Mikah Sargent speaks with David Weinberger, author of Everyday Chaos: Technology, Complexity, and How We’re Thriving in a New World of Possibility about how AI, big data, and the internet are all revealing that the world is vastly more complex and unpredictable than we've allowed ourselves to see and how we're getting acculturated to these machines based on chaos.
Interesting discussion of systems with built in openness or flexibility as a feature. They highlight Slack which has a core product, but allows individual users and companies to add custom pieces to it to use in the way they want. This provides a tremendous amount of addition value that Slack would never have known or been able to build otherwise. These sorts of products or platforms have the ability not only to create their inherent links, but add value by being able to flexibly create additional links outside of themselves or let external pieces create links to them.
Twitter started out like this in some sense, but ultimately closed itself off–likely to its own detriment.
Artificial intelligence, big data, modern science, and the internet are all revealing a fundamental truth: The world is vastly more complex and unpredictable than we've allowed ourselves to see.
Now that technology is enabling us to take advantage of all the chaos it's revealing, our understanding of how things happen is changing--and with it our deepest strategies for predicting, preparing for, and managing our world. This affects everything, from how we approach our everyday lives to how we make moral decisions and how we run our businesses.
Take machine learning, which makes better predictions about weather, medical diagnoses, and product performance than we do--but often does so at the expense of our understanding of how it arrived at those predictions. While this can be dangerous, accepting it is also liberating, for it enables us to harness the complexity of an immense amount of data around us. We are also turning to strategies that avoid anticipating the future altogether, such as A/B testing, Minimum Viable Products, open platforms, and user-modifiable video games. We even take for granted that a simple hashtag can organize unplanned, leaderless movements such as #MeToo.
Through stories from history, business, and technology, philosopher and technologist David Weinberger finds the unifying truths lying below the surface of the tools we take for granted--and a future in which our best strategy often requires holding back from anticipating and instead creating as many possibilities as we can. The book’s imperative for business and beyond is simple: Make. More. Future.
The result is a world no longer focused on limitations but optimized for possibilities.
César Hidalgo has a radical suggestion for fixing our broken political system: automate it! In this provocative talk, he outlines a bold idea to bypass politicians by empowering citizens to create personalized AI representatives that participate directly in democratic decisions. Explore a new way to make collective decisions and expand your understanding of democracy.
“It’s not a communication problem, it’s a cognitive bandwidth problem.”—César Hidalgo
He’s definitely right about the second part, but it’s also a communication problem because most of political speech is nuanced toward the side of untruths and covering up facts and potential outcomes to represent the outcome the speaker wants. There’s also far too much of our leaders saying “Do as I say (and attempt to legislate) and not as I do.” Examples include things like legislators working to actively take away things like abortion or condemn those who are LGBTQ when they actively do those things for themselves or their families or live out those lifestyles in secret.
“One of the reasons why we use Democracy so little may be because Democracy has a very bad user interface and if we improve the user interface of democracy we might be able to use it more.”—César Hidalgo
This is an interesting idea, but definitely has many pitfalls with respect to how we know AI systems currently work. We’d definitely need to start small with simpler problems and build our way up to the more complex. However, even then, I’m not so sure that the complexity issues could ultimately be overcome. On it’s face it sounds like he’s relying too much on the old “clockwork” viewpoint of phyiscs, though I know that obviously isn’t (or couldn’t be) his personal viewpoint. There’s a lot more pathways for this to become a weapon of math destruction currently than the utopian tool he’s envisioning.
This course aims to push the field of Origins of Life research forward by bringing new and synthetic thinking to the question of how life emerged from an abiotic world.
This course begins by examining the chemical, geological, physical, and biological principles that give us insight into origins of life research. We look at the chemical and geological environment of early Earth from the perspective of likely environments for life to originate.
Taking a look at modern life we ask what it can tell us about the origin of life by winding the clock backwards. We explore what elements of modern life are absolutely essential for life, and ask what is arbitrary? We ponder how life arose from the huge chemical space and what this early 'living chemistry'may have looked like.
We examine phenomena, that may seem particularly life like, but are in fact likely to arise given physical dynamics alone. We analyze what physical concepts and laws bound the possibilities for life and its formation.
Insights gained from modern evolutionary theory will be applied to proto-life. Once life emerges, we consider how living systems impact the geosphere and evolve complexity.
The study of Origins of Life is highly interdisciplinary - touching on concepts and principles from earth science, biology, chemistry, and physics. With this we hope that the course can bring students interested in a broad range of fields to explore how life originated.
The course will make use of basic algebra, chemistry, and biology but potentially difficult topics will be reviewed, and help is available in the course discussion forum and instructor email. There will be pointers to additional resources for those who want to dig deeper.
This course is Complexity Explorer's first Frontiers Course. A Frontiers Course gives students a tour of an active interdisciplinary research area. The goals of a Frontiers Course are to share the excitement and uncertainty of a scientific area, inspire curiosity, and possibly draw new people into the research community who can help this research area take shape!
This book explores the interdisciplinary field of complex systems theory. By the end of the book, readers will be able to understand terminology that is used in complex systems and how they are related to one another; see the patterns of complex systems in practical examples; map current topics, in a variety of fields, to complexity theory; and be able to read more advanced literature in the field. The book begins with basic systems concepts and moves on to how these simple rules can lead to complex behavior. The author then introduces non-linear systems, followed by pattern formation, and networks and information flow in systems. Later chapters cover the thermodynamics of complex systems, dynamical patterns that arise in networks, and how game theory can serve as a framework for decision making. The text is interspersed with both philosophical and quantitative arguments, and each chapter ends with questions and prompts that help readers make more connections.
In this episode, Angie talks with human-centric leader, futurist and CEO of Toffler Associates, Deborah Westphal. Westphal shares the history and legacy of Toffler Associates and provides insights into their mission to help organizations understand the dynamics of change, plan their way to the future, and then adapt. Westphal also explains four macro-drivers that are causing uncommon disruption and influencing everything we know about organizations. She explores very important questions and assumptions about power structures, technology, and societal values and advocates for leaders to focus on people, rather than processes or technology.
This episode feels a bit like the interviewer is selling me something instead of enlightening me. I do appreciate here emphasis on human-centric approaches however. This episode focuses a lot on philosophy and approach rather than science and direct examples of applications. Meh…
In this episode, Haley talks with Dr. Mihaela Ulieru, a scholar of distributed intelligent systems, Founder and President of the IMPACT Institute for the Digital Economy, and a Fourth Industrial Revolution champion at the World Economic Forum, where she advocated to include Blockchain among the "Top 10" in 2016. Ulieru talks about the interplay between society and technology and its effects on our humanity. She shares many paradoxical examples for how technology, like artificial intelligence and blockchain, can help us transcend our limitations while also preying on them. Ulieru also urges leaders to educate themselves on the ways blockchain can streamline their business, stating it’s now “a matter of survival”.
Sometimes I get the impression that our hosts in this series can be a bit too credulous when they don’t have the technical background to push back on their interviewees. This episode is a prime example.
While Dr. Ulieru may have some of the technical background to talk about blockchain, I think it’s a bit irresponsible for her to be evangelizing it the way she is without more concrete and successful examples. This interview falls into the trap of many conversations about blockchain and evangelizing it without enough push back on its long term potential.
About 30 minutes in she mentions the Sapien Network as a replacement for social media using blockchain. I’m curious to dig into it a bit to see what it is and how it actually works. Is it or could it be IndieWeb friendly? I don’t have high hopes, but I’ll try to take a peek shortly. Again here she simply evangelizes that it’s the solution to our problems without any discussion about why except to say “but blockchain!”. At present their site says they have 5,800 users.
At about 34 minutes in she also mentions a YouTube replacement on blockchain called Snacked (perhaps I misheard her?), but I was unable to track down such a site with the functionality she mentioned. Here again she states a reasonable problem, and simply states the solution as “blockchain!” without any direct specifics about why blockchain is a good solution and how it works to make a marked improvement.
“For any business that can use blockchain (to improve their processes) and is not using it now, I think it’s a race against time right now, so educate yourself because it’s a matter of survival for your business. Especially educate your leaders.” — Dr. Mihaela Ulieru
Statements like this can be deadly for businesses when they’re done in this sort of evangelizing fashion without any supporting reasoning below it. There is too much blockchain FUD out there, particularly when the technology is over a decade old, and there are very few, if any, real success stories and lots and lots of vaporware.
Organisms live and die by the amount of information they acquire about their environment. The systems analysis of complex metabolic networks allows us to ask how such information translates into fitness. A metabolic network transforms nutrients into biomass. The better it uses information on available nutrient availability, the faster it will allow a cell to divide.
I here use metabolic flux balance analysis to show that the accuracy I (in bits) with which a yeast cell can sense a limiting nutrient's availability relates logarithmically to fitness as indicated by biomass yield and cell division rate. For microbes like yeast, natural selection can resolve fitness differences of genetic variants smaller than 10-6, meaning that cells would need to estimate nutrient concentrations to very high accuracy (greater than 22 bits) to ensure optimal growth. I argue that such accuracies are not achievable in practice. Natural selection may thus face fundamental limitations in maximizing the information processing capacity of cells.
The analysis of metabolic networks opens a door to understanding cellular biology from a quantitative, information-theoretic perspective.
As a species, human beings are barely more intelligent than kindergarten kids. We revel at our place at the top of the food chain, and praise our technological ingenuity but, let’s face it, we’ve barely begun to work life out. We’ve created one directional extractive systems that undermine our own life support systems, like kindergarten …
There’s some interesting philosophy here. It dances around the idea of fitness landscapes, but doesn’t mention them directly, though this is essentially what the article is exploring from the perspective of businesses.
In 1964 Quastler's book The Emergence of Biological Organization was published posthumously. In 2002, Harold J. Morowitz described it as a "remarkably prescient book" which is "surprisingly contemporary in outlook". In it Quastler pioneers a theory of emergence, developing model of "a series of emergences from probionts to prokaryotes".
The work is based on lectures given by Quastler during the spring term of 1963, when he was Visiting Professor of Theoretical Biology at Yale University. In these lectures Quastler argued that the formation of single-stranded polynucleotides was well within the limits of probability of what could have occurred during the pre-biologic period of the Earth. However, he noted that polymerization of a single-stranded polymer from mononucleotides is slow, and its hydrolysis is fast; therefore in a closed system consisting only of mononucleotides and their single-stranded polymers, only a small fraction of the available molecules will be polymerized. However, a single-stranded polymer may form a double-stranded one by complementary polymerization, using a single-stranded polynucleotide as a template. Such a process is relatively fast and the resulting double-stranded polynucleotide is much more stable than the single single-stranded one since each monomer is bound not only along the sugar phosphate backbone, but also through inter-strand bonding between the bases.
The capability for self-replication, a fundamental feature of life, emerged when double-stranded polynucleotides disassociated into single-stranded ones and each of these served as a template for synthesis of a complementary strand, producing two double-stranded copies. Such a system is mutable since random changes of individual bases may occur and be propagated. Individual replicators with different nucleotide sequences may also compete with each other for nucleotide precursors. Mutations that influence the folding state of polynucleotides may affect the ratio of association of strands to dissociation and thus the ability to replicate. The folding state would also affect the stability of the molecule. These ideas were then developed to speculate on the emergence of genetic information, protein synthesis and other general features of life.
Lily E. Kay says that Quastler's works "are an illuminating example of a well reasoned epistemic quest and a curious disciplinary failure". Quastler's aspiration to create an information based biology was innovative, but his work was "plagued by problems: outdated data, unwarranted assumptions, some dubious numerology, and, most importantly, an inability to generate an experimental agenda." However Quastler's "discursive framework" survived.
Forty-five years after Quastler's 1964 proposal, Lincoln and Joyce described a cross-catalytic system that involves two RNA enzymes (ribosymes) that catalyze each other's synthesis from a total of four component substrates. This synthesis occurred in the absence of protein and could provide the basis for an artificial genetic system.
There was a single used copy in the UK for $12.49 and all the rest are $149.00+ so I snapped it up. Should be an interesting read in and of itself, but I suspect it’s got an interesting niche of the history of science covered with respect to bit history, complexity, and biological organization.
Should arrive some time between March 13 – March 25.
Walter Pitts was pivotal in establishing the revolutionary notion of the brain as a computer, which was seminal in the development of computer design, cybernetics, artificial intelligence, and theoretical neuroscience. He was also a participant in a large number of key advances in 20th-century science. ❧
I’ve seen a few places in the text where he references “group(s) of Japanese scientists” in a collective way where as when the scientists are from the West he tends to name at least a principle investigator if not multiple members of a team. Is this implicit bias? I hope it’s not, but it feels very conspicuous and regular to me and I wish it weren’t there.