Flux is a political party running in this year's state election. Here's why you shouldn't vote for them.
Flux claims they will be giving power back to the people, by asking them to vote on how their member should vote on any given bit of legislation. Unfortunately, that's not what they actually plan on doing.
In order to claim a seat in the Legislative Council in the first place, Flux has traded large numbers of their internal votes to other minor parties. In return, those minor parties will preference Flux higher on their voting ticket. Because of the way Flux votes accumulate more weight when they're not used, on the issues those parties care about they will essentially control the member's vote.
There is no indication of how much influence Flux has traded to minor parties - although there's some evidence that the proportion of power left for members of the public is as low as 30%:
"They had initially proposed a kind of minor party coalition, where each party gets X votes based on how highly they preference the NVB/Flux Party at elections."
This is still the proposal, just the site is angled differently to attract members instead of provide some grand, detailed, philosophical vision (much less sexy). We anticipate Flux members would probably control 20-30% of the bloc.
Flux's constitution makes reference to "Facilitat[ing] minor parties and independents' productive participation without winning a seat", and has "…no requirement that the voting system for members is the same as the voting system for minor parties.
This isn't actually a bad idea. Our parliamentary democracy allows and encourages single-issue parties to get involved in parliament, but as Senator Ricky Muir of the Motoring Enthusiast's Party discovered, there's a lot more to parliament than your single issues of choice. Banding together to have essentially a time-share senator seems like an excellent way of solving this problem.
Unfortunately, that's not how Flux is campaigning. They're keeping these associations a secret, and handing out voting rights to parties with quite frankly terrible policies (like Fluoride Free WA) with seemingly no considerations other than what will get them elected. They're not redistributing power to the public. They're redistributing it to a handful of randomly-chosen minor parties with little support and no chance of being elected on their own.
Flux is not the kind of party you're looking for - and they're deliberately obtuse about the kind of party they are.
A fundamental principle of democracy is that everyone should be able to participate, regardless of ethnicity, gender, wealth, or religion. Flux claims to be allowing greater participation in democracy, by opening parliament up to the entire public.
But take a look at that again. Democracy is supposed to be open to everyone - but Flux requires a smartphone app to participate. Those without the money, knowledge, or inclination to own a smartphone are barred from participation in government. This is called the digital divide, and it means that those with the least power, who need representation the most, are locked out of participating in the system.
You can't run government like a startup, because government has to work for everybody. That's why we vote on weekends, and have provisions for early and absentee voting, and make allowances for those who might have difficulty voting. Our democracy is designed to work for everybody - at the very least, as many people as possible. Perhaps it makes things slower, but it also makes them fairer.
The other fundamental principle of democracy is that the process is open and accountable. Elections are audited and scrutinised by impartial officials and by all the parties that hope to be elected. The proceedings of our parliament, with a few exceptions, are made publicly available, as are the documents and legislation it produces.
Flux has not released the source code of their app. It is not possible to examine the code responsible for controlling the actions of this elected member. There is no way to audit the vote, to determine that the vote in parliament represented the votes of the public. And Flux's constitution says that "The parameters and design choices of the system are left to the Leader, and not within the scope of this document" - they could change at any time.
Unlike the rest of our democracy, Flux is a black box, with no way of understanding the processes at work inside.
Even if Flux was a good idea in the first place, they're not yet ready to potentially take up a Legislative Council seat come the result of the March 11 election less than two weeks from now.
There is, as yet, no sign app in the app store - on Android or iPhone. There is no information on whether other operating systems, like Windows or Blackberry, will be supported. There is no detail on how vote-swapping, or vote-accruing, will work in practice. No detail on how your votes can be assigned to 'experts', or who those 'experts' even are.
There is no information on how votes will be authenticated or secured, beyond vague references to 'blockchains' - a technology which even if implemented correctly is not necessarily anonymous - if this is implemented wrong, votes could be compromised, falsified, or identifiable.
There is no plan for how this representative will participate in parliament beyond voting. What about proposing legislation? What about participating in debates on the floor? What about the oversight that the upper house of parliament provides, on committees and inquiries? Will the Flux representative just… not? For a platform that is supposedly about participating in the system of democracy, that's an awful lot of not participating.
All of this is based only on what information that could be found publicly - but isn't that the point? If you're planning to dismantle representative democracy one bit at a time, shouldn't you be clear that you have a plan to replace it, and about what that plan is? The fact that you can't find good answers to these questions says that either Flux have no plan, or that they don't want to share their plan with you - and neither of these is a particularly good sign.
Government is serious business. Lives and livelihoods really are at stake. As frustrating as the system might be, it is not to be 'disrupted' lightly, and Flux shows no signs - yet - that they are treating your vote with the respect it deserves.
There is something to be said for having somewhere you fit.
Here are two somewheres where I fit.
You know, they didn't have to give me a desk. I would probably have been fine working in the library, or from home. And the more I think about it, the more it seems that getting me to claim a desk was a ploy to pressure me into doing a research project.
I think it worked.
I have filled its drawers up with teabags and trinkets, but I think the most important thing in the drawers is my notebooks. They live there, and they don't come home with me. Yes, most of my work is on my computer, but the notebook is the thinking space, the page file for my brain, and that goes in the drawer at the end of the day. It's about the symbolism of the thing, more than anything.
I have watched people go crazy doing their thesis, and I have watched people take work home with them, and I am determined that that will not be me. At the end of the day - however late that day goes - I am going to put my uni work in my desk, and I am going to go home, and get some sleep. Maybe that's the real reason they gave me a desk.
I hope it works.
it feels like someone reached into my brain and found all the things I like in music and smashed them together.
In December 2014, by sheer dumb luck, I found the music genre called Post-rock. Thanks to the Spotify subscription that fluke sold me on, I've been able to dig and discover and carve out a perfect little algorithmically curated niche that... well, that reaches into my brain and sparks all the things I like in music.
Here's what I like about it.
I like that there are usually no lyrics to get in the way.
I like that it's not afraid to be epic and deep and rich and melodic
And I like that it sounds like the soundtrack to something really cool happening.
I have found music I like, and possibly for the first time in my life I don't actually care what other people think about my taste.
There is so much else going on right now that is, quite frankly, a bit chaotic. I'm going to Sydney next week to do an internship for a month, and the uni is dragging its heels on my flights and accomodation while I drag my heels on packing. I've just had my only paid published article vanish into the abyss on a defunct website, but I'm already writing a new one for its replacement. I've picked a thesis topic, but I don't want to write about what it is here - at least not yet - because it still feels too soon and I don't want to jinx it. I feel like I've only just wrapped up working on Scitech's Fringe show, and like three nights' break was not long enough. My car needs a wheel alignment, my bike has one Schraeder valve and one Presta valve and I really don't have time to fix it, and I'm a little concerned that my new shoes don't fit properly - again.
And whe I write it all out like that it looks like it must be driving me crazy, but it's not.
Because at the end of the day,
I can put the post-grad away,
and put the post-rock on to play.
Why a neural network in particular? No reason at all. Neural networks are just one way of doing machine learning, but I think they're a pretty interesting one.
You take a program that's easy for another program to change. You give it lots of ways to change, and lots of chances to change, and a testable goal it's trying to achieve, with lots of examples to check against. The rest is basically trial and error on an enormous scale.
My network ran through 23650 generations, and took all night to do it. And at the end, my computer had programmed itself to write. Not just to write, but to write like me. Supposedly.
How is that not intriguing?
Why do this at all though? There are a couple of reasons.
Firstly, because jumping into the deep end of something is the best way to understand it. Machine learning is playing a bigger and bigger part in our world, and I think that understanding how your world works is important. Also, learning new stuff is fun!
There was definitely an element of curiosity, too. Two of the most interesting bits of the internet I watch and listen to, Idea Channel and Flash Foward, have had a go a this. In fact, that's... where I got the idea. If Idea Channel can generate interesting nonsense with five years of scripts, then surely I could get something with over ten of blogs, right?
I wanted to see what a network would think I was like. It's almost a bit of self-discovery. What patterns do I have that a network would be able to discover?
I primed the network with the phrase, 'This post was written by a neural network.', and used a 'temperature' of 0.5, where 0 is entirely unoriginal and 1 is entirely too original. I generated a couple of posts, and picked the one that made me go 'whoa' - the post which not only included correct paragraphing and punctuation, but which had generated an entirely valid image embed code. Broken, sure - the filename it links to doesn't exist - but everything else about the link was perfectly formatted.
Reading this stuff is weirdly compelling, even though it's utterly meaningless. Some of it is surprisingly poetic. I felt bad editing it, like I was changing something that someone had worked really hard on. I can't bring myself to delete any of it either, even though it's the opposite of precious - this thing could literally generate more stuff than I have time to read in a lifetime. And somehow I keep wanting to read more, to pan for gems, wondering where that train of thought was going even though I know there's nothing there doing any thinking. Something about it is close enough to real to keep you looking for personality and meaning in structured nonsense, and I think that's completely fascinating.
A neural network is basically a collection of little units, all chained together in kind of a grid. Or, well, a network. These units are very simple computer programs. They get signals from the units behind them, weight those signals according to some settings, and if they meet a threshold, they signal the next units along - which do the same thing, all the way through the network.
So, for any given input, you get some units activating and passing on signals, and some not. Eventually, you get a result out the other end which depends on the input you put in, but in a pretty complex and convoluted way.
You adjust a network by changing the weightings that the units give their incoming signals, and the thresholds that control whether or not they send signals. Different settings in different parts of the network mean that different bits of the network - different paths through it - will light up and transmit signals from end to end. And different signals at the end combine to produce a different result.
You assess how close the results are to the ones you want by using a cost function. If the network is spitting out the wrong results, the cost will be higher. If the result is right, the cost will be lower.
Cost is the mathematical difference between what the network is doing and what we want it to do - an error value. We pass this error value back through the network, and adjust the network's internal weights and thresholds to try and make the error smaller next time. And so, over many iterations, the network gets better at doing what it's supposed to be doing.
After enough training, all of those little settings are perfectly tuned, through trial and error on a massive scale. You'll have a program that gives you exactly the results you trained it to.
The advantage that this has over programming a computer the traditional way, with explicit instructions, is that a neural network can learn pretty abstract processes or concepts or patterns. It can learn things would be very difficult to describe how to do to a computer explicitly and logically or mathematically - but as long as you can check that the result is correct reliably, you can train a network to do it.
The result coming from the network could be a number. You could train it to do maths - any maths, in theory. Or it could be a category (probably expressed as a number) so you could train it to sort things. Or it could be a word (again, probably also expressed as a number), so you could train it to 'describe' things. As long as you can check it against something, you can train a network to do it.
This makes neural networks really good at processing large amounts of real-world data, where yes, there are patterns - but programming computers to detect them is hard. Things like image recognition, or human language, or speech processing. Neural networks let computers be a bit better at the kind of things that brains are usually good at.
Still with me? Good.
Our little network, with its inputs and results, is all well and good if you want just one answer for one question at a time, but what if - like many complex problems - your problem depends on context? This is where recurrent neural networks come in.
Recurrent networks accept some level of input from themselves. The result of one run of the program can depend on the result of the previous run. And the weighting of that result as input is one of the adjustments we can make, so we can attempt to change the output of the loop as a whole by changing how much influence the previous result has.
It's like an infinite chain of programs stuck together, and while we're getting a result from each individual one, we're also feeding that back into another copy of the program.
So essentially, what this network does is output a single letter - the single most likely letter to come next, given the letter that came before it as input - and before that, and before that, and before that too. It knows which letters are likely because it was trained to minimise the end result's difference from the text on this blog.
For example, it might see that in that text full stops appear in two places - sometimes in web addresses, and sometimes at the end of sentences. If it was just looking at one input and using overall likelihood, it'd get this wrong a lot - but it doesn't.
It knows that, perhaps given the previous characters contained a space, or something else non-address-y, that what comes after this full stop probably isn't a 'c' (to be followed by an 'o' and an 'm'), but another space. And as well as outputting that space as a result, it also passes it along. The next neural network along will know that a space is likely to be followed by a capital letter, given there was a full stop two characters back. Basically, it doesn't just know how to write letters - it knows how to write letters in context. It knows that it's not in the middle of 'writing a web address', because statistically they don't have spaces.
At least I assume that's how it does it - one of the weird things about neural nets is that you're never quite sure how they arrive at the conclusion they did, only that they work.
But even though it understands context, this is still a pretty simple network. It's only two layers deep, with a few thousand units. Which is why it's produced writing that looks and acts and feels a lot like mine, but that doesn't mean anything. Intuiting actual meaning from context is probably about a bazillion layers deeper - Google or Facebook might get close, but not this dinky little thing I ran on my laptop.
Cheers to Morgan for advice, links and fact-checking.
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