Data Science Insider: April 14th, 2023

In This Week’s SuperDataScience Newsletter: China Introduces New AI Regulations. John Snow's Epidemiology Approach Influences NLP Testing. Advanced Data Science Books for Practitioners. Automated Data Entry Revolutionises Healthcare. AI Newsreader Debuts in Kuwait. 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. --------------------------------------------------------------- [China Introduces New AI Regulations]( brief: The Cyberspace Administration of China has unveiled draft regulations covering generative AI. In accordance with the regulations, companies must register such products with the agency and submit them for security assessment prior to public release. In addition, businesses will be responsible for checking the “legitimacy of the source of pre-training data”, to ensure content reflects the “core value of socialism” and must not include calls for the subversion of state power or encourage activities deemed detrimental to national unity. The businesses will also be prevented from using personal data for generative AI training and must require users to verify their identities. Those breaking the rules could face fines between CNY10,000 ($1,454) and CNY100,000 ($14,545) as well as possible criminal investigations. Why this is important: Here at SuperDataScience we’ve frequently covered the AI war between China and the US. The release of ChatGPT was seen as proof that the US was significantly more advanced and these new regulations have been seen by many as an opportunity to play catchup. [Click here to learn more!]( [John Snow's Epidemiology Approach Influences NLP Testing]( brief: John Snow, a pioneer in the field of epidemiology, is often credited with the discovery of the source of a cholera outbreak in London in 1854. However, he was also interested in understanding the social determinants of health and how they influenced the spread of disease. Today, his approach to epidemiology has been applied to natural language processing (NLP) through the creation of a test library that goes beyond simply measuring accuracy. The John Snow NLP Test Library includes tests for understanding the context and social implications of language use, as well as the ability to identify and address biases in language models. By using this library, developers and researchers can create more robust and socially responsible models. Why this is important: The NLP Test Library is available to try now, for free, and offers data scientists the chance to build responsible NLP models. Why not take the opportunity to learn from John Snow’s approach today? [Click here to read on!]( [Advanced Data Science Books for Practitioners]( In brief: This article by Medium recommends five data science books for practitioners that go beyond ML. These tombs are lengthy but offer significant insights for data scientists which may broaden your horizons. These include Information Theory, Inference, and Learning Algorithms by David MacKay which explores the exciting world of information theory, Reinforcement Learning and Stochastic Optimization: A Unified Framework for Sequential Decisions by Warren Powell where he discusses the new field he’s created called sequential decision analytics. Other books that are recommended are Bayesian Data Analysis by Andrew Gelman which looks at probability and statistical modeling, Bayesian Optimization by Roman Garnett which offers a thrilling adventure into Gaussian Processes and Principles of Econometrics by Carter Hill. Why this is important: As data scientists we owe it to ourselves to explore theories beyond ML. The SuperDataScience newsletter offers insights every week but long-form novels offer the opportunity for in-depth hypotheses and explanations of complex thoughts. [Click here to discover more!]( [Automated Data Entry Revolutionises Healthcare]( In brief: The use of automated data entry in healthcare settings is on the rise, allowing for more efficient and accurate data collection. Digital healthcare solutions are being used in a wide variety of ways, including being developed to automate the entry of patient data from various sources, such as electronic health records and wearables, into a single platform. This not only saves time for healthcare professionals but also reduces the risk of errors caused by manual data entry. Automated data entry can also improve patient outcomes by providing real-time monitoring and analysis of health data. With the emergence of AI and ML technologies, these platforms can provide more personalized and predictive insights to inform treatment decisions. Why this is important: While there are still a wide variety of challenges to be addressed, such as data privacy and security concerns, the adoption of automated data entry in healthcare has the potential to revolutionise the way patient data is collected and used. [Click here to see the full picture!]( [AI Newsreader Debuts in Kuwait]( In brief: Kuwait has launched its first AI-generated newsreader on a state-run media outlet. The virtual presenter is a blonde-haired computer-generated woman named Fedha who is based on a real-life journalist and uses ML to produce news stories in Arabic and English. The AI system can identify breaking news and create stories in just a few seconds, with the aim of enhancing news production efficiency. However, some journalists and media experts have raised concerns about the impact on jobs and the quality of news reporting. This move comes amid a wider global trend towards the use of AI in news production, with several media outlets experimenting with virtual news anchors and automated news writing. Why this is important: We’ve explored many times in this newsletter the human impact of workers’ roles being replaced by AIs. Whether Fedha is simply a publicity stunt - time will tell, but her existence definitely highlights real-world concerns about the future of certain professions. [Click here to find out more!]( [Super Data Science podcast]( this week's Super Data Science Podcast, Jon Krohn welcomes Adrian Kosowski, Co-Founder and Chief Product Officer at Pathway, who shares insights on streaming data processing and reactive data processing, and how they're shaping the future of machine learning. Tune in now for an unforgettable episode. [Click here to find out more!]( --------------------------------------------------------------- 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? Check out the [SuperDataScience platform]( and sign up for membership today! Know someone who would benefit from getting The Data Science Insider? Send them [this link to sign up.]( # # If you wish to stop receiving our emails or change your subscription options, please [Manage Your Subscription]( SuperDataScience Pty Ltd (ABN 91 617 928 131), 15 Macleay Crescent, Pacific Paradise, QLD 4564, Australia