Logic Functions Bonus Round for Synth Nerds

I learned about the XOR function, and pretty much everything I know about logic functions, from modular synthesis. Modular synthesis, like AI or any other media technology, works on a set of conventions ensconced in a set of standards. A modular synthesizer is basically an analog computer (this is a whole other post, which I will at some point write up) that separates sound from control (yes you can mix them up but let’s not worry about that for now), and works according to a set of standard voltages. So in my synthesizer, if I’m controlling pitch, a pitch will rise one octave with one volt. This is purely an agreed upon convention. A media standard. If you’re controlling a gate, let’s say to hear a pitched sound or not, it generally looks for the difference between 0 and some other number–maybe 1, 3 or 5 volts. So if the threshold is 3 volts, every time it receives 5 volts, it will make a sound. Every time it receives 2 volts, nothing happens. Yet of course the numbers 5 and 2 are different, as are those voltages.

Now, one can imagine controlling our synth sound with an XOR logic gate. Send continuously varying voltages, let’s say a pair of varying sine waves of different phase — one into input A and one into input B — and our logic module compares them. If it’s set to an XOR comparison, every time they are different, no matter what the amount or difference is, the gate outputs a 1 and you get sound. Every time they are the same, the gate outputs a zero and you get no sound. With this kind of XOR setup, most of the time you’ll have sound, with an occasional silence. Switch it to XAND, which outputs a 1 only when the voltages are the same, and you have the opposite scenario, only sound once in awhile. But again, the voltages could be any number, and could be varying quite wildly in different ways.

So in essence, the whole point of a binary logic gate is to reduce the blooming buzzing confusion of reality to two states: same or different. This is not a problem in modular synthesis: reduction and quantization are useful for all sorts of things. For instance, turning a set of continuously rising and dropping tones into a melody that makes musical sense–like a double bassist knowing where to put their finger on the fingerboard to play a note in tune. Quantization in audio is also incredibly useful and important, and the sampling theorem means that we can reconstruct continuous waves from discrete data points, as well as store big sounds in small places.

But when those binary operations are judgments about people, processes, or things that matter to people, the issue becomes something else entirely.

Sound or no sound is very different from qualified or not qualified, threat or no threat, human or gorilla. This is why a critique of quantification–or quantization as such is never enough.

A Few Random Thoughts on the Politics of the Logic Functions

Burç Kostem pointed me me to this wonderful piece by Matteo Pasquinelli on the history of neural networks. In the middle, there’s a small historical detail that I never quite grasped before:

In 1969 Marvin Minsky and Seymour Papert’s book, titled Perceptrons, attacked Rosenblatt’s neural network model by wrongly claiming that a Perceptron (although a simple single-layer one) could not learn the XOR function and solve classifications in higher dimensions. This recalcitrant book had a devastating impact, also because of Rosenblatt’s premature death in 1971, and blocked funds to neural network research for decades. What is termed as the first ‘winter of Artificial Intelligence’ would be better described as the ‘winter of neural networks,’ which lasted until 1986 when the two volumes Parallel Distributed Processing clarified that (multilayer) Perceptrons can actually learn complex logic functions.

In terms of the emerging historiography of machine learning, this is a place where the whig historians (aka, internalist histories by computer scientists) and the critical historians seem to agree.

But XOR as a test of neural networks, or intelligence, is a very interesting reduction of pattern recognition to a binary option. It is basically a binary calculation that compares two inputs. It answers “yes” if the two inputs are the different, and “no” if the two inputs are the same. Here’s a picture from Wikipedia to illustrate:

XOR Truth Table from Wikipedia

The whole political argument around pattern recognition in AI is basically reducible to what counts as a 1 and what counts as a 0 in that B column: this is why Google had to block its image recognition algorithms from identifying gorillas. Solving for XOR (are they different) or XAND (are they the same?) is never quite enough in real cultural contexts.

Here’s why. Let’s consider this against a famous statement of morphological resemblance from the history of social thought:

Is it surprising that prisons resemble factories, schools, barracks, hospitals, which all resemble prisons?

(Michel Foucault, Disipline and Punish)

This is an argument about general morphology. It is not that prisons and schools are exactly the same but that they share some meaningful aspects. Can an AI be trained to understand whether or not a given social arrangement fits a “panoptic diagram”? Only if you can parameterize every element of the description of a social milieu.

So we now have a media environment where neural nets can and do solve for binary logic functions all the time. The question is what trips that switch from 0 to 1 in either column. It is, in other words, built around a politics of classification.

For all the talk about process fairness and ethics in AI, we know from the history, anthropology, and STS study of classification that classifications are always tied to power.

Dynamic range compression isn’t “the problem” with music

Writers like Milner and a music business that still focuses on Top 40 charts are.

In a recent New York Times piece, Greg Milner argues that the “loudness wars” and “listener fatigue” are the reasons that music isn’t as good as it used to be. Here are some reasons why he’s wrong:

  1. Milner’s greatest offence is devaluating the work of thousands or hundreds of thousands of musicians making incredible new music, with less financial support and backing than ever. We are living through a “golden age” in more genres than I can possibly name or count. Go out and find the good music. There is nothing stopping you.
  2. Any analysis of any cultural phenomenon that explains it with a single causal factor is always wrong.
  3. If you were to actually look at the pop music charts from any of the years of the golden oldie hits references by Milner, you would find most of the music didn’t have the staying power or meaning he ascribes to the songs he uses as reference points.
  4. Any study of popular music today that uses top 40 charts and ignores the vast swaths of creativity one can find elsewhere–bandcamp, soundcloud, YouTube–has no right to say anything about the state or quality of music.
  5. An analogous argument about harmonic distortion and excessive studio production could have been made by fans of 1940s big band music, Mambo or Sinatra decrying the rock and pop that Milner celebrates.
  6. “I don’t understand hip hop” is not a convincing argument. Neither is “get off my lawn.”
  7. The listener fatigue argument is pseudo-scientific at best. Commercial success does not mean aesthetic merit; there are exactly zero reproducible psychology studies that connect musical pleasure in all people with specific sonic effects. Musical sound is only meaningful in context. The perceptual situation of someone listening on earbuds on the train is wholly different from that of someone paying attention in their living room with better speakers or headphones. That today’s most capitalized recommendation engines–Spotify, Google, etc–mostly rely on factors other than musical sound for their recommendations should tell you that little inherent meaning can be gleaned from tone or timbre alone.
  8. “There are millions of people in the basements, waiting to blow your mind.” — Vernon Reid.

Rupert Cox

Another new feature. When I meet cool or interesting people, or hear a talk that I find particularly engaging in one way or another, I will make mention of them here with a link to their work. I may or may not be loquacious.

So, first up is Rupert Cox, social anthropologist, who’s been doing interesting work on listening, sound, aircraft and the memory of war in Japan. He’s working on a book for Bloomsbury, but in the meantime, here’s a link to a short snippet of his work (you will need university library access for this one, sorry).

One of the things we talked about was the experience of sound outside the sound sounding in a physical way — remembered or imagined sounds, for instance. This seems especially important in writing about war and trauma, but has also become increasingly important for other areas: not only does this point come up a couple times in Remapping Sound Studies, but it’s important for thinking about sound, impairment and disability, as in Mack Hagood’s discussion of tinnitus.

…and we’re back…

So that whole social media “platform” this was an interesting ride, wasn’t it? Turns out, nothing is ever free, the new captains of industry are as selfish and narrow minded as the old ones, and we are just the product. Oh wait, we knew that already:

I submit that the materialist answer to the question — What is the commodity form of mass-produced, advertiser-supported communications under monopoly capitalism? — is audiences and readerships (hereafter referred to for simplicity as audiences). The material reality under monopoly capitalism is that all non-sleeping time of most of the population is work time.

Sure, it’s more complicated than what Dallas Smythe laid out in 1977, but is it also still as he laid it out in 1977. The irony is the social media companies, and media industries in general as more cynical about “content”–code for everything that fills up media, from the most meaningful personal thoughts and experiences, to text generated to draw in searches for medical information–than any Marxist professor ever could be.

There’s value in controlling the rights to one’s own writing–and more importantly, one’s own thoughts–and putting it out there on a website that doesn’t control who sees it and who doesn’t. For now I’m still on the big 3 social media companies, but I’m sick of writing thoughtful stuff and it disappearing on Facebook (“read more” is designed so you don’t), and I’m sick of trying to be clever on Twitter. Yay long form.

I missed blogs and blogging, so I am doing something about it.

Probably this will be more or less the same random collection of musings as before, except I’ll talk more about music and music tech because, why not? Also I’m in two bands and Carrie plays drums now. And I owe the world a NAMM 2019 report. Don’t know what NAMM is? All the better.

I still have cancer (coming up on 10 years), my voice still ebbs and flows, and I still love cats.

Other changes: I’ve moved from a shitty for-profit hosting company (ipowerweb, oh how I hated them) to an awesome local not-for-profit company. With their help, the back catalog is cleaned up*, so you can read about Pierre the Nationalist Dishwasher Salesman (and my very early days of learning about Quebec politics) without weird diacritical marks everywhere.

The words “I must respond to” have been banned from my thinking about my public writing. The internet is so full of that. If I want to talk about wave shapers or crip science while the world races to melt the polar ice caps, kill off legions of species, and flood coastal cities; while political leaders say and do awful things; and celebrities (regular and academic) continue to die and/or do stupid shit, I will do just that. Life is short. This is just writing.

*This blog is so old that WordPress changed the character set they use for their database. Also, I started on B2, because I didn’t know about WordPress.

PS–on academia.edu: I told you so. Academics should use websites they control themselves, or use their universities’ repositories. But more on that another time.