Do our models get in the way?

We’ve seen quite a few descriptions of an emerging paradigm known as the collaborative commons (CC). But a problem arises when we take another step by extrapolating from that data and then try to prescribe what we need to do in order to create a CC. I.e., we form a model of what the CC should be, and top down we try to implement it. Whereas the technology that enables the CC to grow organically has no apparent need of this top down imposition. To the contrary, it seems more of a capitalistic holdover instead of the middle out way the CC is naturally evolving.

Bonnita Roy has noted that “In a world as diverse in people and rich in meanings as ours, big change might come from small acts by everyone operating everywhere in the contexts that already present themselves in their ordinary lives.” It is quite the contrast from the enlightened heroes figuring it all out from their complex ivory towers which supposedly and hopefully ‘trickles down’ to the rest of us. This seems much more how the CC works in practice. Political and social revolution arises from the external socioeconomic system, the mode of production. Development is accomplished not by having a ‘higher’ model to which one must conform, but by the actual practice of operating within the emerging socioeconomic system.

Jennifer Gidley noted a similar phenomenon in that there is a difference between research that identifies postformal operations from those who enact those operations. And much of that research identifying it has itself “been framed and presented from a formal, mental-rational mode.” Plus those enacting postformal operations don’t “necessarily conceptualize it as such.” So are those that identify postformality via formal methodology really just a formal interpretation of what it might be? Especially since those enacting it disagree with some of the very premises of those identifying them?

The online discussions I engage with on meta-models is representative of this difference. It seems the abstract modeling of the development of the CC is what is operating to create it in a top-down manner. Not only that, what appears to be happening in all cases is that not only does each individual have their own thoughts and opinions on the topic, which is to be expected in diverse groups, we all end up justifying our own take over others. We all seem to be so attached to our own discoveries that we build an edifice and seek out and find supporting evidence to justify it. When confronted with different perspectives or evidence, our first inclination is to see how it fits into our own model or worldview, how we can twist and manipulate it to support our biases. What is there in common that holds us together if we are so closed to taking in new information from other perspectives, allowing them to sit in their own right, their own space, instead of trying to fit them into our own predispositions?

I’m reminded of what Said Dawlabani said, that the distributed network of the collaborative commons follows no ideologies. That it is open source, highly networked and depends on the wisdom of the crowd. I’m guessing that equally applies to our models on trying to create the CC, as we tend to idealize and attach to them. Is our ownership of our ideas more indicative of capitalism that the CC? It also seems that those who are enacting this new paradigm are doing so without need of any explicit theory or model about it. So is arguing about the correct theory even a necessary part of its enactment, as if like capitalism it too needs a top down elite model to implement it? Are our models just getting in the way and actually counter-productive to its natural evolution?

40 year update on memes

From this piece:

“There is not one, but at least four, hereditary systems recognized by biologists today. Eva Jablonka and Marion Lamb lay this out clearly in their 2006 book, Evolution in Four Dimensions, as they walk through the research literature on genetics, epigenetics, behavioral repertoires, and symbolic culture as four distinct pathways where traits are ‘heritable’ in appropriately defined fashion.”

“Specifically, I am thinking of three areas where significant progress has been made during the last forty years: the birth of complexity science in the early 1980’s, developments in the study of human conceptualization and cognitive linguistics since the mid-70’s, and the explosion of digital media in the age of personal computers and later via the internet.”

“Applied to meme theory, this body of tools and techniques [cognitive linguistics] demonstrates that researchers across many fields have found value in the perspective that culture can be studied as information patterns that arise in a variety of social settings routinely and with modular elements that are readily discernible in each new instance. The claim that information patterns do not replicate is contradicted by the evidence for image-schematic structures.”

The neuroscience of creativity

Since this came up in our book discussion or Range yesterday,  something relevant from this article. It’s interesting how the salience network mediates between and integrates two normally one on, one off networks.  And how it is the connections between networks that seems to do the trick akin to the book’s description of how those with range make analogous connections between ideas and domains.

“Three of these distinct brain networks — the default mode, the executive control network and the salience network — have been identified by Dr Beaty and colleagues as being associated with creativity.

“The default mode network is activated when people are relaxed and their mind is wandering to different topics or experiences, associated with remembering past experiences, thinking about possible future experience and daydreaming.

“The executive control network comes into play when you need to pay close attention and focus on something in the environment. It comes online when we have to focus our attention and cognitive resources on more demanding tasks that require us to hone our attention and manage multiple things in our mind at one time, directing the content of our thoughts.

“The salience network plays a significant role in detecting and filtering important — or salient — information. It’s called salience because it helps us to pick up on salient information in the environment or internally. Interestingly, the default mode and the executive control networks don’t typically work together — when one network is activated, the other tends to be deactivated. One thing that we think the salience network might be doing is switching between an idea-generation mode, which is more of a default process, and the idea-evaluation mode, which is more of a control way of thinking. […] More creative people tended to have more network connections.”

The root of the power law religion

New draft paper by me. Update: Published here. The abstract:

A ‘power law’ refers specifically to a statistical relationship between quantities, such that a change in one quantity has a proportional change in another. One property of this law is scale invariance, otherwise known as ‘scale-free,’ meaning the same proportion repeats at every scale in a self-similar pattern. Mathematical fractals are an example of such a power law. Power laws are taken as universal and have been applied to any and all phenomena to prove the universality of this law.

However, a recent study (Broido and Clauset, 2019) claims that “scale free networks are rare.” They conducted an extensive review of one thousand social, biological, technological and information networks using state of the art statistical methods and concluded what the title of their article states. To the contrary, “log-normal distributions fit the data as well or better than power laws.” And that scale-free structure is “not an empirically universal pattern.” Hence it should not be used to model and analyze real world structures.

Consciousness in Humanoid Robots

New ebook from Frontiers in Science. The blurb:

Building a conscious robot is a grand scientific and technological challenge. Debates about the possibility of conscious robots and the related positive outcomes and hazards for human beings are today no more confined to philosophical circles. Robot consciousness is a research field aimed to a unified view of approaches as cognitive robotics, epigenetic and affective robotics, situated and embodied robotics, developmental robotics, anticipatory systems, biomimetic robotics. Scholars agree that a conscious robot would completely change the current views on technology: it would not be an “intelligent companion” but a complete novel kind of artifact. Notably, many neuroscientists involved in the study of consciousness do not exclude this possibility. Moreover, facing the problem of consciousness in robots may be a major move on the study of consciousness in humans and animals.

The Frontiers Research Topic on consciousness in humanoid robots concerns the theoretical studies, the models and the case studies of consciousness in humanoid robots. Topics related to this argument are:
– the needs of a body for robot consciousness;
– robot self-consciousness;
– the capability of a robot to reason about itself, its body and skills;
– the episodic memory in a robot, i.e., the ability to take into account its operational life;
– design strategies versus developmental approaches in assessing consciousness in a robot;
– robot architectures candidates for consciousness;
– symbolic versus neural networks representations in robot consciousness;
– consciousness, theory of mind and emotions in a humanoid robot;
– measurements and assessments of consciousness and self-consciousness in a robot;
– ethical and trust issues in a conscious humanoid robot.

The Map and the Territory

Recent book by Wuppulari and Doria. F___ing Amen man. This would be a good one for discussion. From the Intro by Penrose:

“Is there a global map that can simulate every other map under some constraint? […] If two maps cannot be integrated, is this a limitation of our scientific cartography or is it the nature of the underlying territory itself that prevents us from such an attempt? […] It is safer to let the gaps remain as gaps while we let our maps remain as maps, rather than giving in to the seemingly seductive approach of trading in our understanding and intermingling maps with territory to fill in the conceptual gaps—however, much this may comfort us and appeal to our tastes!”


From the blurb at b-ok.org:

This volume presents essays by pioneering thinkers including Tyler Burge, Gregory Chaitin, Daniel Dennett, Barry Mazur, Nicholas Humphrey, John Searle and Ian Stewart. Together they illuminate the Map/Territory Distinction that underlies at the foundation of the scientific method, thought and the very reality itself.

It is imperative to distinguish Map from the Territory while analyzing any subject but we often mistake map for the territory. Meaning for the Reference. Computational tool for what it computes. Representations are handy and tempting that we often end up committing the category error of over-marrying the representation with what is represented, so much so that the distinction between the former and the latter is lost. This error that has its roots in the pedagogy often generates a plethora of paradoxes/confusions which hinder the proper understanding of the subject. What are wave functions? Fields? Forces? Numbers? Sets? Classes? Operators? Functions? Alphabets and Sentences? Are they a part of our map (theory/representation)? Or do they actually belong to the territory (Reality)? Researcher, like a cartographer, clothes (or creates?) the reality by stitching multitudes of maps that simultaneously co-exist. A simple apple, for example, can be analyzed from several viewpoints beginning with evolution and biology, all the way down its microscopic quantum mechanical components. Is there a reality (or a real apple) out there apart from these maps? How do these various maps interact/intermingle with each other to produce a coherent reality that we interact with? Or do they not?

Does our brain uses its own internal maps to facilitate “physicist/mathematician” in us to construct the maps about the external territories in turn? If so, what is the nature of these internal maps? Are there meta-maps? Evolution definitely fences our perception and thereby our ability to construct maps, revealing to us only those aspects beneficial for our survival. But the question is, to what extent? Is there a way out of the metaphorical Platonic cave erected around us by the nature? While “Map is not the territory” as Alfred Korzybski remarked, join us in this journey to know more, while we inquire on the nature and the reality of the maps which try to map the reality out there.

The book also includes a foreword by Sir Roger Penrose and an afterword by Dagfinn Follesdal.

Decentralized collective intelligence

Jordan Hall of the Neurohacker Collective on decentralized collective intelligence. Sounds a lot how our group works, our collaborations creating something greater than our individual contributions, even though the latter are part and parcel of the process. What happens when we node thyself.

Bezos projects capitalism into space

Yes, space exploration is critical but we need to do it for the right reasons. And Bezos and other futurists want it without awareness or regard for the socio-economic system that has created hell on earth. So dump the earth and take our destruction into space? How about we change our worldview and socio-economic system and do it for the right reasons? And invest most of our time, energy and money into saving this world?

“The saying ‘it’s easier to imagine the end of the world than to imagine the end of capitalism’ is very clear in Bezos’ future imaginings. He is unable to challenge the capitalist system from which he’s derived so much wealth. Thus the only positive future he can imagine involves leaving the only planet habitable to human beings. […] We don’t need space colonies; we need to get rid of billionaires and let the future be decided collectively, instead of letting a few powerful men rule the world.”

Their are alternatives to capitalism consistent with the above. As but one example see “From capitalism to the collaborative commons” in this journal issue.

Rapid Personality Change and the Psychological Rebirth

Informative video on this process. Ofttimes we need to descend into hell before we can ascend into a new life. And this seems the overall process of human development, that for each stage we must go through this spiraling process of dissolution and reorganization. Hence we are far more than twice-born; we are multiply born anew at each stage. It seems though that the further we go in this process the greater the risks and rewards.

Speaking of which, the inaugural issue of Phi Mi Sci will address this issue:

“The inaugural issue of PhiMiSci will be a Special Topic on Radical Disruptions of Self-Consciousness (see the Manifesto of the Selfless Minds workshop). The call for papers for this Special Topic was closed on May 1. Submissions are currently under review. The guest editors of this Special Topic are Thomas Metzinger (Mainz) & Raphaël Millière (Oxford). The expected publication date of this Special Topic is late 2019.”

Book: Range: Why Generalists Triumph in a Specialized World

In his new book, Range: Why Generalists Triumph in a Specialized World, David J. Epstein investigates the significant advantages of generalized cognitive skills for success in a complex world. We’ve heard and read many praises for narrow expertise in both humans and AIs (Watson, Alpha Go, etc.). In both humans and AIs, however, narrow+deep expertise does not translate to adaptiveness when reality presents novel challenges, as it does constantly. 

As you ingest this highly readable, non-technical book, please add your observations to the comments below. 

Albuquerque Brain, Mind, and Artificial Intelligence Discussion Group