neutralid

The primary reason why there wasn't much automation in the past was the combination of doctors being conservative (which is a good thing) and lack of competition among established medical companies (the ones conservative doctors depend on). You can see how the two couple stifling innovation not through any conspiracy but just preferences.

Both of those aspects are being relaxed today. Doctors are become tech-oriented and more diagnostic companies (run by first-rate medical/engineering teams) are starting up that may upend more established medical companies. We will see a rapid change in the diagnostics landscape in the next decade. This may also add some risk to the diagnostic field, but the benefits far outweigh the risks.

Especially if you're taking multiple types of medicine, know their interactions. There may be a specific sequence of consumption that you should use otherwise side effects get amplified, e.g., NSAIDs.

Micro-/macroeconomics and computer science (queueing theory) could cover most of the key items ... but people would need to understand the connections / generalizations / limitations. Perhaps MBAs make it obvious with case studies and in-class debates.

Once the spinner picks the right number, a code is revealed.

> Controlling and maintaining a complex system of feedback loops (that we still don't completely understand) is a very difficult task though, so I'm not surprised that currently the most crude methods (genocidal chemical warfare) are also the cheapest / most efficient.

Blanket chemical warfare is like feedback linearization. Wasteful in terms of energy and has other flaws associated with stability. There is a better approach, e.g., passivity based control, which requires understanding the underlying nonlinear dynamical system.

Interestingly this has been the same problem in medicine. However, there are more nuanced control-oriented medical techniques being developed (need better observers and actuating mechanisms).

> We don't need science if we are just going to rely on easy, intuitive explanations of everything. Anybody can decide that eating fat makes you fat and fills your arteries with fat; you don't need any particular expertise for that.

Science comes in when you want to know how plaque consisting of macrophages containing fats/cholesterol on arterial walls are embedded, and how macrophage uptake of fats/cholesterol is increased/decreased. There's current work in trying to understand the role of TMAO (primarily from animal foods) in increasing macrophage uptake of fats/cholesterol:

http://journals.lww.com/co-lipidology/Abstract/2016/04000/Tr...

The research in this area is promising enough that insurance may derive TMAO-based measures of heart health:

https://www.thepermanentejournal.org/files/Winter2015/Artery...

I've had some experience with flaky colleagues asking "why" without putting much effort into understanding what was actually said. A more specific question addressing the person's lack of understanding in some area reflects sincerity in wanting to know rather than just wasting other's time with "academic" interests. You'll be surprised by the number of times when why is asked in return, the answer is disingenuously "just curious."

Your two questions could elicit a better response, even though it's basically the same as "why," because it's at least showing a semblance of effort and the interest to probe deeper.

Author may be somewhat right but probably not in the way intended. Discrimination tends to be more effective in areas that lack competition. The article itself states that Asians started to own more businesses due to discriminatory practices. With discriminatory laws were relaxed, Asians on average may have put themselves in a more competitive position (through education/training) than whites and blacks. So, with increased competition, white executives may have had to pay equal otherwise risk losing an asset to their competition. Consequently, with more competition, Americans may appear to be less racist towards Asians.

Discrimination apparently still exists with the disparity in terms of executive positions when comparing equivalent levels of education. There's less competition at the very top where who you know with money likely counts more than technical skill, i.e. paying for CEO's rolodex.

Google search across languages would be amazing, e.g., accessing old scholarly research written in a native tongue. Wonder what the underlying structure of the neural network is for translations between all languages:

http://www.kurzweilai.net/googles-new-multilingual-neural-ma...

Optimizations like this one with Rockefeller sells well, i.e., relatable, to many people because they tend to optimize locally themselves. As you alluded, local optimizations could lead to problems at the global level, e.g., lack of system robustness. Unintended consequences.

Unfortunately, manufacturing has taken this road in developing fragile products. Even the food industry "optimizes" production to maximize taste preferences at the expense of nutrition: http://ajcn.nutrition.org/content/72/6/1424.full

Thanks very much for your suggestions.

I have a utilitarian understanding of mathematics (vector spaces, SVD, orthogonality, invariances, etc.) and over time appreciating the underlying characteristics/relationships, which I recently got a taste of from T. Wickens, The Geometry of Multivariate Statistics.

I look forward to understanding measure theory and related math.

This is very interesting. Thank you.

What book would you recommend for this discussion?