Note on Wittgenstein, grammar and privacy

Posted on by
Reply

I need to write more. As a forcing function I have chosen a number of conferences and journals to submit pieces to. The first, to my horror, was today. So I have submitted a note on an outline of a grammar of privacy to the 35th International Wittgenstein Symposium. The note below. Comments always welcome. Be gentle. It will get better. I will also publish the deadlines here to commit to them more profoundly. And I will publish the rejection letters too…:)

lundblad_grammarofprivacy

Turing tests III: The notion of NO intelligence

Posted on by
1

One commenter on the previous post raised an interesting point in identifying our financial markets as post-human, and those algorithms and agents as essentially opaque black box systems. And predicting that they would be the origin of artificial intelligence.

First, I think that the origin of AI is an interesting question. If we believe that intelligence will emerge from a set of algorithms it seems important what algorithms they are, since all algorithms are under different selective pressures. We could imagine that algorithms selected for in financial markets are different than those selected for in turing tests, driving cars or playing jeopardy. Intelligence stemming from DRM would be an interesting premise for a sci-fi short story.

Second, I think the black box nature of some algorithms also makes it interesting to think about what we ascribe zero intelligence to. If we can predict exactly what results an interaction with a system will lead to. If we can predict the system completely, we ascribe no intelligence to it. A clock is not intelligent, and we can reproduce and predict its behavior easily. But as soon as we leave the wholly predictable we end up with a system where the question of intelligence can be raised.

This says something about why we as human beings detect intelligence. We do it in order to find ways an methods to predict systems, and intelligence simply provides us with a new set of tools to do that. If we think a system is intelligent we shift to the conceptual structures, of wants, needs, rationality, feelings, logic et cetera, and we have developed a pretty good predictive apparatus for that.

And that may be the evolutionary explanation for why we are so well-equipped to detect intelligence. Because once we do, we are able to better predict the systems, and interact with them to our, sometimes, mutual benefit.

Now, I find this interesting, because you could imagine a weird world in which people failed the Turing test all the time, i.e. failed and identified systems as intelligent that did not meet any more in-depth examination of intelligence. Why should we have the ability to identify intelligent systems, one may ask, and the answer is probably that it has a strong selective advantage in predicting what the system will do.

That which you can predict and explain fully, however, has no intelligence whatsoever. This needs more thought.

Cleverbot and being somewhat human…or a unicorn

Posted on by
1

Cleverbot is an interesting project that just recently crossed my radarscreen. I like the online interface, and it has also brought an interesting instance of the Turing test to my attention. In this case it is rapid fire Turing tests, where the participants rate “how human” something is on a scale from 0-100 percent. Cleverbot, in one of its incarnations, got to 42.1% human.

This highlights a weakness of the Turing test, I think. The notion that something can be somewhat human is clearly wrong, a misuse of the concept humanity. Or is it? Worrying examples from human history indicate that we think this way about enemies, other tribes and other races to an extent that is awful. We dehumanize that which we think we need to destroy, or that which threatens us, for scares us. But would any racist say that another race is just 42.1% percent human? No, probably not. It doesn’t work that way. We would probably agree with them being human or we would define them as something else. Being human might actually be far more binary than we think.

In one way, however, cleverbot is a great example of the limitations of the Turing test. But it has also produced some great humor. Witness this fantastic video on cleverbot talking to another instance of itself, to see how language sounds when it, truly, runs on empty.

My favorite comment. “I am not a robot. I am a unicorn”.

An interesting aside. Their discussion sounds very much like an old married couple arguing in parts. Myabe that is also language running on empty…

But I may be a “meanie”.

 

Understanding prejudice and racism online through search data

Posted on by
2

In a recent paper by Seth I. Stephens-Davidowitz Google Search Data is used to assess how much racist-sentiment affected the 2008 vote. The method is interesting, and the outcome nothing short of sensational:

The results imply that, relative to the areas in the United States with the lowest racial animus, racial animus cost Obama between 3.1 percentage points and 5.0 percentage points of the national popular vote. This implies racial animus gave Obama’s opponent roughly the equivalent of a home-state advantage country-wide. The cost of racial animus was not decisive in the 2008 election. But a four percentage point loss by the winning candidate would have changed the popular vote winner in the majority of post-war presidential elections.

Now, read the paper for yourself and determine if you agree with the methodology or not, but it does look interesting. Ultimately it becomes a correlation/causation issue to some extent, but still – interesting.

The notion that we could track prejudice and racist sentiment like this seems to open for new ways to track the dark sides of society and perhaps bring our creativity to bear on the problem of how to counter the fear and ignorance that underpins the memes involved.

A parliament of a million

Posted on by
Reply

One thing that people skeptical of government often miss is that less of government is not always a good thing. Big government is a bad idea when we refer to the growth of agencies and new government spending, but big government as in big parliaments is not necessarily a bad idea. Now, hear me out. The reason I think we should revisit the notion that parliaments should be small, for example, is that I think the size of a parliament directly affects special interests’ ability to influence the parliament. If you are A Big Company and decide to spend X million on lobbying you will have to divide that over the decision makers. If there are 100 of them you can exercise quite some influence, but what if there were a million of them, distributed in a network of national reach? A decentralized and distributed parliament would actually be harder to lobby than a concentrated one.

So rather than a parliament of 349 or less we could construct vast influence-resilient network parliaments that would be intrinsically much harder to lobby than the ones we have today. Anyone seriously interested in lessening special interests and incumbent influence should revisit the notion that fewer elected parliamentarians are better. There may even be an equation here where money spent on additional parliamentarians and the pulverization of power actually serves as an inoculation against special interests influence. When you increase the size of a parliament by an order of ten you may well reduce special interests capacity to influence that parliament by an order of a 100, say.

And the cost for large parliaments have gone down radically with new technologies, of course, resetting the transaction cost argument soundly.

The rise of the new nostalgia services

Posted on by
3

Memolane and other similar services offer an intriguing business proposition. They will remind you of what you wrote, thought and tweeted in the past, and so from time to time I get an email setting out what I did and said in different social media and I find it interesting. Much as brilliant author Donna Tartt notes in The Little Friend we are the stories we tell about ourselves as a family, and she cites the peculiar practice that many families (including mine) engage in, in telling the same stories about family members over and over again. Those stories become the narrative backbone of the family and create a sense of identity over time.

This is very close to what these memory services do. The little mementos become parts of me, just as if I was leafing through notes in a diary and found tidbits that reminded me of what happened a year ago or more.

But why would we like this? Why would we need to be reminded of what happened 6 months ago or 2 years ago? I think there is something fascinating going on here. Our need of the past, our yearning for it in “an idealized form” as the Wikipedia has it, is greater than ever before – we simply are more nostalgic than before. Nostalgic because of the pace of change and the speed with which everything happens, but also because of the fleeting nature of reality with perpetual crises in the economy, in jobs, in housing prices…

So we get cohesion and build identity from the little fragments that we have left behind in social media, we find stability and continuity in the memories served up through these new nostalgia services. Not only in services like Memolane, but also in I Done This and the peculiar new photo genre exemplified by Everyday, where people take pictures of themselves every day.

The new nostalgia services try to capture and tame time for us, as it seemingly has become more fleeting and passes more quickly than ever.  They make us more real. Or as the advertising text for Everyday says, tongue-in-cheek:

Make a movie. You’d be surprised how great the effect of a time lapse video of your face can be. Watch yourself change, just like a real person.

Look for yourself:

Patent system quality and diversity

Posted on by
Reply

One of my pet peeves has always been that we measure innovation in a country by using patents as a proxy. Now, there is a lot to be said for the patent system, and a well working and built out patent system can be a force for good. But the mere number of patents seems a very bad measure. So it is with great interest that I see new research coming out that seems more geared towards understanding the distribution of patents between individuals and the concentration to a few firms. In the paper “Power Law Distributions of Patents as Indicators of Innovation” the authors examine who actually gets the patents. They write:

In conclusion, we have found that distribution of patents amongst applicants within OECD countries generally follow power laws. This provides a new way of looking at the structure of national economies and strengthens the analogy between innovating firms and ecosystems. Indeed, we fi nd that the power law exponents that describe these distributions diff er between countries and are correlated with measures such as national expenditure on research and development, and the ubiquity, or degree of specialisation, of the basket of goods that a country exports. Countries that export more specialised goods tend to have a smaller proportion of companies that hold a larger share of the patents where countries that export more ubiquitous goods tend to have a larger share of patents held in small portfolios. It seems that the innovator of today is more likely to work in the research laboratory of a large multinational company than in the suburban garage or small start-up company.

But this is where I think they go wrong. What the authors have shown is not that the innovators work in research laboratories and large companies, but that the patent holders do. And they are not the same. The power law that the study finds seems to be an indicator of patent concentration in systems, and hence also of lack of patent holder diversity. Both factors that should be used to gauge the health of a patent system.

And this is where I think we need to go. We need to look not at patents as a proxy for innovation, but dig deeper and examine the patent system quality, diversity and concentration to understand if it is serving the purposes it set out to serve, or if it is just creating an economy of transaction costs on top of the small start-ups that do not necessarily patent what they do to the same extent.