For more than half of my life I have had faith in the potential of social technology to change the world for the better — making all of us happier, ending worldwide conflicts, eliminating poverty and funding medical research. But there is no guarantee that the tools and techniques invented will be used only for good. Now there is a very dangerous technique, Recursive Exhaustion, which can be used for the very large scale collection of social data.
This data can (and will) be collected automatically without people’s knowledge or permission. It will be used to collect information on people who do not use computers. It will be used to collect information on people whose friends and family do not use computers. It will be used to collect information on young children. Even children who have never seen a cellphone.
On the one hand, this could be a very good thing. Having a lot of information about poor people or refugees in distant countries could make it possible to direct governmental and non-governmental aid to the most needy without delay. It could also be used for all the other worthy goals discussed on these websites. On the other hand there will be a complete loss of privacy. Unless kept out of the wrong hands, this information will leave individuals wide open to blackmail and intimidation.
I hope that this is not already being done. It is almost impossible to stop. Perhaps it could be used by law enforcement officers to find the people abusing it. That would mean governments around the world using this technology, justifying their use of it by the need to stop the new wave of crime. I cannot bring myself to trust even the most benevolent democratic government with an overwhelming amount of information about everybody. The prospect of every government in the world using it scares me.
Using recursive exhaustion for the very large scale collection of social data means acquiring vast amounts of information about every person in the world, including children. The idea of governments run by self-obsessed dictators having so much knowledge about people in truly civilized free world countries terrifies me.
I am sorry to say that I have had a hand in this, discovering or more likely rediscovering it. On reflection I must assume other people know of what I call recursive exhaustion. I hope they are not using it, but I must assume they are.
So what can I do? Aside from my usual attempts to come up with new ideas by writing fiction, all I can do is warn people. Consider yourself warned.
The most exciting new piece of social technology is Recursive Exhaustion, as applied to the very large scale collection of social data.
Most interesting is the wide range of applications to which this data can be put. All of the goals listed on the front page can be achieved with it, and all of the mathematical methods listed there can make use of it.
Much more about this subject will be added here as soon as possible.
As I noted recently in a post on my personal site, I have been working on my websites a lot lately, which includes creating several new ones. Notable are MakingSocietyWork, DecisionMakingAndEstimation, ErrorCovariance, BipartiteMatching and ContentManagement. I have added these sites because I am now attempting to put together a network of sites, one for each of the main ideas behind what I am calling the SocialSystemsProject.
Whether anything come of this or not will depend on public reception of my sites. I am not expecting any. There are just too many other websites out there, too many distractions, and people just don’t care.
Well, all I can do is work away at it and hope.
I’ve completely changed the home page for this site. Here is the former one:
This site is nominally devoted to Social Technology, but will include discussions, not only of related topics but of topics dear to the heart of its author.
Most especially, this site exists to promote a specific view of Social Technology. It is one highly influenced by mathematics and information theory. Various pages and posts explain how and why.
A fundamental concept is that of a social network, which is what computer scientists and mathematicians call a graph. Each link, or edge, in such a graph may be given a weight, which is important for manipulating the graph. Here we discuss graphs (networks) in which the weight or strength of a link is a representation of how well the individuals in the social network communicate. This is discussed in terms of signal strength and distortion, important concepts in information theory.
Signal strength is further broken down into the compatibility of the individuals involved and the amount of communication between them. Compatibility also affects distortion, so it would be more correct to express signal strength and distortion in terms of compatibility and contact.
An analysis of social networks in this way reveals that how badly information flow through them is affected by how many compatible friends one has, and at what levels. A scale is presented for judging the compatibility, and its use is explained. From this analysis one basic conclusion is drawn: that having few very compatible friends and being in close contact with them is much much better than having many less important “friends” in your life.
Click on the images to visit related sites:
A website about languages including programs, data and fiction is at:
Natural, Artificial and Non-Arbitrary LanguagesA complete online novel about the application of social technology in a high-school is:
Social Tech High
Why am I getting so many registrations from Russia?
I hope that means what I think it means. I did try to learn some Russian once, but I didn’t learn very much and it hasn’t stayed with me. I never did learn Cyrillic. So I am trusting that Google Translate knows what it is talking about. Anyway, that is the question — why am I getting so many registrations from Russia. I’d like to think that someone over there understands that I am saying something which matters. Let’s hope so. My thanks to all of you who have registered, from wherever. — dpw
I will remain interested in having others do illustrations and animations for me, in return for ad revenue, but I am working on some myself, to show what I have in mind.
Most interesting to me are animations. On an old page, http://www.SocialTechnology.ca/oldpages/diagrams.html I posted “before” and “after” diagrams of social networks:
image of social network before transformation
image of social network after transformation
What I want to do is create an animation, probably an animated GIF file, to show how the “before” network is changed by some social tech tools to the “after” network.
To do this, I need to create a number of images showing successive stages in the transformation. This can be done using the Python Imaging Library to create the individual image files, then Image Magick to turn them into an animation.
So, that is one thing I am working on. I am also working on Chapter Fourteen of the online book about social tech missions to Africa, at http://socialtechmissionaryorganization.socialtechnology.ca/ — that chapter is turning out to be a lot of work, but should be interesting when finished, probably tomorrow.
I haven’t figured out or found on the net exactly what algorithms StumbleUpon uses, but I have found over the years that the correct measure for the similarity of two lists of things, e.g. websites two people liked, is the number of matches divided by the number of possible matches, which is the length of the shorter list:
Similarity = MatchCount / Length(ShortestList)
Also, looking for similar people, people with the same interests, or same kinds of page approval as you is all very well, useful for some purposes, but don’t expect to actually like or communicate well with such people. People with too much in common often disagree and often have communications problems.
What you really want to know are people similar to those who like and communicate well with people like you.
You may notice appearance changes, if I keep them in place. I have been experimenting with different themes and with different bookmarking options. I have trouble getting the latter to work. Will let you know.