Questioning Experts: How to Avoid Being Misled by Data | Quentin Gallea

Описание: In this episode, Quentin and I discuss the importance of causal inference and its applications in various fields. We cover topics such as its relevance for data scientists and its impact on decision-making for business owners and executives. We also highlight the importance of questioning experts, something that is accessible to anyone regardless of their background.
We touch on the complexity of causality in health and fitness, external validity and generalizability, and the role of causal inference in policy research.

Highlights:
Causal inference sounds like a niche topic but is used everywhere in decision-making.
Data scientists should learn causal inference to gain a competitive advantage in the job market.
Causal inference requires the ability to think critically about the mechanisms behind data.
Business owners and executives can benefit from a causal mindset and understanding biases in decision-making.
Questioning experts and measuring causal effects is essential for making informed decisions.
The causal mindset requires an openness to challenging one’s own beliefs.
Causal thinking can be applied in everyday life to make better decisions and avoid misleading information.

Where to find Quentin

Website: https://www.quentingallea.com/
LinkedIn: https://www.linkedin.com/in/quentin-gallea...


Where to find Ida

Website: https://idajohnsson.com/
LinkedIn: https://www.linkedin.com/in/ida-johnsson/
X: https://twitter.com/IdaBJohnsson


00:00 Preview
00:56 Quentin and causality - introduction
03:12 Causal inference for data scientists
05:29 Where prediction fails
10:58 No substitute for domain expertise
11:59 Can you automate causal inference?
14:38 Practical advice on how to learn causal inference tools
18:40 Causality is everywhere
19:49 Causality for business executives
23:13 Common biases
26:17 You don't need to be an expert to question experts
29:16 Assessing causal estimates
30:27 Cold exposure
35:38 Causal inference for everyone
40:12 Confirmation bias and willingness to question one's beliefs
42:44 Causality in complex systems
43:57 Medical research on male vs. female data
46:26 Effect of weapons on the probability of conflict
48:01 COVID and lockdowns
51:55 Two things can be true at the same time
52:28 Wage discrimination
54:54 How to question conclusions if you're not an expert


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