June 19, 2025

Dear Reader,

Welcome to the Juneteenth issue of the Data Science Briefing!

We’re proud to announce that a brand new Data Visualization with Python on-demand video is now available on the O’Reilly website: Python Data Visualization: Create impactful visuals, animations and dashboards. This in depth tutorial is almost 7h in length and covers fundamental and advanced usage of matplotlib, seaborn, plotly and bokeh as well as tips on how to use Jupyter widgets. Check it out!

The latest blog post on the Epidemiology series is also out: Demographic Processes. In this post we explore how to include birth and death rates in your epidemik models. Check it out!

This week’s newsletter highlights several cutting-edge developments in the world of AI agents and security. A standout is the new paper, “Design Patterns for Securing LLM Agents against Prompt Injections,” which introduces six actionable patterns—such as the Action-Selector and Plan-Then-Execute patterns—to help developers build large language model (LLM) agents that are robust against prompt injection attacks. These patterns offer a practical balance between agent utility and security, directly addressing the growing risks as LLMs are increasingly integrated with external tools and data sources. Complementing this, recent research on the automated design of agentic systems explores how meta-agents can autonomously generate and optimize agent architectures in code, potentially leading to more powerful and adaptable AI systems that outperform traditional hand-designed agents. Together, these advancements signal a shift toward both safer and more innovative agentic AI, underscoring the importance of security and automation in the next generation of intelligent systems.

Recent research continues to reveal the intricate interplay between social structures, technology, and human behavior. A large-scale study mapping face-to-face social networks in isolated Honduran villages demonstrates how understanding the fabric of personal relationships, such as trust and time spent together, can inform strategies for public health interventions and the spread of information. These findings are echoed in new epidemiological modeling work, where scalable Bayesian inference methods like ScITree leverage both genomic and social data to reconstruct transmission pathways, underscoring the value of detailed network knowledge in managing disease outbreaks. Meanwhile, as AI systems become more integrated into daily life, evidence is mounting that clinical knowledge encoded in large language models does not seamlessly translate to effective human interactions, highlighting a persistent gap between technical proficiency and social competence. Together, these studies emphasize the importance of both mapping and understanding human networks—whether for health, technology, or communication—and the ongoing challenge of ensuring that advanced models align with real-world human needs.

This week’s book is “Behavioral Network Science: Language, Mind, and Society” by T. T. Hills. You can find all the previous book recommendations on our website. In this week’s video, we have a lecture on How We Build Effective Agents by Barry Zhang of Anthropic.

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Semper discentes,

The D4S Team