<div dir="ltr"><div class="gmail_default" style="font-family:comic sans ms,sans-serif;font-size:small;color:rgb(0,0,0)">Anders, I am going to give you the greatest challenge of your life. Explain the following to me in plain English (say that I am the head of the insurance company and don't understand the math. (from Bill W)<br><br><div>Simple model: Imagine that a condition X will have a cost C it it
occurs, and has a base probability P0. The actual probability
P=P0(1+aL+bG), where L is lifestyle and G is genetic factors (0 means no
effect) and a,b small constants. The expected cost of X is C P0
(1+aL+bG) if we assume independence of L and G. However, the total
expected cost is the sum across all conditions: E[C] = sum_i C_i P0_i
(1+a_i L_i + b_i G_i). Here we are again assuming independence, which is
problematic: if you die of X, you cannot die of Y, but I have not had
breakfast yet, so I will handwave this. The P0s are skew distributed:
there are loads of rare illnesses, and a few common ones. I would guess
that they roughly follow a power-law: let's set P0_i = i^-alpha, where
alpha>1 is a parameter denoting how common rare illnesses are. I
think, based on the fact that hospitals are not treating just a single
dominant disorder, that alpha is likely somewhere around 2.5</div><div><br></div><div>So,
assume you figure out that you have increased risk of condition i. Then
your expected costs go up by C_i P0_i b_i. If i is randomly distributed
as i^-2, then the expected i is around 3, and P0=3^-2.5. So the change
in expectation is 0.064*C_i b_i. This tells us that if the general
noise level Std[C] is much larger than this, it is likely not worth
checking. Now, the Std[C] for this example depends on the distributions
of all the different factors which I definitely do not have the mettle
to guess, but I would guess it is pretty big since P0 has infinite
variance (ah, those delightful power-laws!) Even if all P0s were equal,
if we assume b's tend to be relatively small, the sum is dominated by
the C_iP_0 terms and the variance becomes due to the variance in
treatment costs - which I think I remember is another heavy-tailed
distribution. So unless C_i or b_i is *unusually* high - like in
Huntingdon - or you have an effect on a high P0_i condition - then the
insurer will not care much.</div><div><br></div><div>And if it can be
offset by a monitorable change in L_i, so much better. In a sense
lifestyle changes are like (usually) low-cost treatments: you can move
that term into the C term.</div><div><br></div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Sun, Nov 9, 2014 at 4:28 AM, Anders Sandberg <span dir="ltr"><<a href="mailto:anders@aleph.se" target="_blank">anders@aleph.se</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div><div><span><span title="pharos@gmail.com">BillK</span><span> <<a href="mailto:pharos@gmail.com" target="_blank">pharos@gmail.com</a>></span></span> , 9/11/2014 10:59 AM:<span class=""><br><blockquote style="margin:0 0 0 .8ex;border-left:2px blue solid;padding-left:1ex"><br><<a href="http://www.bbc.co.uk/news/science-environment-29760212" title="http://www.bbc.co.uk/news/science-environment-29760212" target="_blank">http://www.bbc.co.uk/news/science-environment-29760212</a>>
<br>28 October 2014. Two genes linked with violent crime.
</blockquote></span></div><div><br></div><div>The problem with those gene variants is that they are very common; about 20% of us have the "dangerous" version. They only seem to become risky when combined with a bad upbringing and other factors. </div><div><br></div><div>So if we want to use genetics to reduce violent crime we need to check about a fifth of all children for how they are brought up, and give them nicer upbringings if they are in trouble. In fact, skipping the gene test and just helping kids in trouble seems to be even better, since there are non-genetic social causes of kids to go bad too. </div><span class=""><div><br></div><br><div><blockquote style="margin:0 0 0 .8ex;border-left:2px blue solid;padding-left:1ex">If gene treatments become fashionable and/or compulsory the population
<br>could gradually change into a healthy monoculture nation of tall
<br>handsome people with blue eyes and a very placid disposition.
</blockquote></div><div><br></div></span><div>Would it? I can see strong selective forces for health, intelligence and other general purpose goods, but multifactorial traits are harder to move than single factor traits. Parents generally do not seem to think hair colour merits genetic interventions; in fact, they are surprisingly conservative when it comes to any interventions unless they seem really good. Having a placid disposition doesn't sound like what any parents would go for. And the more blonds there are, the more other hair colors will look cool and exotic - there is a very interesting culture and availability interaction. </div><div><br></div><div>In any case, human genetic changes are unlikely to matter unless we stall on nanotech, AI and other radical technologies: the latter category evolves far faster than the human generation time right now. Plus, of course, we are getting way better at gene therapy too. Genetics may cease to be irreversible. </div><div><br></div><div>I am more worried about psychological hacks that make populations content than genetic hacks. </div><span class=""><br><br>Anders Sandberg, Future of Humanity Institute Philosophy Faculty of Oxford University</span></div><br>_______________________________________________<br>
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