Risk savvy
"Risk-taking is essential for innovation, fun, and the courage to face the uncertainties in life. Yet for many important decisions, we are often presented with statistics and probabilities that we don't really understand and we inevitably rely on experts in the relevant fields—policy makers, financial advisors, doctors—to analyse and choose for us. But what if they don't quite understand the way the information is presented either? How do we make sure we're asking doctors the right questions about proposed treatment? Is there a rule of thumb that could help choose the right partner? This entertaining book shows us how to recognize when we don't have all the information and know what to do about it. Gerd Gigerenzer looks at examples from every aspect of life to identify the reasons for our collective misunderstanding of the risks we face. He shows how we can all use simple rules to avoid being manipulated into unrealistic fears or hopes, to make better-informed decisions, and to learn to understand risk and uncertainty in our own lives."--Publisher's description.
Stats for nerds
7recommend
12mentions
7people
2015–2023years
92% recommend8% neutral
Mentions per year
What Hacker News says
- These are the over-diagnosis bias and the lead-time bias for anyone interested in learning more.
The book Risk Savvy by Gerd Gigerenzer has a chapter that does a good job of covering these. The entire book is worth a read.
- This random person's thesis describes 1/N in a way I think is understandable:
> In circa 400 A.D. Jewish Rabbi Issac Bar Aha recommended always to invest a third into land, a third into merchandise and to keep a third at hand. This method later became well-known under the name “1/n asset allocation strategy”, “equal asset allocation strategy” or “naïve strategy” and is further defined by DeMiguel et al.(2009) as ”the one in which a segment 1/n of wealth is allocated to each of N assets available for investment at each rebalancing data.” The strategy requires investing an equal part of the capital in the different present assets. Nowadays this rule is often labelled as naïve and too simple, by McClatchy and VandenHul (2005) for example.
http://arno.uvt.nl/show.cgi?fid=129399
Gerd Gigerenzer has a number of books, the one I recently read was, "Risk Savvy" and he goes into some detail about the topic. All I'd do here is write a terrible book review, so if you're curious, I definitely recommend taking a look at the book. I'm not sure I totally agree with his arguments (I had a hard time understanding how he would suggest accounting for human bias), but they're definitely interesting.
- This is a great point. There is a good book which i think features a statistical perspective on screening in relation to dying with prostate cancer vs dying from prostate cancer. This book is a great read and i would advise anyone who is interested in health issues to get an intuition of "risk".
https://www.amazon.co.uk/Risk-Savvy-Make-Good-Decisions/dp/0...
- Here's an easy to read introduction to over-testing and over-diagnosis. This isn't talking about false postives. It's talking about harm caused by actual positives. https://ebm.bmj.com/content/23/1/1
Gerd Gigerenzer has done a lot of work on this, so his books are useful. Reckoning With Risk or Risk Savvy are good.
> What I would prefer to see is that screening comes with patient education so they understand the potential risks and inaccuracies and then let 'er rip. If something goes south, it's on them.
Informed choice should already be built into all healthcare systems because it's a feature of international human rights laws and patients are usually allowed to decline to have a test done. And there's usually a doctor somewhere who'll perform an unnecessary test if you're prepared to pay.
Communicating risk is difficult.
We know that merely giving people information and letting them take full responsibility won't work. We know it won't work because we already study whether people understand the risks of testing and treatment, and we find a disturbingly large number of people don't, and that includes the HCPs recommending the testing and treatments.
Most people struggle with this question: "A machine has been invented to scan a population for a disease. The machine is good but not perfect. If you have the disease there is a 90% chance it will return positive. If you do not have the disease there is a 1% chance it will return positive. About 1% of the population have the disease. Mr Smith is tested, and the test comes back positive. What's the chance Mr Smith actually has the disease?"
But the problem of lack of numeracy is more severe: only 20% - 25% of people understand that 0.1% is 1 in 1,000. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3310025/
People do not understand the difference between "absolute" vs "relative" risk increases, so we see newspapers reporting "100% increase in risk from eating X" when the numbers are an increase from 1:100,000 to 2:100,000 deaths.
https://bestpractice.bmj.com/info/toolkit/practise-ebm/under...
https://www.eufic.org/en/understanding-science/article/absol...
- A test exists. It's good but not perfect. If you have the disease it will return positive 99% of the time. If you do not have the disease it will return positive about 1% of the time. About 0.1% of the population has the disease. You take the test. It returns positive.
What are the chances you have the disease?
People on HN may be able to work this out, but I guarantee that many people (including doctors and nurses) can't.
See Gerd Gigerenzer's work on this in Reckoning With Risk or Risk Savvy.
- I haven't read that. I've read Reckoning with Risk and Risk Savvy.
Risk Savvy is later and better because he's had time to refine the ideas.
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