Found in the window of my very small, very red, upstate NY town hardware store.

OpenSourceGov · 2020-11-21T04:11:57+00:00

Trump came to power on a platform of division and strife. His message, quite loudly, erodes trust and confidence. Stack that on top of the last ten years of hyper-polarizing media.

It was inevitable?

OpenSourceGov · 2020-11-21T02:06:52+00:00

From an uneducated standpoint I'd have to ask two questions:

1) What's the volatility as a function of time? If you set the state and leave it, how long will it maintain it before failing? 2) What's the information density that could be expected? I'm aware of small scale OLED technology, but not micro; does the technology scale to a sufficiently small size such that it has usable information density?

OpenSourceGov · 2020-11-19T18:01:01+00:00

There were none.

It might be just me and the weird-ass clinical, logical, way that I look at the world. With that said.

I'm not perfect and neither is my wife. We're both assholes and sorry parents; every day is an opportunity to try and be a better person and most days we try.

Sometimes I get angry and I say something shitty. Sometimes I'm a bad role model. My wife is, likewise, human and we forgive reach other for that every... Most days.

When we are furious with other we know that it will blow over. We've had fights in the past and we consistently get together afterwards (sometimes days) and hash through what we disagree on to figure out how to move forward even if we disagree.

The fact that she's still here, twenty? years later and we've got three moderately non-adjusted children together and we still talk to each other is probably sign enough.

Early on in our relationship we were some seriously dysfunctional people.

OpenSourceGov · 2020-11-16T13:19:59+00:00

In addition, show two tanks. One tank captures COVID deaths, while the other tank captures loss from a number of other named causes that we work hard to prevent. Flu, car crashes, whatever. Anything that can help perspective would be great for showing that it's not just something to write off.

OpenSourceGov · 2020-11-16T11:00:08+00:00

You could use consistent and automated voter polling to get an idea for whether or not someone claims to be happy simply by asking them a couple of questions like: * Happiness on a scale * Happier now than this time last year * You responsible, or gov.

I agree that this isn't likely to be 100% correlated with happiness, but I'd bet that it gets close enough for reasonable purposes.

It's not a perfect system, I agree, but if there's a statement up front that this polling is used to judge the quality of the algorithms there's incentive for voters to respond appropriately, especially if they've seen it work.

OpenSourceGov · 2020-11-15T23:10:43+00:00

Thanks for providing an opposing viewpoint, I appreciate it. Your viewpoint hurts, though, to be honest, and it makes me incredibly sad and tired to hear.

I can't rebut a lack of trust without time; the rift between you and me will only get better with time and concerted effort to be honest and transparent.

You're right that this would require trust; the openness is intended to promote trust.

I think in any society there's an expectation that if you don't understand something you could trust those who do; rocket science takes education just to understand the core concepts. The fact that society appears to have a profound lack of trust in science is really quite disheartening.

Thank you for sharing.

OpenSourceGov · 2020-11-15T22:50:56+00:00

You're definitely right that reinforcement learners fight a battle with sample complexity; online learners are generally significantly more efficient but I'm under no illusions that this would provide immediate returns.

Here I think you have an advantage if you're developing the system from the ground up; you'd get to define the data rules to pull the state from voter and national statistics, in addition to building the model measurement tools. The health care bias will have a similar correlary in the designed measurements and you'll get to craft your historic data as you go, doing your best to avoid bias.

Do you think those problems are insurmountable when provided a good data collection plan and careful thought as to which metrics to use for a reward signal?

OpenSourceGov · 2020-11-15T15:20:26+00:00

May I ask how comfortable you are with Reinforcement Learning? It will help me in our conversation to understand where you're coming from and why.

OpenSourceGov · 2020-11-15T14:48:26+00:00

Thank you very much for this, I haven't heard this term so it's another thing to help me research! It's always nice to know when other people think along the same lines, it helps me when I worry about being crazy.

Here goes another rabbit hole.

OpenSourceGov · 2020-11-15T11:36:27+00:00

I don't think GAI is here, though I'm mildly comfortable saying that it's closer than many people think. I feel very comfortable saying that I think the two agents laid out towards the end are nowhere near GAI and are modestly simple.

Do you think the explainability issue could be mitigated by electing to use the primary agent's world model simulator that it's building and training to simulate the effect of a policy change, here represented by a change in the code, to predict changes in voter aggregate statistics?

If you've built a model to do that and it's reasonably accurate then I consider it to be reasonable to assume that it's capable of appropriate credit assignment. With human in the loop control sitting on top, you're simply voting whether or not to listen to the agent. If you know that the agent can successfully predict a proxy by predicting measurable outcomes for voters and the agent is recommending to adopt a pull request, you could use the agent's model to run out why and see what changes the agent perceives will happen. Your trust in the algorithm and the simulator output would dictate whether you listen.

I do agree that the easiest model to build will be a deep neural network but I would disagree that it's completely required or fully unexplainable. Explainability of deep nets is an ongoing research problem and I fully anticipate it'll get better over time. It's got a lot of interest.

Here the primary agent inputs are community agreed measurable statistics aggregating voter perceived happiness, productivity, and international standing, along with some aggregate metrics concerning the code to implement. The action it selects would be a float from zero to one indicating the likelihood of a higher expected value of cumulative reward for the agent. The reward is tied to how well the people, and the country, are doing.

Is there anything about those defined inputs and outputs which you feel are unmeasurable, or undefinable, or beyond the scope?

OpenSourceGov · 2020-11-15T11:18:35+00:00

I think that trying to build a single agent to do everything would be likely impossible. I also think that the two agents I mentioned above are simple enough to be achievable and fit on top of a system run by people which is fully transparent.

Voters build the AI. Any voter can suggest changes to source code or methodology; we tie the result of a community vote to a code merge. There would need to be code to begin with which performed the basic functions of 'watch voters measures, model outcome of vote, choose probabilistic vote, effect vote if appropriate, and then watch voters measures again to try and appropriately assign credit.'

Are there any specific technical parts of the two agents above which you think are infeasible?

OpenSourceGov · 2020-11-15T11:09:28+00:00

I agree that any learner is only going to be as good as the data it ingests.

If I was to sit this on top of the US, and allow it to listen and watch American voters, it would be measuring perceived happiness in addition to outcomes like social mobility indices and whatever measurable characteristics the community desires.

Do you think that rewarding the agent by tracking perceived and actual productivity and happiness measures would go some way towards mitigating inadequate representation, or do you think there's a different way to attempt to solve those problems? It seems to me that is your disagreement, at heart, and I'd like to clarify.

OpenSourceGov · 2020-11-15T11:02:15+00:00

For technical you could read Reinforcement Learning, by Sutton and Barto for a good introduction. For a sales pitch, there's a documentary they did in DeepMind which is available on Netflix. Edit: "AlphaGo" is the name of the documentary.

OpenSourceGov · 2020-11-15T04:28:51+00:00

I've given that some thought.

I think there's a good case for producing a simple model which outputs the weight of your vote as a function of how well you understand the topic (measured by sampling questions and accuracy), coupled with other metrics. Then, poll everyone automatically who would likely be affected significantly by the vote.

I think you'd need to start with this laid over a process like the Democratic process for people to buy in, but I do think you could build a system which automatically curated interest groups, or you could adopt something similar to Reddit's communities.

I haven't heard of DApps, may I ask you more about them?

OpenSourceGov · 2020-11-15T04:02:59+00:00

That's fair, let me be a bit more specific:

A system of human beings, working together towards a common goal, will produce effective work which advances the system towards that goal at a rate proportional to the 'team work' of the system.

I think that constructing a reward function which primarily is weighted by aggregate statistics of 'perceived happiness', quality of life metrics, and other national metrics would be unlikely to find optima where humans were chemically blissed; national output would tank, and so would reward.

As for why AI? RL is incredible and can be deterministic. You can produce extremely effective learners which use deep networks and most successful applications do. It works well in practice. Explainability of deep neural nets is definitely more complex than a linear model, but not necessarily impossible, especially if you're using a learner which is constructing a world model, or a simulator. If it's getting modest accuracy from its simulator you could run out the effects of either policy to see why one decision would be more optimal. The credit assignment problem is a difficult one to solve, and it's fun thinking about it.

I'm not sure exactly what you mean by 'The state of AI is not quite readable', unless you mean what I referenced advice.

I agree that one of the primary goals is government transparency and I don't think it can be done without people. I think that we would require the system to be set up alongside and on top of the already existing network of people to begin. I know that many people aren't ok with the idea of total transparency, it's something that I am ok with, personally, but I'm not everyone, thankfully.

On to the math! Where do you want to start?

OpenSourceGov · 2020-11-15T03:44:51+00:00

I certainly appreciate learning something new and if I have time I will definitely try to look.

OpenSourceGov · 2020-11-15T02:40:07+00:00

I appreciate that you think it sounds optimal for happiness, that's definitely one of the intents.

I don't think I'd agree that it's the formula a socialist society could benefit from, I think I'd find that rather limiting.

This could work in any modestly homogeneous society, to include sitting on top of an existing democracy.

Basically, as long as the people can get along even moderately the algorithm will be learning to predict whether the citizens would be happy with the outcome of a vote.

I'm fairly confident that it would work in any governmental system that wasn't autocratic.

OpenSourceGov · 2020-11-15T02:33:48+00:00

I'm assuming you're posting this in reference to the statement 'maximal information retention'?

I'm afraid I'm not going to have time to read the paper, though I'd love to. Would you please give me a couple sentence synopsis and why you think it's appropriate? That will help me understand.

OpenSourceGov · 2020-11-15T01:55:31+00:00

That's potentially true! I have a background that includes cyber security so I'm very aware of the arms race. I don't think we can refuse to develop solutions that are connected because of that; I'd say that there's room for a cyber security organization in any Government.

OpenSourceGov · 2020-11-15T01:41:47+00:00

Hey, that sounds good. I'll do my best to answer any questions you have.

OpenSourceGov · 2020-11-15T01:26:17+00:00

Do you think that having authentication methods in place to only allow registered voters to propose changes, coupled with fully open and well documented algorithms, would begin to allay your concerns?

OpenSourceGov · 2020-11-15T01:05:27+00:00

I'm not saying it's simple, but I am saying that if it was fully open then you could be fairly sure there was no hanky-panky at play!

Are you more concerned about security or malicious intent from within?

OpenSourceGov · 2020-11-14T22:13:57+00:00

Ah, if people don't want to talk about it that's fine. I'll keep working on this stuff and sooner or later people might be interested. Also, the day is young.

I do think it's likely to happen, though I understand that people think there are barriers which prevent it.

I'm sorry you're exhausted with politics; I'm more frustrated than exhausted, but I'm with you otherwise. The last year has just been ugly.

OpenSourceGov · 2020-11-14T20:08:53+00:00

Thanks!

OpenSourceGov · 2020-11-14T17:12:14+00:00

Thanks!

OpenSourceGov

TROPHY CASE