Multiculturalism’s role in radicalization

The children of immigrants have, historically, had two choices:

  1. Assimilate into the culture, retaining vestiges of their original culture (typically foods, celebrations, and perhaps a bias towards marrying cultural cognates);
  2. Remain part of an enclave of their original culture.

Option 1 is by far the most common. Option 2 only works when the original culture is itself highly organized, and it carries high risks for the immigrants. This option has often been followed by the Jewish diaspora (with obvious downsides, including periodic expulsions from European countries, and worse), but there are other examples. Note the wisdom of the formal Amish mechanism of rumspringa, which provides a choice point for young people to commit to the culture, or not.

In historical immigrations, these choices are clearly differentiated and there is little midde ground.

The invention of the idea of multiculturalism created the opportunity to move to a new country, assimilate (apparently), and preserve the culture of origin (apparently). This sounds like a great idea (“best of both worlds”) apart from one simple fact: it doesn’t work.

The set of those who have been radicalized in Western countries and either carried out attacks there, or made their ways to the Middle East is almost entirely made up of the children of immigrants. Many of these individuals have been studied and interviewed, and there is one clear pattern: feeling like they didn’t belong in either their original culture (their parents often being glad to have escaped it at some level and so having moved away from it), nor in the “new” culture in which they have grown up. Not feeling like they fit into the culture in which they grow up is, of course, a common teenage pattern — but most teenagers don’t have such a ready-made explanation for why they feel as they do. Multiculturalism, because it creates the apparent space to avoid commitment to one culture or the other, must bear some of the responsibility for radicalization. (This may also be part of the explanation for why engineers are so over-represented in the ranks of the radicalized — a tolerance for ambiguity may help those growing up between two cultures to navigate the difficult years of adolescence and young adulthood. Most engineers I know are more comfortable with black and white settings than with ambiguity.)

Of course, this can only be part of the explanation. One of the pitfalls for those who seek an explanation for radicalization is that, for every individual who becomes radicalized, there are 99 others who experienced apparently identical life trajectories (sometimes even siblings) without becoming radicalized, often without seeming to feel even the faintest pull towards radical ideologies.Personality must, therefore, play a huge part, and this is often underappreciated.

Religious does not equal stupid

A range of people, from David Brooks to Peter Bergen, have responded to the rhetoric associated with the Countering Violent Extremism Summit held in Washington this week. They point out that the motivation for Daish (aka ISIL [nobody knows why the U.S. White House, alone in the world, insists on this acronym] or ISIS) cannot be understood in terms of the American middle class and its aspirations: jobs, relationships, family, economic prosperity. Islam did not come boiling out of the deserts of Arabia in the 7th century because of the lack of economic opportunity in the sphere of camel raising.

But behind these misunderstanding lies a deeper one. Many of the elites in government and industry in Western countries think that people who have religious beliefs are either: stupid for believing something so self-evidently wrong; or devious and cunning in pretending to have religious beliefs as a tool for exerting power (in the best traditions of post-modernism). Now of course they don’t necessarily think this explicitly, but the language being used in much of the discussion of radicalization and its causes makes it fairly obvious that they do think this implicitly. In other words, one or other of these two views informs the way they frame the problem of islamist radicalism to themselves.

Why do sane young men (and women) give up a lifestyle in the West that, while often not perfect, is much better than third-world conditions and the prospect of death in Syria? Holding either of these misconceptions distorts the view of the problem, and of the West’s opponents, to the point of delusion. If you think your opponents must somehow be intellectually stunted to believe what they do, you are never going to understand why other people find these beliefs attractive, and so will never be able to craft a strategy to defend against islamist propaganda that has any chance of working. If you think your opponents are hypocritical and opportunistic (not believing their own message) then you will equally never be able to craft a working defence. The temptation is to think (again implicitly) that radicalization must somehow be a kind of mental illness; perhaps we’ll begin to see “solutions” with that flavour rather than the current socio-economic flavour, coming into vogue soon.

I don’t have a solution. But the evidence so far (and I’ve done some empirical work in this area) is that socio-economic explanations for radicalization do not go very far; and that de-radicalization programs (or early-stage counter-radicalization strategies) that start with this assumption are even less useful. A more nuanced, and more realistic, view of our opponents and their motivations is desperately needed.

[Added later: The weekend news programs, which were filled with post mortems on the Countering Violent Extremism meeting, were great examples of the misconceptions I suggested in this post. Farid Zakaria actually made the claim that ISIS were faking their apparent beliefs to gain power. For a IMHO more realistic view, this article from the Atlantic: What ISIS Really Wants.]

Empirical Assessment of Al Qaeda, Isis, and Taliban Propaganda

I’ve just been working on assessing the potential impact of the three major magazines: Inspire (AQAP), Azan (Taliban), and Dabiq (ISIS), competing for the market in lone wolf jihadists in the West.

I compare these magazines using models for the intensity of informative, imaginative, deceptive, jihadist, and gamification language, and build an empirical model for propaganda which combines these into a single scale.

Unsurprisingly, Dabiq ranks highest in propaganda intensity.

The details can be found in the full draft paper, posted to SSRN:

Skillicorn, David, Empirical Assessment of Al Qaeda, Isis, and Taliban Propaganda (January 7, 2015). Available at SSRN: http://ssrn.com/abstract=2546478.

More subtle lessons from the Sony hack

There are some obvious lessons to learn from the Sony hack: perimeter defence isn’t much use when the perimeter has thousands of gates in it (it looks as if the starting point was a straightforward spearphishing attack); and if you don’t compartmentalise your system inside the perimeter, then anyone who gets past it has access to everything.

But the less obvious lesson has to do with the difference between our human perception of the difficulties of de-anonymization and aggregation, and the actual power of analytics to handle both. For example, presumably Sony kept data on their employees health in properly-protected HIPAA-compliant storage — but there were occasional emails that mentioned individuals and their health status. The people sending these emails presumably didn’t feel as if any particular one was a breach of privacy — the private content in each one was small. But they failed to realise that all of these emails get aggregated, at least in backups. So now all of those little bits of information are in one place, and the risks of building significant models from them has increased substantially.

Anyone with analytic experience and access to a large number of emails can find structures that are decidedly non-obvious; but this is far from intuitive to the public at large, and hence to Sony executives.

We need to learn to value data better, and to understand in a deep way that the value of data increases superlinearly with the amount that is collected into a single coherent unit.

Making recommendations different enough

One of the major uses of data analytics in practice is to make recommendations, either explicitly or implicitly. This is one area where the interests of marketers and the interests of consumers largely run together. If I want to buy something (a product or access to an experience such as listening to a song or seeing a movie) I’d just as soon buy something I actually want — so a¬† seller who can suggest something that fits has a better chance of getting my business than one that presents a set of generic choices. Thus businesses build models of me to try and predict what I am likely to buy.

Some of these businesses are middlemen, and what they are trying to predict is what kind of ads to show me on behalf of other businesses. Although this is a major source of revenue for web-based businesses, I suspect it to be an edge-case phenomenon — that is, the only people who actually see ads on the web are people who are new to the web (and there are still lots of them every day) while those who’ve been around for a while develop blindness to everything other than content they actually want. You see businesses continually developing new ways to make their ads more obtrusive but, having trained us to ignore them, this often seems to backfire.

Other businesses use permission marketing, which they can do because they already have a relationship. This gives them an inside track — they know things about their customers that are hard to get from more open sources, such as what they have actually spent money on. When they can analyse the data available to them effectively, they are able to create the win-win situation where what they want to sell me is also what I want to buy.

But there’s a huge hole in the technology that represents an opportunity at least as large as that on which Google was founded: how new and different should the suggestion be?

For example, if you buy a book from Amazon by a popular author, your recommendation list is populated by all of the other books by that same author, the TV programs based on that author’s books, the DVDs of the TV shows, and on and on. This is largely a waste of the precious resource of quality attention. Most humans are capable of figuring out that, if they like one book by an author, they may well like others. (In fact, sites like Amazon are surprisingly bad at figuring out that, when an author writes multiple series featuring different characters and settings, an individual might like one series but not necessarily the others.)

So what would be better? The goal, surely, is to suggest products that are similar to the ones the individual has already liked or purchased, but also sufficiently different that that individual would not necessarily have noticed them. In other words, current systems present products in a sphere around the existing product, but what they should do is present products in an annulus around the existing product. Different, but not too different.

This is surprisingly difficult to do. Deciding what similarity means is already a difficult problem; deciding what “just enough dissimilarity” means has been, so far, a too difficult problem. But what an opportunity!

Election winning language patterns

One of the Freakonomics books makes the point that, in football aka soccer, a reasonable strategy when facing a free kick is to stay in the middle of the goal rather than diving to one side or the other — but goaltenders hardly ever follow this strategy because they look like such fools if it doesn’t pay off. Better to dive, and look as if you tried, even if it turns out that you dived the wrong way.

We’ve been doing some work on what kind of language to use to win elections in the U.S. and there are some similarities between the strategy that works, and the goal tending strategy.

We looked at the language patterns of all of the candidates in U.S. presidential elections over the past 20 years, and a very clear language pattern for success emerged. Over all campaigns, the candidate who best deployed this language won, and the margin of victory relates quite strongly to how well the language was used (for example, Bush and Gore used this pattern at virtually identical levels in 2000).

What is this secret language pattern that guarantees success? It isn’t very surprising: high levels of positive words, non-existent levels of negative words, abstract words in preference to concrete ones, and complete absence of reference to the opposing candidate(s).

What was surprising is how this particular pattern of success was learned and used. Although the pattern itself isn’t especially surprising, no candidate used it from the start; they all began with much more conventional patterns: negativity, content-filled policy statements, and comparisons between themselves and the other candidates. With success came a change in language, but the second part of the surprise is that the change happened, in every case, over a period of little more than a month. For some presidents, it happened around the time of their inaugurations; for others around the time of their second campaign, but it was never a gradual learning curve. This suggests that what happens is not a conscious or unconscious improved understanding of what language works, but rather a change of their view of themselves that allows them to become more statesmanlike (good interpretation) or entitled (bad interpretation). The reason that presidents are almost always re-elected is that they use this language pattern well in their second campaigns. (It’s not a matter of changing speechwriting teams or changes in the world and so in the topics being talked about — it’s almost independent of content.)

So there’s plenty of evidence that using language like this leads to electoral success but, just as for goaltenders, no candidate can bring himself or herself to use it, because they’d feel so silly if it didn’t work and they lost.



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