Data Science Insider: May 28th, 2021

In this week’s Super Data Science newsletter: Hyperconverged Analytics. Court Rules GCHQ’s Mass Data Interception Violated Right to Privacy. Microsoft boss warns AI may mean Orwell’s 1984 by 2024. Nokia Launches World’s First Telecoms AI Use Case Library. Networking Communities for Underrepresented Data Scientists. 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. --------------------------------------------------------------- [Hyperconverged Analytics]( brief: This article by Forbes looks at how analytics are becoming hyperconverged and the impact that this will have on the future of the data science industry. Hyperconvergence is an IT framework that combines storage, computing, and networking into a single system in an effort to reduce data center complexity and increase scalability. Hyperconverged platforms include a hypervisor for virtualized computing, software-defined storage, and virtualized networking, and they typically run on standard, off-the-shelf servers. Multiple nodes can be clustered together to create pools of shared computing and storage resources, designed for convenient consumption. The use of commodity hardware, supported by a single vendor, yields an infrastructure that's designed to be more flexible and simpler to manage than traditional enterprise storage infrastructure. Hyperconvergence is winning over enterprises that are drawn to its potential to ease management, streamline the deployment of new workloads, and optimise infrastructure costs. Why this is important: This article takes “one of the IT watershed tier moments of our age,” breaks down its application, and explores how data analytics is being transformed by its increased usage, making a tricky concept easy to understand. [Click here to find out!]( [GCHQ’s Mass Data Interception Violated Right to Privacy]( brief: The UK spy agency GCHQ’s methods for bulk interception of online communications violated the right to privacy and the regime for the collection of data was unlawful, the grand chamber of the European court of human rights has ruled. In what was described as a “landmark victory” by Liberty (one of the applicants) the judges also found the bulk interception regime breached the right to freedom of expression and contained insufficient protections for confidential journalistic material but said the decision to operate a bulk interception regime did not of itself violate the European convention on human rights. The chamber, the ultimate court of the ECHR, also concluded that GCHQ’s regime for sharing sensitive digital intelligence with foreign governments was not illegal. The judgment stated: “In order to minimise the risk of the bulk interception power being abused, the court considers that the process must be subject to ‘end-to-end safeguards’.” Why this is important: Although most of us are unlikely to be conducting mass surveillance, the ECHR’s decision shows the importance of data protection across all of society. As data scientists, we must pay heed to the ruling and be aware of the need for ‘end-to-end safeguards’ when processing sensitive data. [Click here to read on!]( [AI may mean Orwell’s 1984 by 2024]( In brief: George Orwell’s dystopian vision of the world in his novel 1984 “could come to pass in 2024” if AI is not better regulated, the president of Microsoft has warned. Brad Smith has called on politicians around the world to enact stricter laws to govern the development and use of AI. Smith told the BBC’s ‘Panorama’ during a special exploring China's increasing use of AI: “If we don’t enact the laws that will protect the public in the future, we are going to find the technology racing ahead, and it’s going to be very difficult to catch up. I’m constantly reminded of […] 1984. You know the fundamental story was about a government who could see everything that everyone did and hear everything that everyone said all the time. Well, that didn’t come to pass in 1984, but if we’re not careful that could come to pass in 2024.” Why this is important: The documentary and this subsequent article have many shocking examples of China’s use of AI in order to spy on its citizens. As with the article on GCHQ, this should teach us important lessons about surveillance, technology, and ethics. This will be particularly significant as the AI race between China and the US ramps up speed. [Click here to discover more!]( [World’s First Telecoms AI Use Case Library]( In brief: Nokia has announced the world’s first deployment of multiple AI use cases delivered over public cloud, through a collaboration with Microsoft. The vendor stated the move enables AI to be added nine times faster than using private cloud, a capability it expects to be in high demand as operators add automation to their networks to manage the complexities of 5G use cases. Data sovereignty, security, and global regulations are all key considerations for network operators as they leverage AI. Nokia claims that its security framework combines the security of a private cloud with the speed of a public one. It named Australian mobile operator TPG Telecom as the first commercial adopter of Nokia AVA AI on public cloud. Rick Lievano, CTO of telecom, media, and communications at Microsoft, said “public clouds are ready to help service providers drive AI closed-loop automation while increasing speed, agility, and scalability.” Why this is important: AI use cases are essential for communications service providers (CSPs) to manage the business complexity that 5G and cloud networks bring, and will help accelerate digital transformation. The library allows CSPs to deploy AI use cases quickly and securely, completing data setup in as little as four weeks. [Click here to see the full picture!]( [Networking Communities for Underrepresented Data Scientists]( In brief: As we have explored on many occasions in these newsletters, our industry has a serious issue with equality. Approximately 15 to 20% of people in data science-related roles are female, and approximately one-sixth is underrepresented minorities. Black women account for only 3% of employees in data and analytics roles. Management is approximately five-sixths Caucasian. Women in technical positions are twice as likely to leave a position as men and will receive, on average $10,000 Less per year than a man. These figures are shocking and need to be challenged. This article lists ten networking groups that are doing just that and offer support with the aim of advancing women, people of color, and people with disabilities in the data field. Some of the organisations are well established and lobby for change in the industry, whilst others are relatively new – all offer resources to help bridge the gaps. Why this is important: By engaging with these groups, underrepresented parts of our industry can gain support and find a safe space in a sometimes-hostile industry. By tackling our industry’s issues with diversity, we can make society better and also help to eradicate technological issues caused by bias. [Click here to find out more!]( [SuperDataScience podcast]( In this week's [SuperDataScience Podcast](, Anima Anandkumar stops by for an incredible discussion on her work at NVIDIA, the neuroscience components of deep learning, her favorite data science tools, and the path to generalized artificial intelligence. --------------------------------------------------------------- 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 more conversations like this? Are you either a data professional or an executive trying to implement AI technologies in your organization? We’re sure you’re always exploring some upskilling opportunities for yourself or your team. Please share your experience with corporate and self-education [right here](. 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