#dataannotation — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #dataannotation, aggregated by home.social.
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Computyne launches AI Data Annotation service, bringing 15+ years of BPO expertise to address the critical shortage of quality training data for machine learning development. #AI #DataAnnotation
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Computyne launches AI Data Annotation service, bringing 15+ years of BPO expertise to address the critical shortage of quality training data for machine learning development. #AI #DataAnnotation
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Computyne launches AI Data Annotation service, bringing 15+ years of BPO expertise to address the critical shortage of quality training data for machine learning development. #AI #DataAnnotation
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Computyne launches AI Data Annotation service, bringing 15+ years of BPO expertise to address the critical shortage of quality training data for machine learning development. #AI #DataAnnotation
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Computyne launches AI Data Annotation service, bringing 15+ years of BPO expertise to address the critical shortage of quality training data for machine learning development. #AI #DataAnnotation
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AI Language Insights Using Text Labeling Methods
Understanding language patterns requires structured datasets. Annotation defines context and relationships within text. Businesses use text labeling services to improve NLP learning and automation accuracy.
Know more: https://www.hitechdigital.com/text-annotation-services
#TextAnnotation #TextLabelingServices #DataAnnotation #AITrainingData #MachineLearning #ArtificialIntelligence #DataLabeling #NLP
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Data Annotation vs. Data Labeling for AI Model Accuracy
AI models depend on structured datasets to understand relationships. Data Annotation vs. Data Labeling explains contextual annotation benefits. A Data Annotation Company helps prepare datasets for improved prediction accuracy.
Know more: https://www.hitechdigital.com/blog/data-annotation-vs-data-labeling
#DataAnnotationCompany #DataAnnotation #DataLabeling #AITrainingData #MachineLearning #ArtificialIntelligence #DataAnnotationServices
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‘There’s a lot of desperation’: skilled older workers turn to #AItraining to stay afloat
5 skilled workers aged 50 and older spoke to Guardian about how, after struggling to find work in their fields, they turned to an emerging and growing category of work: using their expertise to train #artificialintelligence models. Known as #dataannotation, the work involves labeling and evaluating the information used to train #AI models like #OpenAI's #ChatGPT or #Google's #Gemini.
https://www.theguardian.com/technology/ng-interactive/2026/apr/07/ai-training-work-jobs -
‘There’s a lot of desperation’: skilled older workers turn to #AItraining to stay afloat
5 skilled workers aged 50 and older spoke to Guardian about how, after struggling to find work in their fields, they turned to an emerging and growing category of work: using their expertise to train #artificialintelligence models. Known as #dataannotation, the work involves labeling and evaluating the information used to train #AI models like #OpenAI's #ChatGPT or #Google's #Gemini.
https://www.theguardian.com/technology/ng-interactive/2026/apr/07/ai-training-work-jobs -
‘There’s a lot of desperation’: skilled older workers turn to #AItraining to stay afloat
5 skilled workers aged 50 and older spoke to Guardian about how, after struggling to find work in their fields, they turned to an emerging and growing category of work: using their expertise to train #artificialintelligence models. Known as #dataannotation, the work involves labeling and evaluating the information used to train #AI models like #OpenAI's #ChatGPT or #Google's #Gemini.
https://www.theguardian.com/technology/ng-interactive/2026/apr/07/ai-training-work-jobs -
‘There’s a lot of desperation’: skilled older workers turn to #AItraining to stay afloat
5 skilled workers aged 50 and older spoke to Guardian about how, after struggling to find work in their fields, they turned to an emerging and growing category of work: using their expertise to train #artificialintelligence models. Known as #dataannotation, the work involves labeling and evaluating the information used to train #AI models like #OpenAI's #ChatGPT or #Google's #Gemini.
https://www.theguardian.com/technology/ng-interactive/2026/apr/07/ai-training-work-jobs -
‘There’s a lot of desperation’: skilled older workers turn to #AItraining to stay afloat
5 skilled workers aged 50 and older spoke to Guardian about how, after struggling to find work in their fields, they turned to an emerging and growing category of work: using their expertise to train #artificialintelligence models. Known as #dataannotation, the work involves labeling and evaluating the information used to train #AI models like #OpenAI's #ChatGPT or #Google's #Gemini.
https://www.theguardian.com/technology/ng-interactive/2026/apr/07/ai-training-work-jobs -
RE: https://infosec.exchange/@mttaggart/116135607712424980
The myth that AI is this magical technology that 'just works' is actively harming tens of thousands of marginalized people. Propagating this idea is harmful. Promoting AI in general is harmful.
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RE: https://infosec.exchange/@mttaggart/116135607712424980
The myth that AI is this magical technology that 'just works' is actively harming tens of thousands of marginalized people. Propagating this idea is harmful. Promoting AI in general is harmful.
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RE: https://infosec.exchange/@mttaggart/116135607712424980
The myth that AI is this magical technology that 'just works' is actively harming tens of thousands of marginalized people. Propagating this idea is harmful. Promoting AI in general is harmful.
-
RE: https://infosec.exchange/@mttaggart/116135607712424980
The myth that AI is this magical technology that 'just works' is actively harming tens of thousands of marginalized people. Propagating this idea is harmful. Promoting AI in general is harmful.
-
RE: https://infosec.exchange/@mttaggart/116135607712424980
The myth that AI is this magical technology that 'just works' is actively harming tens of thousands of marginalized people. Propagating this idea is harmful. Promoting AI in general is harmful.
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Rapidata promises to shrink AI model cycles from months to days by tackling data‑annotation bottlenecks. Their approach blends human feedback, reinforcement learning and robotics to speed up model iteration—backed by ETH Zurich research. Curious how this could reshape open‑source ML pipelines? Read the full story. #AI #DataAnnotation #ModelIteration #Robotics
🔗 https://aidailypost.com/news/rapidata-aims-cut-model-cycles-from-months-days-cites-dataannotation
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Rapidata promises to shrink AI model cycles from months to days by tackling data‑annotation bottlenecks. Their approach blends human feedback, reinforcement learning and robotics to speed up model iteration—backed by ETH Zurich research. Curious how this could reshape open‑source ML pipelines? Read the full story. #AI #DataAnnotation #ModelIteration #Robotics
🔗 https://aidailypost.com/news/rapidata-aims-cut-model-cycles-from-months-days-cites-dataannotation
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Rapidata promises to shrink AI model cycles from months to days by tackling data‑annotation bottlenecks. Their approach blends human feedback, reinforcement learning and robotics to speed up model iteration—backed by ETH Zurich research. Curious how this could reshape open‑source ML pipelines? Read the full story. #AI #DataAnnotation #ModelIteration #Robotics
🔗 https://aidailypost.com/news/rapidata-aims-cut-model-cycles-from-months-days-cites-dataannotation
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#Women in rural #India report experiencing #trauma from #dataannotation work, which requires them to review #violentcontent and #porn for global tech companies. The workers describe hours of exposure to #abusivecontent while #training #AI systems, with lasting psychological effects. The investigation highlights the human cost behind AI development and raises questions about labor practices in the tech industry. https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?eicker.news #India #Tech #IndiaTech #Technews
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#Women in rural #India report experiencing #trauma from #dataannotation work, which requires them to review #violentcontent and #porn for global tech companies. The workers describe hours of exposure to #abusivecontent while #training #AI systems, with lasting psychological effects. The investigation highlights the human cost behind AI development and raises questions about labor practices in the tech industry. https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?eicker.news #India #Tech #IndiaTech #Technews
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#Women in rural #India report experiencing #trauma from #dataannotation work, which requires them to review #violentcontent and #porn for global tech companies. The workers describe hours of exposure to #abusivecontent while #training #AI systems, with lasting psychological effects. The investigation highlights the human cost behind AI development and raises questions about labor practices in the tech industry. https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?eicker.news #India #Tech #IndiaTech #Technews
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#Women in rural #India report experiencing #trauma from #dataannotation work, which requires them to review #violentcontent and #porn for global tech companies. The workers describe hours of exposure to #abusivecontent while #training #AI systems, with lasting psychological effects. The investigation highlights the human cost behind AI development and raises questions about labor practices in the tech industry. https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?eicker.news #India #Tech #IndiaTech #Technews
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#Women in rural #India report experiencing #trauma from #dataannotation work, which requires them to review #violentcontent and #porn for global tech companies. The workers describe hours of exposure to #abusivecontent while #training #AI systems, with lasting psychological effects. The investigation highlights the human cost behind AI development and raises questions about labor practices in the tech industry. https://www.theguardian.com/global-development/2026/feb/05/in-the-end-you-feel-blank-indias-female-workers-watching-hours-of-abusive-content-to-train-ai?eicker.news #India #Tech #IndiaTech #Technews
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Why AI Data Annotation Services Face Hidden Obstacles
Scaling data annotation exposes hidden pitfalls: inconsistent labels, QC gaps, and resource strain. Solve them early to avoid costly AI model failures.
#AIAnnotation #DataAnnotation #MachineLearning #AITraining #MLWorkflow #DataLabeling #ArtificialIntelligence #AIServices
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What Is LiDAR Annotation and Why Does AI Need It?
LiDAR captures rich 3D environments, but actionable intelligence needs precise annotation. This blog explains how point cloud labeling for AI/ML powers autonomous driving, robotics, and smart infrastructure to detect objects, measure distances, and understand spatial relationships LiDAR annotation matters.
Know More: https://www.hitechdigital.com/blog/lidar-annotation-for-ai
#LiDARAnnotation #AITraining #AutonomousVehicles #3DPointCloud #MachineLearning #DataAnnotation
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Prompt Engineering vs Fine-Tuning: How AI Models Improve
If your AI model feels unpredictable, retraining is not always the answer. This article explains prompt engineering vs fine-tuning in plain terms, helping teams get more consistent results, avoid unnecessary costs, and choose the right optimization approach for real-world AI & data annotation services.
Know More: https://www.hitechdigital.com/blog/prompt-engineering-vs-fine-tuning
#PromptEngineering #FineTuning #ArtificialIntelligence #MachineLearning #AIModelData #DataAnnotation
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Prompt Engineering vs Fine-Tuning: How AI Models Improve
If your AI model feels unpredictable, retraining is not always the answer. This article explains prompt engineering vs fine-tuning in plain terms, helping teams get more consistent results, avoid unnecessary costs, and choose the right optimization approach for real-world AI & data annotation services.
Know More: https://www.hitechdigital.com/blog/prompt-engineering-vs-fine-tuning
#PromptEngineering #FineTuning #ArtificialIntelligence #MachineLearning #AIModelData #DataAnnotation
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Prompt Engineering vs Fine-Tuning: How AI Models Improve
If your AI model feels unpredictable, retraining is not always the answer. This article explains prompt engineering vs fine-tuning in plain terms, helping teams get more consistent results, avoid unnecessary costs, and choose the right optimization approach for real-world AI & data annotation services.
Know More: https://www.hitechdigital.com/blog/prompt-engineering-vs-fine-tuning
#PromptEngineering #FineTuning #ArtificialIntelligence #MachineLearning #AIModelData #DataAnnotation
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Prompt Engineering vs Fine-Tuning: How AI Models Improve
If your AI model feels unpredictable, retraining is not always the answer. This article explains prompt engineering vs fine-tuning in plain terms, helping teams get more consistent results, avoid unnecessary costs, and choose the right optimization approach for real-world AI & data annotation services.
Know More: https://www.hitechdigital.com/blog/prompt-engineering-vs-fine-tuning
#PromptEngineering #FineTuning #ArtificialIntelligence #MachineLearning #AIModelData #DataAnnotation
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Prompt Engineering vs Fine-Tuning: How AI Models Improve
If your AI model feels unpredictable, retraining is not always the answer. This article explains prompt engineering vs fine-tuning in plain terms, helping teams get more consistent results, avoid unnecessary costs, and choose the right optimization approach for real-world AI & data annotation services.
Know More: https://www.hitechdigital.com/blog/prompt-engineering-vs-fine-tuning
#PromptEngineering #FineTuning #ArtificialIntelligence #MachineLearning #AIModelData #DataAnnotation
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In just eight months, #micro1, an #AIpowered #recruitmentservice, pivoted to #dataannotation for #AItraining and achieved a $2.5 billion valuation. CEO #AliAnsari, recognising the growing demand for #highqualitydata to train #AImodels, anticipates the market for AI training to surpass $100 billion in two years. https://www.forbes.com/sites/annatong/2025/12/04/this-24-year-old-built-a-multibillion-dollar-ai-training-empire-in-eight-months/?eicker.news #tech #media #news
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In just eight months, #micro1, an #AIpowered #recruitmentservice, pivoted to #dataannotation for #AItraining and achieved a $2.5 billion valuation. CEO #AliAnsari, recognising the growing demand for #highqualitydata to train #AImodels, anticipates the market for AI training to surpass $100 billion in two years. https://www.forbes.com/sites/annatong/2025/12/04/this-24-year-old-built-a-multibillion-dollar-ai-training-empire-in-eight-months/?eicker.news #tech #media #news
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In just eight months, #micro1, an #AIpowered #recruitmentservice, pivoted to #dataannotation for #AItraining and achieved a $2.5 billion valuation. CEO #AliAnsari, recognising the growing demand for #highqualitydata to train #AImodels, anticipates the market for AI training to surpass $100 billion in two years. https://www.forbes.com/sites/annatong/2025/12/04/this-24-year-old-built-a-multibillion-dollar-ai-training-empire-in-eight-months/?eicker.news #tech #media #news
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In just eight months, #micro1, an #AIpowered #recruitmentservice, pivoted to #dataannotation for #AItraining and achieved a $2.5 billion valuation. CEO #AliAnsari, recognising the growing demand for #highqualitydata to train #AImodels, anticipates the market for AI training to surpass $100 billion in two years. https://www.forbes.com/sites/annatong/2025/12/04/this-24-year-old-built-a-multibillion-dollar-ai-training-empire-in-eight-months/?eicker.news #tech #media #news
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In just eight months, #micro1, an #AIpowered #recruitmentservice, pivoted to #dataannotation for #AItraining and achieved a $2.5 billion valuation. CEO #AliAnsari, recognising the growing demand for #highqualitydata to train #AImodels, anticipates the market for AI training to surpass $100 billion in two years. https://www.forbes.com/sites/annatong/2025/12/04/this-24-year-old-built-a-multibillion-dollar-ai-training-empire-in-eight-months/?eicker.news #tech #media #news
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The Key Role of Data Annotation in Building Smarter ML Models
High-quality data annotation is essential for strong AI and ML models. It adds clarity to text, images, audio, and video, improving accuracy, reducing bias, and enabling scalable, trustworthy solutions across industries while boosting innovation.
Know More: https://www.datasciencesociety.net/why-data-annotation-is-important-for-machine-learning/
#dataannotation #machinelearning #deeplearning #aitraining #datalabeling #aidevelopment #techinnovation
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Building smarter AI starts with better data. At Macgence, our Image Annotation Services turn raw visuals into structured, high-quality datasets for computer vision, autonomous systems, and more. From bounding boxes to pixel-level labeling, we bring accuracy, scale, and security to every project.
Read More: https://macgence.com/blog/image-annotation-services
#AI #MachineLearning #ImageAnnotationServices #DataAnnotation #ComputerVision
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Data Annotation for Smarter AI & Recommendations in E-commerce
Discover how quality data annotation empowers e-commerce businesses to train smarter AI systems and recommendation engines. From image and text labeling to scalable automation, learn how accurate datasets drive personalization, better search, and higher engagement in online retail.
#DataAnnotation #EcommerceAI #RecommendationEngine #AIDrivenRetail #MachineLearning #DataLabeling #PersonalizedShopping
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"AI tools have become ubiquitous, entering many facets of everyday life. More often than not, “artificial intelligence” models are presented as fully automated, having dispensed with the need for human intervention. The human workers who train, test, and maintain AI models and act as the first line of defense against model failures are made visible only occasionally. Media coverage sometimes emerges of hundreds of Indian workers1 who remotely ensure the checkout process goes smoothly while creating the illusion of automation at Amazon Go stores and African content moderators2 who make social media platforms safer at great personal cost. But these stories only scratch the surface of the labor that underpins every part of the AI production process.
Despite being touted as the definitive technological breakthrough of this century, the conditions under which AI models and tools are produced by data workers, in a highly opaque and fissured global supply chain, are still underexplored. Studies of data workers in the Global South have begun to fill gaps in knowledge about the low-paid outsourced labor behind AI, but less is known about U.S. data workers’ conditions.In this report, we begin to address this gap through a study of the working conditions of U.S.-based data workers, conducted by AWU-CWA and TechEquity.These workers are essential to the development of tools and models developed by big tech companies, but are employed by complex webs of contractors in the U.S.-based sections of the global AI supply chain. Combining data from a survey of 160 data workers with insights from 15 in-depth interviews, we’ve found that the poor working conditions seen in the Global South are also widespread in data work in the U.S."
https://cwa-union.org/ghost-workers-ai-machine
#DataLabour #DataLabelling #DataAnnotation #BigTech #AI #GenerativeAI #WageSlavery
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"AI tools have become ubiquitous, entering many facets of everyday life. More often than not, “artificial intelligence” models are presented as fully automated, having dispensed with the need for human intervention. The human workers who train, test, and maintain AI models and act as the first line of defense against model failures are made visible only occasionally. Media coverage sometimes emerges of hundreds of Indian workers1 who remotely ensure the checkout process goes smoothly while creating the illusion of automation at Amazon Go stores and African content moderators2 who make social media platforms safer at great personal cost. But these stories only scratch the surface of the labor that underpins every part of the AI production process.
Despite being touted as the definitive technological breakthrough of this century, the conditions under which AI models and tools are produced by data workers, in a highly opaque and fissured global supply chain, are still underexplored. Studies of data workers in the Global South have begun to fill gaps in knowledge about the low-paid outsourced labor behind AI, but less is known about U.S. data workers’ conditions.In this report, we begin to address this gap through a study of the working conditions of U.S.-based data workers, conducted by AWU-CWA and TechEquity.These workers are essential to the development of tools and models developed by big tech companies, but are employed by complex webs of contractors in the U.S.-based sections of the global AI supply chain. Combining data from a survey of 160 data workers with insights from 15 in-depth interviews, we’ve found that the poor working conditions seen in the Global South are also widespread in data work in the U.S."
https://cwa-union.org/ghost-workers-ai-machine
#DataLabour #DataLabelling #DataAnnotation #BigTech #AI #GenerativeAI #WageSlavery
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"AI tools have become ubiquitous, entering many facets of everyday life. More often than not, “artificial intelligence” models are presented as fully automated, having dispensed with the need for human intervention. The human workers who train, test, and maintain AI models and act as the first line of defense against model failures are made visible only occasionally. Media coverage sometimes emerges of hundreds of Indian workers1 who remotely ensure the checkout process goes smoothly while creating the illusion of automation at Amazon Go stores and African content moderators2 who make social media platforms safer at great personal cost. But these stories only scratch the surface of the labor that underpins every part of the AI production process.
Despite being touted as the definitive technological breakthrough of this century, the conditions under which AI models and tools are produced by data workers, in a highly opaque and fissured global supply chain, are still underexplored. Studies of data workers in the Global South have begun to fill gaps in knowledge about the low-paid outsourced labor behind AI, but less is known about U.S. data workers’ conditions.In this report, we begin to address this gap through a study of the working conditions of U.S.-based data workers, conducted by AWU-CWA and TechEquity.These workers are essential to the development of tools and models developed by big tech companies, but are employed by complex webs of contractors in the U.S.-based sections of the global AI supply chain. Combining data from a survey of 160 data workers with insights from 15 in-depth interviews, we’ve found that the poor working conditions seen in the Global South are also widespread in data work in the U.S."
https://cwa-union.org/ghost-workers-ai-machine
#DataLabour #DataLabelling #DataAnnotation #BigTech #AI #GenerativeAI #WageSlavery
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"AI tools have become ubiquitous, entering many facets of everyday life. More often than not, “artificial intelligence” models are presented as fully automated, having dispensed with the need for human intervention. The human workers who train, test, and maintain AI models and act as the first line of defense against model failures are made visible only occasionally. Media coverage sometimes emerges of hundreds of Indian workers1 who remotely ensure the checkout process goes smoothly while creating the illusion of automation at Amazon Go stores and African content moderators2 who make social media platforms safer at great personal cost. But these stories only scratch the surface of the labor that underpins every part of the AI production process.
Despite being touted as the definitive technological breakthrough of this century, the conditions under which AI models and tools are produced by data workers, in a highly opaque and fissured global supply chain, are still underexplored. Studies of data workers in the Global South have begun to fill gaps in knowledge about the low-paid outsourced labor behind AI, but less is known about U.S. data workers’ conditions.In this report, we begin to address this gap through a study of the working conditions of U.S.-based data workers, conducted by AWU-CWA and TechEquity.These workers are essential to the development of tools and models developed by big tech companies, but are employed by complex webs of contractors in the U.S.-based sections of the global AI supply chain. Combining data from a survey of 160 data workers with insights from 15 in-depth interviews, we’ve found that the poor working conditions seen in the Global South are also widespread in data work in the U.S."
https://cwa-union.org/ghost-workers-ai-machine
#DataLabour #DataLabelling #DataAnnotation #BigTech #AI #GenerativeAI #WageSlavery
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"Scale AI is basically a data annotation hub that does essential grunt work for the AI industry. To train an AI model, you need quality data. And for that data to mean anything, an AI model needs to know what it's looking at. Annotators manually go in and add that context.
As is the means du jour in corporate America, Scale AI built its business model on an army of egregiously underpaid gig workers, many of them overseas. The conditions have been described as "digital sweatshops," and many workers have accused Scale AI of wage theft.
It turns out this was not an environment for fostering high-quality work.
According to internal documents obtained by Inc, Scale AI's "Bulba Experts" program to train Google's AI systems was supposed to be staffed with authorities across relevant fields. But instead, during a chaotic 11 months between March 2023 and April 2024, its dubious "contributors" inundated the program with "spam," which was described as "writing gibberish, writing incorrect information, GPT-generated thought processes."
In many cases, the spammers, who were independent contractors who worked through Scale AI-owned platforms like Remotasks and Outlier, still got paid for submitting complete nonsense, according to former Scale contractors, since it became almost impossible to catch them all. And even if they did get caught, some would come back by simply using a VPN.
"People made so much money," a former contributor told Inc. "They just hired everybody who could breathe.""
https://futurism.com/scale-ai-zuckerberg-incompetence
#AI #GenerativeAI #Meta #ScaleAI #DataAnnotation #DataLabeling #GigWork
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"Scale AI is basically a data annotation hub that does essential grunt work for the AI industry. To train an AI model, you need quality data. And for that data to mean anything, an AI model needs to know what it's looking at. Annotators manually go in and add that context.
As is the means du jour in corporate America, Scale AI built its business model on an army of egregiously underpaid gig workers, many of them overseas. The conditions have been described as "digital sweatshops," and many workers have accused Scale AI of wage theft.
It turns out this was not an environment for fostering high-quality work.
According to internal documents obtained by Inc, Scale AI's "Bulba Experts" program to train Google's AI systems was supposed to be staffed with authorities across relevant fields. But instead, during a chaotic 11 months between March 2023 and April 2024, its dubious "contributors" inundated the program with "spam," which was described as "writing gibberish, writing incorrect information, GPT-generated thought processes."
In many cases, the spammers, who were independent contractors who worked through Scale AI-owned platforms like Remotasks and Outlier, still got paid for submitting complete nonsense, according to former Scale contractors, since it became almost impossible to catch them all. And even if they did get caught, some would come back by simply using a VPN.
"People made so much money," a former contributor told Inc. "They just hired everybody who could breathe.""
https://futurism.com/scale-ai-zuckerberg-incompetence
#AI #GenerativeAI #Meta #ScaleAI #DataAnnotation #DataLabeling #GigWork
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"Scale AI is basically a data annotation hub that does essential grunt work for the AI industry. To train an AI model, you need quality data. And for that data to mean anything, an AI model needs to know what it's looking at. Annotators manually go in and add that context.
As is the means du jour in corporate America, Scale AI built its business model on an army of egregiously underpaid gig workers, many of them overseas. The conditions have been described as "digital sweatshops," and many workers have accused Scale AI of wage theft.
It turns out this was not an environment for fostering high-quality work.
According to internal documents obtained by Inc, Scale AI's "Bulba Experts" program to train Google's AI systems was supposed to be staffed with authorities across relevant fields. But instead, during a chaotic 11 months between March 2023 and April 2024, its dubious "contributors" inundated the program with "spam," which was described as "writing gibberish, writing incorrect information, GPT-generated thought processes."
In many cases, the spammers, who were independent contractors who worked through Scale AI-owned platforms like Remotasks and Outlier, still got paid for submitting complete nonsense, according to former Scale contractors, since it became almost impossible to catch them all. And even if they did get caught, some would come back by simply using a VPN.
"People made so much money," a former contributor told Inc. "They just hired everybody who could breathe.""
https://futurism.com/scale-ai-zuckerberg-incompetence
#AI #GenerativeAI #Meta #ScaleAI #DataAnnotation #DataLabeling #GigWork
