{"id":7432,"date":"2023-11-15T15:45:08","date_gmt":"2023-11-15T15:45:08","guid":{"rendered":"https:\/\/dailyai.com\/?p=7432"},"modified":"2023-11-15T15:52:47","modified_gmt":"2023-11-15T15:52:47","slug":"the-stories-of-underage-workers-in-the-ai-and-data-services-industry","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2023\/11\/the-stories-of-underage-workers-in-the-ai-and-data-services-industry\/","title":{"rendered":"As hist\u00f3rias de trabalhadores menores de idade no sector da IA e dos servi\u00e7os de dados"},"content":{"rendered":"

A ind\u00fastria da IA tem um historial problem\u00e1tico de explora\u00e7\u00e3o laboral, com os trabalhadores a manifestarem-se na Venezuela, no Qu\u00e9nia e noutras partes do mundo com grandes mercados de rotulagem de dados e de forma\u00e7\u00e3o em IA.\u00a0<\/b><\/p>\n

Os grandes modelos de IA como o ChatGPT e a fam\u00edlia de modelos GPT requerem grandes quantidades de dados, incluindo dados de texto moderados e rotulados por humanos.<\/p>\n

O objetivo \u00e9 rotular o texto para instruir os modelos sobre os diferentes tipos de conte\u00fados, em especial os conte\u00fados nocivos ou ilegais. Isto ajuda a criar filtros e barreiras de prote\u00e7\u00e3o.<\/p>\n

Em casos anteriores no Qu\u00e9nia, trabalhadores da empresa de servi\u00e7os de dados Sama, num projeto para a OpenAI, foram expostos a conte\u00fados que continham temas de abuso sexual perturbadores. <\/span><\/p>\n

V\u00e1rios trabalhadores afirmaram ter sofrido problemas de sa\u00fade mental em consequ\u00eancia disso, acabando por que culmina com uma peti\u00e7\u00e3o e uma a\u00e7\u00e3o judicial<\/a>.\u00a0<\/span><\/p>\n

O mesmo foi observado no sector da modera\u00e7\u00e3o de conte\u00fados, em que os trabalhadores s\u00e3o respons\u00e1veis pela an\u00e1lise de conte\u00fados potencialmente il\u00edcitos nas plataformas das redes sociais.\u00a0<\/span><\/p>\n

De acordo com um novo relat\u00f3rio da WIRED<\/a>No entanto, este trabalho estende-se a indiv\u00edduos particularmente jovens, frequentemente oriundos de meios pobres, que s\u00e3o atra\u00eddos para plataformas em linha que prometem flexibilidade de trabalho e sal\u00e1rios mais elevados do que os padr\u00f5es locais. Isto acontece \u00e0 custa da exposi\u00e7\u00e3o a conte\u00fados nocivos.<\/span><\/p>\n

Hassan, um pseud\u00f3nimo de um jovem de 18 anos do Paquist\u00e3o, \u00e9 um desses indiv\u00edduos que se tornou um trabalhador mal pago na cadeia global de fornecimento de IA, rotulando dados para treinar algoritmos para algumas das maiores empresas de IA do mundo.<\/span><\/p>\n

Os trabalhadores por conta pr\u00f3pria em plataformas de crowdsourcing como a Toloka e a Amazon Mechanical Turk realizam frequentemente estas tarefas. Hassan come\u00e7ou a sua carreira online na Toloka. Utilizou os dados de um familiar para contornar as restri\u00e7\u00f5es de idade, uma pr\u00e1tica comum entre os menores que procuram este tipo de trabalho.<\/span><\/p>\n

A investiga\u00e7\u00e3o da WIRED revelou v\u00e1rios casos de trabalhadores menores de idade no Paquist\u00e3o e no Qu\u00e9nia que aderiram a plataformas como a Toloka e a Appen sob falsos pretextos.\u00a0<\/span><\/p>\n

O lado negro da rotulagem de dados\u00a0<\/span><\/h2>\n

Embora o trabalho de etiquetagem de dados possa parecer in\u00f3cuo, por vezes envolve a an\u00e1lise de conte\u00fados perturbadores.\u00a0<\/span><\/p>\n

Hassan partilhou grava\u00e7\u00f5es de ecr\u00e3 de tarefas em que foi exposto a linguagem expl\u00edcita e imagens sexualmente sugestivas. Lembra-se de ter lidado com conte\u00fados profundamente perturbadores, incluindo imagens sexualizadas de menores e descri\u00e7\u00f5es de actos violentos, que continuam a afetar a sua sa\u00fade mental.<\/span><\/p>\n

O fasc\u00ednio de ganhar mais do que o sal\u00e1rio m\u00ednimo nacional \u00e9 um forte fator de motiva\u00e7\u00e3o para estes jovens.\u00a0<\/span><\/p>\n

Para muitos, o trabalho tempor\u00e1rio come\u00e7a por ser um meio para atingir um fim, como o financiamento de uma viagem ou o sustento da fam\u00edlia. No entanto, os trabalhadores suportam por vezes longas horas por uma remunera\u00e7\u00e3o escassa, enfrentando o risco de suspens\u00e3o ou proibi\u00e7\u00e3o da conta por pequenos desvios no seu trabalho.<\/span><\/p>\n

Para Hassan, este trabalho continua a ser a sua \u00fanica fonte de rendimento, apesar de estar a frequentar um curso de licenciatura. Observa que o sal\u00e1rio diminuiu significativamente \u00e0 medida que mais trabalhadores aderiram a estas plataformas, o que o leva a classificar a situa\u00e7\u00e3o como \"escravatura digital\".<\/span><\/p>\n

A situa\u00e7\u00e3o aqui espelha precisamente a de outros relat\u00f3rios da Venezuela e do Qu\u00e9nia. Na Venezuela, fam\u00edlias inteiras, incluindo crian\u00e7as de 13 anos, foram envolvidas em tarefas de etiquetagem de dados.\u00a0<\/span><\/p>\n

Combinado com a utiliza\u00e7\u00e3o centralizada da IA em sociedades predominantemente mais ricas, este facto levou a cr\u00edticas \u00e0 <\/span>a tecnologia como \"colonial<\/span><\/a> na sua mec\u00e2nica assustadoramente semelhante \u00e0 sistem\u00e1tica de trabalho da era colonial - uma forma de \"servid\u00e3o digital\".\u00a0<\/span><\/p>\n

Este facto sublinha a necessidade de processos de verifica\u00e7\u00e3o de idade mais rigorosos nestas plataformas e levanta quest\u00f5es sobre o fornecimento \u00e9tico de m\u00e3o de obra na ind\u00fastria tecnol\u00f3gica.\u00a0<\/span><\/p>\n

Verificaram-se ocorr\u00eancias semelhantes noutros sectores, como o facto de os menores de 18 anos contornarem a verifica\u00e7\u00e3o da idade para <\/span>trabalhar para plataformas de entrega como a Deliveroo<\/span><\/a>.<\/span><\/p>\n

\u00c0 medida que a IA avan\u00e7a, torna-se cada vez mais crucial garantir que as suas pr\u00e1ticas laborais fundamentais cumprem as normas \u00e9ticas.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

A ind\u00fastria da IA tem um historial problem\u00e1tico de explora\u00e7\u00e3o laboral, com trabalhadores a falarem na Venezuela, no Qu\u00e9nia e noutras partes do mundo com grandes mercados de rotulagem de dados e de forma\u00e7\u00e3o em IA. Grandes modelos de IA como o ChatGPT e a fam\u00edlia de modelos GPT requerem grandes quantidades de dados, incluindo dados de texto moderados e rotulados por humanos. O objetivo \u00e9 rotular o texto para instruir os modelos sobre diferentes tipos de conte\u00fados, em especial conte\u00fados nocivos ou ilegais. Isto ajuda a criar filtros e barreiras de prote\u00e7\u00e3o. Em casos anteriores, no Qu\u00e9nia, os trabalhadores da empresa de servi\u00e7os de dados Sama, num projeto para a OpenAI, foram expostos a conte\u00fados<\/p>","protected":false},"author":2,"featured_media":7433,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[377,160],"class_list":["post-7432","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-data-labeling","tag-data-science"],"yoast_head":"\nThe stories of underage workers in the AI and data services industry | DailyAI<\/title>\n<meta name=\"description\" content=\"The AI industry has a tricky history of labor exploitation, with workers speaking out in Venezuela, Kenya, and other parts of the world with large data labeling and AI training markets.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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