rexiMar 27

https://www.svd.se/a/K8nrV4/metas-ai-smart-glasses-and-data-privacy-concerns-workers-say-we-see-everything

callled #Sama…subcontractor to Meta…in Kenya’s capital, thousands of people train AI systems, teaching them to recognise and interpret the world.

…called data #annotators…they are the manual labourers of the #AI revolution. On the screens they draw boxes around flower pots and traffic signs, follow contours, register pixels and name objects: cars, lamps, people…

…workers in #Kenya say that it feels uncomfortable to go to work. They tell us about deeply private video…

Meta’s AI Smart Glasses and Data Privacy Concerns: Workers Say “We See Everything”

Bank details, sex and naked people who seem unaware they are being recorded. Behind Meta’s new smart glasses lies a hidden workforce, uneasy about peering into the most intimate parts of other people’s lives.

Svenska Dagbladet
New Submissions to TMLRJul 25, 2023

One-Round Active Learning through Data Utility Learning and Proxy Models

https://openreview.net/forum?id=8HQCOMRa7g

#labeled #labeling #annotators

One-Round Active Learning through Data Utility Learning and Proxy...

While active learning (AL) techniques have demonstrated the potential to produce high-performance models with fewer labeled data, their application remains limited due to the necessity for multiple...

OpenReview
beSpacificJun 13, 2023
The secret to making #AIChatbots sound #smart and #spew less #toxic nonsense is to use a technique called reinforcement learning from #HumanFeedback, which uses input from people to improve the model’s answers. It relies on a small army of #human #data #annotators who evaluate whether a string of text makes sense and sounds fluent and natural. They decide whether a response should be kept in the AI model’s database or removed. https://www.technologyreview.com/2023/06/13/1074560/we-are-all-ais-free-data-workers
We are all AI’s free data workers

Plus: DeepMind’s game-playing AI just found another way to make code faster.

MIT Technology Review
New Submissions to TMLRFeb 19, 2023

Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios

https://openreview.net/forum?id=dXnccpSSYF

#labeling #sampling #annotators

Pareto Optimization for Active Learning under Out-of-Distribution...

Pool-based Active Learning (AL) has proven successful in minimizing labeling costs by sequentially selecting the most informative unlabeled data from large pool and querying their labels from an...

OpenReview