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Kurt Laitner

Ethereum whitepaper - 0 views

www.ethereum.org/ethereum.html

paper Ethereum

shared by Kurt Laitner on 11 Feb 14 - No Cached
  • The general concept of a "decentralized autonomous organization" is that of a virtual entity that has a certain set of members or shareholders which, perhaps with a 67% majority, have the right to spend the entity's funds and modify its code. The members would collectively decide on how the organization should allocate its funds. Methods for allocating a DAO's funds could range from bounties, salaries to even more exotic mechanisms such as an internal currency to reward work. This essentially replicates the legal trappings of a traditional company or nonprofit but using only cryptographic blockchain technology for enforcement. So far much of the talk around DAOs has been around the "capitalist" model of a "decentralized autonomous corporation" (DAC) with dividend-receiving shareholders and tradable shared; an alternative, perhaps described as a "decentralized autonomous community", would have all members have an equal share in the decision making and require 67% of existing members to agree to add or remove a member. The requirement that one person can only have one membership would then need to be enforced collectively by the group.
    • Kurt Laitner
      Kurt Laitner on 11 Feb 14
       
      key application for OVNs
  • Note that the design relies on the randomness of addresses and hashes for data integrity; the contract will likely get corrupted in some fashion after about 2^128 uses
  • This implements the "egalitarian" DAO model where members have equal shares. One can easily extend it to a shareholder model by also storing how many shares each owner holds and providing a simple way to transfer shares.
    • Kurt Laitner
      Kurt Laitner on 11 Feb 14
       
      interesting...
  • ...5 more annotations...
  • DAOs and DACs have already been the topic of a large amount of interest among cryptocurrency users as a future form of economic organization, and we are very excited about the potential that DAOs can offer. In the long term, the Ethereum fund itself intends to transition into being a fully self-sustaining DAO.
  • In Bitcoin, there are no mandatory transaction fees.
  • In Ethereum, because of its Turing-completeness, a purely voluntary fee system would be catastrophic. Instead, Ethereum will have a system of mandatory fees, including a transaction fee and six fees for contract computations.
  • The coefficients will be revised as more hard data on the relative computational cost of each operation becomes available. The hardest part will be setting the value of
  • There are currently two main solutions that we are considering: Make x inversely proportional to the square root of the difficulty, so x = floor(10^21 / floor(difficulty ^ 0.5)). This automatically adjusts fees down as the value of ether goes up, and adjusts fees down as computers get more powerful due to Moore's Law. Use proof of stake voting to determine the fees. In theory, stakeholders do not benefit directly from fees going up or down, so their incentives would be to make the decision that would maximize the value of the network.
Tiberius Brastaviceanu

What is an ontology and why we need it - 1 views

protege.stanford.edu/...ntology101-noy-mcguinness.html

protege ontologies infrastructure tutorial

shared by Tiberius Brastaviceanu on 29 Jul 12 - Cached
  • an ontology designer makes these decisions based on the structural properties of a class.
  • an ontology is a formal explicit description of concepts in a domain of discourse (classes (sometimes called concepts)), properties of each concept describing various features and attributes of the concept (slots (sometimes called roles or properties)), and restrictions on slots (facets (sometimes called role restrictions)). An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.
  • Classes describe concepts in the domain
  • ...16 more annotations...
  • A class can have subclasses that represent concepts that are more specific than the superclass.
  • Here we discuss general issues to consider and offer one possible process for developing an ontology. We describe an iterative approach to ontology development: we start with a rough first pass at the ontology. We then revise and refine the evolving ontology and fill in the details. Along the way, we discuss the modeling decisions that a designer needs to make, as well as the pros, cons, and implications of different solutions.
  • In practical terms, developing an ontology includes: �         defining classes in the ontology, �         arranging the classes in a taxonomic (subclass–superclass) hierarchy, �         defining slots and describing allowed values for these slots, �         filling in the values for slots for instances.
  • We can then create a knowledge base by defining individual instances of these classes filling in specific slot value information and additional slot restrictions.
  • Slots describe properties of classes and instances:
  • There is no one correct way to model a domain— there are always viable alternatives. The best solution almost always depends on the application that you have in mind and the extensions that you anticipate. 2)      Ontology development is necessarily an iterative process. 3)      Concepts in the ontology should be close to objects (physical or logical) and relationships in your domain of interest. These are most likely to be nouns (objects) or verbs (relationships) in sentences that describe your domain.
  • some fundamental rules in ontology design
  • how detailed or general the ontology is going to be
  • what we are going to use the ontology for
  • concepts in the ontology must reflect this reality
  • We suggest starting the development of an ontology by defining its domain and scope. That is, answer several basic questions: �         What is the domain that the ontology will cover? �         For what  we are going to use the ontology? �         For what types of questions the information in the ontology should provide answers? �         Who will use and maintain the ontology?
  • plan to use
  • domain
  • If the people who will maintain the ontology describe the domain in a language that is different from the language of the ontology users, we may need to provide the mapping between the languages.
  • One of the ways to determine the scope of the ontology is to sketch a list of questions that a knowledge base based on the ontology should be able to answer, competency questions
  • These competency questions are just a sketch and do not need to be exhaustive.
Tiberius Brastaviceanu

Welcome to the new reputation economy (Wired UK) - 1 views

www.wired.co.uk/...-to-the-new-reputation-economy

economy Reputation paper

shared by Tiberius Brastaviceanu on 02 Oct 12 - No Cached
  • banks take into account your online reputation alongside traditional credit ratings to determine your loan
  • headhunters hire you based on the expertise you've demonstrated on online forums
  • reputation data becomes the window into how we behave, what motivates us, how our peers view us and ultimately whether we can or can't be trusted.
  • ...37 more annotations...
  • At the heart of Movenbank is a concept call CRED.
  • The difference today is our ability to capture data from across an array of digital services. With every trade we make, comment we leave, person we "friend", spammer we flag or badge we earn, we leave a trail of how well we can or can't be trusted.
  • An aggregated online reputation having a real-world value holds enormous potential
  • peer-to-peer marketplaces, where a high degree of trust is required between strangers; and where a traditional approach based on disjointed information sources is currently inefficient, such as recruiting.
  • opportunity to reinvent the way people found jobs through online reputation
  • "It's not about your credit, but your credibility," King says.
  • But this wealth of data raises an important question -- who owns our reputation? Shouldn't our hard-earned online status be portable? If you're a SuperHost on Airbnb, shouldn't you be able to use that reputation to, say, get a loan, or start selling on Etsy?
  • "People are currently underusing their networks and reputation," King says. "I want to help people to understand and build their influence and reputation, and think of it as capital they can put to good use."
  • Social scientists have long been trying to quantify the value of reputation.
  • Using functional magnetic resonance imaging, the researchers monitored brain activity
  • "The implication of our study is that different types of reward are coded by the same currency system." In other words, our brains neurologically compute personal reputation to be as valuable as money.
  • Personal reputation has been a means of making socioeconomic decisions for thousands of years. The difference today is that network technologies are digitally enabling the trust we used to experience face-to-face -- meaning that interactions and exchanges are taking place between total strangers.
  • Trust and reputation become acutely important in peer-to-peer marketplaces such as WhipCar and Airbnb, where members are taking a risk renting out their cars or their homes.
  • When you are trading peer-to-peer, you can't count on traditional credit scores. A different measurement is needed. Reputation fills this gap because it's the ultimate output of how much a community trusts you.
  • Welcome to the reputation economy, where your online history becomes more powerful than your credit history.
  • Presently, reputation data doesn't transfer between verticals.
  • A wave of startups, including Connect.Me, TrustCloud, TrustRank, Legit and WhyTrusted, are trying to solve this problem by designing systems that correlate reputation data. By building a system based on "reputation API" -- a combination of a user's activity, ratings and reviews across sites -- Legit is working to build a service that gives users a score from zero to 100. In trying to create a universal metric for a person's trustworthiness, they are trying to "become the credit system of the sharing economy", says Jeremy Barton, the 27-year-old San Francisco-based cofounder of Legit.
  • His company, and other reputation ventures, face some big challenges if they are to become, effectively, the PayPal of trust. The most obvious is coming up with algorithms that can't be easily gamed or polluted by trolls. And then there's the critical hurdle of convincing online marketplaces not just to open up their reputation vaults, but create a standardised format for how they frame and collect reputation data. "We think companies will share reputation data for the same reasons banks give credit data to credit bureaux," says Rob Boyle, Legit cofounder and CTO. "It is beneficial for one company to give up their slice of reputation data if in return they get access to the bigger picture: aggregated data from other companies."
  • PeerIndex, Kred and Klout,
  • are measuring social influence, not reputation. "Influence measures your ability to drag someone into action,"
  • "Reputation is an indicator of whether a person is good or bad and, ultimately, are they trustworthy?"
  • Early influence and reputation aggregators will undoubtedly learn by trial and error -- but they will also face the significant challenge of pioneering the use of reputation data in a responsible way. And there's a challenge beyond that: reputation is largely contextual, so it's tricky to transport it to other situations.
  • Many of the ventures starting to make strides in the reputation economy are measuring different dimensions of reputation.
  • reputation is a measure of knowledge
  • a measure of trust
  • a measure of propensity to pay
  • measure of influence
  • Reputation capital is not about combining a selection of different measures into a single number -- people are too nuanced and complex to be distilled into single digits or binary ratings.
  • It's the culmination of many layers of reputation you build in different places that genuinely reflect who you are as a person and figuring out exactly how that carries value in a variety of contexts.
  • The most basic level is verification of your true identity
  • reliability and helpfulness
  • do what we say we are going to do
  • respect another person's property
  • trusted to pay on time
  • we will be able to perform a Google- or Facebook-like search and see a picture of a person's behaviour in many different contexts, over a length of time. Slivers of data that have until now lived in secluded isolation online will be available in one place. Answers on Quora, reviews on TripAdvisor, comments on Amazon, feedback on Airbnb, videos posted on YouTube, social groups joined, or presentations on SlideShare; as well as a history and real-time stream of who has trusted you, when, where and why. The whole package will come together in your personal reputation dashboard, painting a comprehensive, definitive picture of your intentions, capabilities and values.
  • idea of global reputation
  • By the end of the decade, a good online reputation could be the most valuable currency in your possession.
Kurt Laitner

Guidelines on Measuring Subjective Well-being.pdf - 0 views

www.oecd.org/...%20Subjective%20Well-being.pdf

OECD well being subjective measures

shared by Kurt Laitner on 21 Mar 13 - No Cached
  • such as interest,engagement and meaning,
  • subjective well-being is taken to be:2Good mental states, including all of the various evaluations, positive and negative, that peoplemake of their lives, and the affective reactions of people to their experiences
  • “subjective well-being is an umbrella term for the different valuationspeople make regarding their lives, the events happening to them, their bodies and minds,and the circumstances in which they live”.
  • ...16 more annotations...
  • In measuring overall human well-being then, subjective well-being should be placedalongside measures of non-subjective outcomes, such as income, health, knowledge andskills, safety, environmental quality and social connections
  • Inparticular, a distinction is commonly made between life evaluations, which involve acognitive evaluation of the respondent’s life as a whole (or aspects of it), and measures ofaffect, which capture the feelings experienced by the respondent at a particular point in time(Diener, 1984; Kahneman et al., 1999
  • eudaimonic aspect ofsubjective well-being, reflecting people’s sense of purpose and engagement
  • The framework used here covers all three concepts of well-being:●Life evaluation.●Affect.●Eudaimonia (psychological “flourishing”)
  • the result of a judgement by the individual rather than thedescription of an emotional state.
  • Elements of subjective well-beingLife evaluation
  • making an evaluation of this sort as involving the individual constructing a “standard” thatthey perceive as appropriate for themselves, and then comparing the circumstances oftheir life to that standard
  • Life evaluations are based on how people remember their experiences (Kahneman et al.,1999) and can differ significantly from how they actually experienced things at the time
  • It is for this reason that life evaluations are sometimes characterised as measures of“decision utility” in contrast to “experienced utility”
  • One of the mostwell documented measures of life evaluation – thePersonal Wellbeing Index– consists of eightquestions, covering satisfactions with eight different aspects of life, which are summedusing equal weights to calculate an overall index (International Wellbeing Group, 2006)
  • (job satisfaction, financial satisfaction, house satisfaction, healthsatisfaction, leisure satisfaction and environmental satisfaction),
  • AffectAffect is the term psychologists use to describe a person’s feelings. Measures of affectcan be thought of as measures of particular feelings or emotional states, and they aretypically measured with reference to a particular point in time.
  • Such measures capturehow people experience life rather than how they remember it (Kahneman and Krueger,2006
  • While an overall evaluation of life can be captured in a single measure, affect has atleast two distinct hedonic dimensions: positive affect and negative affect (Kahneman et al.,1999; Diener et al., 1999
  • positive affect is thought to be largely uni-dimensional
  • negative affect may be more multi-dimensional.
Tiberius Brastaviceanu

Votorola - 1 views

zelea.com/...home.xht

decision making tool tools

shared by Tiberius Brastaviceanu on 04 Jun 12 - Cached
  • Tiberius Brastaviceanu on 04 Jun 12
     
    Votorola is social software in support of non-party primary elections and public rule making. We develop the tools to enable a radically free democracy based on unrestricted voting, drafting and discussion. Our alpha prototypes cover everything from voter registration in electoral districts to consensus making, and we lead the field in design, theory and inventions.
Tiberius Brastaviceanu

Design Like No One Is Patenting - How SparkFun Stays Ahead of the Pack - 0 views

www.wired.com/...sparkfun-10-years

open hardware business model Sparkfun paper innovation

shared by Tiberius Brastaviceanu on 26 Jan 13 - No Cached
  • Electronics supplier SparkFun designs dozens of products a year and they haven’t patented a single one. It’s worked out pretty well so far.
  • makes its living by shipping kits and components like bread boards, servo motors and Arduino parts to a mixture of students, hobbyists, and professionals making prototypes
  • the company has made its name is in a stable of its own custom parts and kits, the designs for which it gives away for free.
  • ...40 more annotations...
  • “We find that people will copy your design no matter what you do,” she says. “You might as well just play the game and go ahead and innovate. It’s fun, it keeps us on our toes.”
  • “The open source model just forces us to innovate,” says Boudreaux.
  • the open hardware model means that SparkFun’s existence depends not on any particular product, but on an ongoing relationship with customers that’s not too dissimilar to the loyalty commanded by a fashion house.
  • wolf of obsolescence is always at electronics’ door
  • don’t spend much time worrying about the copyists, they just keep releasing new looks
  • it’s about staying relevant and filling the needs of the community
  • SparkFun’s rapid turnover model is one that echoes the fashion industry.
  • keep their service exemplary
  • listening to their customers
  • developed a community of loyal users and fans
  • weekly new product posts
  • You can learn a lot about what a company cares about by looking at what they give away and what they protect.
  • SparkFun’s actual value is in the community of fans and loyal customers that keep coming back, and the expertise under its roof in servicing their needs.
  • Their catalog has about 2,500 items at any given time
  • SparkFun orders parts from 500 suppliers
  • 15 new products every week
  • hey retire products at a similar rate, due to either low sales, or obsolescence
  • Of the 2,500 items, about 400 are things designed internally.
  • To handle the pace of change, SparkFun needs to keep its inventory lean.
  • “We try to do small runs and order in small quantities. Especially something that’s going to be obsolete quickly.”
  • To help manage the demand, they use an in-house software system
  • along with inventory and CMS management, tries to predict demand for different components and ensure they get ordered with sufficient lead time to account for how long it takes to get there.
  • the innovation (revisions and new releases) here at SparkFun is organic and not planned,” says Boudreaux, “But we do a few things to make sure we are keeping up.”
  • monitors all costumer feedback from emails to the comment section that is present on every page of the company’s site. They also ensure that team members have time to tinker in the office, write tutorials, and visit hackerspaces and maker events. “For us, designing (and revising) widgets is the job.”
  • anyone in the company can suggest ideas and contribute designs.
  • ideas run through an internal process of design, review, prototyping, testing and release.
  • “They eat these products up, even if the products are not ready for the mainstream & educator community due to minimal documentation or stability.”
  • symbiotic relationship with these early adopters, where feedback helps SparkFun revised and improve products for use by the rest of the community
  • I don’t think they help much
  • The risk of this rate of change is that SparkFun can end up outpacing some of their customers.
  • “There’s balance in everything,” says Boudreaux, “Innovation does not necessarily need speed in order to create valuable change. Sometimes innovation works at a slower pace, but that does not mean it is any less valuable to those that benefit from it, and we are constantly balancing the needs of two very different customers.”
  • unprotected and unencumbered by patents
  • racing to get the latest, coolest things in the hands of its customers.
  • patents
  • “We have to be willing to kill ideas that don’t work, take a lot of tough criticism, and move fast. If we stay agile, we stay relevant.”
  • cost $30,000 to $50,000
  • USPTO is so backed up you’ll have to wait three to five years to even hear back on their decision.
  • how much does technology change in five years?
  • company’s blog where they’ve been documenting production and business practices for years.
  • they even want to open source Sparkle. “It’s a wild ride,” she says, “but a fun one for sure.”
  • Tiberius Brastaviceanu on 26 Jan 13
     
    shared by Jonathan, annotated by Tibi
Tiberius Brastaviceanu

The New Normal in Funding University Science | Issues in Science and Technology - 1 views

issues.org/...-in-funding-university-science

open science paper

shared by Tiberius Brastaviceanu on 07 Aug 14 - No Cached
  • Government funding for academic research will remain limited, and competition for grants will remain high. Broad adjustments will be needed
  • he sequester simply makes acute a chronic condition that has been getting worse for years.
  • the federal budget sequester
  • ...72 more annotations...
  • systemic problems that arise from the R&D funding system and incentive structure that the federal government put in place after World War II
  • Researchers across the country encounter increasingly fierce competition for money.
  • unding rates in many National Institutes of Health (NIH) and National Science Foundation (NSF) programs are now at historical lows, declining from more than 30% before 2001 to 20% or even less in 2011
  • even the most prominent scientists will find it difficult to maintain funding for their laboratories, and young scientists seeking their first grant may become so overwhelmed that individuals of great promise will be driven from the field
  • anxiety and frustration
  • The growth of the scientific enterprise on university campuses during the past 60 years is not sustainable and has now reached a tipping point at which old models no longer work
  • Origins of the crisis
  • ederal funding agencies must work with universities to ensure that new models of funding do not stymie the progress of science in the United States
  • The demand for research money greatly exceeds the supply
  • the demand for research funding has gone up
  • The deeper sources of the problem lie in the incentive structure of the modern research university, the aspirations of scientists trained by those universities, and the aspirations of less research-intensive universities and colleges across the nation
  • competitive grants system
  • if a university wants to attract a significant amount of sponsored research money, it needs doctoral programs in the relevant fields and faculty members who are dedicated to both winning grants and training students
  • The production of science and engineering doctorates has grown apace
  • Even though not all doctorate recipients become university faculty, the size of the science and engineering faculty at U.S. universities has grown substantially
  • proposal pressure goes up
  • These strategies make sense for any individual university, but will fail collectively unless federal funding for R&D grows robustly enough to keep up with demand.
  • At the very time that universities were enjoying rapidly growing budgets, and creating modes of operation that assumed such largess was the new normal, Price warned that it would all soon come to a halt
  • the human and financial resources invested in science had been increasing much faster than the populations and economies of those regions
  • growth in the scientific enterprise would have to slow down at some point, growing no more than the population or the economy.
  • Dead-end solutions
  • studies sounded an alarm about the potential decline in U.S. global leadership in science and technology and the grave implications of that decline for economic growth and national security
  • Although we are not opposed to increasing federal funding for research, we are not optimistic that it will happen at anywhere near the rate the Academies seek, nor do we think it will have a large impact on funding rates
  • universities should not expect any radical increases in domestic R&D budgets, and most likely not in defense R&D budgets either, unless the discretionary budgets themselves grow rapidly. Those budgets are under pressure from political groups that want to shrink government spending and from the growth of spending in mandatory programs
  • The basic point is that the growth of the economy will drive increases in federal R&D spending, and any attempt to provide rapid or sustained increases beyond that growth will require taking money from other programs.
  • The demand for research money cannot grow faster than the economy forever and the growth curve for research money flattened out long ago.
  • Path out of crisis
  • The goal cannot be to convince the government to invest a higher proportion of its discretionary spending in research
  • Getting more is not in the cards, and some observers think the scientific community will be lucky to keep what it has
  • The potential to take advantage of the infrastructure and talent on university campuses may be a win-win situation for businesses and institutions of higher education.
  • Why should universities and colleges continue to support scientific research, knowing that the financial benefits are diminishing?
  • esearch culture
  • attract good students and faculty as well as raise their prestige
  • mission to expand the boundaries of human knowledge
  • faculty members are committed to their scholarship and will press on with their research programs even when external dollars are scarce
  • training
  • take place in
  • research laboratories
  • it is critical to have active research laboratories, not only in elite public and private research institutions, but in non-flagship public universities, a diverse set of private universities, and four-year colleges
  • How then do increasingly beleaguered institutions of higher education support the research efforts of the faculty, given the reality that federal grants are going to be few and far between for the majority of faculty members? What are the practical steps institutions can take?
  • change the current model of providing large startup packages when a faculty member is hired and then leaving it up to the faculty member to obtain funding for the remainder of his or her career
  • universities invest less in new faculty members and spread their internal research dollars across faculty members at all stages of their careers, from early to late.
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 07 Aug 14
       
      Sharing of resources, see SENSORICA's NRP
  • national conversation about changes in startup packages and by careful consultations with prospective faculty hires about long-term support of their research efforts
  • Many prospective hires may find smaller startup packages palatable, if they can be convinced that the smaller packages are coupled with an institutional commitment to ongoing research support and more reasonable expectations about winning grants.
  • Smaller startup packages mean that in many situations, new faculty members will not be able to establish a functioning stand-alone laboratory. Thus, space and equipment will need to be shared to a greater extent than has been true in the past.
  • construction of open laboratory spaces and the strategic development of well-equipped research centers capable of efficiently servicing the needs of an array of researchers
  • phaseout of the individual laboratory
  • enhanced opportunities for communication and networking among faculty members and their students
  • Collaborative proposals and the assembly of research teams that focus on more complex problems can arise relatively naturally as interactions among researchers are facilitated by proximity and the absence of walls between laboratories.
  • An increased emphasis on team research
  • investments in the research enterprise
  • can be directed at projects that have good buy-in from the faculty
  • learn how to work both as part of a team and independently
  • Involvement in multiple projects should be encouraged
  • The more likely trajectory of a junior faculty member will evolve from contributing team member to increasing leadership responsibilities to team leader
  • nternal evaluations of contributions and potential will become more important in tenure and promotion decisions.
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 07 Aug 14
       
      Need value accounting system
  • relationships with foundations, donors, state agencies, and private business will become increasingly important in the funding game
  • The opportunities to form partnerships with business are especially intriguing
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 07 Aug 14
       
      The problem is to change the model and go open source, because IP stifles other processes that might benefit Universities!!!
  • Further complicating university collaborations with business is that past examples of such partnerships have not always been easy or free of controversy.
  • some faculty members worried about firms dictating the research priorities of the university, pulling graduate students into proprietary research (which could limit what they could publish), and generally tugging the relevant faculty in multiple directions.
  • developed rules and guidelines to control them
  • University faculty and businesspeople often do not understand each other’s cultures, needs, and constraints, and such gaps can lead to more mundane problems in university/industry relations, not least of which are organizational demands and institutional cultures
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 07 Aug 14
       
      Needs for mechanisms to govern, coordinate, structure an ecosystem -See SENSORICA's Open Alliance model
  • n addition to funding for research, universities can receive indirect benefits from such relationships. High-profile partnerships with businesses will underline the important role that universities can play in the economic development of a region.
  • Universities have to see firms as more than just deep pockets, and firms need to see universities as more than sources of cheap skilled labor.
  • foundations or other philanthropy
  • We do not believe that research proposed and supervised by individual principal investigators will disappear anytime soon. It is a research model that has proven to be remarkably successful and enduring
  • However, we believe that the most vibrant scientific communities on university and college campuses, and the ones most likely to thrive in the new reality of funding for the sciences, will be those that encourage the formation of research teams and are nimble with regard to funding sources, even as they leave room for traditional avenues of funding and research.
Tiberius Brastaviceanu

James Grier Miller, Living Systems (1978) - 0 views

www.panarchy.org/...livingsystems.html

Grier Miller living systems theory concepts paper

shared by Tiberius Brastaviceanu on 23 Jun 11 - No Cached
  • reality as an integrated hierarchy of organizations of matter and energy
  • General living systems theory is concerned with a special subset of all systems, the living ones
  • a space is a set of elements which conform to certain postulate
  • ...266 more annotations...
  • s. Euclidean space
  • metric space
  • topological space
  • Physical space is the extension surrounding a point
  • My presentation of a general theory of living systems will employ two sorts of spaces in which they may exist, physical or geographical space and conceptual or abstracted spaces
  • Physical or geographical space
  • Euclidean space
  • distance
  • moving
  • maximum speed
  • objects moving in such space cannot pass through one another
  • friction
  • The characteristics and constraints of physical space affect the action of all concrete systems, living and nonliving.
  • information can flow worldwide almost instantly
  • Physical space is a common space
  • Most people learn that physical space exists, which is not true of many spaces
  • They can give the location of objects in it
  • Conceptual or abstracted spaces
  • Peck order
  • Social class space
  • Social distance
  • Political distance
  • life space
  • semantic space
  • Sociometric space
  • A space of time costs of various modes of transportation
  • space of frequency of trade relations among nations.
  • A space of frequency of intermarriage among ethnic groups.
  • These conceptual and abstracted spaces do not have the same characteristics and are not subject to the same constraints as physical space
  • Social and some biological scientists find conceptual or abstracted spaces useful because they recognize that physical space is not a major determinant of certain processes in the living systems they study
  • interpersonal relations
  • one cannot measure comparable processes at different levels of systems, to confirm or disconfirm cross-level hypotheses, unless one can measure different levels of systems or dimensions in the same spaces or in different spaces with known transformations among them
  • It must be possible, moreover, to make such measurements precisely enough to demonstrate whether or not there is a formal identity across levels
  • fundamental "fourth dimension" of the physical space-time continuum
  • is the particular instant at which a structure exists or a process occurs
  • or the measured or measurable period over which a structure endures or a process continues.
  • durations
  • speeds
  • rates
  • accelerations
  • irreversible unidirectionality of time
  • thermodynamics
  • negentropy
  • "time's arrow."
  • Matter and energy
  • Matter is anything which has mass (m) and occupies physical space.
  • Energy (E) is defined in physics as the ability to do work.
  • kinetic energy
  • potential energy
  • rest mass energy
  • Mass and energy are equivalent
  • Living systems need specific types of matter-energy in adequate amounts
  • Energy for the processes of living systems is derived from the breakdown of molecules
  • Any change of state of matter-energy or its movement over space, from one point to another, I shall call action.
  • It is one form of process.
  • information (H)
  • Transmission of Information
  • Meaning is the significance of information to a system which processes it: it constitutes a change in that system's processes elicited by the information, often resulting from associations made to it on previous experience with it
  • Information is a simpler concept: the degrees of freedom that exist in a given situation to choose among signals, symbols, messages, or patterns to be transmitted.
  • The set of all these possible categories (the alphabet) is called the ensemble or repertoire
  • .) The unit is the binary digit, or bit of information
  • . The amount of information is measured as the logarithm to the base 2 of the number of alternate patterns
  • Signals convey information to the receiving system only if they do not duplicate information already in the receiver. As Gabor says:
  • [The information of a message can] be defined as the 'minimum number of binary decisions which enable the receiver to construct the message, on the basis of the data already available to him.'
  • meaning cannot be precisely measured
  • Information is the negative of uncertainty.
  • information is the amount of formal patterning or complexity in any system.
  • The term marker was used by von Neumann to refer to those observable bundles, units, or changes of matter-energy whose patterning bears or conveys the informational symbols from the ensemble or repertoire.
  • If a marker can assume n different states of which only one is present at any given time, it can represent at most log2n bits of information. The marker may be static, as in a book or in a computer's memory
  • Communication of almost every sort requires that the marker move in space, from the transmitting system to the receiving system, and this movement follows the same physical laws as the movement of any other sort of matter-energy. The advance of communication technology over the years has been in the direction of decreasing the matter-energy costs of storing and transmitting the markers which bear information.
  • There are, therefore, important practical matter-energy constraints upon the information processing of all living systems exerted by the nature of the matter-energy which composes their markers.
  • organization is based upon the interrelations among parts.
  • If two parts are interrelated either quantitatively or qualitatively, knowledge of the state of one must yield some information about the state of the other. Information measures can demonstrate when such relationships exist
  • The disorder, disorganization, lack of patterning, or randomness of organization of a system is known as its entropy (S)
  • the statistical measure for the negative of entropy is the same as that for information
  • entropy becomes a measure of the probability
  • Increase of entropy was thus interpreted as the passage of a system from less probable to more probable states.
  • according to the second law, a system tends to increase in entropy over time, it must tend to decrease in negentropy or information.
  • therefore no principle of the conservation of information
  • The total information can be decreased in any system without increasing it elsewhere
  • but it cannot be increased without decreasing it elsewhere
  • . Making one or more copies of a given informational pattern does not increase information overall, though it may increase the information in the system which receives the copied information.
  • transforms information into negative entropy
  • smallest possible amount of energy used in observing one bit of information
  • calculations of the amount of information accumulated by living systems throughout growth.
  • the concept of Prigogine that in an open system (that is one in which both matter and energy can be exchanged with the environment) the rate of entropy production within the system, which is always positive, is minimized when the system is in a steady state.
  • in systems with internal feedbacks, internal entropy production is not always minimized when the system is in a stationary state. In other words, feedback couplings between the system parameters may cause marked changes in the rate of development of entropy. Thus it may be concluded that the "information flow" which is essential for this feedback markedly alters energy utilization and the rate of development of entropy, at least in some such special cases which involve feedback control. While the explanation of this is not clear, it suggests an important relationship between information and entropy
  • amount of energy actually required to transmit the information in the channel is a minute part of the total energy in the system, the "housekeeping energy" being by far the largest part of it
  • In recent years systems theorists have been fascinated by the new ways to study and measure information flows, but matter-energy flows are equally important. Systems theory is more than information theory, since it must also deal with energetics - such matters as
  • the flow of raw materials through societies
  • Only a minute fraction of the energy used by most living systems is employed for information processing
  • I have noted above that the movement of matter-energy over space, action, is one form of process. Another form of process is information processing or communication, which is the change of information from one state to another or its movement from one point to another over space
  • Communications, while being processed, are often shifted from one matter-energy state to another, from one sort of marker to another
  • transformations go on in living systems
  • One basic reason why communication is of fundamental importance is that informational patterns can be processed over space and the local matter-energy at the receiving point can be organized to conform to, or comply with, this information
  • the delivery of "flowers by telegraph."
  • Matter-energy and information always flow together
  • Information is always borne on a marker
  • . Conversely there is no regular movement in a system unless there is a difference in potential between two points, which is negative entropy or information
  • If the receiver responds primarily to the material or energic aspect, I shall call it, for brevity, a matter-energy transmission; if the response is primarily to the information, I shall call it an information transmission
  • Moreover, just as living systems must have specific forms of matter-energy, so they must have specific patterns of information
  • example
  • example
  • develop normally
  • have appropriate information inputs in infancy
  • pairs of antonyms
  • one member of which is associated with the concept of information (H)
  • the other member of which is associated with its negative, entropy (S)
  • System
  • A system is a set of interacting units with relationships among them
  • .The word "set" implies that the units have some common properties. These common properties are essential if the units are to interact or have relationships. The state of each unit is constrained by, conditioned by, or dependent on the state of other units. The units are coupled. Moreover, there is at least one measure of the sum of its units which is larger than the sum of that measure of its units.
  • Conceptual system
  • Units
  • terms
  • Relationships
  • a set of pairs of units, each pair being ordered in a similar way
  • expressed by words
  • or by logical or mathematical symbols
  • operations
  • The conceptual systems of science
  • observer
  • selects
  • particular sets to study
  • Variable
  • Each member of such a set becomes a variable of the observer's conceptual system
  • conceptual system may be loose or precise, simple or elaborate
  • Indicator
  • an instrument or technique used to measure fluctuations of variables in concrete systems
  • Function
  • a correspondence between two variables, x and y, such that for each value of x there is a definite value of y, and no two y's have the same x, and this correspondence is: determined by some rule
  • Any function is a simple conceptual system
  • Parameter
  • An independent variable through functions of which other functions may be expressed
  • The state of a conceptual system
  • the set of values on some scale, numerical or otherwise, which its variables have at a given instant
  • Formal identity
  • variables
  • varies comparably to a variable in another system
  • If these comparable variations are so similar that they can be expressed by the same function, a formal identity exists between the two systems
  • Relationships between conceptual and other sorts of systems
  • Science advances as the formal identity or isomorphism increases between a theoretical conceptual system and objective findings about concrete or abstracted systems
  • A conceptual system may be purely logical or mathematical, or its terms and relationships may be intended to have some sort of formal identity or isomorphism with units and relationships empirically determinable by some operation carried out by an observer
  • Concrete system
  • a nonrandom accumulation of matter-energy, in a region in physical space-time, which is organized into interacting interrelated subsystems or components.
  • Units
  • are also concrete systems
  • Relationships
  • spatial
  • temporal
  • spatiotemporal
  • causal
  • Both units and relationships in concrete systems are empirically determinable by some operation carried out by an observer
  • patterns of relationships or processes
  • The observer of a concrete system
  • distinguishes a concrete system from unorganized entities in its environment by the following criteria
  • physical proximity of its units
  • similarity of its units
  • common fate of its units
  • distinct or recognizable patterning of its units.
  • Their boundaries are discovered by empirical operations available to the general scientific community rather than set conceptually by a single observer
  • Variable of a concrete system
  • Any property of a unit or relationship within a system which can be recognized by an observer
  • which can potentially change over time, and whose change can potentially be measured by specific operations, is a variable of a concrete system
  • Examples
  • number of its subsystems or components, its size, its rate of movement in space, its rate of growth, the number of bits of information it can process per second, or the intensity of a sound to which it responds
  • A variable is intrasystemic
  • not to be confused with intersystemic variations which may be observed among individual systems, types, or levels.
  • The state of a concrete system
  • its structure
  • represented by the set of values on some scale which its variables have at that instant
  • Open system
  • Most concrete systems have boundaries which are at least partially permeable, permitting sizable magnitudes of at least certain sorts of matter-energy or information transmissions to pass them. Such a system is an open system. In open systems entropy may increase, remain in steady state, or decrease.
  • Closed system
  • impermeable boundaries through which no matter-energy or information transmissions of any sort can occur is a closed system
  • special case
  • No actual concrete system is completely closed
  • In closed systems, entropy generally increases, exceptions being when certain reversible processes are carried on which do not increase it. It can never decrease.
  • Nonliving system
  • the general case of concrete systems, of which living systems are a very special case. Nonliving systems need not have the same critical subsystems as living systems, though they often have some of them
  • Living system
  • a special subset of the set of all possible concrete systems
  • They all have the following characteristics:
  • open systems
  • inputs
  • throughputs
  • outputs
  • of various sorts of matter-energy and information.
  • maintain a steady state of negentropy even though entropic changes occur in them as they do everywhere else
  • by taking in inputs
  • higher in complexity or organization or negentropy
  • than their outputs
  • The difference permits them to restore their own energy and repair breakdowns in their own organized structure.
  • In living systems many substances are produced as well as broken down
  • To do this such systems must be open and have continual inputs of matter-energy and information
  • entropy will always increase in walled-off living systems
  • They have more than a certain minimum degree of complexity
  • They either contain genetic material composed of deoxyribonucleic acid (DNA)
  • or have a charter
  • blueprint
  • program
  • of their structure and process from the moment of their origin
  • may also include nonliving components.
  • They have a decider, the essential critical sub-system which controls the entire system, causing its subsystems and components to interact. Without such interaction under decider control there is no system.
  • other specific critical sub-systems or they have symbiotic or parasitic relationships with other living or nonliving systems
  • Their subsystems are integrated together to form actively self-regulating, developing, unitary systems with purposes and goals
  • They can exist only in a certain environment
  • change in their environment
  • produces stresses
  • Totipotential system
  • capable of carrying out all critical subsystem processes necessary for life is totipotential
  • Partipotential system
  • does not itself carry out all critical subsystem processes is partipotential
  • A partipotential system must interact with other systems that can carry out the processes which it does not, or it will not survive
  • parasitic
  • symbiotic
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 25 Jun 11
       
      The Exchange fime is a symbiotic system to SENSORICA
  • Fully functioning system
  • when it
  • Partially functioning system
  • it must do its own deciding, or it is not a system
  • Abstracted system
  • Units
  • relationships abstracted or selected by an observer in the light of his interests, theoretical viewpoint, or philosophical bias.
  • Some relationships may be empirically determinable by some operation carried out by the observer, but others are not, being only his concepts
  • Relationships
  • The relationships mentioned above are observed to inhere and interact in concrete, usually living, systems
  • these concrete systems are the relationships of abstracted systems.
  • The verbal usages of theoretical statements concerning abstracted systems are often the reverse of those concerning concrete systems
  • An abstracted system differs from an abstraction, which is a concept
  • representing a class of phenomena all of which are considered to have some similar "class characteristic." The members of such a class are not thought to interact or be interrelated, as are the relationships in an abstracted system
  • Abstracted systems are much more common in social science theory than in natural science.
  • are oriented toward relationships rather than toward the concrete systems
  • spatial arrangements are not usually emphasized
  • their physical limits often do not coincide spatially with the boundaries of any concrete system, although they may.
  • important difference between the physical and biological hierarchies, on the one hand, and social hierarchies, on the other
  • Most physical and biological hierarchies are described in spatial terms
  • we propose to identify social hierarchies not by observing who lives close to whom but by observing who interacts with whom
  • intensity of interaction
  • in most biological and physical systems relatively intense interaction implies relative spatial propinquity
  • To the extent that interactions are channeled through specialized communications and transportation systems, spatial propinquity becomes less determinative of structure.
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 25 Jun 11
       
      This is the case of SENSORICA, built on web-based communication and coordination tools. 
  • PARSONS
  • the unit of a partial social system is a role and not the individual.
  • culture
  • cumulative body of knowledge of the past, contained in memories and assumptions of people who express this knowledge in definite ways
  • The social system is the actual habitual network of communication between people.
  • RUESCH
  • A social system is a behavioral system
  • It is an organized set of behaviors of persons interacting with each other: a pattern of roles.
  • The roles are the units of a social system
    • Tiberius Brastaviceanu
      Tiberius Brastaviceanu on 25 Jun 11
       
      That is why we need a role system in SENSORICA
  • On the other hand, the society is an aggregate of social subsystems, and as a limiting case it is that social system which comprises all the roles of all the individuals who participate.
  • What Ruesch calls the social system is something concrete in space-time, observable and presumably measurable by techniques like those of natural science
  • To Parsons the system is abstracted from this, being the set of relationships which are the form of organization. To him the important units are classes of input-output relationships of subsystems rather than the subsystems themselves
  • system is a system of relationship in action, it is neither a physical organism nor an object of physical perception
  • evolution
  • differentiation
  • growth
  • from earlier and simpler forms and functions
  • capacities for specializations and gradients
  • [action] is not concerned with the internal structure of processes of the organism, but is concerned with the organism as a unit in a set of relationships and the other terms of that relationship, which he calls situation
  • Abstracted versus concrete systems
  • One fundamental distinction between abstracted and concrete systems is that the boundaries of abstracted systems may at times be conceptually established at regions which cut through the units and relationships in the physical space occupied by concrete systems, but the boundaries of these latter systems are always set at regions which include within them all the units and internal relationships of each system
  • A science of abstracted systems certainly is possible and under some conditions may be useful.
  • If the diverse fields of science are to be unified, it would be helpful if all disciplines were oriented either to concrete or to abstracted systems.
  • It is of paramount importance for scientists to distinguish clearly between them
Tiberius Brastaviceanu

Co-Creating as Disruption to the Dominant Cultural Framework » Wirearchy - 0 views

wirearchy.com/...he-dominant-cultural-framework

paper Wirearchy John Husband

shared by Tiberius Brastaviceanu on 18 Jun 14 - No Cached
  • more open people processes
  • Participative processes like Open Space, World Cafes, Unconferences, Peer Circles
  • Barcamps, Wordcamps, Govcamps, Foo Camps, Unconferences, high-end celebrity-and-marketing-and venture-capital ‘experience’ markets, new cultural and artistic festivals with technology-and-culture-making themes
  • ...45 more annotations...
  • maker faires
  • community-and-consensus building, organizing for activism and fundraising
  • The impetus behind this explosion is both technological and sociological
  • Technological
  • information technology and the creation and evolution of the Internet and the Web
  • appearance, development and evolution of social tools, web services, massive storage, and the ongoing development of computer-and-smart-devices development
  • Sociological
  • People are searching for ways to find others with similar interests and motivations so that they can engage in activities that help them learn, find work, grow capabilities and skills, and tackle vexing social and economic problems
  • get informed and take action
  • Developing familiarity and practice with open and collaborative processes
  • play and work together
  • rules about self-management, operate democratically, and produce results grounded in ownership and the responsibilities that have been agreed upon by the ‘community’
  • The relationships and flows of information can be transferred to online spaces and often benefit from wider connectivity.
  • Today, our culture-making activities are well engaged in the early stages of cultural mutation
  • What’s coming along next ?  “Smart” devices and Internet everywhere in our lives ?  Deep(er) changes to the way things are conceived, carried out, managed and used ?  New mental models ?  Or, will we discover real societal limits to what can be done given the current framework of laws, institutions and established practices with which people are familiar and comfortable ?
  • Shorter cycle-based development and release
  • Agile development
  • It is clear evidence that the developmental and learning dynamics generated by continuous or regular feedback loops are becoming the norm in areas of activity in which change and short cycles of product development are constants.
  • The Internet of Things (IoT)
  • clothes, homes, cars, buildings, roads, and a wide range of other objects that have a place in peoples’ daily life activities
  • experiencing major growth, equally in terms of hardware, software and with respect to the way the capabilities are configured and used
  • The IoT concept is being combined with the new-ish concepts of Open Data and Big Data
  • ethical, political and social impact policy decisions
  • that key opportunities associated with widespread uptake of the IoT are derived from the impact upon peoples’ activities and lives
  • ‘we’ are on our way towards more integrated eco-systems of issues, people and technologies
  • participation and inclusion enabled by interconnectedness are quickly becoming the ‘new rules’
  • What the Future May Hold
  • the ‘scenario planning’ approach
  • world’s politics, economics, anthropology, technology, psychology, sociology and philosophy
  • A scenario planning exercise carried out by the Rockefeller Foundation
  • Clearly these early (and now not-so-weak) signals and patterns tell us that the core assumptions and principles that have underpinned organized human activities for most of the past century
  • are being changed by the combinations and permutations of new, powerful, inexpensive and widely accessible information-processing technologies
  • The short description of each scenario reinforces the perception that we are both individually and collectively in transition from a linear, specialized, efficiency-driven paradigm towards a paradigm based on continuous feedback loops and principles of participation, both large and small in scope.
  • cultural ‘mutation’
  • Wirearchy
  • a dynamic two-way flow of power and authority based on knowledge, trust, credibility and a focus on results, enabled by interconnected people and technology.
  • the role of social media and smart mobile devices in the uprisings in Egypt, Libya and elsewhere in the Middle East
  • The roots of organizational development (OD) are in humanistic psychology and sociology action and ethnographic and cybernetic/ socio-technical systems theory.  It’s a domain that emerged essentially as a counter-balance to the mechanistic and machine-metaphor-based core assumptions about the organized activities in our society.
  • Organizational development principles are built upon some basic assumptions about human motivations, engagement and activities.
  • Participative Work Design – The Six Criteria
  • in recent years created models that help clarify how to evaluate and respond to the continuous turbulence and ambiguity generated by participating in interconnected flows of information.
  • contexts characterized by either Simple, Complicated or Chaotic dynamics (from complexity theory fundamentals). Increasingly, Complexity is emerging as a key definer of the issues, problems and opportunities faced by our societies.
  • peer-to-peer movement(s) unfolding around the world
  • Co-creating in a wide range of forms, processes and purpose may become an effective and important antidote to the spreading enclosure of human creative activity.
  • But .. the dominant models of governance, commercial ownership and the use and re-use of that which is co-created by people are going to have to undergo much more deep change in order to disrupt the existing paradigm of proprietary commercial creation and the model of socio-economic power that this paradigm enables and carries today.
Kurt Laitner

heathr: We're in a time when... - App.net - 1 views

alpha.app.net/...1561697

*authenticity *authority *decision -making *attention

shared by Kurt Laitner on 16 Nov 12 - No Cached
  • Kurt Laitner on 16 Nov 12
     
    some of my favorite words all strung together in a tweet - goes to value equation and what dimensions are linked, an 'exchange' of value that requires no exchange
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