PyData Ireland is excited to present the first meetup of 2025 in association with AI Safety Dublin.

AI Safety Dublin is a growing grassroots AI community working to reduce risks from advanced AI by raising awareness, upskilling and creating opportunities for a safer AI world of tomorrow.

About This Event

Join us for an insightful examination of the limitations and ethical considerations of big data analysis as presented in Seth Stephens-Davidowitz's popular book "Everybody Lies." While big data offers powerful insights, this talk challenges us to think critically about what data can truly tell us and the ethical boundaries we should observe.

Talk Description

In his bestselling book "Everybody Lies," Seth Stephens-Davidowitz claims to use big data to reveal hidden truths about human behavior and answer society's most pressing questions. But how reliable are these conclusions? Can Google searches and social media truly unlock the secrets of human nature? Aonghus McGovern, Staff Product Analyst at HubSpot, will deconstruct the methodological foundations of big data analysis and explore the ethical implications of mining personal data. Through practical examples and case studies, this talk will demonstrate how seemingly compelling narratives can be built on faulty assumptions about data, people, and the complex relationship between the two. Whether you're a data professional, privacy advocate, or simply curious about the limits of big data's explanatory power, this session will equip you with frameworks to approach data analysis more critically and ethically.

What You'll Learn

1. How to effectively probe datasets to understand their limitations and determine what questions they can and cannot answer
2. Techniques for developing more robust analyses that combine quantitative insights with qualitative human expertise
3. Practical approaches to protecting user privacy and anonymity in the age of ubiquitous data collection
4. Common pitfalls in big data interpretation and how to avoid them
5. Ethical frameworks for deciding when and how to use sensitive data

Who Should Attend

• Data scientists and analysts
• Product managers and UX researchers
• Privacy and ethics professionals
• Anyone interested in the societal impact of big data
• Readers of "Everybody Lies" seeking a critical perspective

About the Speaker

Aonghus McGovern, Staff Product Analyst at HubSpot LinkedIn Profile

Aonghus brings extensive experience in product analytics, with a focus on balancing data-driven insights with ethical considerations. At HubSpot, he works closely with product teams to develop responsible data practices that respect user privacy while delivering actionable business intelligence.

Send us a text The authors of Machine Learning for Dummies – Judith Hurwitz, and Daniel Kirsch — are here to help you. In this episode, Judith, Daniel and Al discuss the state of machine learning today, how to use it to advance your business as well as discoveries they made while writing their book. Learn how small and large businesses alike can find insights from data to enhance relationships with customers. We’ll also share where you can get a copy of Machine Learning for Dummies at no cost. Show notes 01.00 Connect with Al Martin on Twitter and LinkedIn. 01.10 Connect with Kate Nichols on Twitter and LinkedIn. 01.15 Connect with Fatima Sirhindi on Twitter and LinkedIn. 02.00 Learn more about Hurwitz & Associates. 02.10 Connect with Judith Hurwitz on Twitter, LinkedIn and find her blog here. 03.20 Connect with Daniel Kirsch on Twitter and  Hurwitz & Associates 04.00 Read Machine Learning for Dummiesby Judith Hurwitz and Daniel Kirsch. 04.40 Learn what neural nets are here. 04.50 Learn more about Arthur Samuel here. 05.00 Learn more about how Deep Blue beat the world chess champion. 15.39 Learn more about Apache Hadoop.  17.30 Learn more about IBM Watson. 26.50 Find Cognitive Computing and Big Data Analytics by Judith Hurwitz, Marcia Kaufman and Adrian Bowles. 27.45 FindEverybody Lies: Big Data, New Data and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

In this podcast, Seth Stephens-Davidowitz (@SethD_S), author of New York Times Bestseller Everybody Lies, discussed what our social data knows about us. He shares some critical insights into the human psyche on how humans behave differently to machines than fellow humans. This sheds some interesting light on today's data-driven disruptive times when curiosity to stay relevant and data-driven is at an all-time high. This is a great podcast to understand the capability that data has and how it could benefit humanity, businesses, and clients if used properly—a great session for anyone willing to understand the depth of data and how to use it effectively.

Timelines: 0:29 Seth's journey. 4:23 Story behind "Everybody lies". 7:27 Finding the right searches to analyze. 8:42 Surprising findings on analyzing the internet searches of people. 10:50 Confusion and human search data. 12:55 Google search recommendation's effect on human search data. 15:47 To google or not to google. 17:48 Are surveys reliable? 19:29 Safeguarding against fake data. 22:30 Compromised privacy may be a good thing. 24:30 Seth's favorite tool or language. 25:40 Challenges in working with data. 26:22 Finding a hypothesis in human search data. 28:02 Political predictions through data. 32:10 On Cambridge Analytica 35:05 The ethics of data. 39:05 On AI 41:24 Defining a data scientist. 43:11 Key points of "Everybody lies". 44:17 Secret behind Seth's success. 45:50 Journey from a basketball to data scientist. 48:03 Seth's favorite reads. 48:34 Key takeaways.

Seth's Book: Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz amzn.to/2OA0YBs

Seth's Recommended Read: Enlightenment Now: The Case for Reason, Science, Humanism, and Progress by Steven Pinker amzn.to/2Kl2nsr

Podcast Link: https://futureofdata.org/understand-social-data-to-know-human-psyche-seths_d-author-nytbestseller-everybody-lies-futureofdata-podcast/

Seth's BIO: Seth Stephens-Davidowitz has used data from the internet -- particularly Google searches -- to get new insights into the human psyche.

Seth has used Google searches to measure racism, self-induced abortion, depression, child abuse, hateful mobs, the science of humor, sexual preference, anxiety, son preference, and sexual insecurity, among many other topics.

His 2017 book, Everybody Lies, published by HarperCollins, was a New York Times bestseller, a PBS NewsHour Book of the Year, and an Economist Book of the Year.

Seth worked for one-and-a-half years as a data scientist at Google and is currently a contributing op-ed writer for the New York Times. He is a former visiting lecturer at the Wharton School at the University of Pennsylvania. He received his BA in philosophy, Phi Beta Kappa, from Stanford, and his Ph.D. in economics from Harvard.

In high school, Seth wrote obituaries for the local newspaper, the Bergen Record, and was a juggler in theatrical shows. He now lives in Brooklyn and is a passionate fan of the Mets, Knicks, Jets, Stanford football, and Leonard Cohen.

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

Wanna Join? If you or any you know wants to join in, Register your interest by mailing us @ [email protected]

Want to sponsor? Email us @ [email protected]

Keywords: FutureOfData,

DataAnalytics,

Leadership,

Futurist,

Podcast,

BigData,

Strategy