How data deceives and informs us - with Emma McCoy

What are the risks and benefits of data analysis and output from AI tools?
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This lecture was recorded at the Ri on 20 April 2024, in collaboration with the Martingale Foundation. Martingale Foundation supports a new generation of postgraduates to become STEM leaders, enabling talented students facing financial barriers to pursue Masters and PhDs at some of the leading research universities in the UK. Find out more here: martingale.fou...
As our world becomes increasingly digital, the role of data science and AI literacy is more important than ever. Whether in academia, the professional world, or as engaged citizens, understanding these technologies has become indispensable for informed decision-making.
Join Emma McCoy, Vice President and Pro-Vice Chancellor (Education) and Professor of Statistics at the London School of Economics (LSE), as she sheds light on the importance of these skills by drawing on her own experiences. Emma will guide us through the landscape of data science, emphasising its role in extracting meaningful insights. She will also highlight the importance of AI literacy, going beyond basic understanding to critically assess and interpret AI outputs.
Finally, Emma will address the potential pitfalls of these skills as well as their applications, arming us with tips and tricks to avoid biases in the quest for accurate results.
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Emma McCoy is Vice President and Pro-Vice Chancellor (Education) and Professor of Statistics at the London School of Economics (LSE). She has a particular interest in mathematics education and is a member of the Royal Society Advisory Committee of Mathematics Education (ACME), and its A-level Contact Group for Mathematics. Emma’s research interests are in time series and causal inference, with a particular focus on how best to use data to inform intervention policies in transport applications. She is a Fellow of the Institute of Mathematics and its Applications and the Royal Statistical Society.
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[@duncang7372]

Thought provoking and entertaining - thanks to the RI for sharing

[@jonnscott4858]

Very 1st lesson I was told about computers was "sh@# in = sh@# out" 40 years later and it also applies to AI.

[@relwalretep]

GIGO

[@JAJAJA99999]

Are you a plumber?

[@dimitristsagdis7340]

I don't get that point about smoking and Alzheimers, most studies I've seen report that smoking increases the risk of dementia.

[@KWierd]

It was a joke about how they wanted to die/ be killed by something before the got Alzheimer's. So, they stopped smoking to live longer, but didn't want to love long enough to get Alzheimer's.

[@dimitristsagdis7340]

@@KWierd Tnx now I get it - 😂

[@markdatko4832]

I don't suppose Dr McCoy remembers 30 years ago

[@gidi1899]

love it

[@Neverforget71324]

Too much rambling and talking about herself. Please stick to the subject, start from the beginning, don't assume that your audience are already experts.

[@rejophilipjose7763]

I swear

[@CoachPegasus]

🎯 Key points for quick navigation: 00:35 *📊 Data collection and its implications* - Data collection has expanded dramatically, posing challenges in storage and utilization. - Emphasizes the shift towards purpose-driven data collection. 02:00 *🌐 Challenges in establishing causality* - Explores complexities in causal inference and decision-making. - Discusses data quality's impact on effective decision-making. 03:23 *🧠 Approaches to counterfactual reasoning* - Strategies and methodologies for counterfactual reasoning. - Insights into robust causal inference frameworks. 21:12 *📊 Causal inference in experimental design and statistics* - Discusses experimental design challenges and COVID-19 data interpretation. - Highlights the role of counterfactuals in causal studies. 23:42 *🧪 Test and Trace data analysis: Understanding missing data and counterfactuals* - Analyzes Test and Trace data discrepancies and observational study limitations. 31:00 *📉 Simpson's Paradox: Misleading conclusions from aggregated data* - Explains Simpson's Paradox in data aggregation. - Discusses the impact of confounding variables. 34:41 *📊 Directed Acyclic Graphs (DAGs) in causal inference* - Introduces DAGs for identifying causal relationships. - Emphasizes understanding variables in causal studies. 42:56 *📊 Causal Inference Foundations* - Understanding causal inference conditions for valid outcomes. 45:27 *🌍 Impact of Low Traffic Zones* - Studied air quality improvements in low traffic neighborhoods. - Demonstrates effectiveness despite COVID-19 disruptions. 49:12 *📚 Academic Reflections* - Reflects on academic critique and the role of free speech in academia. - Discusses historical critiques and their impact on modern data science. Made with HARPA AI

[@jf-jx4ym]

I have never zoomed so intensely on a video. Her earrings are so pretty.

[@jf-jx4ym]

Exactly right in The end abt inherent determinism problem in all modern systems and people using them. A learning problem... But for many the damage is done. Especially if facing a conflicting motif or error. Which there are plenty... Structural, intentional or unintentional. Explicit or implicit.

[@GedLi784]

Let's talk about me and my career!

[@Gringohuevon]

Poor, me me me me me

[@why-no-investigation-reports]

So you don't care about disclosing US crimes ??? ?

[@weiyuquan2425]

Come on, stop talking about yourself

[@herbsandflowers8152]

A bit too excited about people dying or maybe it was an attempt at humor

[@BabarizamDK]

She is not good at explaining in simplicity

[@R.T.A.J.E..S.t.a.r.t.e]

❤❤❤

[@rockapedra1130]

Made it until 5 minutes in. That's when the gender talk started. Can't we just talk about the topic at hand for once? It's pretty sad.

[@Neverforget71324]

Agree. Also didn't like her comment about the university she works at now is a lot more "political"... geez... pretty sure that doesn't affect her impartiality / findings. 🙄 Also seems to really miss the Covid hysteria times. She's a bit too much "Ministry of Truth" for my liking. About the focus on gender: As a man, I am sick and tired of the insinuation that it's somehow my gender's fault that not enough girls go into STEM. In my first year of engineering (1983), there were 500 students and maybe 20-25 of them were girls. I would have LOVED to have 50 percent girls... for one, it would've made the parties a lot more interesting, but also because women approach problems differently than men and having different approaches come together is so enriching and powerful. I have worked with quite a few female engineers and scientists over the years and many (not all) can run circles around the men. I tried very hard to make my daughter go into the STEM field... and it pains me to say that I wasn't successful. I know she would have been great.

[@rockapedra1130]

@@Neverforget71324 My daughter also scored ridiculously high in STEM evaluation. Top 1%. So yes, she can do it, but she has no interest in it. I tried to get her to consider it as a career but she thinks the whole thing is BORING to death. She went into theater, and is super happy. Loves her job every single day. We have to stop trying to shoehorn OTHER people into places WE think they should go.

[@timothy8426]

Especially when you follow the normal information that is not probable but speculation that is pushed by the norm. Magnetism is a force of pressure equalization to distance traveling. Space is a weak external magnetic field filled with dark heat energy outside of entanglement of mass as potential renewable heat energy when entanglement with mass occurs. Earth's internal magnetic field grounding currents through its core or nucleus is absolute fact. Heat currents grounding of renewable incoming heat energy and outgoing heat energy currents grounding to surrounding gasses and earth's internal magnetic field synchronization of quantum magnetic fields as force of pressure known as bonding currents as force of weight. The closer to the core of a magnetic field, cycling circulation is the strongest force of pressure. Force is always equalization to distance traveling cycling circulation patterns as mass in and out of entanglement of mass. Repulsion of occupational space as neutralized repulsion within mass as outward force of pressure outside of a greater internal magnetic field grounding currents like earth's internal magnetic field as weightless. Mass occupies equalization of space itself as cold repulsion within mass and repulsion without mass equalization to force and distance traveling. Mass falls in equalization to repulsion within and without. As mass moves away from earth's internal magnetic field, distance traveling increases, and force of pressure known as weight decreases. Heat currents grounding towards earth's greater internal magnetic field. Electricity is rapid heat exchanging through mass as renewable heat energy grounding currents towards earth's internal magnetic field as synchronized flow of pressure cycling circulation patterns as quantum internal magnetic fields grounding currents through the nucleus or core where force is strongest. External magnetic fields don't ground currents through the nucleus or core but circulation around these monopoles of pure repulsion as magnetic field generators that spin all external heat energy within its magnetic field. As mass expands, its magnetic field expands and weakens. Hydrogen has the strongest internal magnetic field grounding currents of the elements. Hydrogen under extreme pressure expands into helium and contains more heat energy currents grounding than hydrogen and occupies more cold space within. More energy equalization to more cold repulsion within and without entanglement of mass. Light is only present in resistance to mass as renewable heat energy unabsorbed bouncing off mass as striking sparks of electrons as friction lighting up surrounding atmospheres. External heat energy outside of entanglement of mass in space and atmospheres outside of entanglement of mass as potential renewable heat energy when entanglement with mass absorption. Unabsorbed heat singularities striking sparks of friction lighting up surrounding atmospheres. Heat magnification of refraction as light sparks known as electrons. Heat is the lifeblood of everything throughout space and mass as the only renewable source of energy within and without entanglement of mass. Physics works. Hydrogen occupies space as mass. Cold repulsion within mass is an outward force of pressure as heat propulsion momentum from cold repulsion within and without entanglement of mass in equalization to force of pressure and distance traveling. Hydrogen has the strongest force of pressure and minimum distance traveling cycling circulation patterns as mass. Helium has more heat energy currents grounding and occupies more space in equalization to force and distance traveling cycling circulation. Repulsion increases in equalization to mass as an area of repulsion. More mass, occupational space, and current grounding. Impaction of force increases, and distance traveling decreases. Force decreases in equalization to distance traveling, which increases within and without entanglement of mass. Magnetism works for physics without gravity. Theoretically factual probability that works with quantum physics without gravity.

[@johncarter1150]

Facts of flat earth... thanks, Terrence Howard

[@Neverforget71324]

Maybe you should talk at the RI.

[@kenpumphrey8384]

First RI video that I couldn't watch until the end. She talked way too much about herself and biking. I stopped 16 minutes in.