Skip to main content

Tech and tech idealism

It's been almost 2 years since my last post! I don't know if anyone is still reading this. If you are, thank you!

Why haven't I posted more? Partly it is the broad transition to microblogging, which everyone is using more than long form. But part also is that I have negative feelings about where tech has been going.

I'm a tech idealist. I think tech can and should be a force for good in the world. I have spent most of my life trying to build systems where computers are helping humans. Sometimes this is by computers sifting information that is hard for people to find on their own. Sometimes this is by computers surfacing other people that can help.

Lately, some tech companies have been favoring exploitation and deception. Data is being used to manipulate. Tech is becoming customer hostile.

I've been lucky. I have gotten to work on some amazing things. There is a joy to helping someone discover a new book they will love, a bit of knowledge added to a life. Many people feel overwhelmed by the news and information in their lives, and sorting through to find what is truly important is too hard. Ads shouldn't be so annoying and irrelevant, and, you know what, they don't have to be. I've enjoyed helping people find and discover whatever they need online.

But looking at where we are in tech now, it feels like a dot com bubble again. Get rich quick. It's not building something that people love, but get the buck. Greed feeds short-term thinking. Grab that next bonus and get out before the wreckage hits.

Tech idealism is still out there. There still are many people building things that help people. There is research, the creation of knowledge and new ways to help even more people. There are many people using computers and data for good.

And there are many new people getting into computer science, which is fantastic. Computers are a force multiplier. Computers make people more productive and more powerful. Computer science and data science are just starting to have an impact in other fields.

The interdisciplinary opportunities are everywhere and exciting. We know almost nothing about our own oceans; there are huge opportunities for discoveries in biology from undersea probes and drones. We are just starting to image the entire night sky frequently, and sifting through that data with massive computing power will forever change astronomy. The field of economics is shifting to data and behavior over theory. Archeology can be fueled by processing massive amounts of satellite imagery. In field after field, computers and data are making the once impossible possible.

Tech idealism is coming back. Something may have to come to flush away some of those just seeking quick profits. Some of the worst abuses may have to be obvious failures before they are rained in. But it will change.

Computers and data are a force multiplier, allowing people to do more than they could before. Working at massive scale, computers help us understand and discover. In long-term, tech is a force for good.

from Geeking with Greg http://bit.ly/2H8Fwkk
via IFTTT

Comments

Popular posts from this blog

Controlling legend appearance in ggplot2 with override.aes

[This article was first published on Very statisticious on Very statisticious , 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. In ggplot2 , aesthetics and their scale_*() functions change both the plot appearance and the plot legend appearance simultaneously. The override.aes argument in guide_legend() allows the user to change only the legend appearance without affecting the rest of the plot. This is useful for making the legend more readable or for creating certain types of combined legends. In this post I’ll first introduce override.aes with a basic example and then go through three additional plotting scenarios to how other instances where override.aes comes in handy. Table of Contents R packages Introducing override.aes Adding a guides() layer Using the guide argument in scale_*() Changing multiple aesthetic par...

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 ...