Cataloging a year of blogging: cancer and biology

Welcome to 111101111.

Another year has come to an end, and it is time to embrace tradition and reflect on the past twelve months. In fact, I will try to do one better and start a new tradition: cataloging a year of blogging.

Last year, I split up the 83 content heavy posts of 2013 into nine categories in three themes: established applications of evolutionary game theory (ethnocentrism and the public good; and mathematical oncology), expanding from behavior to society and mind (representations and rationality for replicators; feedback between finance & economics and ecology & evolution; and, learning, intelligence, and the social brain), and envisioning the algorithmic world (proof, automata, and physics; natural algorithms and biology; fitness landscapes and evolutionary equilibria; and, metamodeling and the (algorithmic) philosophy of science). In 2014 there was a sharp decrease in number of posts with only 44 articles of new content (and the 3 posts cataloging 2013, so 47 total) — this was due to a nearly 4 month blogging silence in the middle of the year — but a quarter increase in readership with 151,493 views compared to 2013’s 119,935 views. This time, I will need only two posts to survey the past year; this post for the practical and the next for the philosophical.

MathOncoFor me, the year was distributed between three cities, the usual suspects of Montreal and New York, and in October I moved down to Tampa, Florida to work with David Basanta and Jacob Scott in the Intergrated Mathematical Oncology department of the H. Lee Moffitt Cancer Center and Research Institute. A winter without snow is strange but wearing shorts in December makes up for it; plus the sunsets over the Gulf of Mexico are absolutely beautiful. Unsurprisingly, this move has meant that the practical aspects of my focus have shifted almost completely to biology; cancer, in particular.

This post is about the biology and oncology articles that made up about half of last year’s content. Given the autobiographical turn of this post, it will be (loosely) structured around three workshops that I attended in 2014, and the online conversations and collaborations that TheEGG was a host to.

Computational theories of evolution

    I believe — and repeat like a broken record player — that the methods of theoretical computer science are a neglected tool (compared to the tools of physics; statistical mechanics, in particular) that has a lot to offer biology. In particular, I think that cstheory is essential for understanding learning, evolution, and their interaction. One of the most interesting topics for me in this area is the Baldwin effect (Baldwin, 1886; Simpson, 1953), which fits under the broader framework of phenotypic plasticity:

  1. Phenotypic plasticity, learning, and evolution (February 4th, 2014)
  2. Phenotypic plasticity is not only for the aspiration of applying cstheory to biology, but also one of the main to-improve-on points for the modern evolutionary synthesis. It is also of great interest for studying cancer, although I have not yet written much on that connection. Here at Moffitt, Dan Nichol is doing a lot of thinking on phenotypic plasticity — especially bet hedging — and at times taking the algorithmic perspective by thinking about how and what cell cycle switches compute (Cardelli & Csikász-Nagy, 2012). Hopefully I will convince him to contribute some guest posts to TheEGG in 2015.

  3. Misleading models: “How learning can guide evolution” (February 7th, 2014)
  4. Given that phenotypic plasticity and learning are sore points for the modern synthesis, it has been studied extensively. However, some of the old and celebrated models (e.g. Hinton & Nowlan, 1987) do not hold up well when peered at through the algorithmic lens. In fact, I think they might be completely misleading; attributing a ‘speed-up’ to an error in counting on the part of the modelers.

  5. Evolution is a special kind of (machine) learning (February 14th, 2014)
  6. To avoid such errors, it is important to have a good formal model in which to look at evolutionary dynamics. Since there is interest in incorporating (or comparing to) learning then why not adapt an existing model from computational learning theory? This is precisely what Leslie Valiant (2009) did and thus gave cstheorists a formal invitation to evolutionary biology.

  7. Computational theories of evolution (March 16th, 2014)
  8. This invitation was taken up by cstheorists, physicists, and biologists at the Simmons Institute’s workshop on computational theories of evolution. An event I had the please of attending between March 17th and 21st in Berkeley; my first time visiting California. There was a wide range of topics covered and perspectives offered, and although my conference notes are extensive, I have only posted this introductory article and one follow up:

  9. Algorithmic Darwinism (March 25th, 2014)
  10. Leslie Valiant’s algorithmic approach to evolution was a major topic at the conference, with 5 different presenters discussing the model and their results or extensions. However, I thought that Valiant’s name of ‘evolvability’ conflicted with the more common use of the term in biology; a conflict that lead to some confusion during the workshop, given that several of the other attendees spoke on evolvability in the more traditional sense. In the above article, I suggested ‘algorithmic Darwinism’ as an alternative and advocated — along with Chrisantha Fernando during the workshop — for using the model as a lower bound for what is evolution can achieve without the phenotypic plasticity mechanisms of the sort we see in the Baldwin effect.

    Toward the end of the workshop, I presented my work on the complexity of evolutionary equilibria (Kaznatcheev, 2013) along with some approximability results that I have not published yet:

    I’ll be updating my evolutionary equilibrium work on in the following months, so you should expect more posts on this topic in 2015. But if you can’t wait then want to watch all the great talks from the workshop; there is a YouTube playlist of them. Let me know if you want me to write more about a specific topic that was discussed.

These 5 posts had a corpus of around 7.8 thousand words and garnered around 10.0 thousand views

Ecology and evolution of cancer

My second workshop of 2014 was at the Mathematical Biosciences Institute of Ohio State University from September 15th to 19th on ecology and evolution of cancer.

  1. Approximating spatial structure with the Ohtsuki-Nowak transform (February 26th, 2014)
  2. From heuristics to abductions in mathematical oncology (March 12th, 2014)
  3. My talk at the workshop was structured in two parts. First was my classification of four types of models, of which three are from 2013 and although the fourth category of abductions was suggested right away by Ishanu Chattopadhyay, I didn’t fully incorporate it into my thinking until March of 2014. This part was the more popular one. The second part concentrated on my work with David Basanta and Jacob Scott on edge effects in solid tumours (Kaznatcheev et al., 2014). Although most of the work on this project was done in 2013, and my preliminary explorations of the Ohtsuki-Nowak transform date to 2012, there was still more thinking to be done this past year.

  4. Colon cancer, mathematical time travel, and questioning the sequential mutation model (September 16th, 2014)
  5. Experimental and comparative oncology: zebrafish, dogs, elephants (September 18th, 2014)
  6. Ecology of cancer: mimicry, eco-engineers, morphostats, and nutrition (October 9th, 2014)
  7. Stem cells, branching processes and stochasticity in cancer (October 25th, 2014)
  8. Much like with the 2013 workshop on natural algorithms and the sciences, my goal was to produce a list of articles summarizing all the talks. Unfortunately, my will power is much higher in prime-number years, so the project is incomplete but this means that you have more posts on the ecology and evolution of cancer to look forward to in 2015.

These 6 posts had a corpus of around 9.0 thousand words and garnered around 2.5 thousand views

Viruses in cancer

    Before moving down to Tampa this past October, I had visited Moffitt twice. During the first visit, we put together our basic results on edge effects. The second was for an annual tradition at the integrated mathematical oncology department: a hackaton/workshop in which four teams compete to model four different (but thematically related) cancer related topics. With the top team being awarded a $50,000 pilot grant to continue their research. In 2013, I was on David Basanta’s team thinking about chronic myeloid leukemia:

    This past year, between November 17th and 21st, I was on Heiko Enderling’s team and the theme was viruses, microbes, and other transmittable vectors in cancer. This was a topic I knew little about, although serendipitously, I had written about the vaguely related concept of transmissible cancers earlier in the year:

  1. Dogs are hosts to the oldest and most widely disseminated cancer (January 24th, 2014)
  2. From H. pylori to Spanish colonialism: the scales of cancer (November 18th, 2014)
  3. Helicobacter pylori and stem cells in the gastric crypt (November 24th, 2014)
  4. As always, it was a great learning experience and we accomplished a lot in a few days. Our team secured first place, and I am looking forward to seeing where the project goes. If the above posts get you excited then you should consider joining the Moffitt team by applying to be Heiko’s postdoc (more info on his site).

  5. Diversity working together: cancer, immune system, and microbiome by Jill Gallaher (December 12th, 2014)
  6. This year, Jill Gallaher — the leader for team microbiome — also contributed a post giving another perspective on the workshop. I am curious to know where they’ll go from here.

These 4 posts had a corpus of around 6.6 thousand words and garnered around 1.9 thousand views

Collaboration outside the workshop

    Workshops are meant to inspire collaboration and seed ideas for future and current projects. But obviously, not all collaboration is from workshops. ThEGG is intended to be a place where we can bring ideas together, and so I’ve tried to encourage discussions and guest contributions here:

  1. Cooperation, enzymes, and the origin of life by Eric Bolo (February 27th, 2014)
  2. Although Eric’s post is not about cancer, I think it is a great point for starting to talk about cellularity and then multi-cellularity. The latter concept is a natural dual to cancer, and thus important to understand. Hopefully I will be able to convince Eric to pursue this thread further in 2015.

  3. Misleading models in mathematical oncology (March 5th, 2014)
  4. Early in the year, Philip Gerlee asked if there is a single landmark discovery that justifies mathematical oncology, Heiko Enderling suggested Michor et al. (2005) as a candidate, and I had to disagree. I definitely think mathematical oncology is very important and insightful, but I am not sure if Philip, Heiko, and I are using the same metrics for those qualities.

  5. Bernstein polynomials and non-linear public goods in tumours (November 7th, 2014)
  6. Is cancer really a game? by Philip Gerlee and Philipp Altrock (December 1st, 2014)
  7. As part of a project that Robert Vander Veldge, David Basanta, Jacob Scott, and I are starting, I reviewed some recent papers on public goods games in cancer (Archetti, 2013; 2014). This prompted an active discussion on twitter and then a joint commentary from Philip Gerlee and Philipp Altrock on the (lack of) usefulness of EGT models in mathematical oncology. This post has one of the most exciting discussion threads of the year, and I recommend reading through it. Look for my response in blog post form in the coming weeks.

  8. Memes, compound strategies, and factoring the replicator equation (December 3rd, 2014)
  9. Although the post questioning EGT was stimulating for discussion, it did not decrease my interest in cute EGT tricks. So I closed off my posting in 2014 by sharing a trick that I’ve found useful in our project on public goods in cancer. The article itself is not related to cancer, and has a spin that relates it back to this posts’ opening topic of evolution and learning.

These 5 posts had a corpus of around 8.5 thousand words and garnered around 2.7 thousand views

References

Archetti, M. (2013). Evolutionary game theory of growth factor production: implications for tumour heterogeneity and resistance to therapies. British Journal of Cancer, 109(4): 1056-1062.

Archetti, M. (2014). Evolutionary dynamics of the Warburg effect: glycolysis as a collective action problem among cancer cells. Journal of Theoretical Biology, 341: 1-8.

Baldwin, J.M. (1886). A new factor in evolution. Amer. Nat., 30: 441-451, 536-553.

Cardelli, L., & Csikász-Nagy, A. (2012). The cell cycle switch computes approximate majority. Scientific Reports, 2.

Hinton, G.E., & Nowlan, S.J. (1987). How learning can guide evolution. Complex Systems, 1(3), 495-502

Kaznatcheev, A. (2013). Complexity of evolutionary equilibria in static fitness landscapes. ArXiv: 1308.5094v1

Kaznatcheev, A., Scott, J.G., & Basanta, D. (2014). Edge effects in game theoretic dynamics of spatially structured tumours. arXiv arXiv: 1307.6914v2

Michor, F., Hughes, T., Iwasa, Y., Branford, S., Shah, N., Sawyers, C., & Nowak, M.A. (2005). Dynamics of chronic myeloid leukaemia. Nature, 435(7046): 1267-1270.

Simpson, G.G. (1953). The Baldwin effect. Evolution, 7(2): 110-117.

Valiant, L.G. (2009). Evolvability. Journal of the ACM, 56(1).

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About Artem Kaznatcheev
From the Department of Computer Science at Oxford University and Department of Translational Hematology & Oncology Research at Cleveland Clinic, I marvel at the world through algorithmic lenses. My mind is drawn to evolutionary dynamics, theoretical computer science, mathematical oncology, computational learning theory, and philosophy of science. Previously I was at the Department of Integrated Mathematical Oncology at Moffitt Cancer Center, and the School of Computer Science and Department of Psychology at McGill University. In a past life, I worried about quantum queries at the Institute for Quantum Computing and Department of Combinatorics & Optimization at University of Waterloo and as a visitor to the Centre for Quantum Technologies at National University of Singapore. Meander with me on Google+ and Twitter.

15 Responses to Cataloging a year of blogging: cancer and biology

  1. Steve says:

    Cool! Are you planning a post on the (half-debunked) Vogelstein et al. paper that’s been making headlines in the media?

    • I wasn’t planning to, since I don’t have a particular passion about that result and because it’s already gotten lots of coverage so I doubt I’d add anything worthwhile. However, I can take a look at it if there is interest. Maybe there is a way to relate it to how metaphors and talk about cancer effects cancer outcomes then I might have something to say. Thanks for the suggestion.

      • Steve says:

        Thanks for the link. Interesting point.

        The cancer paper has what looks like one cool figure, correlating cancer risk across tissues with cell division count. My concern is that Science would not have published it if not for the bogus interpretation that came along with it. Wondering if bullshit hasn’t been institutionalized as part of the incentive structure of science publishing.

        • As you noticed already, I recruited Rob Noble to write a post on a reanalysis of the T&V paper that he did with his colleagues. I am really enjoying the great discussion that emerged there.

          The reason I responded with what you already knew (apart from directing others that might stumble here) was because It was nice to reread this old comment of yours with new eyes. In particular, you wrote:

          Wondering if bullshit hasn’t been institutionalized as part of the incentive structure of science publishing.

          When I first read this a few months ago, I just registered it as a standard disillusionment with the ‘high-impact’ journals (that I share in to some extent but didn’t have any tools with which to think about seriously). But after recently reading, Frankfurt’s On Bullshit, I feel like I am starting to see a philosophical framework in which to think about this. It definitely seems like certain citation and writing styles (even features as mundane as passive voice) in science are presented not with the goal of uncovering or communicating ‘truth’ but with seeming like we do without necessarily having a real concern for it.

          Another topic that would be fascinating to explore. Thank you for planting the seed!

          • So here’s my thought. Saying that science is broken is neither true (in my opinion) nor useful. But there’s a lot to be done and is not like we will perfect this in a generation or two. While science is something done by humans it will reflect some of our imperfections but I am sure we can do better than we are. But medicine in general can truly do with more science, not less.

  2. gabogoren says:

    Hey Artem,

    I’ve been a regular reader of your blog for more than a year now, and decided to ask you somewhat bluntly for an opinion on my choice of degree —undergrad and graduate school altogether, given the university system of my country, Argentina. I’m about to start a 6 year degree in Physics, and am really thrilled to dive into that world. However, each time I come to your blog I find myself doubting a little whether I should switch from Physics to Computer Science. My main question would be: What pros and cons do you see in taking Physics or Comp Science as a first degree in order to develop the tools and mindset of a “theorist”, as defined in this post? Because in fact, when I first read it I thought: this and not something else is what I want for me.

    (This could, actually, become a request for a blog post if and as long as that pleases you, given that you’ve already touched the subject at some point).

    My interests spread widely, but concentrate around complex adaptive systems and epistemology. Where I see a possible application of evolutionary thought, self-organisation, information theory or statistics, I would love to go, be it in Economics, Sociology, Biology or other fields. I can’t stand reductionism and positivism —in general I really admire your philosophical views. My interest has an important ideological drive: I see, or at least imagine, a deep connection between complex systems and the unification of “humanistic” and “scientific” traditions; one between epistemology and an improvement in personal life, and yet another one between these two and the overcoming of systemic oppression in the world (as far-fetched as it sounds, I can’t keep myself from this idea and it’s what guides me most).

    I guess an obvious aspect of the width of my interests is the fact that I haven’t undergone any process of deep specialisation yet, and part of me doesn’t want to accept the fact that such specialisation is inevitable. However, I still feel I want to pursue some sort of “broad specialisation”, something to do with managing different formalisms and modelling methods, while still being able to instantiate those skills in particular biological and social problems: this fits nicely in what you called a “theorist”; in what you called yourself, and that’s why I value your opinion so much. As complementary information, I’m really between these two degrees and no other, partly because at my university the degree in Mathematics is too pure-oriented for what I understand my interests are.

    Thank you for your time and please continue with your excellent, inspiring blog!
    Gabriel

    • I’m sorry to barge in, gabogoren, but I vote for a Computer Science degree! As I see it there are three main ways to implement knowledge of complex systems – to arrive at understanding of existing natural systems, to create and study artificial systems and the third is to control both/ some mix of both through artificial infrastructure. I feel that this third approach is what is best understood through the CompSci lens (algorithmic complexity, intuitive translation of processes into hands-on representations). At the same time CompSci is abstract enough to meet your broad interests, unlike a degree in engineering or general biology. I would also consider computational biology and mathematical economics though, if there are such options at your University.

      Given your interest in reducing what you call “systemic oppression”, I would start early with researching justice systems, legal practice and political systems of the world and their History to avoid idealism that might otherwise undermine the modelling and interpretation process. The goal of making opportunistic behavior unfavorable for an economic agent in a human institution is a tough nut, that has yet to be cracked.

      Good luck in your research!

    • Hey Gabriel,

      Thank you for the kind words. I am sorry for the delay in my response, you’ve asked a very difficult question and I doubt I am qualified to answer — although I did study both physics and computer science in undergrad — but I will try to offer some thoughts. Note that you are already doing an extremely smart thing, which I never did when I was starting out, you are asking other for advice.

      My gut instinct is to encourage you to stick to your decision of going into physics. Especially when you list your interests as “complex adaptive systems and epistemology” (although see more about this later). You will definitely see more engagement with that in physics. Computer science departments are also highly variable, there are a lot of schools where they are very applied and you would not enjoy being in them. It is also more common in computer science to have students that are apathetic to the ‘big questions’ and just care about technology; this is less of an issue in the relatively standardized curricula of theoretical physics. This is a tension, of course, in an apathetic CS setting you will have to sustain your own interests and in the less apathetic physics setting you will have to work on resisting the logical positivist brainwashing (I wasn’t able to, I think for most undergrad I was a pretty standard logical positivist).

      I would strongly disagree with Alexander’s advice of computational biology. I’ve had a bit of experience with computational biology, and I can’t see a clear route from there to learning the skills of a theorist. I’ve written a bit about the difference between the algorithmic lens and bioinformatics (and computational biology), and I’ve been meaning to write more about this. I can’t say much about mathematical economics, since I have no experience with that (but it hasn’t produced theorists out of my friends who studied math and finance). I do agree with Alex though, on that you should study “justice systems, legal practice and political systems of the world and their History”, especially if you can do this semi-officially — try to take a course. I wish I had taken some history or sociology courses while I was in undergrad; just don’t settle for the intro ones (since you will probably hate those).

      In general, I think there are many ways to being a theorist, or something like a theorist. For instance, consider Jacob Scott’s story and his goal of being a connector. He started off as a physics undergrad, served in the navy on a nuclear sub, got excited about radiology and became a medical doctor, and is not finishing a PhD in mathematical oncology. Or David Basanta, who doesn’t consider himself a theorist but I think he has a pretty cool view on things. He started off with an undergrad in computer science, a very applied one from what I understand, worked in industry for a while before going and getting a PhD in evolutionary computing and now working as a mathematical oncologist. This shows you that either initial degree can lead you to the same place as I am (David, Jake, and I work together at Moffitt right now). I will also ping these guys to see if they have more advice to give you.

      Now moving on to one thing that made me worried in your comment:

      I see, or at least imagine, a deep connection between complex systems and the unification of “humanistic” and “scientific” traditions; one between epistemology and an improvement in personal life, and yet another one between these two and the overcoming of systemic oppression in the world.

      I have seen this sentiment expressed in several places (most recently here) and I have never seen it as productive. It has always been contentless and empty, and felt like just an appeal to the “legitimacy of mathematics” or a buzzword soup. The sort of thing managers chat about at an MBA retreat. Of course, you should not take my dismissal as authoritative, since there are lots of people — the Santa Fe Institute most prominent among them — that would strongly disagree with me. However, I think they are wrong to disagree and — to paraphrase Fermat — I have discovered a truly marvellous proof of this, which this comment is too narrow to contain. Stay tuned for some posts on this in the near future, and I hope you will comment on them with an opinion different from my own.

      Again, thank you for reading the blog! I hope this discussion is helpful. Remember, the most important thing in your education is your passion and everyone’s path will be different. Also, now-you and six-years-from-now-you will be very different people.

      • gabogoren says:

        Thank you both for your replies; they have been quite insightful.

        To Artem: I come from an ideological background which is quite different, if not absolutely opposed, to that of a “manager at an MBA retreat”. Above all, because I’m from Latin America, a place where one could say “capitalism never won” (though also, “never intended to win” in that specific sense) and observing the power structure of the world is not a matter of social consciousness but part of our everyday life. So I guess the “discourse of complexity” lures me, but I have some confidence in my skepticism. And of course, what you linked from the IEET struck me as quite devoid of content. Actually, the fact that you brought that up makes me realise that my far-fetched sentence might be easily misunderstood, but to develop further what I meant may exceed this discussion. To be more synthetic, I’d say I have my own baggage (or more correctly, the baggage of my influences and environments) with which I’d like to engage in science and its social and philosophical consequences. SFI is perhaps the utmost example of my relationship with the world of complexity: I find some of their stuff extremely fascinating, but almost always feel suspicious of the way in which they pretend to “make the world a better place”.

        To Alexander: I’m sympathetic of your (and Artem’s) advice on researching actual history and social literature; this is part of what I thought of when I mentioned the unification of “humanistic” and “scientific” traditions. I think there is a lot to learn from the “philosophical sociology” or however one could call it to differentiate it from the more (recent) empirical studies, and feel as somewhat of an inheritor of the Left tradition (even though I can’t decide whether I’d consider myself as part of it or something else). As a consequence of this, I don’t think I would conceptualise the goal of overcoming oppression as “making opportunistic behavior unfavorable for an economic agent in a human institution”, but rather as finding ways to catalyse a change of values. This by no means implies that institutions and economic systems are not worth studying, but it certainly gives a different perspective on the same problem. When thinking about Economics, for instance, I’m really excited about the possibility of studying the restrictions that the mathematical structure of the theory imposes on the paths that the actual economy or state of material affairs can describe.

        Back to the Physics vs. Comp Sci dilemma: if complexity is about extracting structure from a “substrate”, while ignoring its “irrelevant” nature then a computational (or, following this blog’s terminology, algorithmic) point of view sounds more appropriate to me than that of physics, which (even though statistical physics is devoted to such extraction) is always rooted in the same framework. I’m not absolutely sure of what I’m saying but I sense it might be that “ground truth” that you (Artem) have mentioned at some point. Still, physics is all about abstraction too, and I really wouldn’t mind at all studying the actual physics, non-interdisciplinary stuff. I guess I’ll have to wait and see, get a feel of how the different schools work here. I’ll definitely hop from one degree to the other if I feel it would be a better environment. And yes, sometimes it’s difficult for me not being a little anxious, but it’s true that each path is different, things will end up arranging themselves in one way or another and six-years-from-now-me is an absolute stranger. For the time being, there are some nice blogs to read (wink), and I’d love to participate in future discussion if I happen to feel like I have something to contribute.

        • “As a consequence of this, I don’t think I would conceptualize the goal of overcoming oppression as “making opportunistic behavior unfavorable for an economic agent in a human institution”, but rather as finding ways to catalyze a change of values.”

          Well, do you believe that there is a certain set of values that disallows oppression, or do you believe that the speed of change in values is key? You have to always consider how a certain set of rules handles those who blatantly break the rules, those who disguise themselves as following the rules (including those who have misrepresentations in self-construal, i.e. they are even not aware of not following the rules), etc. And it is often the case that intuitively “positive” sets of values are not feasible in that sense in a real society. I’m interested in this question, but here it is a bit off topic… maybe you would write a post elaborating your views on this as of now, and I would leave a comment with possible critique in you blog? (If your blog is strictly in Spanish, you can write in Spanish – I would understand, but I’d still comment in English as my Spanish is not strong enough to produce text about difficult topics)

          • gabogoren says:

            I don’t really have a blog at the moment (the one my account is associated to was a collective failed attempt), but your idea is a good motivation for taking the decision of starting one up. I hadn’t made the effort of clearly identifying my views about sets of values yet in order to present them in a coherent, self-contained way, so your suggestion brings me to a nice, though difficult, exercise!
            I’ve already started to write something on the subject. I can’t promise much, but I’ll keep you posted, in case I get to a presentable text.

            (As a short and maybe useless answer to your first question, I asked myself a while about it and came to the conclusion that I certainly believe in the existence of at least one set of values that “disallows oppression”, at least systematically).

        • Latin America, a place where one could say “capitalism never won” (though also, “never intended to win” in that specific sense)

          I’ve heard this before (like in passing here from Chomsky) but I don’t really understand it. Can you recommend some history to read so I can learn more about this?

          I’m really excited about the possibility of studying the restrictions that the mathematical structure of the theory imposes on the paths that the actual economy or state of material affairs can describe.

          It is not only the mathematical structure that puts restrictions on how our economy proceeds, but our general philosophical commitments. I tried to say something like this in my mini-review of Capital.

          If you feel relatively comfortable writing about it, and if you have some sources to draw upon, I would be happy to invite you to contribute a post to TheEGG about the connections you see between complexity and having positive impacts on our social systems. I might respond with a critique, but it is always good to have a dialogue with a little bit more formal structure than a comments thread. A note: there are a few people already in the guest blogging pipeline (Alex, Sergio, Marcel, and Milo all have posts in various states of ready, for example) so it might take a little while for it to come out.

          • gabogoren says:

            Wow, that’s such an amazing offer! I’d love to do such a thing, as after all it’s one of the subjects which interest me most. Still, as I said to Alexander (and maybe even more than in that case), I can only take it as a big challenge.

            About my statement on Latin America, I was thinking on something a little broader than what Chomsky refers to in that article. As I understood him, he’s referring to the fact that since the new millennium, neoliberalism has been rejected by significant sectors of many South American countries’ societies, leading to anti-neoliberal, “anti-imperialist” governments (and their corresponding neo-Keynesian economic models). This in great part has to do with the economic disasters produced by preceding neoliberal governments (in Argentina, specifically, ) and with .

            My statement referred to this, but also to the general history of Latin America. Starting with the original European colonialism and continuing with the incorporation of the different (and somewhat artificially produced) nation-states to the international markets through export of raw or low added value materials, the region has always been in a dependence relationship with the industrialised world. What I meant to say was that capitalism “never won” the ideological battle, but it “never intended to win” such battle because, as international dependence was always part of “what capitalism was”, it could never convince in such a way as in the industrialised world. I guess the capitalist worldview has been factically separated from national interests in a recurrent fashion. (I’m well aware I’m using “capitalism” in a rather ambiguous way here, but I guess I can leave it at that for the sake of concision).

            Bear in mind, part of this description comes from mild generalisations of what happened to Argentina to other South American countries (as obviously I’m not as familiar with their particular paths as with my own country’s), but I think it’s mostly an accurate depiction. I’d love to point at some particular read, but I can’t think right now of a specific thing that would be particularly helpful and self-sufficient (least in English). Most of what I know comes from high school classes and general (or maybe not so general) knowledge. I’ll keep an eye for it though, ask a little around. Oh, and I’d really be interested on a full-length review of Piketty’s work.

  3. Pingback: Cataloging a year of blogging: the philosophical turn | Theory, Evolution, and Games Group

  4. Pingback: A year in books | Theory, Evolution, and Games Group

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