Data Science Insider: December 22nd, 2023

In This Week’s SuperDataScience Newsletter: AI Denied Inventor Status in Landmark Decision. Mastering Data Quality for Robust Analytics. Rethinking A/B Tests. AI Image Generators Conceal Child Abuse Imagery. Budget-Friendly Data Science Books. 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 Denied Inventor Status in Landmark Decision]( brief: In a landmark decision, the UK Supreme Court has ruled that AI machines cannot be named as inventors on patents. The unanimous rejection of a challenge, ongoing since 2018, settles the question of whether AI tools, such as Dabus, a neural network responsible for designing a malleable food container and a flashing light, can be designated as inventors. Long-term readers of the SuperDataScience newsletter will be familiar with the case and its potential repercussions. The court upheld the UK Patents Act, stating that only a "natural person" can be considered an inventor. These decision impacts discussions on the rights and protections machines should receive, as AI continues to advance rapidly in various fields. Why this is important: The ruling clarifies that the definition of an inventor, according to existing legal frameworks, is limited to natural persons. But as AI is increasingly used as a tool for creation across society, this brand of dispute is likely to become more common. [Click here to learn more!]( [Mastering Data Quality for Robust Analytics]( brief: In the field of data science, ensuring data quality is paramount for effective platform design and governance. This Medium article by Jose Manuel Garcia Gimenez, is framed within Databricks' Lakehouse platform and delves into implementing data quality principles, emphasizing the six dimensions: Consistency, Accuracy, Validity, Completeness, Timeliness, and Uniqueness. Databricks offers best practices, utilizing Delta features and Delta Live Tables (DLT). Notably, the article underscores challenges and limitations, urging caution in DLT's enterprise application. The proposed implementation addresses schema flexibility, accuracy through Delta constraints, timeliness via structured streaming, and completeness with Delta ACID guarantees. Effective monitoring, including custom metrics and Databricks lakehouse monitoring, is highlighted for comprehensive data quality management. Why this is important: In essence, mastering these six dimensions equips data scientists to architect data platforms with enduring, high-quality data integrity [Click here to read on!]( [Rethinking A/B Tests]( In brief: In this thoroughly illuminating and entertaining Towards Data Science article, Ukrainian product data analyst Kralych Yevhen challenges the conventional wisdom of testing everything through A/B experiments. While industry leaders advocate for continuous testing, Yevhen argues that blindly following this approach can lead to confusion and disaster, particularly for smaller businesses lacking the vast resources of tech giants like Google or Amazon. The article delves into the complexities of statistical power and sensitivity in A/B testing, emphasizing that not all changes require rigorous experimentation. Yevhen instead proposes a resource-first approach, advising businesses to carefully allocate resources based on the sensitivity of tests, ultimately fostering a more pragmatic and effective experimentation mind set. Why this is important: By emphasizing the importance of a resource-first design, the article provides valuable insights for data scientists to navigate the complexities of experimentation and make informed decisions that align with the business's specific needs and constraints [Click here to discover more!]( [AI Image Generators Conceal Child Abuse Imagery]( In brief: In a disturbing revelation, the Stanford Internet Observatory has disclosed that popular AI image generators, including the widely used LAION database, contain thousands of images depicting child sexual abuse. These findings were published this week and prompted immediate action as LAION temporarily removed its datasets, emphasizing a "zero tolerance policy for illegal content." While these images represent a fraction of LAION's vast index, the Stanford group argues that they may be influencing AI tools, impacting their ability to generate harmful outputs and perpetuating the abuse of real victims. For data scientists, this underscores the ethical challenges in AI development; urging stringent measures to ensure responsible data use and mitigate the risk of harmful content generation. Why this is important: This story makes more horrifying reading but the discovery is important and hopefully can be the starting point of ensuring the removal of all abuse imagery. [Click here to see the full picture!]( [Budget-Friendly Data Science Books]( In brief: Unlocking the complexities of data science need not strain your budget. In this list KDNuggets identifies five budget-friendly books to elevate your data science prowess. These include Data Science by John D. Kelleher and Brendan Tierney which delves into the industry's history, applications, tools, ethical concerns, and career growth at a mere $9. Python Data Analysis by Avinash Navlani, Armando Fandango, and Ivan Idris, priced at $16, guides readers through core Python libraries, statistical foundations, advanced analysis, specialized techniques, and computational efficiency. Charles Wheelan's Naked Statistics demystifies statistical concepts, offering real-world applications for $8. The Hitchhiker's Guide to Machine Learning Algorithms by Devin Schumacher, Francis La Bounty Jr., and Devanshu Mahapatra explores ML techniques for a mere $12. Why this is important: Looking for a last minute stocking filler or something to read over the festive break? These books have you covered without breaking the bank. [Click here to see the full picture!]( [Super Data Science podcast]( In this week's [SuperDataScience]( Podcast episode, data visualization remains at the forefront as Dr. Alberto Cairo from the University of Miami guides us beyond numerical figures, exploring the art of weaving compelling narratives through data. In his book, "The Art of Insight," he reveals the varied motivations driving visualization experts and highlights the serene, meditative process inherent in crafting visualizations. Emphasizing the fusion of scientific principles and personal style for effective data communication, Dr. Cairo also discusses with Jon the impending impact of AI on both interactive and static graphics. [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