hugo bowne-anderson
You're absolutely right. And so I want to make this you and I can get relatively abstract on occasion. And I enjoy that I want to make this concrete with an example, which I think what you've done in your career. Yeah, I think I look up to what you and Travis and Bryan and all of you did a continuum and now at Anaconda has very rich information about the intersection of open source and business and venture backed startup land as well. So I'd like to... I don't necessarily consider all of VC necessarily extractive of course, but I do think there is definitely that element to it. So I'm wondering what the trade offs are in working in the open source space, and accepting venture capital, and how that can inform the conversation we're having now.

peter wang
my experience, and this is all just I can only speak through the lens of like, my personal experience on this course, for people at startup land VC seem like at the top of the food chain, but from people who work in the capital markets and work in, you know, institutional investment or whatnot, VCs are just one set of players in a very big ecosystem, that's actually much bigger than VC. So you know, the top tier VCs on Sandhill Road, and that everyone talks about, they have a certain prestige to them, for people who are going, you know, into startup land and coming out of YCombinator and all this stuff. And there's a reason that I think they incubated a lot of the funded and built really good companies, but they are still just one component in a very big set of capital market players. And ultimately, anyone playing the capital markets, you're beholden to your investor, just like startups are awfully beholden to their investors, the investors are beholden to their limited partner

hugo bowne-anderson
LPs. Exactly. I'd love a sociology of like data tooling, LPs one day.

peter wang
yeah, it'd be interesting to actually go upstream. A lot of LPs are interested in this stuff. They're all over the place, right? Some LPS care some of their family offices, every LP has it basically, LPs are just massive, massive, multi 100 millionaires and billionaires and sovereign funds, and college endowments and all these kinds of things. And they write really big checks to investment management firms that then go and give the money to to entrepreneurs or to invest in land or building real estate. So the reason I tend to give this 101 to capital markets, is because the thing that I want people to understand is that anyone in the middle who isn't investing their own money is merely an agent of the principal that actually owns the money. And so there's a concept called the principal agent, problem, principal slash agent problem, or principal dash, which is that agents are incentivized to do certain things that are not always 100% aligned with what the principal wants, they act on behalf of the principal. But ultimately, they have a living they need to make they have a personal reputation, their fund and the firm has reputation they need to maintain. There's all these things that agents have to do. Their incentives are not 100% aligned with the principal, the principal says, I give you a billion dollars, you need to go make me a certain percentage back and you get carry on it, you get all these different things to incentivize you to make money on that money. But ultimately, I give you the money and then that's transactional for me, essentially, you need to give me that money back with a lot of interest. And that's what the principal cares about. And then everyone in the middle is agents, until that money finally hits somebody who's going to take the money and apply it to some problem. That person is putting their own energy, their time, their person reputation. They're not spend time with their family, their kids and the parents. They're putting like, the most precious resource any person has is their time. They're putting personal time and energy into this. So the principal has a unique stake And the entrepreneur, the doer has a unique stake. Everyone in the middle is an agent. Okay? So the reason I say things like that, and that's very reductive, I realize it can be a little offensive to people maybe. But it is actually I'm a physicist, I like to look at things at the fundamentals. This is the fundamental wiring that people get, you can't break out of this pattern, if you're in the pattern, this is the pattern. So that what happens is, if the LP doesn't have a stipulation, or doesn't have a point of view, or doesn't put requirements on those agents, on those VCs or investors to do certain kinds of things, they're not going to do them in general, unless it dramatically de risks or dramatically increases the possibility of the outcome. So funds of firms can say VCs and venture firms, they can tell you, we have a thesis, we're operating this way, we're this kind of firm, we're founder friendly, we're this we're that we're a growth stage firm, we help accelerate today, everyone's had a story to tell. And they will try their best to actually live that story. But when push comes to shove, they are agents. And they have to do certain things that hold them at least what's the term like they have to be at par with everyone else in that ecosystem. Because it's a small world, when you get into the world of managing billions of dollars. It's a very small world, everyone knows each other, and the reputations last a long time. That's the issue there. If you are a company, and you want to do these, like great things, and like a B Corp, this stuff and impact social impact and generativity and all this stuff, you can tell that story till you're blue in the face. At the end of the day, you got to look at your investors it was the investor want? And how am I going to give that return to the investor. And if you're cool on that, and investor says, Yeah, that's actually what it is, then you're great. If you can believe and trust, the investor is going to fight for you to have certain other kinds, like you can perform outside the envelope of expectations, then that's a trust that you have with that maybe they have a big enough portfolio, and everyone's got to play money. Everyone does, right. So all the firms, the partners, that they'll have some play money, they can toss at various random things just as like outsize bets. If it completely blows up, it doesn't matter. And so then if you are lucky enough to receive some of the doesn't matter money, then you're very free to do whatever you want to-- lucky you. But most people don't get that most people there is an expectation of a certain level of return and certain kinds of things. And there's certain time window performance. Those are just that's just the way that play, that whole system works. 

hugo bowne-anderson
How does it impact a company that is building tools? Or maybe a different question? And we can go in either way. How does it impact the data tooling landscape, which as we've seen the incentive system for these agents or venture capitalists is to have a portfolio of tools, which some of which will work, some of which won't? And is there a tragedy of the commons therein in the tooling landscape?

peter wang
There's a lot of fertilizer dandelion seeds being dumped on the pasture, absolutely. Put it that way. And I think I don't know how to put it My inclination. I'm a bit of a, I'm a bit of a rebel in a sense. And so I think I really love the kind of energy and ethos of the open collaboration, environment, SciPy, and pydata on all these things. I think it really brings out the best in a lot of people. And there's such a positivity and generativity in it, that I see my personal mission is to help defend some of that. And the way that I plan to defend that is to number one, just call just talk about these dynamics, even just having conversations like this and just being explicit know about what I think some of the challenges are. That's actually awareness raising is an important thing. But another thing is I do and maybe this is naive, but I do you believe that users are more sophisticated than maybe what sometimes VCs or Gartner analysts or whatever it gives them credit for. Because a lot of the VC money being made that was made in software over the last 20 years, it had a certain playbook of how it would take software to market and there's all these different kinds of things. My hope is that if we can actually build a more sophisticated user base, that market becomes too expensive to go to market in inorganic ways. And that market builds community and builds peer review. And I'm sorry not peer review builds peer review sites and builds connection and builds all these things, so that they're not alienated from each other. If you're about to use something, if I were to get a concrete example, I don't know what kind of data analysis problem that you would encounter that you haven't encountered before. But if you were to encounter some problem, and you want to do something with it, you would do some Google searching probably but then you would also ask some people who would maybe work in that area exactly what do you use?

hugo bowne-anderson
Right? I asked people in Slack channels now I've read we're very good at finding-- especially now given all the bullshit out there. We're very good at finding the highest signal places and we're getting better at that I got people on WhatsApp dude or signal I'll message you sometimes to be like, what's up?. And I'm like, what is happening? All these SEO experts and digital whatever is like pumping crap into my brain. Yeah, the

peter wang
proliferation of the star dash Ops is a very enterprise software move, right? Because what they tell you, what they tell you is that you have to go and be if new categories are emerging, you want to position your product in the category and be a leader in the category and pay off the gartners and whatnot. So the world to get yourself into the Magic Quadrant, and all those other kinds of things. And so if you can't do it, then you should create a category and because it's all top down selling kind of stuff. It's all like, it's vending into the ignorance gap, where you have practitioners sometimes, is it folks, sometimes the software developers, they don't know what to do what's best. So they go, and they search for how to do these things, because it's an emerging area. And that ignorance gap is where people will come in, and just essentially carpet bag and I find that extremely, I find that really just dishonest. But as a technologist, and as like an old school coder nerd, it offends me a little bit. And so that's fine. I don't have a lot of respect for that kind of thing. But I do believe that if we're able to build this one of the reasons why we're building the nucleus of the community site, we really want to create an environment where there is a high trust, high signa; to noise, place for practitioners to actually share their insights and one or the other. And these kinds of forums did once exist on the internet. Right? When we were not all just random alienated avatars, on sites with hundreds of millions of users, we would actually find forums and find places where we'd create an account and would build reputation, we get to know other people would actually have a relationship. And if you can create a place where relationships are possible, then you can have a much more credible and trustful environment for sensemaking, around emerging technologies, or whatever. So that's the hope that's why we're doing that piece of it. And that is exactly I may not have expected how it would come around to all this. But that's exactly the kind of turf grass or trying to basically put the stuff down to put turf grass in so that then the commons don't erode right from this cost of pounding of more like whatever ml dev SEC ops things something no next year now that those concerns, I say these some of these things that flippant manner, it's not that the problems don't exist, or the problems aren't legitimate problems. It's more of this rush to put labels on a category of emergent problems, and then immediately try to find some off the shelf thing that just solves it, it's highly unlikely that an off the shelf product thing solves us and another name I will drop in here is Erich von Hippel and his work on Democratizing Innovation, and his critique of products even as a concept, but his research on the idea that products only ever suffice, 60 to 70% of a user's need, they have to self service, the remaining 30 40% of it. And this applies from track from like tractors in the cornfields of Iowa to hard drives to whatever, right the idea that we can vend products into technology areas of emergent practice that have 100s of 1000s of different possible configurations, that's a pipe dream, like just stop trying to buy stuff, just be you gonna have to build things for a while. So I think that's an area where, yeah, some of this stuff is emerging. It's a hot area of innovation. So my goal is just to be at least one standard one battle standard on the battlefield, to say, this is a credible, crowdsource practitioner led, Kid tested, Mother approved, like innovation looks like and trying to find lines of demarcation trying to find the allies who will join us under that banner.

hugo bowne-anderson
That's awesome. And I'm personally very proud and humbled to have created a bunch of content with coiled on parallel computing and scalable computing. So we've got some videos and blog posts and white paper and then that type of stuff. That's cool to have started off that collaboration. Yeah, I want to go a bit deeper into data. And, like I'm, in turns quite bullish, and then bearish on data science and analytics. And why are we doing this, Peter?

peter wang
the interesting thing is that the world if you really go and you work in industry, for a while, and especially I was very privileged, I really enjoyed my time at Enthought I was quite lucky to have the opportunity to go to many different kinds of businesses, see work with maybe scientists in a particular area or quants at some investment bank. And then also from that vantage point, usually a point that is very data driven, that has sometimes physics equations, sometimes, you know, not so accurate financial equations, whatever, that power computing, and then from that vantage point, look at the rest of the organization. And whether it's an oil and gas company, whether it's an investment bank, wherever you go, what you find is that the landscape of the modern firm, 40-50 years after the PC revolution in the digital era, information age, human decisioning at these firms are, for the most part, not very data driven. They're retroactively data informed, but on a forward looking.

hugo bowne-anderson
mad confirmation bias constantly.

peter wang
There's MAD confirmation bias and the forward looking stuff is always some VP taken a swag,  highest paid person's opinion taking a swag and having the data people generate pretty PDFs and PowerPoints to explain to quarters down the road, why unexpected things caused it to not work? So the sad truth is the world is deeply inefficient and less efficient than it could be because it is not a data driven world where 10 years after the peak of the Hadoop Big Data wave, right with all this marketing, with AI and all these other things, for all of that, it's like professional, that's all pro wrestling. That's all like if you talk if you look at I love watching some of the stock market stuff, especially segments on tech news and everything else. It's all theater all kayfabe. At the end of the day, most of the doesn't work. Most of it is IT overspend on stuff that doesn't work. That really is ultimately most businesses run on spreadsheets be emailed between VPS okay, we've really not progressed to some data systems are more advanced, there's some transactional systems that are incredibly advanced. But for the most part, most businesses are still run based on not just human in a loop. But humans calling all the shots based on a couple of data things confirming their biases. And the way they sometimes there's that that quip that science advances One funeral at a time.

hugo bowne-anderson
That's great.

peter wang
businesses generally advance one VP exit at a time or one SVP or one CVP. I said at the time. And so why is that such a problem, that's a problem. Because it is not just inefficient from a resources perspective, those people get paid a lot. They make crap decisions, they create a tremendous amount of trauma, a lot of wage earners and then go home and export that trauma to their kids and their spouses. It's really horrible dynamics. And then all the money they're getting paid essentially, as a white collar welfare that could be going to feed starving kids. So there's a deep sort of like global humanity level inefficiency. But you put all of that aside, there's an existentially important problem, which is that the world is getting more complex, faster. So all of the businesses that actually facilitate infrastructure, products and goods that we need to live and all these things, all those businesses have to get a lot much better, and much more agile at responding to a more dynamic environment. So part of what happens there, this is the opportunity for those VCs, right is they know those businesses are dinosaurs that can't do crap. They're just paralyzed in place. So essentially, all you do is you go build a business fund some startup, they get some amount of revenue, they challenge some incumbent, the incumbent come in and comes in and buys them. And then usually the thing dies, and whether it's inside the cupboard, so that innovation dies, right? The VC gets their take, they get some multiple on exit, the corporate people that acquired it, they get to give themselves to declare success and give themselves a bonus at the founders. And hopefully they do well, like the people work the business they got acquired. But the end of the day, did that innovation really make it out? In general? Most cases? No, it really doesn't. Sometimes there are success stories for sure. But in general, it's really not even 50/50. So if we look at that, and we say, okay, hold up, why are we doing all of this right to your question. The reason I'm doing all this is, is I'm hoping that the new generation younger people going into these businesses armed with these data tools, are going to basically slash and burn their way through the inefficiencies of the previous models. And one of the ways they do it is from within the belly of the beast. The other ways they do it is by learning all the trade secrets, not trade secrets, but they learn how the beast operates. And they're like, this totally sucks. I'm leaving, taking thrree of my best friends that are super awesome over here wanted to build a startup, we're going to eat this thing's lunch. So that's really so I see myself as  a steward of a large colony of blacksmiths making tools for the revolution, also the data revolution, it's a cybernetic revolution, I love it, we must have firms that are smaller that a more agile data driven, that are that the prediction action observation out in the market back like that has to run tight.

hugo bowne-anderson
And networks of small firms interoperating and being and I think the interoperability in the tooling space via networks of small firms building tools at different points in the pipeline, I think is a very promising future.

peter wang
Consider this: we think about supply chains or physical goods, if you're trying to make a phone or a toaster oven, whatever you're trying to build a physical good, you're gonna say, Okay, I have this prototype of the product, I want to feel this product, I need to sell a million units next year. Let me go look at the supply chain, I'm gonna look at my suppliers who can supply me electric cords, who can supply me a heating element, who can give me who can handle boxing up all of these things and distributing it right? You're gonna ask your Suppliers and distributors and ultimately retailers to give you models of what their stuff looks like. Now, they give you those models on the basis of maybe PDFs with some tables built in with the pricing and lead times and stuff. Sometimes they'll even give you a spreadsheet where you can model out yourself. Imagine the future if that was actually all API's it was actually give me no give me your model. Give me your frickin model. I'm gonna put in here and do like stochastic walks through possibility space of optimizing like I do convex optimization of DryCell toasters or toaster ovens or air fryers, right? I can do all of this stuff on the basis of you having actually given me your model, so I can pull it into my ensemble model, that's a very different world, then we're some VP looking at a thing squinting and be like, Ah, screw it, I think we're gonna do this textbook,

hugo bowne-anderson
I love it. And it comes down to something that we're going to speak to soon, which is cybernetics and getting us as pilots or controllers working well, with the machines. I do think I love the idea of the data revolution and supporting people doing the data work, because what I see now is I have a very poorly formed thesis, I've been reading a book by an anthropologist David Graeber, called bullshit jobs where he actually creates a taxonomy and typology of bullshit jobs. And he's actually identified an increase in the number of people who consider their own jobs bullshit. And part of his project is to discuss, meet and write with people who he would never say your job is bullshit. But speaking with people who actually feel that their jobs create no value, and I don't think data science is like, totally bullshit. But I know a lot of working data scientists and analysts who create all types of work for their organization that they feel is never used. And Graeber uses the term spiritual violence with with respect to this, but there is a very demeaning lack of professional dignity with this type of wage labor, I think, and being part of a revolution to enable people to come up and be proud of the data work they do when it's used, I think is incredibly important for our field.

peter wang
 Yeah, I mean, it's we talk about these kinds of jobs a lot of times the bullshit job actually there's strong correlation bullshit jobs and white collar. Yeah. Oh, absolutely. blue collar jobs, labor, do you get see are you doing? Are you not doing right? But the white collar sounds like Oh I sent some emails today?

hugo bowne-anderson
This is part of the pushback, I think that we're not talking about with remote work is part of the reason corporations don't want people to work remotely isn't because of any of the stuff we've been talking about. It's because they can't see them just sitting in the office pretending to work, it puts the busy work on Slack again, and through email.

Unknown Speaker
If I could actually pull this back to what we talked about the antivalrous vs rivalrous. The industrial era mentality, or modern theory of the firm and a lot of management practices techniques, they come from the industrial era, which then was informed by military type stuff like the Henry Ford stuff and whatnot, they really it was about managing.

hugo bowne-anderson
  Fordism Taylorism.

peter wang
about managing human labor.

hugo bowne-anderson
with a fucking clock, man. Like, the clock, sorry, for timing, the tyranny of the clock. 

peter wang
Tell us how you really think, Hugo! So the interesting thing about that is that when we have such a huge -- when we move in the information age, and then you have such a diversity of outputs possible within the same unit of labor, that labor is no longer the right way to measure it. And a lot of people have not really figured this,

hugo bowne-anderson
Am I paid for my time or for my tasks. I've literally asked that to people before,

peter wang
in small firms even doing information work, there's no place to hide, right? If you're not getting your stuff done, everyone can see you're not getting your stuff done. When you get to a really larger size, when people lose sight of the connection of their work to the bigger output. And there's a tier, what happens is, this is, again, the principal agent problem, the principals of top like the C suite, they know what strategy they want to implement. And the worker bees down here, they know the things they can do. When you put a layer of agents in the middle, whose job is to manage up and down or up and down, then it becomes extremely difficult to-- a lot of stuff kind of filters through and that doesn't quite make it right. It's extremely lossy. And the interesting I was just reading thing about remote work... two different things. One person that was a Reddit comment, this guy bragging about the fact that he quit his previous job with a vengeance. And it felt so good, because the boss was crap. And then he picked up like part time thing, doing something, I think it was some claims processing insurance paperwork kind of thing is getting paid basically 35k a year to do this thing. But it takes him like no time to do it takes an hour to do it. So he picked up a second job, another 35k A year picked up a third one another 35. He works basically a 60% of what used to work and now he's making three times but he's making and this kind of thing is I don't want to extrapolate on one data point. But this is a very interesting kind of thing is the other thing that someone was saying was that one of the challenges with going to remote work is that it really... the tide goes out. And then people really start looking at where am I getting my inputs? And where do my outputs go? Everyone who's doing make work and busy work in the middle gets cut out of it. And so a lot of bosses and managers and whatnot, who have been quite superfluous to the process are all going to get squeezed out of this process. So we're gonna see, I think there'll be a revolution in tooling around corporate and remote work, hybrid work, internal efficacy, and you're gonna end up with a situation where companies are really realizing there's a lot of efficiencies they can gain, you know, it'll be interesting. I'm actually quite hopeful about this, but back to the point about labor Taylorism. Information Age, right? And the meaning, the lack of meaning of some of the very smart people who use data science equipped with these tools, they go into businesses and to what end. And I think this is the thing of we talk about spiritual violence, when you take somebody's time, and you engage them on something, what you owe them is not just the wage, you really owe them some ability to derive some meaning from their work. You can't starve them of meaning, that's not right. And unfortunately, most of corporate America becomes quite starved for being because no other top is said there is no chief meaning officer. So how do we avoid and how do we measure the level of Anomie across the organization? And how do we mitigate I think, in Bhutan or somewhere, they have a gross gross happiness product, their gross national happiness, right, which is a little bit like whatever.

hugo bowne-anderson
 I love that Schmachtenberger right on Rogan, he gave he said GDP is a horrible metric like it goes up with as addiction goes up as war goes up. And he thought he said the inverse of addiction is perhaps a good measure of, he said, a nation's health but we can say that any collection of people.

peter wang
Well, addiction is actually only one kind of dark thing. So it's actually the inverse of the one hole. Yeah, there's a lot of holes people get stuck into. But the general concept I think, is quite good that if we don't know what is we should what the best thing is like, what is gross national happiness that's hard to measure. But can we measure one over gross national suffering, pain, trauma, alcoholism? Suicide? Right? And yeah, we that might be a useful measure just to say, if I don't know where I'm supposed to go, but my distance from the cliff is still a useful measure how far away am I from the edge because I might not end up where I want to go, at least I'm not going over there. So I think with this kind of thing, it's the same thing, the structure of businesses, when you look at information work, which could be a generative thing, could be an abundant thing. And so I was saying, business from the top in order to have management be able to learn how to extract, in order to better metrics, that extractive things, we completely disregard the concept of freedom and autonomy, and the kinds of things that actually give people a sense of meaning at work, making consequential decisions, I've always maintained, that's the root of meaning isn't making consequential decisions, if you're doing all these things, and then it goes up and just flitters away dies in a PDF somewhere, you don't feel good about yourself. And that's I said, life isn't about feeling good, to be clear. But if we create a system of the world, or constantly depriving people of meaning during their waking hours, and in their collaboration with their peers they see during their waking hours, that cannot be possibly be the right architecture for civilization. Yeah, I did you have an original question?

hugo bowne-anderson
I think we've wrapped around with respect. My question was around the idea of bullshit jobs as it relates to analytics and data. Oh, right. I think I think right on that, what I want where I want to go now is, I asked you what's valuable about data? Why we're in data, okay. Oh, right. Right. Yes. Where I want to take this is, now let me get this right. I want to talk about the value of data. And then let's say the suffering caused by data what I mean like we've heard all this shit, like data is the new oil and that that type of stuff, but you may have even sent me this originally years ago. It's a talk by Maciej Ceglowski at Strata called haunted by data. And I'm gonna just read you the opening. But at the start of this talk seven, seven years ago, he wrote in preparing this talk, I decided to check out the data landscape since I hadn't seen it for a while. The terminology around big data is surprisingly bucolic data flows through streams into the data lake or else it's captured in logs. A data silo stands down by the old data warehouse where granddaddy used to sling bits. And high above it all floats the cloud, then this stuff presumably flows into the digital ocean. I would like to challenge this picture and ask you to imagine data not as a pristine resource, but as a waste product, a bunch of radioactive toxic sludge that we don't know how to handle. In particular, I'd like to draw a parallel between what we're doing and nuclear energy. Another technology whose beneficial uses we could never quite untangle from the harmful ones. Discuss.

peter wang
Mic drop. Yeah, he's completely right. I did this podcast with a16z Yes. And I said actually, I don't think there is such thing as data. There's only frozen model and I stand by that statement.  I think our metaphysical approach to data, the Mughals will do the Muggel things to say the muggel things but I think as data practitioners, we should be extremely clear as to what it is we're doing here. Every single datum that you collect is the result of a tremendous amount of processing through the DSP through the hardware, through the software, all that stuff before it even ends up In some CSV, that is probably named wrong.

hugo bowne-anderson
So delimited issues that nothing can figure out.

peter wang
But before we get all waxing poetical about the cybernetic future, for a moment, let's consider the actual present, which is a bit bit off. But the reason I say that so metaphysically that we have to be honest with ourselves is that if as practitioners we don't hold the line, then we will never be able to convince the business users about the right paradigmatic frame to think about this with and so I really do stand by that framing, I agree with a Maciej as well, that it's the data is oils is precious thing to be captured, defended. And oh, these users want to hold on to their own data and is private. So you can't hold on to data. Because most brilliant thing ever said about information information is a verb, right? Information, my whole thing my data is just frozen model is really a riff, it's a corollary on that statement. Information is a verb, information is a difference that makes a difference. So is the number three data depends on who you ask, depends on where it came from, depends on what someone's going to do with it. The idea that there is this objective, distilled thing, so you get a little cup, and I have a number three in it, I have a piece of data, right? No, you don't. It's just the number three. Data is actually the statement about the sensemaking system, and a decisioning system. And in the conjunction of those two things, one might detect some resonant patterns that you can then schematize and say, this is the data flow between the eyeball and the muscle. But if you take the eyeball out of the equation, take the muscle of the equation, it's just some random electrical spikes doesn't mean anything. So this is the kind of.... I like for people to take a more transcendent view metaphysically of what data is, it's all it's just numbers, unless you actually have a sense of where it came from, and how and where it's going and why. So it's one of the Don Draper's thing about happiness, happiness, you know, happiness is the moment before you need more happiness. It's like data. Data is the thing is knowledge just before you're confused again,

hugo bowne-anderson
right? And actually, Cory Doctorow has some great articles on what he calls the half life of data and actually has a premise of how addicted social media is itself to data collection due to the incredibly short half life of data.

peter wang
And the dangerous thing about that, just as a side note on that, it turns out the human mind is very plastic and human behavior is incredibly easy to condition because we're just we're sick, we're still animals, right. So, the world, the entire system of the Western world, the mass consumer world, it is optimizing to make and condition people that are more predictable, that are more homogeneous in their consumption patterns in their designs back

hugo bowne-anderson
to Henry Ford as well actually.

peter wang
any color you want as long as it's black, but Noam Chomsky talks about this with mass media, and yes, and Manufacturing Consent. And what we do is we then conditioned people to look for, as if novelty, as if difference, but there's distinction without a difference. Which jaunt like which the sneaker, there's people who are really obsessed with sneakers, and like the vintages of sneakers, released and all these things, and and it's they're all literally made the same factory as like the $5 Chinese knockoffs. And there's distinctions difference. And we're conditioning consumers, conditioned people to be consumers of lots of distinguished aesthetics that have no difference in the fundamentals and substance. And if you just basically eat that kind of sugar all day long your whole life, ultimately, you end up with a deficiency of meaning. Because actual meaning comes from an embodied consequential set of decisions and relationships, you can't be in right relationship or meaningful relationship with objects that have bolted on esthetics to make you crave the next object. That's just not how it goes. So you end up with this vitamin deficient vitamin meaning is going to be deficient for you. And I think about those sad picture you'd like the fish of the oceans that have eaten all the little microplastics in their bellies are full, but they have no nutrition. And this is essentially what we've, what we're doing over and over again, with the bad uses of data powering the monstrous like engine of consumer capitalism. We're just shoveling more stuff into more people's faces and eyeballs. And we're at the same time trying to condition those eyeballs to expect the same kind of knowledge and that is the system of the world that's quite broken. That's what my friends I called Game A right and the only reason this engine does this, if you maybe people here at listeners here have read, I would imagine many of them heard about the concept of the paperclip optimizer, right? What if you have an AI and it go It's super hyper intelligent and we tell it to go make cheap paper clips or make it really cheap to make good paper clips, and then starts optimizing at some point it basically goes off the rails to decide that the most efficient way to do this is actually kill all humans. We already have that, right the modern system of the world create disposable all sorts of stuff burning up the planet, polluting the oceans, killing off all sorts of biodiversity. And to do what it's not paperclips, but it's 100,000 Different kinds of sneakers, which no one needs. So this is the kind of thing that like fast fashion. There's just been the photos of the places the landfills are having to open up in South America and I think parts of Africa to just dump clothes that were made by sweatshop labor in Southeast Asia. It all of it is to do what it goes, it cycles through the US, cycles through the hot tropics, and the other places come back out, ends up dumped to the global south somewhere to d  what to make some number in a spreadsheet, tick up to show quarterly revenue growth. So some analysts will say this number should tick up because they hit precisely their earnings report. That's again, a really rather flawed way to run human civilization. Anyway, that was a bit of a diatribe. But--

hugo bowne-anderson
I love that you mentioned Game A, because that is where I wanted to go to at some point. Also, if you have heard of the paperclip maximizer great. If you haven't, I think probably Nick Bostrom, his book, super intelligence is one of the places you can, I don't know, Bostrom created that thought experiment, but definitely he, he made it relatively famous. So I actually do want to talk about Game A, we've got somewhat abstract and metaphysical in this conversation. I love it. So I'm actually we might lose some people, but I actually want to lean lean into it for the people who are still here. And I think it's important enough to discuss if you're interested in the ideas that we talk about with Game A, I definitely suggest you look into the work of Jordan Hall, or is it Jordan green Hall these days? I'm sorry, but he's Jordan Hal. And he was on the Jim Rutt podcast. Okay. Yeah. And you were on there once you should go back once. And also Daniel Trachtenberg has some interesting stuff on this. But there are communities waiting, we can include some links in the show notes as well. I'm going to paraphrase some of what Jordan Hall said on the Jim Rutt show, probably quite badly. But essentially, they discussed how a lot of what we have today emerged from when societies were at the band level. So below the Dunbar number below 180 people or something along those lines. And we've developed a bunch of collective intelligence tools, what John Vervaeke, who I encourage everyone to check out,  calls psycho technologies, but a collective intelligence toolkit that tried to solve a lot of the issues and problems we had and have as a community. The first three problems are how to survive in nature, how to survive competition with other groups, and a lot of the time want to actually win that competition not merely survive. And third is how to survive internal defection. This actually comes back to tragedy of the commons free rider internal defection, I encourage everyone to check out the definition of multipolar traps in an incredible essay called meditations on Moloch on slate star Codex, which is with respect to the Astro Codex 10. It is now exactly what's on substack Wait, that's for another conversation by another Congress, by the way, right? So Game A was a collection of all these technologies to solve these very important problems. And these technologies include society and identity, settled agriculture, military hierarchy, which now plagues corporations, and education systems. Competition, finite Games is a technology that was created in order to solve a lot of game A problems, literacy, numeracy, market based societies, feudalism, capitalism, all of these things was things developed to to solve game A, now losing my voice slightly, but that's because I'm getting so excited. The idea was that essentially, Game A would work to a certain extent, but it had problems, then societies would collapse, right? The Game A problems that we encountered were the inability of society to actually police defaction from the bottom up in the context of complex human behavior over a long period of time. Okay, so in the fall of the Roman Empire, we saw a lot of internal defection start to crop up. The second problem was the inability to maintain complicated infrastructure. Similarly, in Rome, maintaining aqueducts and roads and this type of stuff. As a society grows, as you build more and more complicated stuff, you get diminishing returns on what it actually provides for you, and you have a maintenance issue. The third of course, is invasion and enemies and perhaps Imperial Rome, the people at the German border, we can view as that. Now, the thing about evolving through collapse is we learned from previous iterations of Game A right now, what we need for that is for collapse, not to not be global. Right. So Game A has a fourth problem, which is the problem of globalized exponential technology. And once again, Joe Rogan's recent interview with Daniel Schamchtenberger and Tristan Harris Can you can watch that learn a lot more about these but the exponential technologies such as what we see in social media, AI, drones, gain of function research as we've definitely seen recently. So the problem now is that if we have of a civilizational collapse Game A people says there's a high chance and it's a plausible hypothesis that this will actually be global, so that we need a new game. And this is what's referred to as game B. We don't know what it is, but we know certain characteristics that might have. And that's why I actually think open source technology provides a wonderful example of things that could come out in game B. So we want more infinite games is one thing. I'm wondering... my question for you but feel free to answer any other things that come to mind from this riff is, what would data science look like in Game B? Or is there an alternative to the way we practice data science today to make it applicable to a different type of system like that? And is there anything you want to add to my description then as well, I suppose?

peter wang
the way I came to some of this and all, but I think you did a very good job of explaining these concepts. There's a lot. We talked about the scale and scope of civilizations and like the current situations and blood, what Daniel likes to call the kind of the global meta crisis, like our ability to resolve crises as bad. And then, for the first time in human history, we have one single global civilization, that whether it's suitcase nukes, whether it's gray goo, whether it's CRISPR, whether it's whatever, there are a lot of things we're in the middle of pandemic, all sorts of stuff can happen that affects everyone. So in the in history, there have been collapses of civilizations, but they've been like, oh, China's regressed a little bit, or oh, there goes the Incans, as someone else's somewhere else doing something, some other people somewhere else are doing things. So there's a... but now we have a global civilization. And the stakes are much bigger. And there's many more ways for complex interplay of things to cause all sorts of horrible stuff. So we don't even have the capacity to solve those problems. And moreover, a lot of the things that we've built through the medieval institutions to now we're like actually making those problems worse, but we're putting things in our own way to solve those problems. And so Game B is everything that humanity's been doing for the last 10,000 years, things that we think are reasonable approaches, like using competition to incentivize people to do whatever, or always building more technology because it's always good or getting more energy that's always good, or whatever might be all of these things that didn't, you didn't have to think about, okay, I have do a boundary integral over the entire volume of the earth. And overall, like our eight and a half billion souls, no one's ever had the responsibility or needed to do that integral before now we have to because everything we do almost is global scale. So game A, that game is coming up against its hard limits. And part of what makes it hard is also that it's not just one thing, like, oh, well had faster computers, or Oh, if only we could do that. So we'll have clean energy. There's no single thing. It's a complex problem, which means lots of things are intertwined together. So there's no silver bullet that solves all the problems. So the existing orders breaking down. And the theory is that the people who are affiliated with Game B, the theory is that we will see levels of collapse happening. And it's not like instantly overnight, it's gonna be some dystopian thing and everyone dies, what's going to happen is as these things fall down, then we're going to see ourselves regressing to authoritarian regimes, we're gonna see many 10s, or maybe hundreds of millions of people dying of starvation, dying of various natural disasters, dying from wars that come over food and water because of climate change, all sorts of kinds of things. So the regression of human civilization, the decrease in human liberty, that decreased our ability to do science, all these things will start falling down. The system needs to be reformed. Now the problem is how the hell do you reform the entire system of the world? Right with a total global 100 trillion dollar GDP with however many 1000 1000 nuclear warheads and how many you are whatever, like everything we do as a world... 8 billion souls? How do you reform that one of the points that is quoted on the gayby wiki is by Ilya Prigaljin, who is a Nobel Prize winning physicist and he said, what a system is far from equilibrium, small islands of coherence have the capacity to shift the entire another person articulated this a little bit is Bucky Fuller inthe trim tab concept, right? Which the dude Well, I think a Golden Globes talked about. But anyway, so there's this idea here is game B is to figure out can we build non hierarchical bottom up self organizing approaches to explore and build these islands of coherence working groups in economics, currency and monetary theory imagined the future of cities, political meta modernism? 

hugo bowne-anderson
Can you define coherence, as well?

peter wang
I define coherence as something that had that can maintain its own metabolism, right, that there's a homeostasis that when things try to push it with these trying to come at it from outside and push it out of a pattern. it can restore itself into that pattern. And that pattern has a like a standing wave. It's a It's, gosh, I should better answer this question.

hugo bowne-anderson
Complex Systems can be coherent, so maybe a humming birdt is coherent in the way that a Boeing 747 Isn't? Is that an example?

peter wang
 No, that's there's different there's an emergent order versus a complex machine. I guess the concept here of coherence is just these things are they're standalone, they can defend an interiority and interior, despite some stuff on the outside, just, you know, some level of disorder on the outside. Yeah, coherent doesn't necessarily have to mean like in the Cynefin sense, complicate this is complex, as opposed complex, you can have complex systems that have cohere, and your whole body is a complex system, but you have coherence, when your brain is going to epileptic seizure, it doesn't have maybe it's actually too coherent. So maybe that's a poor example. But in any case, the point is, the idea of a game B is for people who are concerned this problem who have the same perspective on game, A, the system, the world, following these collapse modes to get together and form working groups on all these different aspects of what makes a human civilization possible. So that is economics. That's agriculture. That's meaning, that's families, that's culture, that's law, all of these different kinds of things. And so you'll find people who are working on permaculture and sustainability, people think like Zack Stein, he's an affiliate, he's in the game B orbit. And he has this book, education and time between worlds, right? How do we actually teach people, children and adults and everyone, what does education, lifelong education look like their souls working on 3d printing and technologies to build in a low impact way. So you build structures that are durable, but then end up creating all sorts of externalities that are negative for the environment, they're in all these kinds of things, are people working in this game B space. Now, the way all that being said, the way that I got involved in thinking about these things, was when I had the revelation that our open source, human ecology and human ecosystem around the Python data movement, like scipy and all that, of course, I had the realization that the economic value created by this small group of people, relatively small group of people, was absolutely astronomical. And so the concepts of modern capitalism came around through industrial age through through better organization, bookkeeping, and the rise of cities, then to through yeah, pre industrial and then industrial structures, a lot of these things where you can take something like capital, apply it to labor and get some much bigger output out. Capitalism says, look, the surplus, the allocation of surplus should go to the people who provided the capital, should have a bigger say, in how we allocate the surplus, and what we do with it. That's one of the core tenets of capitalism. And the issue is we have a new kind of thing now, which is not labor, but human intellect that provides vastly more amplification than Capital. One of the company provide a laptop and an internet connection. Okay, that cost a few $1,000. But then you get one really bright dude or gal, and you know what, they've just produced code that shifts the productivity of millions of people. So we have to have a different conversation about what attribution of economic surplus looks like. And in fact, if you consider if we look at this powerhouse of open source nerds, who collaborated with each other in a gift economy, and a participatory--- it is as if you think about old school tribal culture, people just nerding out with each other. That's what it was, then we there are conflicts, and there's some adjudication that had to happen. And not everything worked out. But for the most part, it was a very free for all. It was an experiment in gift economies and participation cultures. And guess what happened, it produced the software that literally powers all of the alpha in the world, basically, on a go forward basis. If we have that thing, we have such a powerful human energy, human ecology, it produces this kind of economic lift. If on the basis of this, we cannot build a new economic and new sort of institutional order, then we're totally hosed.

hugo bowne-anderson
I love that you framed it as gifting economy and because in another way, maybe it wasn't conscious, but it was a reaction against all the Fordism and capitalism and corporate hierarchy. It's antithetical to that entire system and stepping back from that frame and reconfiguring how we build things together as people and co-evolve together.

peter wang
It didn't start off as some kind of Marxist rebellion. In fact, I think Travis is a little maybe a little horrified he he's not horrified at the collaboration aspect but he's a very He's very much a market like you Hayek and all these others like He's very much a market a market libertarian but I think of course he knows better than anyone like this that the value of this gift economy and the collaboration and all these things there is there's like the best way of describing this as it hopefully there's not a spoiler if people haven't seen the movie Monsters, Inc. Okay, mute the next maybe 30 seconds because I'm going to give you the spoiler those who have seen it may remember Have you seen it?

hugo bowne-anderson
I haven't seen it, but I'm okay with a spoiler. Okay.

peter wang
The spoiler is the reason why these monsters go into people into little kids bedrooms at night and scare them is when kids scream, then like the outside of the door portal, the monster goes through it to go into a bedroom to scare a kid. There's a little thing that basically captures energy from the kid's fear and they bottle it up and that energy is like this the energy that powers the monster civilization. Okay, but what, at the very end, the cool thing is, they act goofy, these two monsters they don't want to scare this poor girl. They act goofy. And she starts laughing giggling with delight the energy and that goes out that is just absolutely blows up their energy collection thing. And they're like, holy shit, joy and happiness can power civilization too. And okay, spoiler over now that for me is like the most succinct of course Pixar nailed it.  I've got no problem with money as a way of attributing karma. Absolutely. When it becomes just paper games for burning up the world, that becomes a problem. And that's when we move to fiat. And we move to electronic debt currency, that we really created some problems. That's actually where this stuff really has gone off the rails. 

hugo bowne-anderson
And I just want to make clear, I'm not anti market or anti capitalist at all. I think they're, you know,

peter wang
I am a refugee from a communist country. I like the market absolutely here. But that's not where most of the financial constructs sit. The Convention has to send the plane above.

hugo bowne-anderson
And competitive markets are better than markets with monopolies, which we're seeing more and more well,

peter wang
but it bears repeating. The earliest capitalists were monopolists because they were like competition is horribly inefficient. Why would you build two telegraph systems, we have one perfectly good Western Union servicing the entire world where one good one Bell System servicing all the countries. So then we take that when you go back and look at the trust busting and stuff, and Teddy Roosevelt, they put capitalism and monopolists together one sentence all the political cartoons, they were all basically a bunch of just money grubbing fat cats that were looking to extract because they have the capital I built the railroad or I built the telegraph network, of course, I get to charge whatever rent I want. So people nowadays only like the Reagan Thatcher rebranding of all this stuff. Do people get markets and capitalism really mulled together, but China is definitely a socialist, communist country. And they have a lot of healthy markets. And here in the United States, we have markets and we have capitalism doesn't have to be capitalist, we have very significant captured cartels and whatnot here, they don't have healthy ... And yet still capitalism over here. So anyway, but to bring this back to the game B concept, why how open source led me to game B's thinking was really around this idea that if we have, like we have now it's like, Scott, it's like, though, Sally and Mike are like, going through that door. We've just now seen that laughter can just massively power all the stuff. So I'm just like, Oh, shoot. So then what else can we how can we go from here to see if we can't take this dynamic and scale out crowdsourcing participatory stuff, downscaling and going against the Koshien theory of the firm? Or yeah, like all these other things, can we build smaller, more agile things that have people working in small groups high meaning high trust, building valuable things that then sit in a network of other people, and the whole thing becomes a much more vibrant, and actually just as economically powerful, if not more economically powerful system, than the game A sort of way of structuring the world. And the really cool thing is writing into all of these firms on the Trojan horse of this grassroots data and AI revolution.

hugo bowne-anderson
Amazing. So how can listeners get involved, learn more about these concepts?

peter wang
open your mind to the possibility that if you're doing data science, maybe you have a role to play in the revolution, if you think the world is wrong, and broken in so many horrible and interlinked ways, recognize that there's a way out the way out is to actually find other people who agree with you, and then listen and learn more about other ways of framing and thinking about this stuff. But ultimately, we're not going to get from here to there without doing a lot of great...building economic value, but the manner in which you build that economic value significantly sets the tone of what happens next

hugo bowne-anderson
We wanted to talk about cybernetics briefly as well.

peter wang
I just I only think about the cybernetics thing was just that I think people should use the word cybernetics more. Because the cybernetics is really about closing the control loop. It's not just making predictions and sticking them on a PowerPoint. When Norbert Wiener and others pioneered the field of cybernetics and these ideas, there was no PDFs right? So they're really this idea of active control, active guidance, learning from the environment, respond to the environment, building models, that gets smarter that in response to a complex environment, all of that is really cybernetics is control theory, right? And so making all of our organizations and all these human systems as transparently cybernetic as possible. So we can evaluate when they're doing well, when they're not doing well, when they're doing the right things when they do harmful things. Right now there's just it's so loosely coupled, right? It's again VP shooting from the hip most of the time. The reason I like to use the word cybernetic versus AI or machine learning, both of those things really tend to, what do they do? Just like the whole thing about calling data oil and training data as being precious when really data is the ephemeral thing that exists when there's a connection between sensing and cognition. That's information, right. It's the state of the sensor and the cognitive or being in conjunction with each other having coherence. So cybernetics is important for us to not think about intelligence being abstracted out and put in the machine, because that's actually deeply disempowering and inhumane way to approach the world. The more that we as data people and practitioners, the more that we humor, that kind of positioning, the more that we are, we're accepting a frame that says machines are intelligent. So we don't have to think about it the machines fault, the machine decided the trolley problem, I'm sure was fine, I'm sure the output is the best possible output, we could have had, because the machine figured the trolley should go over this way versus that way, we really have to push back on this concept, because the actual things that we need to do as practitioners are nuanced, the actual decisions have to make are in a gray zone a lot of times, and it has to be, we have to pull organizations kicking and screaming into the conversation around understanding the ethics and implications of what they're doing. If they can pay somebody to tell them, it's an off the shelf ethical system, it does the decisioning, it's at fault, if something goes wrong, the more we let again, these VPs want to shoot from the hip, just go and implement AI from the hip, the worse the world is for everyone, because they will then the immediate consequence of that is they will then put in legislation and other things that changed the competitive landscape to where it's a race to the bottom, all companies have to do it this way. Any company that tries to do the honest thing actually ends up getting hosed because now their decision makers are now responsible for the ethical outcomes, right? So you can absolutely see this race to the bottom, unless all of us as practitioners really drive home, this framing, this paradigm that we are building predictive systems were built putting action things in place. And this is us, we are doing it, no one else. There is no AI ghost in the machine that just figured out the right thing to do. We trained that fucking AI, right, we sat there and told it, this is good. And it said that is good. I'm gonna deny these loans. So I'm gonna go and arrest those people. Like we did that. And we have to take responsibility for it. And the problem with game A, and this is really back to the principal agent problem. Not only has the system, the medieval institutions of nationalization, and the joint stock corporation evolved to what it is now, the system of game A has is all about alienation. It's all about you are among people. Marx was not wrong about this point, though. I will say that, but he was more about alienating labor great, but this guy is alienating it alienates everyone, we have absentee ownership with absentee ownership for most corporations, right? And so when you have owners are alienated, the consumers are alienated, the workers are alienated. Who the fuck owns anything? Where's the ownership? Where's the courage to say I am responsible, right? So around these automated decisioning systems, we all as a practice as a movement of practitioners, we actually have to draw a line in the sand and say, the buck stops here. Like we are going to actually be a point of accountability about decision making in this below. And I think that as a demographic, as demographics change, as boomers aged out from their advanced positions, and new generations of people come in, there will I think that I like to think that my generation has people who are willing to step up to the plate and bear that mantle.

hugo bowne-anderson
also I love that one. I'm gonna paraphrase. But one of your statements was we need as data practitioners to drag these organizations like out of these patterns and out of these deeply harmful frameworks. And I also all your data scientists and data analysts and machine learning engineers, and deep learners or whatever you call yourself out there, we're actually all in incredible position currently in the labor market to make certain demands and labor market on the demand side is hot right now. So perhaps don't take a job at all we can try to make not suggesting unionization in the classic form, but we are in a position to make demands. I also, I wasn't going to go there. And I said, go look at Slate star Codex. But seeing that you mentioned the race to the bottom, I thought it might be good to wrap up actually giving the definition of a multipolar trap, which defines so much of what where we all these days and it is an abstraction or a generalization of the Tragedy of Commons such as factories polluting a river of the prisoner's dilemma in which defection is better irrespective of anyone else's choice of the free rider problem where people are just lazy and taking benefit from other people's work and a generalization of the race to the bottom. It's important to note that below the Dunbar number when we're in the band level that it was actually quite easy to police these things. So it's the scale of society which makes it difficult but the definition of multipolar trap is "In some competition, optimizing for X, the opportunity arises to throw some other value under the bus for improved X, those who take it prosper, those who don't take it die out. Now, this is key. Eventually, everyone's relative status is about the same as before, but everyone's absolute status is worse than before." And I think we're all in a position, at least as part of this data revolution to start thinking about how we can create an incentive system which doesn't result in these multipolar traps.

peter wang
Yeah. And I think actually, maybe not unionizing. And creating a Union of data practitioners is quite difficult, but at least creating professional society, where there are some of these things that actually we codify and talk about. That's something that has been on the back burner for me. So they have wanted to do for years now. And I think it's yeah, maybe we should actually kick it off in 2022. But that's

hugo bowne-anderson
a great idea. Anyone who is interested, please reach out to PETA and myself on Twitter. Is Twitter. The best place to say hi to you, Pete? Oh, sure.

peter wang
Yeah, my DMs are open P Wang

hugo bowne-anderson
playing at p Wang.

peter wang
Yeah, right. It's a P

hugo bowne-anderson
Wang at Hugo bound. And, Peter, we've had many conversations over the years. None quiet as wide ranging in there. Oh, no, actually, that's not entirely true. But this is one that I'm incredibly grateful for. And thank you so much for your time.

Unknown Speaker
Thank you for having me on. This has been fantastic. Really appreciate the opportunity to go all over and connect all these different dots. Absolutely. I think I don't think I've really talked about some of the game B stuff and how that connects the open source stuff, really in a public setting quite like this. Fantastic. Thank you for

hugo bowne-anderson
absolutely


Transcribed by https://otter.ai