight often falls on two extremes: the elite class of tech entrepreneurs and the precarious digital proletariat of gig and crowd workers. This narrow focus has left a critical gap in understanding the middle-class professionals operating behind the scenes of digital capitalism.

    Drawing on over 50 original interviews and discourse analytical research conducted in the US and Germany, The Social Codes of Tech Workers takes readers deep into their hearts and minds. Robert Dorschel demonstrates how tech workers’ subjectivity is structured by a return of social critique, hybrid professional roles, and distinctive lifestyles. The book identifies tech workers as a contradictory class formation, oscillating between a spirit of emancipation and yet another spirit of capitalism. This work will appeal to scholars across disciplines concerned with digital labor, identity, and class, as well as to the broader public interested in the culture of the tech industry and the evolving future of work."

    mitpress.mit.edu/9780262553537

    #Capitalism #Class #DigitalCapitalism #Sociology #DigitalLabor #Programming #Coding

  4. The Social Codes of Tech Workers: Class Identity in Digital Capitalism

    Robert Dorschel

    (MIT Press, 2026)

    "Digital technologies shape nearly every aspect of our lives. Yet little attention has been paid to the tech workers who design and program these technologies. Instead, the spotlight often falls on two extremes: the elite class of tech entrepreneurs and the precarious digital proletariat of gig and crowd workers. This narrow focus has left a critical gap in understanding the middle-class professionals operating behind the scenes of digital capitalism.

    Drawing on over 50 original interviews and discourse analytical research conducted in the US and Germany, The Social Codes of Tech Workers takes readers deep into their hearts and minds. Robert Dorschel demonstrates how tech workers’ subjectivity is structured by a return of social critique, hybrid professional roles, and distinctive lifestyles. The book identifies tech workers as a contradictory class formation, oscillating between a spirit of emancipation and yet another spirit of capitalism. This work will appeal to scholars across disciplines concerned with digital labor, identity, and class, as well as to the broader public interested in the culture of the tech industry and the evolving future of work."

    mitpress.mit.edu/9780262553537

    #Capitalism #Class #DigitalCapitalism #Sociology #DigitalLabor #Programming #Coding

  5. The Social Codes of Tech Workers: Class Identity in Digital Capitalism

    Robert Dorschel

    (MIT Press, 2026)

    "Digital technologies shape nearly every aspect of our lives. Yet little attention has been paid to the tech workers who design and program these technologies. Instead, the spotlight often falls on two extremes: the elite class of tech entrepreneurs and the precarious digital proletariat of gig and crowd workers. This narrow focus has left a critical gap in understanding the middle-class professionals operating behind the scenes of digital capitalism.

    Drawing on over 50 original interviews and discourse analytical research conducted in the US and Germany, The Social Codes of Tech Workers takes readers deep into their hearts and minds. Robert Dorschel demonstrates how tech workers’ subjectivity is structured by a return of social critique, hybrid professional roles, and distinctive lifestyles. The book identifies tech workers as a contradictory class formation, oscillating between a spirit of emancipation and yet another spirit of capitalism. This work will appeal to scholars across disciplines concerned with digital labor, identity, and class, as well as to the broader public interested in the culture of the tech industry and the evolving future of work."

    mitpress.mit.edu/9780262553537

    #Capitalism #Class #DigitalCapitalism #Sociology #DigitalLabor #Programming #Coding

  6. Xu hướng lao động số thời AI: Các kỹ sư trẻ tại Philippines nay có thể điều khiển robot làm việc từ xa ở Nhật Bản. Điều này đang định hình lại cách chúng ta làm việc trong kỷ nguyên tự động hoá, mở ra một hình thức làm việc xuyên biên giới hoàn toàn mới.

    #LaoĐộngSố #AI #Robot #TựĐộngHoá #CôngNghệ #NhậtBản
    #DigitalLabor #FutureOfWork #RemoteWork #Robotics #Automation #Japan

    vtcnews.vn/ngoi-o-philippines-

  7. Xu hướng lao động số thời AI: Các kỹ sư trẻ tại Philippines nay có thể điều khiển robot làm việc từ xa ở Nhật Bản. Điều này đang định hình lại cách chúng ta làm việc trong kỷ nguyên tự động hoá, mở ra một hình thức làm việc xuyên biên giới hoàn toàn mới.

    #LaoĐộngSố #AI #Robot #TựĐộngHoá #CôngNghệ #NhậtBản
    #DigitalLabor #FutureOfWork #RemoteWork #Robotics #Automation #Japan

    vtcnews.vn/ngoi-o-philippines-

  8. Wikimedia just launched a database specifically for AI training. The same organization that runs Wikipedia—built entirely by human volunteers—now packages that knowledge for machines.

    The irony cuts deep. Humans created it. Machines will profit from it. The volunteers get nothing.

    #AI #Wikipedia #OpenData #DigitalLabor

    gizmodo.com/wikimedia-is-makin

  9. Wikimedia just launched a database specifically for AI training. The same organization that runs Wikipedia—built entirely by human volunteers—now packages that knowledge for machines.

    The irony cuts deep. Humans created it. Machines will profit from it. The volunteers get nothing.

    #AI #Wikipedia #OpenData #DigitalLabor

    gizmodo.com/wikimedia-is-makin

  10. Wikimedia just launched a database specifically for AI training. The same organization that runs Wikipedia—built entirely by human volunteers—now packages that knowledge for machines.

    The irony cuts deep. Humans created it. Machines will profit from it. The volunteers get nothing.

    #AI #Wikipedia #OpenData #DigitalLabor

    gizmodo.com/wikimedia-is-makin

  11. Wikimedia just launched a database specifically for AI training. The same organization that runs Wikipedia—built entirely by human volunteers—now packages that knowledge for machines.

    The irony cuts deep. Humans created it. Machines will profit from it. The volunteers get nothing.

    #AI #Wikipedia #OpenData #DigitalLabor

    gizmodo.com/wikimedia-is-makin

  12. What an interesting—and unsettling—read: Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” Is this the Uberization of intellectual work? #AIethics #DigitalLabor #CreativeRights Via @melaniemitchell.bsky.social

    The End of Publishing as We Kn...

  13. What an interesting—and unsettling—read: Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” Is this the Uberization of intellectual work? #AIethics #DigitalLabor #CreativeRights Via @melaniemitchell.bsky.social

    The End of Publishing as We Kn...

  14. What an interesting—and unsettling—read: Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” Is this the Uberization of intellectual work? #AIethics #DigitalLabor #CreativeRights Via @melaniemitchell.bsky.social

    The End of Publishing as We Kn...

  15. What an interesting—and unsettling—read:

    Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” But history tells us what happens when platforms remove the so-called middlemen: control shifts, labor is devalued, and creators lose agency.

    Is this the Uberization of intellectual work?

    theatlantic.com/technology/arc
    #AIethics #DigitalLabor #CreativeRights

  16. What an interesting—and unsettling—read:

    Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” But history tells us what happens when platforms remove the so-called middlemen: control shifts, labor is devalued, and creators lose agency.

    Is this the Uberization of intellectual work?

    theatlantic.com/technology/arc
    #AIethics #DigitalLabor #CreativeRights

  17. What an interesting—and unsettling—read:

    Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” But history tells us what happens when platforms remove the so-called middlemen: control shifts, labor is devalued, and creators lose agency.

    Is this the Uberization of intellectual work?

    theatlantic.com/technology/arc
    #AIethics #DigitalLabor #CreativeRights

  18. What an interesting—and unsettling—read:

    Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” But history tells us what happens when platforms remove the so-called middlemen: control shifts, labor is devalued, and creators lose agency.

    Is this the Uberization of intellectual work?

    theatlantic.com/technology/arc
    #AIethics #DigitalLabor #CreativeRights

  19. What an interesting—and unsettling—read:

    Google’s Sundar Pichai suggests a “marketplace” will emerge where creators simply “create for AI.” But history tells us what happens when platforms remove the so-called middlemen: control shifts, labor is devalued, and creators lose agency.

    Is this the Uberization of intellectual work?

    theatlantic.com/technology/arc
    #AIethics #DigitalLabor #CreativeRights

  20. What do platforms really do? 

    In 1986, David S. Landes wrote the essay, ‘What Do Bosses Really Do?’. He argues that the historical role of the ‘boss’ was an essential function for organizing production and connecting producers to markets. Digital platforms have become the new bosses. Platforms have the same functions of market creation, labor specialization, and management, but they have replaced the physical factory floor with algorithmic management. While their methods are novel, platforms are the direct descendants of the merchant-entrepreneurs and factory owners Landes described, solving the same historical problems of production in remarkably similar ways.

    Design for a Teacup (1880-1910) painting in high resolution by Noritake Factory. Original from The Smithsonian Institution. Digitally enhanced by rawpixel.

    So, why am I posting this on my own blog and not on a “platform”? I don’t view writing as a financial transaction. It is a hobby. By putting the financialization lens front and center, platforms are killing the mental space for hobbies. When you monetize tweets, you create incentive to craft tweets that create engagement in particular ways. Usually not healthy ways. 

    If we think of old media or traditional manufacturing, we can compare them to guilds. Guilds kept up prices and controlled production. With the simplification of tasks factories could hire workers who weren’t as highly skilled but didn’t need to be. Nowadays, why should any newspaper or TV channel’s output be limited by the amount of airtime or page space they have?

    Platforms take unskilled and train them. We are in the age of specialization of ideas.  Akin to the “the advantage of disaggregating a productive process”  Platforms leverage this by having many producers explore the same space through millions of different angles. This allows the platform to “purchase exactly that precise quantity of [skill] which is necessary for each process” —paying a viral star a lot and a niche creator a little, perfectly matching reward to market impact. Which is to say platforms make money through whatever sticks.  

    In Landes’s essay, Management became specialized, today management will become algorithmized. Platforms abstract away the issues that factory owners had such as embezzlement of resources, slacking off etc. Platforms don’t care how much or how little you produce, or even if you produce. If you do, the cash is yours (after a cut of course). 

    This may lead to a visceral reaction against platforms. This week when Substack raised a substantial amount they called the writers “the heroes of culture”. This should ring at least a tiny alarm in your head. The platform’s rhetoric of the creator-as-hero is a shrewd economic arrangement. In the putting-out system, the merchant-manufacturer “was able to shift capital expenditures (plant and equipment) to the worker”. Platforms do the same with creative risk. The writer, artist, or creator invests all the time and labor—the “capital” of creation—upfront. If they fail, they bear the entire loss. The platform, like the putter-outer, only participates in the upside, taking its cut from the successful ‘heroes’ while remaining insulated from the failures of the many.

    So what do platforms really do? They have resurrected the essential role of the boss for the digital age. They are the merchant-manufacturers who build the roads to market, and they are the factory owners who discipline production—not with overseers, but with incentive algorithms. By casting the creator as the hero, they obscure their own power and shift the immense risks of creative work onto the individual. While appearing to be mere background IT admins, they are, in fact, the central organizers of production, demonstrating that even in the 21st century, the fundamental challenges of coordinating labor and capital persist, and solving them remains, as it was in the 18th century, a very lucrative role.

    What Do Bosses Really Do?, David S. Landes, The Journal of Economic History, Vol. 46, No. 3 (Sep., 1986), pp. 585-623 (39 pages). https://www.jstor.org/stable/2121476

    #algorithmicManagement #Business #capitalism #creatorEconomy #digitalLabor #economicHistory #economics #futureOfWork #history #IndustrialRevolution #Leadership #management #monetization #philosophy #platforms #Startups #Substack #techCriticism #technology #writing

  21. What do platforms really do? 

    In 1986, David S. Landes wrote the essay, ‘What Do Bosses Really Do?’. He argues that the historical role of the ‘boss’ was an essential function for organizing production and connecting producers to markets. Digital platforms have become the new bosses. Platforms have the same functions of market creation, labor specialization, and management, but they have replaced the physical factory floor with algorithmic management. While their methods are novel, platforms are the direct descendants of the merchant-entrepreneurs and factory owners Landes described, solving the same historical problems of production in remarkably similar ways.

    Design for a Teacup (1880-1910) painting in high resolution by Noritake Factory. Original from The Smithsonian Institution. Digitally enhanced by rawpixel.

    So, why am I posting this on my own blog and not on a “platform”? I don’t view writing as a financial transaction. It is a hobby. By putting the financialization lens front and center, platforms are killing the mental space for hobbies. When you monetize tweets, you create incentive to craft tweets that create engagement in particular ways. Usually not healthy ways. 

    If we think of old media or traditional manufacturing, we can compare them to guilds. Guilds kept up prices and controlled production. With the simplification of tasks factories could hire workers who weren’t as highly skilled but didn’t need to be. Nowadays, why should any newspaper or TV channel’s output be limited by the amount of airtime or page space they have?

    Platforms take unskilled and train them. We are in the age of specialization of ideas.  Akin to the “the advantage of disaggregating a productive process”  Platforms leverage this by having many producers explore the same space through millions of different angles. This allows the platform to “purchase exactly that precise quantity of [skill] which is necessary for each process” —paying a viral star a lot and a niche creator a little, perfectly matching reward to market impact. Which is to say platforms make money through whatever sticks.  

    In Landes’s essay, Management became specialized, today management will become algorithmized. Platforms abstract away the issues that factory owners had such as embezzlement of resources, slacking off etc. Platforms don’t care how much or how little you produce, or even if you produce. If you do, the cash is yours (after a cut of course). 

    This may lead to a visceral reaction against platforms. This week when Substack raised a substantial amount they called the writers “the heroes of culture”. This should ring at least a tiny alarm in your head. The platform’s rhetoric of the creator-as-hero is a shrewd economic arrangement. In the putting-out system, the merchant-manufacturer “was able to shift capital expenditures (plant and equipment) to the worker”. Platforms do the same with creative risk. The writer, artist, or creator invests all the time and labor—the “capital” of creation—upfront. If they fail, they bear the entire loss. The platform, like the putter-outer, only participates in the upside, taking its cut from the successful ‘heroes’ while remaining insulated from the failures of the many.

    So what do platforms really do? They have resurrected the essential role of the boss for the digital age. They are the merchant-manufacturers who build the roads to market, and they are the factory owners who discipline production—not with overseers, but with incentive algorithms. By casting the creator as the hero, they obscure their own power and shift the immense risks of creative work onto the individual. While appearing to be mere background IT admins, they are, in fact, the central organizers of production, demonstrating that even in the 21st century, the fundamental challenges of coordinating labor and capital persist, and solving them remains, as it was in the 18th century, a very lucrative role.

    What Do Bosses Really Do?, David S. Landes, The Journal of Economic History, Vol. 46, No. 3 (Sep., 1986), pp. 585-623 (39 pages). https://www.jstor.org/stable/2121476

    #algorithmicManagement #Business #capitalism #creatorEconomy #digitalLabor #economicHistory #economics #futureOfWork #history #IndustrialRevolution #Leadership #management #monetization #philosophy #platforms #Startups #Substack #techCriticism #technology #writing

  22. What do platforms really do? 

    In 1986, David S. Landes wrote the essay, ‘What Do Bosses Really Do?’. He argues that the historical role of the ‘boss’ was an essential function for organizing production and connecting producers to markets. Digital platforms have become the new bosses. Platforms have the same functions of market creation, labor specialization, and management, but they have replaced the physical factory floor with algorithmic management. While their methods are novel, platforms are the direct descendants of the merchant-entrepreneurs and factory owners Landes described, solving the same historical problems of production in remarkably similar ways.

    Design for a Teacup (1880-1910) painting in high resolution by Noritake Factory. Original from The Smithsonian Institution. Digitally enhanced by rawpixel.

    So, why am I posting this on my own blog and not on a “platform”? I don’t view writing as a financial transaction. It is a hobby. By putting the financialization lens front and center, platforms are killing the mental space for hobbies. When you monetize tweets, you create incentive to craft tweets that create engagement in particular ways. Usually not healthy ways. 

    If we think of old media or traditional manufacturing, we can compare them to guilds. Guilds kept up prices and controlled production. With the simplification of tasks factories could hire workers who weren’t as highly skilled but didn’t need to be. Nowadays, why should any newspaper or TV channel’s output be limited by the amount of airtime or page space they have?

    Platforms take unskilled and train them. We are in the age of specialization of ideas.  Akin to the “the advantage of disaggregating a productive process”  Platforms leverage this by having many producers explore the same space through millions of different angles. This allows the platform to “purchase exactly that precise quantity of [skill] which is necessary for each process” —paying a viral star a lot and a niche creator a little, perfectly matching reward to market impact. Which is to say platforms make money through whatever sticks.  

    In Landes’s essay, Management became specialized, today management will become algorithmized. Platforms abstract away the issues that factory owners had such as embezzlement of resources, slacking off etc. Platforms don’t care how much or how little you produce, or even if you produce. If you do, the cash is yours (after a cut of course). 

    This may lead to a visceral reaction against platforms. This week when Substack raised a substantial amount they called the writers “the heroes of culture”. This should ring at least a tiny alarm in your head. The platform’s rhetoric of the creator-as-hero is a shrewd economic arrangement. In the putting-out system, the merchant-manufacturer “was able to shift capital expenditures (plant and equipment) to the worker”. Platforms do the same with creative risk. The writer, artist, or creator invests all the time and labor—the “capital” of creation—upfront. If they fail, they bear the entire loss. The platform, like the putter-outer, only participates in the upside, taking its cut from the successful ‘heroes’ while remaining insulated from the failures of the many.

    So what do platforms really do? They have resurrected the essential role of the boss for the digital age. They are the merchant-manufacturers who build the roads to market, and they are the factory owners who discipline production—not with overseers, but with incentive algorithms. By casting the creator as the hero, they obscure their own power and shift the immense risks of creative work onto the individual. While appearing to be mere background IT admins, they are, in fact, the central organizers of production, demonstrating that even in the 21st century, the fundamental challenges of coordinating labor and capital persist, and solving them remains, as it was in the 18th century, a very lucrative role.

    What Do Bosses Really Do?, David S. Landes, The Journal of Economic History, Vol. 46, No. 3 (Sep., 1986), pp. 585-623 (39 pages). https://www.jstor.org/stable/2121476

    #algorithmicManagement #Business #capitalism #creatorEconomy #digitalLabor #economicHistory #economics #futureOfWork #history #IndustrialRevolution #Leadership #management #monetization #philosophy #platforms #Startups #Substack #techCriticism #technology #writing

  23. What do platforms really do? 

    In 1986, David S. Landes wrote the essay, ‘What Do Bosses Really Do?’. He argues that the historical role of the ‘boss’ was an essential function for organizing production and connecting producers to markets. Digital platforms have become the new bosses. Platforms have the same functions of market creation, labor specialization, and management, but they have replaced the physical factory floor with algorithmic management. While their methods are novel, platforms are the direct descendants of the merchant-entrepreneurs and factory owners Landes described, solving the same historical problems of production in remarkably similar ways.

    Design for a Teacup (1880-1910) painting in high resolution by Noritake Factory. Original from The Smithsonian Institution. Digitally enhanced by rawpixel.

    So, why am I posting this on my own blog and not on a “platform”? I don’t view writing as a financial transaction. It is a hobby. By putting the financialization lens front and center, platforms are killing the mental space for hobbies. When you monetize tweets, you create incentive to craft tweets that create engagement in particular ways. Usually not healthy ways. 

    If we think of old media or traditional manufacturing, we can compare them to guilds. Guilds kept up prices and controlled production. With the simplification of tasks factories could hire workers who weren’t as highly skilled but didn’t need to be. Nowadays, why should any newspaper or TV channel’s output be limited by the amount of airtime or page space they have?

    Platforms take unskilled and train them. We are in the age of specialization of ideas.  Akin to the “the advantage of disaggregating a productive process”  Platforms leverage this by having many producers explore the same space through millions of different angles. This allows the platform to “purchase exactly that precise quantity of [skill] which is necessary for each process” —paying a viral star a lot and a niche creator a little, perfectly matching reward to market impact. Which is to say platforms make money through whatever sticks.  

    In Landes’s essay, Management became specialized, today management will become algorithmized. Platforms abstract away the issues that factory owners had such as embezzlement of resources, slacking off etc. Platforms don’t care how much or how little you produce, or even if you produce. If you do, the cash is yours (after a cut of course). 

    This may lead to a visceral reaction against platforms. This week when Substack raised a substantial amount they called the writers “the heroes of culture”. This should ring at least a tiny alarm in your head. The platform’s rhetoric of the creator-as-hero is a shrewd economic arrangement. In the putting-out system, the merchant-manufacturer “was able to shift capital expenditures (plant and equipment) to the worker”. Platforms do the same with creative risk. The writer, artist, or creator invests all the time and labor—the “capital” of creation—upfront. If they fail, they bear the entire loss. The platform, like the putter-outer, only participates in the upside, taking its cut from the successful ‘heroes’ while remaining insulated from the failures of the many.

    So what do platforms really do? They have resurrected the essential role of the boss for the digital age. They are the merchant-manufacturers who build the roads to market, and they are the factory owners who discipline production—not with overseers, but with incentive algorithms. By casting the creator as the hero, they obscure their own power and shift the immense risks of creative work onto the individual. While appearing to be mere background IT admins, they are, in fact, the central organizers of production, demonstrating that even in the 21st century, the fundamental challenges of coordinating labor and capital persist, and solving them remains, as it was in the 18th century, a very lucrative role.

    What Do Bosses Really Do?, David S. Landes, The Journal of Economic History, Vol. 46, No. 3 (Sep., 1986), pp. 585-623 (39 pages). https://www.jstor.org/stable/2121476

    #algorithmicManagement #Business #capitalism #creatorEconomy #digitalLabor #economicHistory #economics #futureOfWork #history #IndustrialRevolution #Leadership #management #monetization #philosophy #platforms #Startups #Substack #techCriticism #technology #writing

  24. New publication: “Ethics of Data Work”

    How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research:

    weizenbaum-institut.de/en/news

    Authors: T Yang, @strippel, A Keiner, @dylan, A Chávez, K Kauffman, M Pohl, C Sinders, @milamiceli

    #DataWork #FairWork #ResearchEthics #DigitalLabor #ResponsibleResearch #AIethics #LaborRights #research #openaccess @towardsfairwork

  25. New publication: “Ethics of Data Work”

    How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research:

    weizenbaum-institut.de/en/news

    Authors: T Yang, @strippel, A Keiner, @dylan, A Chávez, K Kauffman, M Pohl, C Sinders, @milamiceli

    #DataWork #FairWork #ResearchEthics #DigitalLabor #ResponsibleResearch #AIethics #LaborRights #research #openaccess @towardsfairwork

  26. New publication: “Ethics of Data Work”

    How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research:

    weizenbaum-institut.de/en/news

    Authors: T Yang, @strippel, A Keiner, @dylan, A Chávez, K Kauffman, M Pohl, C Sinders, @milamiceli

    #DataWork #FairWork #ResearchEthics #DigitalLabor #ResponsibleResearch #AIethics #LaborRights #research #openaccess @towardsfairwork

  27. New publication: “Ethics of Data Work”

    How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research:

    weizenbaum-institut.de/en/news

    Authors: T Yang, @strippel, A Keiner, @dylan, A Chávez, K Kauffman, M Pohl, C Sinders, @milamiceli

    #DataWork #FairWork #ResearchEthics #DigitalLabor #ResponsibleResearch #AIethics #LaborRights #research #openaccess @towardsfairwork

  28. New publication: “Ethics of Data Work”

    How can fairer working conditions for data workers be created? A new Discussion Paper outlines guidelines for the use of data work in academic research:

    weizenbaum-institut.de/en/news

    Authors: T Yang, @strippel, A Keiner, @dylan, A Chávez, K Kauffman, M Pohl, C Sinders, @milamiceli

    #DataWork #FairWork #ResearchEthics #DigitalLabor #ResponsibleResearch #AIethics #LaborRights #research #openaccess @towardsfairwork

  29. Is handover.ai/ a cool #knowledgemanagement hack (software video interviews you, generates a role-specific handoff kit) or a way to get human workers to offboard to #digitallabor replacements. Does what you know belong to you, or your employer?

  30. Is handover.ai/ a cool #knowledgemanagement hack (software video interviews you, generates a role-specific handoff kit) or a way to get human workers to offboard to #digitallabor replacements. Does what you know belong to you, or your employer?

  31. Is handover.ai/ a cool #knowledgemanagement hack (software video interviews you, generates a role-specific handoff kit) or a way to get human workers to offboard to #digitallabor replacements. Does what you know belong to you, or your employer?

  32. Is handover.ai/ a cool #knowledgemanagement hack (software video interviews you, generates a role-specific handoff kit) or a way to get human workers to offboard to #digitallabor replacements. Does what you know belong to you, or your employer?

  33. Is handover.ai/ a cool #knowledgemanagement hack (software video interviews you, generates a role-specific handoff kit) or a way to get human workers to offboard to #digitallabor replacements. Does what you know belong to you, or your employer?

  34. We might #tax close to the edge of harm. Watts and water at data centers (favoring harder-to-meter #decentralized #AI). Collect unemployment insurance (and #basicincome contributions) from employers of #digitallabor.

  35. We might #tax close to the edge of harm. Watts and water at data centers (favoring harder-to-meter #decentralized #AI). Collect unemployment insurance (and #basicincome contributions) from employers of #digitallabor.

  36. We might #tax close to the edge of harm. Watts and water at data centers (favoring harder-to-meter #decentralized #AI). Collect unemployment insurance (and #basicincome contributions) from employers of #digitallabor.

  37. We might #tax close to the edge of harm. Watts and water at data centers (favoring harder-to-meter #decentralized #AI). Collect unemployment insurance (and #basicincome contributions) from employers of #digitallabor.

  38. We might #tax close to the edge of harm. Watts and water at data centers (favoring harder-to-meter #decentralized #AI). Collect unemployment insurance (and #basicincome contributions) from employers of #digitallabor.

  39. 📄 What if we viewed digital economies not just as systems, but as labor-atories - sites of active class struggle and experimentation? In his new #wjds paper, Rafael Grohmann (@uoft) explores how digital labor in Latin America reflects this dynamic.

    ➡️ doi.org/10.34669/wi.wjds/5.1.6

    #research #socialscience #work #DigitalLabor #DigitalEconomies #PlatformWork #LatinAmerica #GlobalSouth #DigitalSovereignty #AI #DataColonialism #TechGovernance #WorkerOrganizing
    @DAIR @towardsfairwork

  40. 📄 What if we viewed digital economies not just as systems, but as labor-atories - sites of active class struggle and experimentation? In his new #wjds paper, Rafael Grohmann (@uoft) explores how digital labor in Latin America reflects this dynamic.

    ➡️ doi.org/10.34669/wi.wjds/5.1.6

    #research #socialscience #work #DigitalLabor #DigitalEconomies #PlatformWork #LatinAmerica #GlobalSouth #DigitalSovereignty #AI #DataColonialism #TechGovernance #WorkerOrganizing
    @DAIR @towardsfairwork

  41. 📄 What if we viewed digital economies not just as systems, but as labor-atories - sites of active class struggle and experimentation? In his new #wjds paper, Rafael Grohmann (@uoft) explores how digital labor in Latin America reflects this dynamic.

    ➡️ doi.org/10.34669/wi.wjds/5.1.6

    #research #socialscience #work #DigitalLabor #DigitalEconomies #PlatformWork #LatinAmerica #GlobalSouth #DigitalSovereignty #AI #DataColonialism #TechGovernance #WorkerOrganizing
    @DAIR @towardsfairwork

  42. 📄 What if we viewed digital economies not just as systems, but as labor-atories - sites of active class struggle and experimentation? In his new #wjds paper, Rafael Grohmann (@uoft) explores how digital labor in Latin America reflects this dynamic.

    ➡️ doi.org/10.34669/wi.wjds/5.1.6

    #research #socialscience #work #DigitalLabor #DigitalEconomies #PlatformWork #LatinAmerica #GlobalSouth #DigitalSovereignty #AI #DataColonialism #TechGovernance #WorkerOrganizing
    @DAIR @towardsfairwork

  43. 📄 What if we viewed digital economies not just as systems, but as labor-atories - sites of active class struggle and experimentation? In his new #wjds paper, Rafael Grohmann (@uoft) explores how digital labor in Latin America reflects this dynamic.

    ➡️ doi.org/10.34669/wi.wjds/5.1.6

    #research #socialscience #work #DigitalLabor #DigitalEconomies #PlatformWork #LatinAmerica #GlobalSouth #DigitalSovereignty #AI #DataColonialism #TechGovernance #WorkerOrganizing
    @DAIR @towardsfairwork

  44. UNPAID LABOR, ALGORITHMIC DENIAL, AND SYSTEMIC SABOTAGE
    May 7, 2025

    YouTube built an empire on our free time, our passion, our technical investments—and above all, on a promise: “share what you love, and the audience will follow.” Thousands of independent creators believed it. So did I. For ten years, I invested, produced, commented, hosted, edited, imported, repaired—with discipline, ambition, and stubborn hope, all in the shadows. What I discovered wasn’t opportunity. It was silence. A system of invisible filters, algorithmic contempt, and structural sabotage. An economic machine built on the unpaid, uncredited labor of creators who believed they had a chance. A platform that shows your video to four people, then punishes you for not being “engaging” enough. This four-part investigation details what YouTube has truly cost me—in money, in time, in mental health, and in collective momentum. Every number is cross-checked. Every claim is lived. Every example is documented. This is not a rant. It’s a report from inside the wreckage.
    ¯

    _
    INVISIBLE COMMENTS: 33,000 CONTRIBUTIONS THROWN IN THE TRASH

    As part of my investigation, I decided to calculate what I’ve lost on YouTube. Not an easy task: if all my videos are shadowbanned, there’s no way to measure the value of that work through view counts. But I realized something else. The comments I leave on channels—whether they perform well or not—receive wildly different levels of visibility. It’s not unusual for one of my comments to get 500 likes and 25 replies within 24 hours. In other words, when I’m allowed to exist, I know how to draw attention.
    ¯

    _
    33,000 COMMENTS... FOR WHAT?

    In 10 years of using the platform, I’ve posted 33,000 comments. Each one crafted, thoughtful, polished, aimed at grabbing attention. It’s a real creative effort: to spontaneously come up with something insightful to say, every day, for a decade. I’ve contributed to the YouTube community through my likes, my reactions, my input. These comments—modest, yes, but genuine—have helped sustain and grow the platform. If each comment takes roughly 3 minutes to write, that’s 99,000 minutes of my life—60 days spent commenting non-stop. Two entire months. Two months talking into the void.
    ¯

    _
    ALGORITHMIC INVISIBILITY

    By default, not all comments are shown. The “Top comments” filter displays only a select few. You have to manually click on “Newest first” to see the rest. The way "Top comments" are chosen remains vague, and there’s no indication of whether some comments are deliberately hidden. When you load a page, your own comment always appears first—but only to you. Officially, it’s for “ergonomics.” Unofficially, it gives you the illusion that your opinion matters. I estimate that, on average, one out of six comments is invisible to other users. By comparing visible and hidden replies, a simple estimate emerges: over the course of 12 months, 2 months’ worth of comments go straight to the trash.
    ¯

    _
    TWO MONTHS A YEAR WRITING INTO THE VOID

    If I’ve spent 60 days commenting over 10 years, that averages out to 6 days per year. Roughly 12 hours of writing every month. So each year, I’m condemned to 1 full day (out of 6) of content invisibilized (while 5 out of 6 remains visible), dumped into a void of discarded contributions. I’m not claiming every comment I write is essential, but the complete lack of notification and the arbitrary nature of this filtering raise both moral and legal concerns. To clarify: if two months of total usage equal 24 hours of actual writing, that’s because I don’t use YouTube continuously. These 24 hours spread across two months mean I spend about 24 minutes per day writing. And if writing time represents just one-fifth of my overall engagement — including watching — that adds up to more than 2.5 hours per day on the platform. Every single day. For ten years. That’s not passive use — it’s sustained, intensive participation. On average, this means that 15 to 20% of my time spent writing comments is dumped into a virtual landfill. In my case, that’s 24 hours of annual activity wiped out. But the proportion is what matters — it scales with your usage. You see the problem.
    ¯

    _
    THE BIG PLAYERS RISE, THE REST ARE ERASED

    From what I’ve observed, most major YouTubers benefit from a system that automatically boosts superficial comments to the top. The algorithm favors them. It’s always the same pattern: the system benefits a few, at the expense of everyone else.
    ¯

    _
    AN IGNORED EDITORIAL VALUE

    In print journalism, a 1,500-word exclusive freelance piece is typically valued at around €300. Most YouTube comments are a few lines long—maybe 25 words. Mine often exceed 250 words. That’s ten times the average length, and far more structured. They’re not throwaway reactions, but crafted contributions: thoughtful, contextual, engaging. If we apply the same rate, then 30 such comments ≈ €1,500. It’s a bold comparison—but a fair one, when you account for quality, relevance, and editorial intent. 33,000 comments = €1,650,000 of unpaid contribution to YouTube. YouTube never rewards this kind of engagement. It doesn’t promote channels where you comment frequently. The platform isn’t designed to recognize individuals. It’s designed to extract value—for itself.
    ¯

    _
    ||#HSLdiary #HSLmichael

    #DigitalLabor #InvisibleWork #ContentModeration #PlatformCapitalism #TechCriticism #UserEngagement

  45. UNPAID LABOR, ALGORITHMIC DENIAL, AND SYSTEMIC SABOTAGE
    May 7, 2025

    YouTube built an empire on our free time, our passion, our technical investments—and above all, on a promise: “share what you love, and the audience will follow.” Thousands of independent creators believed it. So did I. For ten years, I invested, produced, commented, hosted, edited, imported, repaired—with discipline, ambition, and stubborn hope, all in the shadows. What I discovered wasn’t opportunity. It was silence. A system of invisible filters, algorithmic contempt, and structural sabotage. An economic machine built on the unpaid, uncredited labor of creators who believed they had a chance. A platform that shows your video to four people, then punishes you for not being “engaging” enough. This four-part investigation details what YouTube has truly cost me—in money, in time, in mental health, and in collective momentum. Every number is cross-checked. Every claim is lived. Every example is documented. This is not a rant. It’s a report from inside the wreckage.
    ¯

    _
    INVISIBLE COMMENTS: 33,000 CONTRIBUTIONS THROWN IN THE TRASH

    As part of my investigation, I decided to calculate what I’ve lost on YouTube. Not an easy task: if all my videos are shadowbanned, there’s no way to measure the value of that work through view counts. But I realized something else. The comments I leave on channels—whether they perform well or not—receive wildly different levels of visibility. It’s not unusual for one of my comments to get 500 likes and 25 replies within 24 hours. In other words, when I’m allowed to exist, I know how to draw attention.
    ¯

    _
    33,000 COMMENTS... FOR WHAT?

    In 10 years of using the platform, I’ve posted 33,000 comments. Each one crafted, thoughtful, polished, aimed at grabbing attention. It’s a real creative effort: to spontaneously come up with something insightful to say, every day, for a decade. I’ve contributed to the YouTube community through my likes, my reactions, my input. These comments—modest, yes, but genuine—have helped sustain and grow the platform. If each comment takes roughly 3 minutes to write, that’s 99,000 minutes of my life—60 days spent commenting non-stop. Two entire months. Two months talking into the void.
    ¯

    _
    ALGORITHMIC INVISIBILITY

    By default, not all comments are shown. The “Top comments” filter displays only a select few. You have to manually click on “Newest first” to see the rest. The way "Top comments" are chosen remains vague, and there’s no indication of whether some comments are deliberately hidden. When you load a page, your own comment always appears first—but only to you. Officially, it’s for “ergonomics.” Unofficially, it gives you the illusion that your opinion matters. I estimate that, on average, one out of six comments is invisible to other users. By comparing visible and hidden replies, a simple estimate emerges: over the course of 12 months, 2 months’ worth of comments go straight to the trash.
    ¯

    _
    TWO MONTHS A YEAR WRITING INTO THE VOID

    If I’ve spent 60 days commenting over 10 years, that averages out to 6 days per year. Roughly 12 hours of writing every month. So each year, I’m condemned to 1 full day (out of 6) of content invisibilized (while 5 out of 6 remains visible), dumped into a void of discarded contributions. I’m not claiming every comment I write is essential, but the complete lack of notification and the arbitrary nature of this filtering raise both moral and legal concerns. To clarify: if two months of total usage equal 24 hours of actual writing, that’s because I don’t use YouTube continuously. These 24 hours spread across two months mean I spend about 24 minutes per day writing. And if writing time represents just one-fifth of my overall engagement — including watching — that adds up to more than 2.5 hours per day on the platform. Every single day. For ten years. That’s not passive use — it’s sustained, intensive participation. On average, this means that 15 to 20% of my time spent writing comments is dumped into a virtual landfill. In my case, that’s 24 hours of annual activity wiped out. But the proportion is what matters — it scales with your usage. You see the problem.
    ¯

    _
    THE BIG PLAYERS RISE, THE REST ARE ERASED

    From what I’ve observed, most major YouTubers benefit from a system that automatically boosts superficial comments to the top. The algorithm favors them. It’s always the same pattern: the system benefits a few, at the expense of everyone else.
    ¯

    _
    AN IGNORED EDITORIAL VALUE

    In print journalism, a 1,500-word exclusive freelance piece is typically valued at around €300. Most YouTube comments are a few lines long—maybe 25 words. Mine often exceed 250 words. That’s ten times the average length, and far more structured. They’re not throwaway reactions, but crafted contributions: thoughtful, contextual, engaging. If we apply the same rate, then 30 such comments ≈ €1,500. It’s a bold comparison—but a fair one, when you account for quality, relevance, and editorial intent. 33,000 comments = €1,650,000 of unpaid contribution to YouTube. YouTube never rewards this kind of engagement. It doesn’t promote channels where you comment frequently. The platform isn’t designed to recognize individuals. It’s designed to extract value—for itself.
    ¯

    _
    ||#HSLdiary #HSLmichael

    #DigitalLabor #InvisibleWork #ContentModeration #PlatformCapitalism #TechCriticism #UserEngagement

  46. UNPAID LABOR, ALGORITHMIC DENIAL, AND SYSTEMIC SABOTAGE
    May 7, 2025

    YouTube built an empire on our free time, our passion, our technical investments—and above all, on a promise: “share what you love, and the audience will follow.” Thousands of independent creators believed it. So did I. For ten years, I invested, produced, commented, hosted, edited, imported, repaired—with discipline, ambition, and stubborn hope, all in the shadows. What I discovered wasn’t opportunity. It was silence. A system of invisible filters, algorithmic contempt, and structural sabotage. An economic machine built on the unpaid, uncredited labor of creators who believed they had a chance. A platform that shows your video to four people, then punishes you for not being “engaging” enough. This four-part investigation details what YouTube has truly cost me—in money, in time, in mental health, and in collective momentum. Every number is cross-checked. Every claim is lived. Every example is documented. This is not a rant. It’s a report from inside the wreckage.
    ¯

    _
    INVISIBLE COMMENTS: 33,000 CONTRIBUTIONS THROWN IN THE TRASH

    As part of my investigation, I decided to calculate what I’ve lost on YouTube. Not an easy task: if all my videos are shadowbanned, there’s no way to measure the value of that work through view counts. But I realized something else. The comments I leave on channels—whether they perform well or not—receive wildly different levels of visibility. It’s not unusual for one of my comments to get 500 likes and 25 replies within 24 hours. In other words, when I’m allowed to exist, I know how to draw attention.
    ¯

    _
    33,000 COMMENTS... FOR WHAT?

    In 10 years of using the platform, I’ve posted 33,000 comments. Each one crafted, thoughtful, polished, aimed at grabbing attention. It’s a real creative effort: to spontaneously come up with something insightful to say, every day, for a decade. I’ve contributed to the YouTube community through my likes, my reactions, my input. These comments—modest, yes, but genuine—have helped sustain and grow the platform. If each comment takes roughly 3 minutes to write, that’s 99,000 minutes of my life—60 days spent commenting non-stop. Two entire months. Two months talking into the void.
    ¯

    _
    ALGORITHMIC INVISIBILITY

    By default, not all comments are shown. The “Top comments” filter displays only a select few. You have to manually click on “Newest first” to see the rest. The way "Top comments" are chosen remains vague, and there’s no indication of whether some comments are deliberately hidden. When you load a page, your own comment always appears first—but only to you. Officially, it’s for “ergonomics.” Unofficially, it gives you the illusion that your opinion matters. I estimate that, on average, one out of six comments is invisible to other users. By comparing visible and hidden replies, a simple estimate emerges: over the course of 12 months, 2 months’ worth of comments go straight to the trash.
    ¯

    _
    TWO MONTHS A YEAR WRITING INTO THE VOID

    If I’ve spent 60 days commenting over 10 years, that averages out to 6 days per year. Roughly 12 hours of writing every month. So each year, I’m condemned to 1 full day (out of 6) of content invisibilized (while 5 out of 6 remains visible), dumped into a void of discarded contributions. I’m not claiming every comment I write is essential, but the complete lack of notification and the arbitrary nature of this filtering raise both moral and legal concerns. To clarify: if two months of total usage equal 24 hours of actual writing, that’s because I don’t use YouTube continuously. These 24 hours spread across two months mean I spend about 24 minutes per day writing. And if writing time represents just one-fifth of my overall engagement — including watching — that adds up to more than 2.5 hours per day on the platform. Every single day. For ten years. That’s not passive use — it’s sustained, intensive participation. On average, this means that 15 to 20% of my time spent writing comments is dumped into a virtual landfill. In my case, that’s 24 hours of annual activity wiped out. But the proportion is what matters — it scales with your usage. You see the problem.
    ¯

    _
    THE BIG PLAYERS RISE, THE REST ARE ERASED

    From what I’ve observed, most major YouTubers benefit from a system that automatically boosts superficial comments to the top. The algorithm favors them. It’s always the same pattern: the system benefits a few, at the expense of everyone else.
    ¯

    _
    AN IGNORED EDITORIAL VALUE

    In print journalism, a 1,500-word exclusive freelance piece is typically valued at around €300. Most YouTube comments are a few lines long—maybe 25 words. Mine often exceed 250 words. That’s ten times the average length, and far more structured. They’re not throwaway reactions, but crafted contributions: thoughtful, contextual, engaging. If we apply the same rate, then 30 such comments ≈ €1,500. It’s a bold comparison—but a fair one, when you account for quality, relevance, and editorial intent. 33,000 comments = €1,650,000 of unpaid contribution to YouTube. YouTube never rewards this kind of engagement. It doesn’t promote channels where you comment frequently. The platform isn’t designed to recognize individuals. It’s designed to extract value—for itself.
    ¯

    _
    ||#HSLdiary #HSLmichael

    #DigitalLabor #InvisibleWork #ContentModeration #PlatformCapitalism #TechCriticism #UserEngagement

  47. UNPAID LABOR, ALGORITHMIC DENIAL, AND SYSTEMIC SABOTAGE
    May 7, 2025

    YouTube built an empire on our free time, our passion, our technical investments—and above all, on a promise: “share what you love, and the audience will follow.” Thousands of independent creators believed it. So did I. For ten years, I invested, produced, commented, hosted, edited, imported, repaired—with discipline, ambition, and stubborn hope, all in the shadows. What I discovered wasn’t opportunity. It was silence. A system of invisible filters, algorithmic contempt, and structural sabotage. An economic machine built on the unpaid, uncredited labor of creators who believed they had a chance. A platform that shows your video to four people, then punishes you for not being “engaging” enough. This four-part investigation details what YouTube has truly cost me—in money, in time, in mental health, and in collective momentum. Every number is cross-checked. Every claim is lived. Every example is documented. This is not a rant. It’s a report from inside the wreckage.
    ¯

    _
    INVISIBLE COMMENTS: 33,000 CONTRIBUTIONS THROWN IN THE TRASH

    As part of my investigation, I decided to calculate what I’ve lost on YouTube. Not an easy task: if all my videos are shadowbanned, there’s no way to measure the value of that work through view counts. But I realized something else. The comments I leave on channels—whether they perform well or not—receive wildly different levels of visibility. It’s not unusual for one of my comments to get 500 likes and 25 replies within 24 hours. In other words, when I’m allowed to exist, I know how to draw attention.
    ¯

    _
    33,000 COMMENTS... FOR WHAT?

    In 10 years of using the platform, I’ve posted 33,000 comments. Each one crafted, thoughtful, polished, aimed at grabbing attention. It’s a real creative effort: to spontaneously come up with something insightful to say, every day, for a decade. I’ve contributed to the YouTube community through my likes, my reactions, my input. These comments—modest, yes, but genuine—have helped sustain and grow the platform. If each comment takes roughly 3 minutes to write, that’s 99,000 minutes of my life—60 days spent commenting non-stop. Two entire months. Two months talking into the void.
    ¯

    _
    ALGORITHMIC INVISIBILITY

    By default, not all comments are shown. The “Top comments” filter displays only a select few. You have to manually click on “Newest first” to see the rest. The way "Top comments" are chosen remains vague, and there’s no indication of whether some comments are deliberately hidden. When you load a page, your own comment always appears first—but only to you. Officially, it’s for “ergonomics.” Unofficially, it gives you the illusion that your opinion matters. I estimate that, on average, one out of six comments is invisible to other users. By comparing visible and hidden replies, a simple estimate emerges: over the course of 12 months, 2 months’ worth of comments go straight to the trash.
    ¯

    _
    TWO MONTHS A YEAR WRITING INTO THE VOID

    If I’ve spent 60 days commenting over 10 years, that averages out to 6 days per year. Roughly 12 hours of writing every month. So each year, I’m condemned to 1 full day (out of 6) of content invisibilized (while 5 out of 6 remains visible), dumped into a void of discarded contributions. I’m not claiming every comment I write is essential, but the complete lack of notification and the arbitrary nature of this filtering raise both moral and legal concerns. To clarify: if two months of total usage equal 24 hours of actual writing, that’s because I don’t use YouTube continuously. These 24 hours spread across two months mean I spend about 24 minutes per day writing. And if writing time represents just one-fifth of my overall engagement — including watching — that adds up to more than 2.5 hours per day on the platform. Every single day. For ten years. That’s not passive use — it’s sustained, intensive participation. On average, this means that 15 to 20% of my time spent writing comments is dumped into a virtual landfill. In my case, that’s 24 hours of annual activity wiped out. But the proportion is what matters — it scales with your usage. You see the problem.
    ¯

    _
    THE BIG PLAYERS RISE, THE REST ARE ERASED

    From what I’ve observed, most major YouTubers benefit from a system that automatically boosts superficial comments to the top. The algorithm favors them. It’s always the same pattern: the system benefits a few, at the expense of everyone else.
    ¯

    _
    AN IGNORED EDITORIAL VALUE

    In print journalism, a 1,500-word exclusive freelance piece is typically valued at around €300. Most YouTube comments are a few lines long—maybe 25 words. Mine often exceed 250 words. That’s ten times the average length, and far more structured. They’re not throwaway reactions, but crafted contributions: thoughtful, contextual, engaging. If we apply the same rate, then 30 such comments ≈ €1,500. It’s a bold comparison—but a fair one, when you account for quality, relevance, and editorial intent. 33,000 comments = €1,650,000 of unpaid contribution to YouTube. YouTube never rewards this kind of engagement. It doesn’t promote channels where you comment frequently. The platform isn’t designed to recognize individuals. It’s designed to extract value—for itself.
    ¯

    _
    ||#HSLdiary #HSLmichael

    #DigitalLabor #InvisibleWork #ContentModeration #PlatformCapitalism #TechCriticism #UserEngagement

  48. UNPAID LABOR, ALGORITHMIC DENIAL, AND SYSTEMIC SABOTAGE
    May 7, 2025

    YouTube built an empire on our free time, our passion, our technical investments—and above all, on a promise: “share what you love, and the audience will follow.” Thousands of independent creators believed it. So did I. For ten years, I invested, produced, commented, hosted, edited, imported, repaired—with discipline, ambition, and stubborn hope, all in the shadows. What I discovered wasn’t opportunity. It was silence. A system of invisible filters, algorithmic contempt, and structural sabotage. An economic machine built on the unpaid, uncredited labor of creators who believed they had a chance. A platform that shows your video to four people, then punishes you for not being “engaging” enough. This four-part investigation details what YouTube has truly cost me—in money, in time, in mental health, and in collective momentum. Every number is cross-checked. Every claim is lived. Every example is documented. This is not a rant. It’s a report from inside the wreckage.
    ¯

    _
    INVISIBLE COMMENTS: 33,000 CONTRIBUTIONS THROWN IN THE TRASH

    As part of my investigation, I decided to calculate what I’ve lost on YouTube. Not an easy task: if all my videos are shadowbanned, there’s no way to measure the value of that work through view counts. But I realized something else. The comments I leave on channels—whether they perform well or not—receive wildly different levels of visibility. It’s not unusual for one of my comments to get 500 likes and 25 replies within 24 hours. In other words, when I’m allowed to exist, I know how to draw attention.
    ¯

    _
    33,000 COMMENTS... FOR WHAT?

    In 10 years of using the platform, I’ve posted 33,000 comments. Each one crafted, thoughtful, polished, aimed at grabbing attention. It’s a real creative effort: to spontaneously come up with something insightful to say, every day, for a decade. I’ve contributed to the YouTube community through my likes, my reactions, my input. These comments—modest, yes, but genuine—have helped sustain and grow the platform. If each comment takes roughly 3 minutes to write, that’s 99,000 minutes of my life—60 days spent commenting non-stop. Two entire months. Two months talking into the void.
    ¯

    _
    ALGORITHMIC INVISIBILITY

    By default, not all comments are shown. The “Top comments” filter displays only a select few. You have to manually click on “Newest first” to see the rest. The way "Top comments" are chosen remains vague, and there’s no indication of whether some comments are deliberately hidden. When you load a page, your own comment always appears first—but only to you. Officially, it’s for “ergonomics.” Unofficially, it gives you the illusion that your opinion matters. I estimate that, on average, one out of six comments is invisible to other users. By comparing visible and hidden replies, a simple estimate emerges: over the course of 12 months, 2 months’ worth of comments go straight to the trash.
    ¯

    _
    TWO MONTHS A YEAR WRITING INTO THE VOID

    If I’ve spent 60 days commenting over 10 years, that averages out to 6 days per year. Roughly 12 hours of writing every month. So each year, I’m condemned to 1 full day (out of 6) of content invisibilized (while 5 out of 6 remains visible), dumped into a void of discarded contributions. I’m not claiming every comment I write is essential, but the complete lack of notification and the arbitrary nature of this filtering raise both moral and legal concerns. To clarify: if two months of total usage equal 24 hours of actual writing, that’s because I don’t use YouTube continuously. These 24 hours spread across two months mean I spend about 24 minutes per day writing. And if writing time represents just one-fifth of my overall engagement — including watching — that adds up to more than 2.5 hours per day on the platform. Every single day. For ten years. That’s not passive use — it’s sustained, intensive participation. On average, this means that 15 to 20% of my time spent writing comments is dumped into a virtual landfill. In my case, that’s 24 hours of annual activity wiped out. But the proportion is what matters — it scales with your usage. You see the problem.
    ¯

    _
    THE BIG PLAYERS RISE, THE REST ARE ERASED

    From what I’ve observed, most major YouTubers benefit from a system that automatically boosts superficial comments to the top. The algorithm favors them. It’s always the same pattern: the system benefits a few, at the expense of everyone else.
    ¯

    _
    AN IGNORED EDITORIAL VALUE

    In print journalism, a 1,500-word exclusive freelance piece is typically valued at around €300. Most YouTube comments are a few lines long—maybe 25 words. Mine often exceed 250 words. That’s ten times the average length, and far more structured. They’re not throwaway reactions, but crafted contributions: thoughtful, contextual, engaging. If we apply the same rate, then 30 such comments ≈ €1,500. It’s a bold comparison—but a fair one, when you account for quality, relevance, and editorial intent. 33,000 comments = €1,650,000 of unpaid contribution to YouTube. YouTube never rewards this kind of engagement. It doesn’t promote channels where you comment frequently. The platform isn’t designed to recognize individuals. It’s designed to extract value—for itself.
    ¯

    _
    ||#HSLdiary #HSLmichael

    #DigitalLabor #InvisibleWork #ContentModeration #PlatformCapitalism #TechCriticism #UserEngagement

  49. Labor-atories of Digital EconomiesLatin America as a Site of Struggles and Experimentation

    Rafael Grohmann

    "This article argues that digital labor developments and struggles are laboratories of digital economies, with a special focus on Latin America. This means that, on the one hand, capital is experimenting with and updating forms of control and exploitation through the long trajectory of informality and de-pendency and, on the other hand, workers are trying and experimenting with forms of organizing and collectivities, also updating Latin America’s rich histories of organizing, solidarity economies, and community technologies. The emphasis on “labor” implies that these laboratories are products of class struggles and capital – labor relationships. The paper unpacks the argument with four short insights from ongoing research, addressing 1) Latin America as more than a research site, 2) the updating of informality in the Latin American artificial intelligence context, 3) the global implications of data work, artifi-cial intelligence value chains, and the cultural sector, and 4) digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy."

    ojs.weizenbaum-institut.de/ind

    #LatinAmerica #DigitalEconomy #DigitalLabor #AI #Informality #Digital Sovereignty

  50. Labor-atories of Digital EconomiesLatin America as a Site of Struggles and Experimentation

    Rafael Grohmann

    "This article argues that digital labor developments and struggles are laboratories of digital economies, with a special focus on Latin America. This means that, on the one hand, capital is experimenting with and updating forms of control and exploitation through the long trajectory of informality and de-pendency and, on the other hand, workers are trying and experimenting with forms of organizing and collectivities, also updating Latin America’s rich histories of organizing, solidarity economies, and community technologies. The emphasis on “labor” implies that these laboratories are products of class struggles and capital – labor relationships. The paper unpacks the argument with four short insights from ongoing research, addressing 1) Latin America as more than a research site, 2) the updating of informality in the Latin American artificial intelligence context, 3) the global implications of data work, artifi-cial intelligence value chains, and the cultural sector, and 4) digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy."

    ojs.weizenbaum-institut.de/ind

    #LatinAmerica #DigitalEconomy #DigitalLabor #AI #Informality #Digital Sovereignty

  51. Labor-atories of Digital EconomiesLatin America as a Site of Struggles and Experimentation

    Rafael Grohmann

    "This article argues that digital labor developments and struggles are laboratories of digital economies, with a special focus on Latin America. This means that, on the one hand, capital is experimenting with and updating forms of control and exploitation through the long trajectory of informality and de-pendency and, on the other hand, workers are trying and experimenting with forms of organizing and collectivities, also updating Latin America’s rich histories of organizing, solidarity economies, and community technologies. The emphasis on “labor” implies that these laboratories are products of class struggles and capital – labor relationships. The paper unpacks the argument with four short insights from ongoing research, addressing 1) Latin America as more than a research site, 2) the updating of informality in the Latin American artificial intelligence context, 3) the global implications of data work, artifi-cial intelligence value chains, and the cultural sector, and 4) digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy."

    ojs.weizenbaum-institut.de/ind

    #LatinAmerica #DigitalEconomy #DigitalLabor #AI #Informality #Digital Sovereignty

  52. Labor-atories of Digital EconomiesLatin America as a Site of Struggles and Experimentation

    Rafael Grohmann

    "This article argues that digital labor developments and struggles are laboratories of digital economies, with a special focus on Latin America. This means that, on the one hand, capital is experimenting with and updating forms of control and exploitation through the long trajectory of informality and de-pendency and, on the other hand, workers are trying and experimenting with forms of organizing and collectivities, also updating Latin America’s rich histories of organizing, solidarity economies, and community technologies. The emphasis on “labor” implies that these laboratories are products of class struggles and capital – labor relationships. The paper unpacks the argument with four short insights from ongoing research, addressing 1) Latin America as more than a research site, 2) the updating of informality in the Latin American artificial intelligence context, 3) the global implications of data work, artifi-cial intelligence value chains, and the cultural sector, and 4) digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy."

    ojs.weizenbaum-institut.de/ind

    #LatinAmerica #DigitalEconomy #DigitalLabor #AI #Informality #Digital Sovereignty

  53. Labor-atories of Digital EconomiesLatin America as a Site of Struggles and Experimentation

    Rafael Grohmann

    "This article argues that digital labor developments and struggles are laboratories of digital economies, with a special focus on Latin America. This means that, on the one hand, capital is experimenting with and updating forms of control and exploitation through the long trajectory of informality and de-pendency and, on the other hand, workers are trying and experimenting with forms of organizing and collectivities, also updating Latin America’s rich histories of organizing, solidarity economies, and community technologies. The emphasis on “labor” implies that these laboratories are products of class struggles and capital – labor relationships. The paper unpacks the argument with four short insights from ongoing research, addressing 1) Latin America as more than a research site, 2) the updating of informality in the Latin American artificial intelligence context, 3) the global implications of data work, artifi-cial intelligence value chains, and the cultural sector, and 4) digital solidarity economies as a Latin American response to the current digital labor scenario, including digital sovereignty and autonomy."

    ojs.weizenbaum-institut.de/ind

    #LatinAmerica #DigitalEconomy #DigitalLabor #AI #Informality #Digital Sovereignty