On the Evolution of Thinking

What if we are becoming the very same Artificial Intelligence that we are trying to design? The doubt has has been raised by Nicholas Carr in an article published one year ago on The Atlantic and now published on Le Monde. The theory is intriguing and the discourse goes, in the words of developmental psychologist Maryanne Wolf, more or less in this direction:

We are not only what we read, We are how we read.

So, learning directly from the voice of Socrates is not the same as learning from the Internet. The way we approach new ideas and knowledge influences how we assimilate them and how we develop our thinking. The risk is that our mind might find so attractive the effectivness of the Google’s algorithm to try to replicate it forgetting all the ambiguity that has made us what we are. What we are so far.

Update: Have a look at this article on Le Monde about the influence of the new information technologies on culture.

Friday, 5 June 2009

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RSS r-bloggers.com

  • COVID-19 shiny / plotly dashboard
    Governments and COVID-19: Which one stops it faster, better, has fewer people dying? These questions get answered with my dashboard. A contribution to the shiny-contest: https://community.rstudio.com/t/material-design-corona-covid-19-dashboard-2020-shiny-contest-submission/59690 Intro How did Corona spread? Using the animation feature of R-shiny this can be easily tracked.COVID-19 is the major topic in all news channels. The place I live in […]
  • RcppSimdJson 0.0.4: Even Faster Upstream!
    A new (upstream) simdjson release was announced by Daniel Lemire earlier this week, and my Twitter mentions have been running red-hot ever since as he was kind enough to tag me. Do look at that blog post, there is some impressive work in there. We wr...
  • C is for coalesce
    For the letter C, we'll talk about the coalesce function. If you're familiar with SQL, you may have seen this function before. It combines two or more variables into a single column, and is a way to deal with missing data. When you give it a list of va...
  • Introductory videos for Explanatory Model Analysis with R
    Remote teaching at my university encouraged me to prepare some video materials for Explanatory Model Analysis techniques, i.e. techniques of exploration, explanation and visualisation of predictive models.The pyramid for Explanatory Model Analysis. Lef...
  • Custom Power BI visual for Line chart with two Y-Axis
    Power BI support certain type of visuals that are by default available in the document. These are absolutely great and work perfectly fine, have a lot of capabilities to set properties and change the settings. But every so often in…Read more ›

RSS Simply Statistics

  • Is Artificial Intelligence Revolutionizing Environmental Health?
    NOTE: This post was written by Kevin Elliott, Michigan State University; Nicole Kleinstreuer, National Institutes of Health; Patrick McMullen, ScitoVation; Gary Miller, Columbia University; Bhramar Mukherjee, University of Michigan; Roger D. Peng, Johns Hopkins University; Melissa Perry, The George Washington University; Reza Rasoulpour, Corteva Agriscience, and Elizabeth Boyle, National Academies of Sciences, Engineering, and Medicine. […]
  • You can replicate almost any plot with R
    Although R is great for quickly turning data into plots, it is not widely used for making publication ready figures. But, with enough tinkering you can make almost any plot in R. For examples check out the flowingdata blog or the Fundamentals of Data Visualization book. Here I show five charts from the lay press […]
  • So You Want to Start a Podcast
    Podcasting has gotten quite a bit easier over the past 10 years, due in part to improvements to hardware and software. I wrote about both how I edit and record both of my podcasts about 2 years ago and, while not much has changed since then, I thought it might be helpful if I organized […]

RSS Statistical Modeling, Causal Inference, and Social Science

  • Noise-mining as standard practice in social science
    The following example is interesting, not because it is particularly noteworthy but rather because it represents business as usual in much of social science: researchers trying their best, but hopelessly foiled by their use of crude psychological theories and cruder statistics, along with patterns of publication and publicity that motivate the selection and interpretation of […]
  • Conference on Mister P online tomorrow and Saturday, 3-4 Apr 2020
    We have a conference on multilevel regression and poststratification (MRP) this Friday and Saturday, organized by Lauren Kennedy, Yajuan Si, and me. The conference was originally scheduled to be at Columbia but now it is online. Here is the information. If you want to join the conference, you must register for it ahead of time; […]
  • More coronavirus research: Using Stan to fit differential equation models in epidemiology
    Seth Flaxman and others at Imperial College London are using Stan to model coronavirus progression; see here (and I’ve heard they plan to fix the horrible graphs!) and this Github page. They also pointed us to this article from December 2019, Contemporary statistical inference for infectious disease models using Stan, by Anastasia Chatzilena et al. […]