Skip to main content

Optimal amount of input

If you don’t get any outside input into your life, you’re literally an idiot, someone in your own little world. But if you get too much outside input, you become a bland cliche. I’ve written about this a couple times, and ran across a new post this morning from someone expressing a similar idea.

I first wrote about this in a short post on noise removal. After talking about signal processing, I wax philosophical.

This is a metaphor for life. If you only value your own opinion, you’re an idiot in the oldest sense of the word, someone in his or her own world. Your work may have a strong signal, but it also has a lot of noise. Getting even one outside opinion greatly cuts down on the noise. But it also cuts down on the signal to some extent. If you get too many opinions, the noise may be gone and the signal with it. Trying to please too many people leads to work that is offensively bland.

I returned to this theme in The Opposite of an Idiot:

An idiot lives only in his own world; the opposite of an idiot has no world of his own.

This morning I found a new post along these lines via Tyler Cowen. He links to a short post entitled We Can Read Without Learning at All.

We require the friction of other minds to buff away self-generated roughness. Few of us can polish ourselves. We are likelier to grow cranky and conspiracy-minded, mistaking brainstorms for insight while rediscovering what the rest of the world already knows. Had I read only the books assigned in class, I would today be only nominally literate. Had I read only the books that confirmed the thoughts I already possessed, I would remain marginally illiterate.

In our networked world, we’re more likely to have a plethora of low-quality input than to be isolated. There’s more danger of becoming a bland opinion poll than becoming a cranky idiot.

Living inside a partisan bubble may be the worst of both worlds: the blandness of herd mentality and the crankiness of isolation.



from John D. Cook https://ift.tt/2ojezBt
via IFTTT

Comments

Popular posts from this blog

Using RStudio and LaTeX

(This article was first published on r – Experimental Behaviour , and kindly contributed to R-bloggers) This post will explain how to integrate RStudio and LaTeX, especially the inclusion of well-formatted tables and nice-looking graphs and figures produced in RStudio and imported to LaTeX. To follow along you will need RStudio, MS Excel and LaTeX. Using tikzdevice to insert R Graphs into LaTeX I am a very visual thinker. If I want to understand a concept I usually and subconsciously try to visualise it. Therefore, more my PhD I tried to transport a lot of empirical insights by means of  visualization . These range from histograms, or violin plots to show distributions, over bargraphs including error bars to compare means, to interaction- or conditional effects of regression models. For quite a while it was very tedious to include such graphs in LaTeX documents. I tried several ways, like saving them as pdf and then including them in LaTeX as pdf, or any other file ...

Explaining models with Triplot, part 1

[This article was first published on R in ResponsibleML on Medium , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Explaining models with triplot, part 1 tl;dr Explaining black box models built on correlated features may prove difficult and provide misleading results. R package triplot , part of the DrWhy.AI project, is aiming at facilitating the process of explaining the importance of the whole group of variables, thus solving the problem of correlated features. Calculating the importance of explanatory variables is one of the main tasks of explainable artificial intelligence (XAI). There are a lot of tools at our disposal that helps us with that, like Feature Importance or Shapley values, to name a few. All these methods calculate individual feature importance for each variable separately. The problem arises when features used ...