The hidden workforce behind ChatGPT: the drama of “ghost workers” | Technology

It may seem like magic, but it’s not. The evolution of artificial intelligence (AI), constantly celebrated for its exponential innovation and revolutionary capabilities, masks a less glamorous but essential element: its remote workforce. This crucial but often overlooked part of their value chain reminds me of the textile industry supply chain of a few decades ago. Has anyone forgotten the Rana Plaza tragedy in Bangladesh, where more than 100 people died? It’s a side story. Whereas, in the production of cheap clothing, the risk incurred by workers locked in factories in peripheral countries is physical; In this other industry, that of digital technology, psychosocial risk predominates. That is, the psychological damage suffered by its workers due to their constant exposure to brutal, disturbing, traumatic and indescribable content. Their invisibility and their non-employment relationship leave them alone to face the consequences; to which are added the classics of relocation to countries without the rule of law: precarious wages, unpaid work, exploitation, abuse, etc. All videos containing murder, suicide, sexual assault or child abuse that are not seen on the platforms have been reviewed and flagged by a content moderator or by an automated system that has been trained with data provided by a content moderator. Some are already forming the first unions defend their rights, but that will not be enough. This is a new global challenge that requires regulations that standardize working conditions in this rapidly growing sector.

The anthropologist Mary Gray called them “ghost workers“. People we don’t see, working in remote locations, forming the great role models who make the world’s most famous cat produce quality content. It’s not just adults. There are also children. Like those who sew soccer balls. Their working conditions are very different from those enjoyed by employees in Silicon Valley, where you can become a millionaire before turning 30. In this other reality, that of the artificial intelligence supply chain, guys like Hassan earn less than two dollars an hour. He is now 18, but he started in Toloka, a 15-year-old platform dedicated to data annotation. He comes from a region of Pakistan. Their friends also work on these platforms after classes until late at night, according to reports Wired. They manage to circumvent age verification processes and end up performing psychologically exhausting and inappropriate tasks. The problem of child labor in this renowned industry is a subject that is not talked about.

Global Data Collection and Labeling Market Size Expected to Reach $17.1 billion in 2030, with an annual growth rate of almost 30%. It’s a space that has more and more competitors. Amazon Mechanical Turk, Appen, Clickworker, Comeup, Elharefa, Microworkers, PeoplePerHour, Prolific, SoyFreelancer, Scale AI (including its subsidiary Remotasks), Terawork or Workana are just some of the companies in which the team of Oxford Internet Institute analyzed to conclude that many of their labor practices are unfair, to say the least. What can you do about it? He Global AI Partnership (GPAI) through its AI Fairwork project, and the company sama They worked together for a year to voluntarily audit and improve their operations in Africa, benefiting more than 4,000 workers. These changes demonstrate the power of awareness and commitment to responsible practices. Mark Graham, professor at the Oxford Internet Institute, said as technology transforms societies and labor markets, we must remember that there are hundreds of thousands of low-wage workers behind the scenes who make up, annotate and moderate new product datasets. and the services are built. It is therefore imperative to establish fair minimum labor standards for all workers in artificial intelligence production networks.

As has happened in the textile sector, where consumer demand has led to the development of ethical regulations and certifications to improve labor practices and transparency, the artificial intelligence sector is called upon to take similar measures . There is a need to establish a global regulatory framework that ensures fair labor practices and prevents the exploitation of vulnerable workers. Global inequality is evident in both artificial intelligence and clothing, with workers in developing countries receiving minimal pay compared to their counterparts in rich countries. This economic divide perpetuates a form of exploitation that disproportionately benefits businesses and consumers in the Global North.

Faced with this crossroads, it is crucial to choose a path that avoids exploitation and moves toward a more sustainable and just future. This change requires a commitment to transparency and the adoption of decent labor practices, as well as the development of common standards. The burgeoning artificial intelligence sector must absorb lessons learned from the mistakes of previous industries, such as textiles, and set a course that prioritizes not only innovation, but also dignity and well-being of its workforce.

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