@rastinza

Definitely the words “science” and “scientific” are not helping in this debate.

I suspect each of us thought the meaning of those words was clear, and that everybody else would agree with those definitions. Unfortunately, it's clear that they mean different things to different people and that we draw the boundaries in different places.

Let's try to move forward without relying on that specific word.

I stand by [my initial claim](https://qoto.org/@tripu/108376014503251403) slightly edited as so:

/cc @sojournTime @ImperfectIdea

@tripu @rastinza @ImperfectIdea

Alright, let's start with a simple example where scientific reasoning fails (I'll assume that mathematical reasoning falls under this discipline). Suppose I proposed a choice: I give you $100 dollars guaranteed, or I flip a fair coin and if it lands on heads, I give you $200. Decision theory tells me that the expected value for both choices are $100 (1*$100=$100 vs. 0.5*$200=$100). So, there's no reason for me to choose either choice: they are both equally valued.

Now, suppose I changed the values to $1,000,000 and $2,000,000 respectively. Decision theory still tells me that both decisions are equally valued, but I would assume most people would choose the $1,000,000. Nothing in decision theory would have told me to make that choice. Yet it's pretty obvious why: $1,000,000 is life changing and risking a coin flip to get $2,000,000 is not worth the additional $1,000,000. Sure, maybe behavioral economics might be able to provide a better explanation, but it is definitely difficult to give a quantitative answer.

Now, let's change the prompt a little bit. Suppose instead there is a sinking ship, and a life boat has a maximum capacity of 100. If 200 people board the life boat, there is a 50% chance it will sink before it gets to safety. What decision should be made for the people on the ship? Again, decision theory states that both decisions are equivalent, but philosophically, they are not equivalent. I would argue no additional measurements or quantities would help make a more informed decision. This clearly falls into the realm of moral philosophy, not science.

@sojournTime

Very interesting questions. Indeed those interest me especially (because I'm a rationalist, an utilitarian, and an effective altruist).

First of all, and most importantly: even if I were paralysed by those quandaries and were unable to offer a single helpful comment, that would _not_ prove that #SPAOSKPE (“science plus applications of scientific knowledge plus engineering”) don't suffice to solve them — it's much more likely that I personally lack the knowledge, training, intelligence or time to make any progress.

Still, some ideas about how a purely “scientific” mind could proceed:

The concept of risk can be studied and modelled mathematically. Mathematicians working for insurance companies and quants working in Wall St do that routinely.

Even if the expected value is constant in your scenarios, the risk is clearly not. It makes total sense that one always chooses the path that minimises risk, ceteris paribus. I think that criterion alone would “solve” these scenarios.

Now, I agree with you that “it is definitely difficult to give a quantitative answer”. Your scenarios are easy because the expected value is constant. It becomes more tricky if you say that 300 people boarding the life boat risks a 50% chance of everyone dying. Then the expected value changes, and we can't look at risk alone to break the tie.

I don't know how this gets modelled formally. But I do know that there are ways, and I very much doubt that risk departments in banks, nuclear safety agencies, public transport regulators and those tasked with allocating limited resources for public health rely mostly on their gut, scripture or prescient dreams.

/cc @rastinza @ImperfectIdea

@tripu @rastinza @ImperfectIdea

I don't know about banks, nuclear safety agencies, or public transport regulators, but I do know that public health most definitely uses moral philosophy and ethics to resolve resource allocation. This was very acutely applied during the pandemic:

https://qz.com/1821843/ethicists-agree-on-who-should-get-treated-first-for-coronavirus/

@sojournTime our only point (if I'm not mistaken about @tripu's argument) is that the best way to understand why moral philosophers and ethicists "agree on who should get treated first", and the best way to find out if that's actually the best answer or if there are better options, is by expanding our knowledge of the universe and of our brain through science and technology. I argue that moral philosophy is simply an infant science of human well-being.
@rastinza

@ImperfectIdea @tripu @rastinza

"An infant science of human well being" 😆

Tell me you don't understand moral philosophy without telling me you don't understand moral philosophy...

@sojournTime tell me you don't understand my argument with a laughing emoji. Let's leave it here, thanks.
@tripu @rastinza

@sojournTime

I don't deny the valuable input provided by ethics as perhaps the only exception to my initial claim. And even so, as I said before, good modern moral philosophy tries very hard to be rational, evidence-based, objective, parsimonious, coherent and accurate (there's a lot of math there, in the form of estimates, stats, probability, logic, etc). Those traits may not suffice to qualify as “science”, but it surely gets much closer to “scientific” than “all the other stuff” (pre-modern philosophy, religion, hunches, tradition, etc).

In this article, there are nine mentions of “survival/dying odds/chance”, and a few references to “potential years of life” and to the age of the patients. All those are nothing but numbers: either well-known figures, estimates, probabilities, or approximations taken from actuarial tables.

Also, I want to highlight that the article mentions three different moral theories (utilitarianism, contractarianism, and deontology) and three people to represent or defend each… and the conclusion is that for all of them, it makes sense to give priority to those who are more likely to benefit from treatment over those with worse odds.

It's almost as if ethicists mostly agreed and had very little to contribute, once that consensus is reached.

Where is room for progress? In the numbers. Get more accurate analysis and thus better diagnoses, more precise survival chances, better estimations of the effects of different treatments… and the priority queue gets closer and closer to perfect.

/cc @rastinza @ImperfectIdea

@sojournTime
"no additional measurements or quantities would help make a more informed decision"
What do you mean? Knowing how many people are able to swim to safety or float long enough to be rescued would definitely help, for example...
@tripu @rastinza

@ImperfectIdea

Ah, yes. That too. I forgot to object to that sentence.

Expanding on what @ImperfectIdea said: as long as one can

* refine the model,
* consider more variables,
* measure more parameters,
* measure the same parameters but more accurately,
* run more simulations,
* find more instances of the same phenomenon in the past,
* or even survey more experts in the field,

definitely additional measurements would help.

/cc @sojournTime @rastinza

@rastinza @tripu @ImperfectIdea

I'd clarify a little more: science uses inductive reasoning while mathematics uses deductive reasoning. I wouldn't entirely classify mathematics as philosophy due to mathematics' rigor, but yes, I would not clarify mathematics as a science.