Tag Archives: analysis

Uncertain Futures: a history of Cold War era sf in America

You know how it usually works: you get back from a few days away to find your email inbox full of invoices, frantic requests for assistance and other things clamouring for your immediate input. Makes trying to find things to blog about a bit tricky… unless you find something like this email from Morgan Hubbard of the University of Massachusetts-Amherst nestling among the others:

I’m a grad student at the University of Massachusetts-Amherst. I recently debuted Uncertain Futures, an online exhibit on the cold war history of American science fiction. It’s heavy on visuals and media, and I’d like to think it’s breezy and narrative enough to hold a reader’s attention. Is this something Futurismic might like to mention?

It certainly is, Morgan – and not just because of its conveniently timed arrival! Go take a look, folks; it’s good accessible scholarship married to striking yet usable web design. Not just an insight into science fiction’s past, but maybe an insight into the long-overdue future of the academic paper in a multimedia landscape…

Thanks again, Morgan!

Fractal market movements predict deep economic depression just ahead

It’s a great time to be a prophet of economic doom, because everyone’s still smarting badly enough from the last suckerpunch to take the threat of a groin-kick very seriously. And if you want a really bleak prediction, Robert Prechter’s ananlysis of fractal patterns in the market movements of the 1930s and 40s implies that the groin-kick will be delivered by an elephant wearing concrete boots [via TechnOccult]:

Originating in the writings of Ralph Nelson Elliott, an obscure accountant who found repetitive patterns, or “fractals,” in the stock market of the 1930s and ’40s, the theory suggests that an epic downswing is under way, Mr. Prechter said. But he argued that even skeptical investors should take his advice seriously.

“I’m saying: ‘Winter is coming. Buy a coat,’ ” he said. “Other people are advising people to stay naked. If I’m wrong, you’re not hurt. If they’re wrong, you’re dead. It’s pretty benign advice to opt for safety for a while.”


For a rough parallel, he said, go all the way back to England and the collapse of the South Sea Bubble in 1720, a crash that deterred people “from buying stocks for 100 years,” he said. This time, he said, “If I’m right, it will be such a shock that people will be telling their grandkids many years from now, ‘Don’t touch stocks.’ ”

The Dow, which now stands at 9,686.48, is likely to fall well below 1,000 over perhaps five or six years as a grand market cycle comes to an end, he said. That unraveling, combined with a depression and deflation, will make anyone holding cash “extremely grateful for their prudence.”

Prechter’s analysis isn’t very popular, naturally.

The “mathematics don’t work,” Mr. Acampora said, because such a big decline would imply that individual stocks would need to trade at unrealistically low levels. Furthermore, he said, “I don’t want to agree with him, because if he’s right, we’ve basically got to go to the mountains with a gun and some soup cans, because it’s all over.”

Still, on a “near-term” basis, he said, “We’re probably saying the same thing.”

There’s a deep emotional component to Acampora’s response, there – the same one that keeps most of us from considering the real worst case scenarios. Caesar hears only what is pleasing unto Caesar, perhaps… but note that Acampora has shifted his own personal holdings to cash in the short term, so grim times are likely to be on the cards one way or the other.

But Doug Rushkoff, typically enough, sees an opportunity to build a better system on the ruins of the old:

Yes, this is really it. The beginning of a true end-of-cycle economically.

If you own “stocks,” use these bounces to get out completely. If you have to park your money somewhere, consider yourself lucky you have money to park.

The object of the game for those who actually have capital is not how to grow it, but how to keep it. Capital has driven our economy since 1300, and the recent bull market was the end of a cycle that began in the mid-1700′s.

The fact that it is ending is not the end of the world at all. It just means that there’s a whole lot of money out there with no place to go. People can’t find a place to park their money because there’s more money looking for investment than there is stuff to invest in.

And that’s because we’re finally in a technological era where great innovations are more about reducing the need to spend time, resources, and energy than they are about increasing it. iPads aside, of course.

Given the choice, I’ll take Rushkoff’s vision of the future, please. Will we make that choice for ourselves, and carry it through? I guess that’s down to us.

Read blogs, scan Twitter, predict the future… profit?

So much for the nay-sayers, blog critics and Twitter h8rz: economic researchers reckon that keeping a weather eye on the internet Zeitgeist by scanning blogs and tweets for keywords could help predict stock price changes and other market behaviours!

Which is all very nice, so far as it goes. But given the events of the last few years, I think I’d rather hear stories about economists trying to discover how the global economy actually works as a system by analysing historical data, rather than trying to guess what it’ll do tomorrow by reading the internet’s tea leaves…

… yeah, I know, wishful thinking. Scratch a futurist, reveal an embittered utopian optimist. *shrug*

Computerising the music critics

Keeping with today’s vague (and completely unplanned) theme of critical assessments of cultural product, here’s a piece at New Scientist that looks at attempts to create a kind of expert system for music criticism and taxonomy. Well, OK – they’re actually trying to build recommendation engines, but in The Future that’s all a meatbag music critic/curator will really be, AMIRITE*?

So, there’s the melody analysis approach:

Barrington is building software that can analyse a piece of music and distil information about it that may be useful for software trying to compile a playlist. With this information, the software can assign the music a genre or even give it descriptions which may appear more subjective, such as whether or not a track is “funky”, he says.

Before any software can recommend music in this way, it needs to be capable of understanding what distinguishes one genre of music from another. Early approaches to this problem used tricks employed in speech recognition technology. One of these is the so-called mel-frequency cepstral coefficients (MFCC) approach, which breaks down audio into short chunks, then uses an algorithm known as a fast Fourier transform to represent each chunk as a sum of sine waves of different frequency and amplitude.

And then the rhythm analysis approach (which, not entirely surprisingly, comes from a Brazilian university):

Unlike melody, rhythm is potentially a useful way for computers to find a song’s genre, da F. Costa says, because it is simple to extract and is independent of instruments or vocals. Previous efforts to analyse rhythm tended to focus on the duration of notes, such as quarter or eighth-notes (crotchets or quavers), and would look for groups and patterns that were characteristic of a given style. Da F. Costa reasoned that musical style might be better pinpointed by focusing on the probability of pairs of notes of given durations occurring together. For example, one style of music might favour a quarter note being followed by another quarter note, while another genre would favour a quarter note being succeeded by an eighth note.

But there’s a problem with this taxonomy-by-analysis approach:

Barrington, however, believes that assigning genres to entire tracks suffers from what he calls the Bohemian Rhapsody problem, after the 1975 song by Queen which progresses from mellow piano introduction to blistering guitar solo to cod operetta. “For some songs it just doesn’t make sense to say ‘this is a rock song’ or ‘this is a pop song’,” he says.

(Now, doesn’t that remind you of the endless debates over whether a book is science fiction or not? A piece of music can partake of ‘rockness’ and ‘popness’ at the same time, and in varying degrees; I’ve long argued that ‘science fiction’ is an aesthetic which can partaken of by a book, rather than a condition that a book either has or doesn’t have, but it’s not an argument that has made a great deal of impact.)

This analyses of music are a fascinating intellectual exercise, certainly, but I’m not sure that these methods are ever going to be any more successful at taxonomy and recommendation than user-contributed rating and tagging systems… and they’ll certainly never be as efficient in terms of resources expended. And they’ll never be able to assess that most nebulous and subjective of properties, quality

… or will they?

[ * Having just typed this rather flippantly, I am by no means certain that the future role of the critic/curator will be primarily one of recommendation. Will the open playing field offer more opportunity for in-depth criticism that people actually read and engage with for its own sake, or will it devolve into a Klausner-hive of “if you like (X), you’re gonna love (Y)”? ]