Data Science Insider: November 11th, 2022

In This Week’s SuperDataScience Newsletter: AI Diagnosis May Help Reduce Hospital Pressures. Complaint Filed against PimEyes Facial Search Engine. FIA to use AI Against Trolling. Meta Sacks Entire ML Research Team. Amazon Unveils New Warehouse Robot. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [AI Diagnosis May Help Reduce Hospital Pressures]( brief: Researchers from the University of the West of Scotland Lung have announced that diseases like tuberculosis and pneumonia can be diagnosed in a matter of minutes using AI – and could be key in easing winter pressures on hospitals. The technology was originally used to detect Covid-19 from X-ray images but is now being used on other lung diseases, enabling faster diagnosis with fewer resources. Researcher Prof Naeem Ramzan said: "X-ray imaging is a relatively cheap and accessible diagnostic tool that already assists in the diagnosis of various conditions, including pneumonia, tuberculosis, and Covid-19. Recent advances in AI have made automated diagnosis using chest X-ray scans a very real prospect in medical settings. We would like to roll it out worldwide and make it freely available to anyone who would like to use it, either in the NHS or abroad as well." Why this is important: The AI uses X-rays (traditional diagnosis uses a combination of CT scans, blood tests, X-rays, and ultrasound) and then compares them to a database of thousands of images from patients with pneumonia, tuberculosis and Covid. It then uses a deep convolutional neural network to make a diagnosis. It is claimed to be 98% accurate. [Click here to learn more!]( [Complaint Filed against PimEyes Facial Search Engine]( brief: Privacy campaign group Big Brother Watch has made a complaint to the UK data and privacy watchdog, the Information Commissioner's Office (ICO), against the face recognition search engine PimEyes. The search engine allows people to look for faces in images that have been posted publicly on the internet but campaigners claim that this could facilitate stalking. In this press release, Big Brother Watch claims that: “PimEyes places no limits on the type of images that may be used for search and has no safeguards to prevent people using the service to extract a library of photos of someone other than themselves. Instead, it asks customers to use the technology ethically.” It goes on to argue that PimEyes unlawfully processes the biometric data of millions of UK citizens - without obtaining permission from those whose images are analysed. It claims that jigsaw identification will then be possible. Why this is important: Here at SuperDataScience, we’ve regularly covered data concerns when it comes to facial recognition, most notably by Clearview AI. This complaint is another which highlights the very real concerns about how our images are collected and sold. [Click here to read on!]( [FIA to use AI Against Trolling]( In brief: The governing body of Formula One, the Fédération Internationale de l'Automobile (FIA), has announced that it is partnering with AI experts Arwen.ai in order to combat online abuse. The organisation has claimed that abuse has risen to “toxic” levels and is aiming to use the technology to stamp it out. A catalyst for the move was death threats received by F1 FIA race steward Silvia Bellot after a controversial post-race penalty was awarded to Fernando Alonso. Following an already successful trial, Arwen.ai will be applying its AI-enabled content moderation platform in order to help the FIA detect and reduce growing levels of unwanted content on its social media channels. The UK technology company has already worked with Red Bull, Mercedes and Alpine Formula 1 teams in a similar manner. The move is part of a package of measures that the FIA will introduce. Why this is important: The FIA will be working with social media platforms, governments and fellow sports governing bodies in order to try and eradicate hate speech, alongside a research project into digital hate and toxic commentary specific to sport. [Click here to discover more!]( [Meta Sacks Entire ML Research Team]( In brief: This week Meta announced that it is executing the first mass lay-offs in the company's history, resulting in 11,000 employees losing their jobs – a total of 13% of its workforce. The move comes after Meta Chief Executive, Mark Zuckerberg, incorrectly predicted that an upturn in business during the Covid-19 pandemic would be permanent and invested accordingly. In order to combat miscalculation and restore the company’s finances, Zuckerberg has said that the company will focus on high-priority growth areas, such as AI, advertising, and "our long-term vision for the metaverse," whilst reducing spending on office space. One significant casualty of the move is the research organisation “Probability,” which focused on applying ML across the infrastructure stack. According to research scientist, Thomas Ahle, the team comprised: “19 people doing Bayesian Modeling, 9 people doing Ranking and Recommendations, 5 people doing ML Efficiency, 17 people doing AI for Chip Design and Compilers.” Why this is important: Any layoffs are always bad news but this particular action says a lot about how Meta values ML learning projects. [Click here to see the full picture!]( [Amazon Unveils New Warehouse Robot]( In brief: Amazon has debuted a new robotic arm, Sparrow, which can pick up and sort millions of individual unpackaged products. The tasks would previously have been done by employees but the technology has been touted as having the potential to transform the economics of e-commerce. Currently, around three-quarters of packages delivered by Amazon have been touched by some kind of robotic system. The aim is that within the next five years that will hit 100%. The giant robotic arm can move freely on the warehouse floor alongside humans and can pick up items before they have been packed in boxes, although it may still struggle with loose or complex packaging. Tye Brady, chief technologist at Amazon Robotics said: “I don’t view it as replacing people. It’s humans and machines working together—not humans versus machines—and if I can allow people to focus on higher-level tasks, that’s the win.” Why this is important: Many times, here at SuperDataScience, we’ve discussed how automation, in various forms, may result in job losses. In many ways, Amazon is rather behind the curve but it will always be newsworthy when such a giant retailer adopts new practices. [Click here to find out more!]( [Super Data Science podcast]( this week's [Super Data Science Podcast](, we welcome Chainalysis' Director of Research, Kim Grauer, to explore the state of economic-data analysis on the blockchain. --------------------------------------------------------------- What is the Data Science Insider? This email is a briefing of the week's most disruptive, interesting, and useful resources curated by the SuperDataScience team for Data Scientists who want to take their careers to the next level. Want to take your data science skills to the next level? 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