RSS DS+AI Section

The RSS DS+AI Section Substack is dedicated to the professional development, research advancements, and ethical considerations within the field of Data Science and AI. It provides updates on committee activities, industry news, ethical debates, and practical applications of AI, emphasizing engagement with the community and promoting best practices.

Ethics and Diversity in AI AI Policy and Regulation Generative AI and Research Developments Data Science Professional Development AI in Healthcare Open Source AI Projects AI Safety and Accountability Real-World AI Applications AI and Data Science Events AI for Social Good

The hottest Substack posts of RSS DS+AI Section

And their main takeaways
53 implied HN points β€’ 31 Dec 23
  1. The focus for the year was 'Effective and Efficient Data Science' to highlight the critical aspects of the field beyond hype.
  2. Various events and discussions were held throughout the year to promote best practices in Data Science.
  3. Engagement with the community through events, surveys, and articles was emphasized to ensure diverse voices are heard in influencing policy.
11 implied HN points β€’ 01 Mar 24
  1. The newsletter discussed various updates and activities in the field of data science and AI, including committee activities, advancements in research, and real-world applications.
  2. Ethical considerations, bias, diversity, regulation, and safety in AI and data science were highlighted as hot topics in the newsletter, with examples of AI-related consequences and efforts to improve safety.
  3. The newsletter also featured practical tips, how-to guides, and bigger picture ideas in the field, providing a broad range of information for data science practitioners.
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23 implied HN points β€’ 04 Nov 23
  1. The newsletter covers various topics in Data Science and AI including ethics, research, and practical applications.
  2. Committee activities include calls for new members, updates on AI Safety Summit, and announcements for events like the Christmas social.
  3. The newsletter also highlights significant developments in AI research, such as GenAI, robotics, and Large Language Models.
23 implied HN points β€’ 02 Oct 23
  1. The newsletter discusses various Committee Activities like professional development certification and sessions at the RSS conference.
  2. Ethics, bias, and diversity are hot topics in data science and AI, with ongoing discussions on AI regulation and accountability.
  3. The newsletter covers exciting developments in Data Science and AI research, including generative AI, real-world applications, and practical tips.
11 implied HN points β€’ 03 Dec 23
  1. The December newsletter covers a wide range of activities and achievements in the field of Data Science and AI.
  2. There is a focus on topics like ethics, regulations, and bias in the AI industry.
  3. The newsletter also delves into the latest developments in Generative AI and provides practical tips for driving analytics and ML into production.
11 implied HN points β€’ 28 Nov 23
  1. Join the Data Science and AI Christmas mixer on December 5th at Artillery Arms in London.
  2. Bring merry cheer and mingle with like-minded data scientists and AI engineers at the pub.
  3. Look out for attendees in tasteful hats to navigate the full pub.
11 implied HN points β€’ 19 Sep 23
  1. The Royal Statistical Society is seeking input on its 2024 strategy via a short survey.
  2. They are interested in how to best promote statistics and data in society and drive evidence-based decision making.
  3. Participating in the survey could enter you into a prize draw for a year of RSS fellow membership.
11 implied HN points β€’ 03 Jul 23
  1. The newsletter features updates on industrial strength data science, including committee activities and upcoming events.
  2. Ethics, bias, and diversity remain hot topics in data science and AI, with examples of generative AI misuse and intentional misuse.
  3. The newsletter includes practical tips, developments in research, and fun projects in the data science and AI field.
11 implied HN points β€’ 02 Jun 23
  1. June newsletter focuses on Open Source special, including recent developments in the open source community.
  2. The newsletter highlights activities of the committee, discussions on AI ethics and diversity, and advancements in generative AI.
  3. An in-depth exploration of the open source explosion driven by the development of generative AI, showcasing the surge of open source capabilities and research contributions.
5 implied HN points β€’ 01 May 23
  1. The May newsletter contains updates on data science and AI developments, including information on the Royal Statistical Society's activities.
  2. There is a focus on ethics, bias, and diversity in data science, along with concerns about AI model safety and regulatory challenges.
  3. Generative AI remains a hot topic, with discussions on training models, practical applications, and real-world impact of AI in healthcare, design, and storytelling.
0 implied HN points β€’ 04 Oct 21
  1. The newsletter highlights the committee's activities, such as advocacy for data science practitioners and preparation for next year's conference.
  2. The newsletter covers various topics in data science like ethics, bias, diversity, and practical real-world applications of AI.
  3. The newsletter provides insights on recent developments in data science, including research papers, projects, and learning opportunities, as well as tips and advice for practitioners.
0 implied HN points β€’ 13 Sep 21
  1. The UK's AI Strategy may not be aligned with the needs of the technical community.
  2. There is a need for better collaboration between academia and industry in AI research and development.
  3. Emphasizing open-source, supporting startups, and prioritizing ethics are key recommendations for the UK's AI Strategy.
0 implied HN points β€’ 01 Sep 21
  1. Ethics, bias, and diversity are important topics in data science.
  2. New developments in data science like reinforcement learning and deep learning are happening constantly.
  3. Practical applications of data science are making a real-world impact, from face mask recognition to early dementia detection.
0 implied HN points β€’ 01 Aug 21
  1. The newsletter covers a variety of data science topics and updates from the Royal Statistical Society Data Science Section.
  2. The August edition discusses ethics in data science, recent developments in the field, and real-world applications of AI.
  3. Practical projects, learning opportunities, and insights into driving ML into production are also highlighted in the newsletter.
0 implied HN points β€’ 01 Jul 21
  1. The newsletter shares curated data science reading materials for the month.
  2. There are updates on developments in data science, including ethics, technologies, and real-world applications.
  3. The newsletter also discusses understanding different approaches, driving machine learning into production, and the art of decision making.
0 implied HN points β€’ 06 Jun 21
  1. The RSS aims to shape the government's AI strategy by highlighting the importance of statistics and data science.
  2. The RSS plans to gather input from data science professionals to inform the AI roadmap.
  3. The RSS will engage with government stakeholders through events and roundtables to refine their thinking on AI strategy.
0 implied HN points β€’ 01 Jun 21
  1. Ethics, bias, and diversity are important topics in data science
  2. New developments and advancements are always happening in data science
  3. Real world applications of data science have a positive impact in areas like healthcare and sports
0 implied HN points β€’ 03 May 21
  1. Ethics and diversity are hot topics in data science, with calls for regulation against questionable AI use cases.
  2. Exciting new developments in data science include deep learning aiding scientific discovery and advancements in model compression.
  3. Real world applications of data science are making a difference, from early detection of colon cancer to decoding whale language.
0 implied HN points β€’ 01 Apr 21
  1. The UK's efforts to provide Covid-19 updates have shown the importance of good visualization of data.
  2. Ethical concerns continue to be prominent in the field of data science, with issues like bias and diversity gaining attention.
  3. Developments in data science, such as outlier detection and advancements in AI research, are continuously evolving and offer new opportunities.
0 implied HN points β€’ 26 Mar 21
  1. The inaugural RSS Data Science Ethics Happy Hour focused on discussing ethics of data science in addressing the public health crisis during COVID-19.
  2. Experts at the event discussed the importance of data sharing, technical solutions like Privacy Enhancing Technologies, and the implications of relying too much on data and AI.
  3. The event highlighted complex ethical issues with data science and emphasized the key role of statistical methods in navigating the future.
0 implied HN points β€’ 07 Mar 21
  1. The Ethics Happy Hour event on March 17th will focus on ethical data science in the context of COVID-19.
  2. Three experts will share their thoughts on the ethics of data science in addressing the public health crisis.
  3. Attendees can participate in an open discussion with the experts and share questions and comments during the event.
0 implied HN points β€’ 01 Mar 21
  1. Positive developments in the Covid-19 vaccination rollout, with successful real-world efficacy studies for various vaccines.
  2. Ongoing discussions and developments in data science ethics, diversity, and bias, including recent events at Google.
  3. Advancements in data science technologies and techniques like GPT-3 models, switch transformers, and challenges in model generalization.
0 implied HN points β€’ 01 Feb 21
  1. The newsletter highlighted the ongoing impact of the COVID-19 pandemic, especially regarding vaccination rollout and testing controversies.
  2. The data science community is actively engaged in various activities like AI ethics discussions, AI in healthcare developments, and understanding different data science techniques.
  3. Updates from members and contributors showcased practical projects, learning opportunities, as well as events and interesting work in the field.
0 implied HN points β€’ 13 Jan 21
  1. Andrew Ng has made significant contributions to AI and machine learning, beyond his popular Stanford University course.
  2. The fireside chat will focus on technical leadership in artificial intelligence and offer advice on becoming effective AI leaders.
  3. The event will feature discussions on running successful R&D teams for AI product development and supporting a new generation of AI leaders in the UK.
0 implied HN points β€’ 04 Jan 21
  1. 2021 starts with updates on Covid, where mutations are affecting transmission rates.
  2. Exciting news on vaccine developments, like the mRNA technology breakthrough.
  3. Data science is evolving with topics ranging from ethics to new advancements in DeepMind's projects.
0 implied HN points β€’ 09 Dec 20
  1. Andrew Ng will be speaking at the RSS Data Science Section about leadership in AI and data science.
  2. The discussion will focus on creating successful R&D teams and delivering business value.
  3. Guests can submit questions for Andrew Ng, such as structuring R&D teams and deciding important research topics.
0 implied HN points β€’ 04 Dec 20
  1. The December newsletter covers topics like Covid updates, data science ethics, and AI advancements.
  2. The newsletter also highlights data science committee activities and member contributions.
  3. Various real-world data science applications and practical projects are discussed in the newsletter.
0 implied HN points β€’ 03 Nov 20
  1. Covid cases are rising, and understanding numbers, statistics, and models is crucial in managing the virus.
  2. Data science community is actively engaged in various initiatives like AI Ethics Happy Hours and data science accreditation discussions.
  3. Advancements in data science include training models with less data, leveraging machine learning in scientific research, and tackling bias using Bayesian Networks.