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Kurt Laitner

The Energy Efficiency of Trust & Vulnerability: A Conversation | Switch and Shift - 0 views

  • trusting people because of who they are personally vs. who they are professionally
  • also need to trust systems
  • our ability to understand the context we are in
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  • How much we need to trust others depends on the context,
  • how much we trust ourselves,
  • our own resources
  • When we trust, we re-allocate that energy and time to getting things done and making an impact
  • If the alternative is worse, we might opt for no trust
  • Trust is a tool to assess and manage (reduce and/or increase) risk, depending on the situation.
  • Trusting someone implies making oneself more vulnerable
  • When we don’t trust, we exert a lot of energy to keep up our guard, to continually assess and verify.  This uses a lot of energy and time.
  • the more information and/or experience we have, the better we can decide whether or not to trust
  • As we let ourselves be vulnerable, we also leave ourselves more open to new ideas, new ways of thinking which leads to empathy and innovation.
  • Being vulnerable is a way to preserve energy
  • trusting is efficient….and effective
  • the more we can focus on the scope and achievement of our goals
  • It lets us reallocate our resources to what matters and utilize our skills and those around us to increase effectiveness…impact.
  • If we are working together, we need to agree on the meaning of ‘done’.  When are we done, what does that look like?
  • make sure we hear and see the same thing (reduce buffers around our response)
  • Strategic sloppiness is a way to preserve energy
  • Build on the same shared mental models
  • use the same language
  • As the ability to replicate something has become more of a commodity, we are increasingly seeing that complex interactions are the way to create ‘value from difference’ (as opposed to ‘value from sameness’).
  • allow for larger margins of error in our response and our acceptance of others
  • higher perfection slows down the tempo
  • We can’t minimize the need to be effective.
  • Efficient systems are great at dealing with complicated things – things that have many parts and sequences, but they fall flat dealing with complex systems, which is most of world today.
  • “Control is for Beginners”
  • timing
  • intuition
  • judgment
  • experience
  • ability to look at things from many different perspective
  • to discover, uncover, understand and empathize is critical
  • focus on meaning and purpose for work (outcomes) instead of just money and profit (outputs)
  • When we have a common goal of WHY we want to do something, we are better able to trust
  • When we never do the same thing or have the same conversation twice, it becomes much more important to figure out why and what we do than how we do it (process, which is a given)
  •  
    spot on conversation on *trust, I see creating a trustful environment quickly among strangers as a key capability of an OVN, we need to quickly get past the need to protect and verify and move on to making purpose and goals happen
Tiberius Brastaviceanu

Engaging For the Commons - Global Pull Platform - Helene Finidori - 0 views

  • "activating" human agency and political will and addressing the root causes for power unbalance and resistance to change is at the heart of tomorrow's paradigm shift.
  • action-oriented strategy and process methodology for generating engagement, accountability and outcomes in the political, economic, social and environmental spheres, which may contribute to enable this activation.
  • empowering individuals and communities, nurturing public wisdom
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  • The platform is structured around commons, issues of social, environmental, economic nature,
  • treated as social objects: the nodes around which social networks are created, conversations and repeated interactions are initiated, new territories explored, meaning and intents shared, learning achieved.
  • ‘pinging of actors’ by ‘citizen-followers’ creates a pull dynamic
  • will yield conversations, knowledge flow, and feedback loops beneficial to learning, progress visualization, and evaluation
  • reate a context favorable to collaboration, exchange of ideas and know-how.
  • The process consists in letting people/organizations:
  • Select, follow,
  • Keep informed and track progress
  • Self assign actor role and communicate/report on self-activity and impact and status of issue.
  • Share
  • Find solutions and potential collaborators for action
  • Select or refer designated actors to acknowledge or request their engagement and action at various levels
  • participate in the conversation, report on activity and impact
  • evaluate and rate activity/impact of and trust toward actors' activity, impact and progress.
  • organize for collective action
  • garner follower participation
  • Initiate and participate in conversations, debates, deliberations
  • The ecosystem is composed of
  • Common’s spaces
  • Common’s graph
  • Progress & Impact or Situation Dashboard
  • The platform creates a context for the following
  • Curate the knowledge flow and increase learning
  • Connect and interrelate people, stakeholders, issues, and knowledge.
  • Help situate an issue
  • Define boundaries
  • Help situate self and others
  • Identify roles and interdependence between actors and issues.
  • Visualize the emergent bigger picture
Tiberius Brastaviceanu

David Lametti | Faculty of Law - McGill University - 1 views

  •  
    See tibi's email, also included in the conversation were Ishan, Kurt, Yasir, Francois, Mai, Soumaya and Genevieve.
Tiberius Brastaviceanu

Is Shame Necessary? | Conversation | Edge - 0 views

  • What is shame's purpose? Is shame still necessary?
  • Shame is what is supposed to occur after an individual fails to cooperate with the group.
  • Whereas guilt is evoked by an individual's standards, shame is the result of group standards. Therefore, shame, unlike guilt, is felt only in the context of other people.
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  • Many animals use visual observations to decide whether to work with others.
  • humans are more cooperative when they sense they're being watched.
  • The feeling of being watched enhances cooperation, and so does the ability to watch others. To try to know what others are doing is a fundamental part of being human
  • Shame serves as a warning to adhere to group standards or be prepared for peer punishment. Many individualistic societies, however, have migrated away from peer punishment toward a third-party penal system
  • Shame has become less relevant in societies where taking the law into one's own hands is viewed as a breach of civility.
  • Many problems, like most concerning the environment, are group problems. Perhaps to solve these problems we need a group emotion. Maybe we need shame.
  • Guilt prevails in many social dilemmas
  • It is perhaps unsurprising that a set of tools has emerged to assuage this guilt
  • Guilt abounds in many situations where conservation is an issue.
  • The problem is that environmental guilt, though it may well lead to conspicuous ecoproducts, does not seem to elicit conspicuous results.
  • The positive effect of idealistic consumers does exist, but it is masked by the rising demand and numbers of other consumers.
  • Guilt is a valuable emotion, but it is felt by individuals and therefore motivates only individuals. Another drawback is that guilt is triggered by an existing value within an individual. If the value does not exist, there is no guilt and hence no action
  • Getting rid of shaming seems like a pretty good thing, especially in regulating individual behavior that does no harm to others. In eschewing public shaming, society has begun to rely more heavily on individual feelings of guilt to enhance cooperation.
  • five thousand years ago, there arose another tool: writing
  • Judges in various states issue shaming punishments,
  • shaming by the state conflicts with the law's obligation to protect citizens from insults to their dignity.
  • What if government is not involved in the shaming?
  • Is this a fair use of shaming? Is it effective?
  • Shaming might work to change behavior in these cases, but in a world of urgent, large-scale problems, changing individual behavior is insignificant
  • vertical agitation
  • Guilt cannot work at the institutional level, since it is evoked by individual scruples, which vary widely
  • But shame is not evoked by scruples alone; since it's a public sentiment, it also affects reputation, which is important to an institution.
  • corporate brand reputation outranked financial performance as the most important measure of success
  • shame and reputation interact
  • in our early evolution we could gauge cooperation only firsthand
  • Shaming, as noted, is unwelcome in regulating personal conduct that doesn't harm others. But what about shaming conduct that does harm others?
  • why we learned to speak.1
  • Language
  • The need to accommodate the increasing number of social connections and monitor one another could be
  • allowed for gossip, a vector of social information.
  • in cooperation games that allowed players to gossip about one another's performance, positive gossip resulted in higher cooperation.
  • Of even greater interest, gossip affected the players' perceptions of others even when they had access to firsthand information.
  • Human society today is so big that its dimensions have outgrown our brains.
  • What tool could help us gossip in a group this size?
  • We can use computers to simulate some of the intimacy of tribal life, but we need humans to evoke the shame that leads to cooperation. The emergence of new tools— language, writing, the Internet—cannot completely replace the eyes. Face-to-face interactions, such as those outside Trader Joe's stores, are still the most impressive form of dissent.
  • what is stopping shame from catalyzing social change? I see three main drawbacks:
  • Today's world is rife with ephemeral, or "one-off," interactions.
  • Research shows, however, that if people know they will interact again, cooperation improves
  • Shame works better if the potential for future interaction is high
  • In a world of one-off interactions, we can try to compensate for anonymity with an image score,
  • which sends a signal to the group about an individual's or institution's degree of cooperation.
  • Today's world allows for amorphous identities
  • It's hard to keep track of who cooperates and who doesn't, especially if it's institutions you're monitoring
  • Shaming's biggest drawback is its insufficiency.
  • Some people have no shame
  • shame does not always encourage cooperation from players who are least cooperative
  • a certain fraction of a given population will always behave shamelessly
  • if the payoff is high enough
  • There was even speculation that publishing individual bankers' bonuses would lead to banker jealousy, not shame
  • shame is not enough to catalyze major social change
  • This is why punishment remains imperative.
  • Even if shaming were enough to bring the behavior of most people into line, governments need a system of punishment to protect the group from the least cooperative players.
  • Today we are faced with the additional challenge of balancing human interests and the interests of nonhuman life.
  •  
    The role of non-rational mechanisms in convergence - social emotions like shame and guilt 
Kurt Laitner

Digital Reality | Edge.org - 0 views

  • When you snap the bricks together, you don't need a ruler to play Lego; the geometry comes from the parts
  • first attribute is metrology that comes from the parts
  • digitizing composites into little linked loops of carbon fiber instead of making giant pieces
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  • In a 3D printer today, what you can make is limited by the size of the machine. The geometry is external
  • is the Lego tower is more accurate than the child because the constraint of assembling the bricks lets you detect and correct errors
  • That's the exponential scaling for working reliably with unreliable parts
  • Because the parts have a discrete state, it means in joining them you can detect and correct errors
  • detect and correct state to correct errors to get an exponential reduction in error, which gives you an exponential increase in complexity
  • The next one is you can join Lego bricks made out of dissimilar materials.
  • The last one is when you're done with Lego you don't put it in the trash; you take it apart and reuse it because there's state in the materials. In a forest there's no trash; you die and your parts get disassembled and you're made into new stuff. When you make a 3D print or laser cut, when you're done there's recycling attempts but there's no real notion of reusing the parts
  • The metrology coming from the parts, detecting and correcting errors, joining dissimilar materials, disconnecting, reusing the components
  • On the very smallest scale, the most exciting work on digital fabrication is the creation of life from scratch. The cell does everything we're talking about. We've had a great collaboration with the Venter Institute on microfluidic machinery to load designer genomes into cells. One step up from that we're developing tabletop chip fab instead of a billion dollar fab, using discrete assembly of blocks of electronic materials to build things like integrated circuits in a tabletop process
  • a child can make a Lego structure bigger than themself
  • There's a series of books by David Gingery on how to make a machine shop starting with charcoal and iron ore.
  • There are twenty amino acids. With those twenty amino acids you make the motors in the molecular muscles in my arm, you make the light sensors in my eye, you make my neural synapses. The way that works is the twenty amino acids don't encode light sensors, or motors. They’re very basic properties like hydrophobic or hydrophilic. With those twenty properties you can make you. In the same sense, digitizing fabrication in the deep sense means that with about twenty building blocks—conducting, insulating, semiconducting, magnetic, dielectric—you can assemble them to create modern technology
  • By discretizing those three parts we can make all those 500,000 resistors, and with a few more parts everything else.
  • Now, there's a casual sense, which means a computer controls something to make something, and then there's the deep sense, which is coding the materials. Intellectually, that difference is everything but now I'm going to explain why it doesn't matter.
  • Then in turn, the next surprise was they weren't there for research, they weren't there for theses, they wanted to make stuff. I taught additive, subtractive, 2D, 3D, form, function, circuits, programming, all of these skills, not to do the research but just using the existing machines today
  • What they were answering was the killer app for digital fabrication is personal fabrication, meaning, not making what you can buy at Walmart, it’s making what you can't buy in Walmart, making things for a market of one person
  • The minicomputer industry completely misread PCs
  • the Altair was life changing for people like me. It was the first computer you could own as an individual. But it was almost useless
  • It was hard to use but it brought the cost from a million dollars to 100,000 and the size from a warehouse down to a room. What that meant is a workgroup could have one. When a workgroup can have one it meant Ken Thompson and Dennis Ritchie at Bell Labs could invent UNIX—which all modern operating systems descend from—because they didn't have to get permission from a whole corporation to do it
  • At the PC stage what happened is graphics, storage, processing, IO, all of the subsystems got put in a box
  • To line that up with fabrication, MIT's 1952 NC Mill is similar to the million-dollar machines in my lab today. These are the mainframes of fab. You need a big organization to have them. The fab labs I'll tell you about are exactly analogous to the cost and complexity of minicomputers. The machines that make machines I'll tell you about are exactly analogous to the cost and complexity of the hobbyist computers. The research we're doing, which is leading up to the Star Trek Replicator, is what leads to the personal fabricator, which is the integrated unit that makes everything
  • conducting, resistive, insulating.
  • The fab lab is 2 tons, a $100,000 investment. It fills a few thousand square feet, 3D scanning and printing, precision machining, you can make circuit boards, molding and casting tooling, computer controlled cutting with a knife, with a laser, large format machining, composite layup, surface mount rework, sensors, actuators, embedded programming— technology to make technology.
  • Ten years you can just plot this doubling. Today, you can send a design to a fab lab and you need ten different machines to turn the data into something. Twenty years from now, all of that will be in one machine that fits in your pocket.
  • We've been living with this notion that making stuff is an illiberal art for commercial gain and it's not part of the means of expression. But, in fact, today, 3D printing, micromachining, and microcontroller programming are as expressive as painting paintings or writing sonnets but they're not means of expression from the Renaissance. We can finally fix that boundary between art and artisans
  • You don't go to a fab lab to get access to the machine; you go to the fab lab to make the machine.
  • Over the next maybe five years we'll be transitioning from buying machines to using machines to make machines. Self-reproducing machines
  • But they still have consumables like the motors, and they still cut or squirt. Then the interesting transition comes when we go from cutting or printing to assembling and disassembling, to moving to discretely assembled materials
  • because if anybody can make anything anywhere, it challenges everything
    • Kurt Laitner
       
      great quote (replace challenges with changes for effect)
  • Now, the biggest surprise for me in this is I thought the research was hard. It's leading to how to make the Star Trek Replicator. The insight now is that's an exercise in embodied computation—computation in materials, programming their construction. Lots of work to come, but we know what to do
  • And that's when you do tabletop chip fab or make airplanes. That's when technical trash goes away because you can disassemble. 
  • irritated by the maker movement for the failure in mentoring
  • At something like a Maker Faire, there's hall after hall of repeated reinventions of bad 3D printers and there isn't an easy process to take people from easy to hard
  • We started a project out of desperation because we kept failing to succeed in working with existing schools, called the Fab Academy. Now, to understand how that works, MIT is based on scarcity. You assume books are scarce, so you have to go there for the library; you assume tools are scarce, so you have to go there for the machines; you assume people are scarce, so you have to go there to see them; and geography is scarce. It adds up to we can fit a few thousand people at a time. For those few thousand people it works really well. But the planet is a few billion people. We're off by six orders of magnitude. 
  • Next year we're starting a new class with George Church that we've called "How to Grow Almost Anything", which is using fab labs to make bio labs and then teach biotech in it. What we're doing is we're making a new global kind of university
  • Amusingly, I went to my friends at Educause about accrediting the Fab Academy and they said, "We love it. Where are you located?" And I said, "Yes" and they said, "No." Meaning, "We're all over the earth." And they said, "We have no mechanism. We're not allowed to do that. There's no notion of global accreditation."
  • Then they said something really helpful: "Pretend."
  • Once you have a basic set of tools, you can make all the rest of the tools
  • The way the Fab Academy works, in computing terms, it's like the Internet. Students have peers in workgroups, with mentors, surrounded by machines in labs locally. Then we connect them globally by video and content sharing and all of that. It's an educational network. There are these critical masses of groups locally and then we connect them globally
  • You still have Microsoft or IBM now but, with all respect to colleagues there, arguably that's the least interesting part of software
  • To understand the economic and social implications, look at software and look at music to understand what's happening now for fabrication
  • There's a core set of skills a place like MIT can do but it alone doesn't scale to a billion people. This is taking the social engineering—the character of MIT—but now doing it on this global scale.
  • Mainframes didn't go away but what opened up is all these tiers of software development that weren't economically viable
  • If you look at music development, the most interesting stuff in music isn't the big labels, it's all the tiers of music that weren't viable before
  • You can make music for yourself, for one, ten, 100, 1,000, a million. If you look at the tracks on your device, music is now in tiers that weren't economically viable before. In that example it's a string of data and it becomes a sound. Now in digital fab, it's a string of data and it becomes a thing.
  • What is work? For the average person—not the people who write for Edge, but just an average person working—you leave home to go to a place you'd rather not be, doing a repetitive operation you'd rather not do, making something designed by somebody you don't know for somebody you'll never see, to get money to then go home and buy something. But what if you could skip that and just make the thing?
    • Kurt Laitner
       
      !!!
  • It took about ten years for the dot com industry to realize pretty much across the board you don't directly sell the thing. You sell the benefits of the thing
  • 2016 it's in Shenzhen because they're pivoting from mass manufacturing to enabling personal fabrication. We've set Shenzhen as the goal in 2016 for Fab Lab 2.0, which is fab labs making fab labs
  • To rewind now, you can send something to Shenzhen and mass manufacture it. There's a more interesting thing you can do, which is you go to market by shipping data and you produce it on demand locally, and so you produce it all around the world.
  • But their point was a lot of printers producing beautiful pages slowly scales if all the pages are different
  • In the same sense it scales to fabricate globally by doing it locally, not by shipping the products but shipping the data.
  • It doesn't replace mass manufacturing but mass manufacturing becomes the least interesting stuff where everybody needs the same thing. Instead, what you open up is all these tiers that weren't viable before
  • There, they consider IKEA the enemy because IKEA defines your taste. Far away they make furniture and flat pack it and send it to a big box store. Great design sense in Barcelona, but 50 percent youth unemployment. A whole generation can't work. Limited jobs. But ships come in from the harbor, you buy stuff in a big box store. And then after a while, trucks go off to a trash dump. They describe it as products in, trash out. Ships come in with products, trash goes out
    • Kurt Laitner
       
      worse actually.. the trash stays
  • The bits come and go, globally connected for knowledge, but the atoms stay in the city.
  • instead of working to get money to buy products made somewhere else, you can make them locally
    • Kurt Laitner
       
      this may solve greece's problem, walk away from debt, you can't buy other people's (country's) stuff anymore, so make it all yourself
  • The biggest tool is a ShotBot 4'x8'x1' NC mill, and you can make beautiful furniture with it. That's what furniture shops use
  • Anything IKEA makes you can make in a fab lab
  • it means you can make many of the things you consume directly rather than this very odd remote economic loop
  • the most interesting part of the DIY phone projects is if you're making a do-it-yourself phone, you can also start to make the things that the phones talk to. You can start to build your own telco providers where the users provide the network rather than spending lots of money on AT&T or whoever
  • Traditional manufacturing is exactly replaying the script of the computer companies saying, "That's a toy," and it's shining a light to say this creates entirely new economic activity. The new jobs don't come back to the old factories. The ability to make stuff on demand is creating entirely new jobs
  • To keep playing that forward, when I was in Barcelona for the meeting of all these labs hosted by the city architect and the city, the mayor, Xavier Trias, pushed a button that started a forty-year countdown to self-sufficiency. Not protectionism
  • I need high-torque efficient motors with integrated lead screws at low cost, custom-produced on demand. All sorts of the building blocks that let us do what I'm doing currently rest on a global supply chain including China's manufacturing agility
  • The short-term answer is you can't get rid of them because we need them in the supply chain. But the long-term answer is Shenzhen sees the future isn't mass producing for everybody. That's a transitional stage to producing locally
  • My description of MIT's core competence is it's a safe place for strange people
  • The real thing ultimately that's driving the fab labs ... the vacuum we filled is a technical one. The means to make stuff. Nobody was providing that. But in turn, the spaces become magnets. Everybody talks about innovation or knowledge economy, but then most things that label that strangle it. The labs become vehicles for bright inventive people who don't fit locally. You can think about the culture of MIT but on this global scale
  • My allegiance isn't to any one border, it's to the brainpower of the planet and this is building the infrastructure to scale to that brainpower
  • If you zoom from transistors to microcode to object code to a program, they don't look like each other. But if we take this room and go from city, state, country, it's hierarchical but you preserve geometry
  • Computation violates geometry unlike most anything else we do
  • The reason that's so important for the digital fabrication piece is once we build molecular assemblers to build arbitrary systems, you don't want to then paste a few lines of code in it. You need to overlay computation with geometry. It's leading to this complete do-over of computer science
  • If you take digital fab, plus the real sense of Internet of Things—not the garbled sense—plus the real future of computing aligning hardware and software, it all adds up to this ability to program reality
  • I run a giant video infrastructure and I have collaborators all over the world that I see more than many of my colleagues at MIT because we're all too busy on campus. The next Silicon Valley is a network, it's not a place. Invention happens in these networks.
  • When Edwin Land was kicked out of Polaroid, he made the Rowland Institute, which was making an ideal research institute with the best facilities and the best people and they could do whatever they want. But almost nothing came from it because there was no turnover of the gene pool, there was no evolutionary pressure.  
  • the wrong way to do research, which is to believe there's a privileged set of people that know more than anybody else and to create a barrier that inhibits communication from the inside to the outside
  • you need evolutionary pressure, you need traffic, you need to be forced to deal with people you don't think you need to encounter, and you need to recognize that to be disruptive it helps to know what people know
  • For me the hardest thing isn't the research. That's humming along nicely. It's that we're finding we have to build a completely new kind of social order and that social entrepreneurship—figuring out how you live, learn, work, play—is hard and there's a very small set of people who can do that kind of organizational creation.
    • Kurt Laitner
       
      our challenge in the OVN space
  •  
    what is heavy is local, what is light is global, and increasingly manufacturing is being recreated along this principle
sebastianklemm

Prof. Dr. Andrea Kruse: University of Hohenheim - 0 views

  •  
    Managing Director of the "Institute of Agricultural Engineering" & Prof.for "Conversion Technologies of Biobased Resources" at University of Hohenheim
Tiberius Brastaviceanu

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

  • 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
       
      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
       
      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
       
      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
       
      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

Why Great Innovations Fail: It's All in the Ecosystem - 0 views

  • “It is no longer enough to manage your innovation. Now you must manage your innovation ecosystem,”
  • example
  • Michelin developed a revolutionary new kind of tire with sensors and an internal hard wheel that could run almost perfectly for 125 miles after a puncture.
  • ...13 more annotations...
  • Yet by 2007 the product was such a failure that Michelin had to abandon it.
  • The company hadn’t confronted the entire ecosystem the tire would rely on
  • conversion costs
  • expensive new equipment
  • legal challenges
  • Mastery of the ecosystem is the great strength that made Apple the supreme success story of our time,
  • The iPod
  • a beginning ecosystem that Jobs enlarged by introducing the iTunes Music Store.
  • the ecosystem further by opening up the Mac-only device to PC users.
  • In a world where mobile phone makers sold their devices to operators to sell to consumers, Jobs had such a powerful ecosystem that he could get operators to compete to partner with him: “And here was Apple, offering not just exclusive access to the most talked-about phone in history, but also exclusive access to Apple consumers—the most desirable customer segment imaginable
  • How do you take the measure of the ecosystem that your innovation will need to be part of and rely on? How do you not miss the blind spots that can lurk almost anywhere?
  • three main steps to take.
  • There are terrible pitfalls in the usual progression from prototype to pilot to rollout. It relies perilously on getting everything right from the very start. Often a far wiser and safer approach can be what Adner calls a “minimum viable footprint (MVF) rollout followed by a staged expansion.” In other words, start with a complete ecosystem, but a limited one.
Tiberius Brastaviceanu

Democrasoft Town Hall Online - 1 views

  •  
    Town Hall meetings are designed to give voice to everyone within a community. Town Hall Online allows any and all members of the community to ask questions, voice their opinions and vote on issues of mutual concern. Discussion topics are self-contained engagement modules that can include attachments like documents, videos, links and more. They provide a written record of the conversation and include the ability for community members to vote and be counted on individual issues. Town Hall Online topics are organized by categories created by community members and/or moderators, which can be modified anytime, as needed. Best of all, with one click, any individual discussion topic can be shared to Facebook, LinkedIn or any of more than 200 social networks, so sharing the discussion with others outside your immediate community is quick, easy and effective. It's the ultimate in building consensus and getting the word out.
Kurt Laitner

Crowding Out - P2P Foundation - 1 views

  • The curve indicates that while workers will initially chose to work more when paid more per hour, there is a point after which rational workers will choose to work less
    • Kurt Laitner
       
      in other words, people are financially motivated until they are financially secure, then other motivations come in
  • "leaders" elsewhere will come and become your low-paid employees
  • At that point, the leaders are no longer leaders of a community, and they turn out to be suckers after all, working for pittance, comparatively speaking
    • Kurt Laitner
       
      so part of the dynamic is that everyone is paid fairly, if not there is the feeling of exploitation
  • ...36 more annotations...
  • under certain structural conditions non-price-based production is extraordinarily robust
    • Kurt Laitner
       
      which are... abundance?
  • There is, in fact, a massive amount of research that supports the idea that when you pay people to do something for you, they stop enjoying it, and distrust their own motivations. The mysterious something that goes away, and that “Factor X” even has a name: intrinsic motivation.
    • Kurt Laitner
       
      the real question though is why, and whether it is the paying them that is the problem, or perhaps how that is determined, and who else gets what on what basis..  if you have to have them question the fairness of the situation, they will likely check out
  • giving rewards to customers can actually undermine a company’s relationship with them
  • It just is not so easy to assume that because people behave productively in one framework (the social process of peer production that is Wikipedia, free and open source software, or Digg), that you can take the same exact behavior, with the same exact set of people, and harness them to your goals by attaching a price to what previously they were doing in a social process.
  • Extrinsic rewards suggest that there is actually an instrumental relationship at work, that you do the activity in order to get something else
  • If you pay me for it, it must be work
    • Kurt Laitner
       
      only because a dichotomy of work and play exists in western culture
  • It’s what we would call a robust effect. It shows up in many contexts. And there’s been considerable testing to try to find out exactly why it works. A major school of thought is that there is an “Overjustification Effect.” (http://kozinets.net/archives/133)
    • Kurt Laitner
       
      yes, why is key
  • interesting examples of an effect called crowding
  • Offering financial rewards for contributions to online communities basically means mixing external and intrinsic motivation.
  • A good example is children who are paid by their parents for mowing the family lawn. Once they expect to receive money for that task, they are only willing to do it again if they indeed receive monetary compensation. The induced unwillingness to do anything for free may also extend to other household chores.
  • Once ‘gold-stars’ were introduced as a symbolic reward for a certain amount of time spent practicing the instrument, the girl lost all interest in trying new, difficult pieces. Instead of aiming at improving her skills, her goal shifted towards spending time playing well-learned, easy pieces in order to receive the award (Deci with Flaste 1995)
    • Kurt Laitner
       
      this is a more troubling example, as playing the harder pieces is also practicing - I would take this as a more complex mechanism at work - perhaps the reinterpretation by the girl that all playing was considered equal, due to the pricing mechanism, in which case the proximal solution would be to pay more for more complex pieces, or for levels of achievement - the question remains of why the extrinsic reward was introduced in the first place (unwillingness to practice as much as her parents wanted?) - which would indicate intrinsic motivation was insufficient in this case
  • Suddenly, she managed to follow the prescription, as her own (intrinsic) motivation was recognized and thereby reinforced.
    • Kurt Laitner
       
      or perhaps the key was to help her fit the medication into her day, which she was having trouble with...
  • The introduction of a monetary fine transforms the relationship between parents and teachers from a non-monetary into a monetary one
    • Kurt Laitner
       
      absolutely, in some sense the guilt of being late is replaced by a rationalization that you are paying them - it is still a rationalization, and parents in this case need to be reminded that staff have lives too to reinforce the moral suasion
  • "The effects of external interventions on intrinsic motivation have been attributed to two psychological processes: (a) Impaired self-determination. When individuals perceive an external intervention to reduce their self-determination, they substitute intrinsic motivation by extrinsic control. Following Rotter (1966), the locus of control shifts from the inside to the outside of the person affected. Individuals who are forced to behave in a specific way by outside intervention, feel overjustified if they maintained their intrinsic motivation. (b) Impaired self-esteem. When an intervention from outside carries the notion that the actor's motivation is not acknowledged, his or her intrinsic motivation is effectively rejected. The person affected feels that his or her involvement and competence is not appreciated which debases its value. An intrinsically motivated person is taken away the chance to display his or her own interest and involvement in an activity when someone else offers a reward, or commands, to undertake it. As a result of impaired self-esteem, individuals reduce effort.
    • Kurt Laitner
       
      these are finally very useful - so from (a) as long as self determination is maintained (actively) extrinsic reward should not shut down intrinsic motivation AND (b) so long as motivations are recognized and reward dimensions OTHER THAN financial continue to operate, extrinsic reward should not affect intrinsic motivation
  • External interventions crowd-out intrinsic motivation if the individuals affected perceive them to be controlling
    • Kurt Laitner
       
      emphasis on "if" and replacing that with "in so far as"
  • External interventions crowd-in intrinsic motivation if the individuals concerned perceive it as supportive
    • Kurt Laitner
       
      interesting footnote
  • In that case, self-esteem is fostered, and individuals feel that they are given more freedom to act, thus enlarging self-determination
    • Kurt Laitner
       
      so effectively a system needs to ensure it is acting on all dimensions of reward, or at least those most important to the particular participant, ego (pride, recognition, guilt reduction, feeling needed, being helpful, etc), money (sustenance, beyond which it is less potent), meaning/purpose etc.  If one ran experiments controlling for financial self sufficiency, then providing appreciation and recognition as well as the introduced financial reward, they might yield different results
  • cultural categories that oppose marketplace modes of behavior (or “market logics”) with the more family-like modes of behavior of caring and sharing that we observe in close-knit communities (”community logics”)
    • Kurt Laitner
       
      are these learned or intrinsic?
  • this is labor, this is work, just do it.
    • Kurt Laitner
       
      except that this cultural meme is already a bias, not a fact
  • When communal logics are in effect, all sorts of norms of reciprocity, sacrifice, and gift-giving come into play: this is cool, this is right, this is fun
    • Kurt Laitner
       
      true, and part of our challenge then is to remove this dichotomy
  • So think about paying a kid to clean up their room, paying parishioners to go to church, paying people in a neighborhood to attend a town hall meeting, paying people to come out and vote. All these examples seem a little strange or forced. Why? Because they mix and match the communal with the market-oriented.
    • Kurt Laitner
       
      and perhaps the problem is simply the conversion to money, rather than simply tracking these activities themselves (went to church 50 times this year!, helped 50 orphans get families!) (the latter being more recognition than reward
  • Payment as disincentive. In his interesting book Freakonomics, economist Steven Levitt describes some counterintuitive facts about payment. One of the most interesting is that charging people who do the wrong thing often causes them to do it more, and paying people to do the right thing causes them to do it less.
    • Kurt Laitner
       
      and tracking them causes them to conform to cultural expectations
  • You direct people _away_ from any noble purpose you have, and instead towards grubbing for dollars
    • Kurt Laitner
       
      and we are left with the challenge, how to work to purpose but still have our scarce goods needs sufficiently provided for?  it has to be for love AND money
  • When people work for a noble purpose, they are told that their work is highly valued. When people work for $0.75/hour, they are told that their work is very low-valued
    • Kurt Laitner
       
      so pay them highly for highly valued labour, and don't forget to recognize them as well... no?
  • you're going to have to fight your way through labour laws and tax issues all the way to bankruptcy
    • Kurt Laitner
       
      this is a non argument, these are just interacting but separate problems, use ether or bitcoin, change legislation, what have you
  • Market economics. If you have open content, I can copy your content to another wiki, not pay people, and still make money. So by paying contributors, you're pricing yourself out of the market.
    • Kurt Laitner
       
      exactly, so use commonsource, they can use it all they want, but they have to flow through benefit (provide attribution, recognition, and any financial reward must be split fairly)
  • You don't have to pay people to do what they want to do anyways. The labour cost for leisure activities is $0. And nobody is going to work on a wiki doing things they don't want to do.
    • Kurt Laitner
       
      wow, exploitative in the extreme - no one can afford to do work for free, it cuts into paid work, family time etc.  if they are passionate about something they will do it for free if they cannot get permission to do it for sustenance, but they still need to sustain themselves, and they are making opportunity cost sacrifices, and if you are in turn making money off of this you are an asshole.. go ahead look in the mirror and say "I am an asshole"
  • No fair system. There's simply no fair, automated and auditable way to divvy up the money
    • Kurt Laitner
       
      this is an utter cop out - figure out what is close enough to fair and iterate forward to improve it, wow
  • too complicated to do automatically. But if you have a subjective system -- have a human being evaluate contributions to an article and portion out payments -- it will be subject to constant challenges, endless debates, and a lot of community frustration.
    • Kurt Laitner
       
      yes to the human evaluation part, but "it's too complicated" is disingenuous at the least
  • Gaming the system. People are really smart. If there's money to be made, they'll figure out how to game your payment system to get more money than they actually deserve
    • Kurt Laitner
       
      yes indeed, so get your metrics right, and be prepared to adjust them as they are gamed - and ultimately, as financial penalties are to BP, even if some people game the system, can we better the gaming of the capitalist system.. it's a low bar I know
  • They'll be trying to get as much money out of you as possible, and you'll be trying to give as little as you can to them
    • Kurt Laitner
       
      it doesn't have to be this way, unless you think that way already
  • If you can't convince people that working on your project is worth their unpaid time, then there's probably something wrong with your project.
    • Kurt Laitner
       
      wow, talk about entrepreneurial taker attitude rationalization
  • People are going to be able to sense that -- it's going to look like a cover-up, something sleazy
    • Kurt Laitner
       
      and getting paid for others free work isn't sleazy, somehow...?
  • Donate.
    • Kurt Laitner
       
      better yet, give yourself a reasonable salary, and give the rest away
  • Thank-you gifts
    • Kurt Laitner
       
      cynical.. here have a shiny bobble you idiot
  • Pay bounties
    • Kurt Laitner
       
      good way to get people to compete ineffectively instead of cooperating on a solution, the lottery mechanism is evil
  •  
    while good issue are brought up in this article, the solutions offered are myopic and the explanations of the observed effects not satisfying
Tiberius Brastaviceanu

The Baffler - 0 views

  • This tendency to view questions of freedom primarily through the lens of economic competition, to focus on the producer and the entrepreneur at the expense of everyone else, shaped O’Reilly’s thinking about technology.
  • the O’Reilly brand essence is ultimately a story about the hacker as hero, the kid who is playing with technology because he loves it, but one day falls into a situation where he or she is called on to go forth and change the world,
  • His true hero is the hacker-cum-entrepreneur, someone who overcomes the insurmountable obstacles erected by giant corporations and lazy bureaucrats in order to fulfill the American Dream 2.0: start a company, disrupt an industry, coin a buzzword.
  • ...139 more annotations...
  • gospel of individualism, small government, and market fundamentalism
  • innovation is the new selfishness
  • mastery of public relations
  • making it seem as if the language of economics was, in fact, the only reasonable way to talk about the subject
  • memes are for losers; the real money is in epistemes.
  • “Open source software” was also the first major rebranding exercise overseen by Team O’Reill
  • It’s easy to forget this today, but there was no such idea as open source software before 1998; the concept’s seeming contemporary coherence is the result of clever manipulation and marketing.
  • ideological cleavage between two groups
  • Richard Stallman
  • Free Software Foundation, preoccupied with ensuring that users had rights with respect to their computer programs. Those rights weren’t many—users should be able to run the program for any purpose, to study how it works, to redistribute copies of it, and to release their improved version (if there was one) to the public
  • “free software.”
  • association with “freedom” rather than “free beer”
  • copyleft
  • profound critique of the role that patent law had come to play in stifling innovation and creativity.
  • Plenty of developers contributed to “free software” projects for reasons that had nothing to do with politics. Some, like Linus Torvalds, the Finnish creator of the much-celebrated Linux operating system, did so for fun; some because they wanted to build more convenient software; some because they wanted to learn new and much-demanded skills.
  • Stallman’s rights-talk, however, risked alienating the corporate types
  • he was trying to launch a radical social movement, not a complacent business association
  • By early 1998 several business-minded members of the free software community were ready to split from Stallman, so they masterminded a coup, formed their own advocacy outlet—the Open Source Initiative—and brought in O’Reilly to help them rebrand.
  • “open source”
  • The label “open source” may have been new, but the ideas behind it had been in the air for some time.
  • In those early days, the messaging around open source occasionally bordered on propaganda
  • This budding movement prided itself on not wanting to talk about the ends it was pursuing; except for improving efficiency and decreasing costs, those were left very much undefined.
  • extremely decentralized manner, using Internet platforms, with little central coordination.
  • In contrast to free software, then, open source had no obvious moral component.
  • “open source is not particularly a moral or a legal issue. It’s an engineering issue. I advocate open source, because . . . it leads to better engineering results and better economic results
  • While free software was meant to force developers to lose sleep over ethical dilemmas, open source software was meant to end their insomnia.
  • Stallman the social reformer could wait for decades until his ethical argument for free software prevailed in the public debate
  • O’Reilly the savvy businessman had a much shorter timeline: a quick embrace of open source software by the business community guaranteed steady demand for O’Reilly books and events
  • The coup succeeded. Stallman’s project was marginalized. But O’Reilly and his acolytes didn’t win with better arguments; they won with better PR.
  • A decade after producing a singular vision of the Internet to justify his ideas about the supremacy of the open source paradigm, O’Reilly is close to pulling a similar trick on how we talk about government reform.
  • much of Stallman’s efforts centered on software licenses
  • O’Reilly’s bet wa
  • the “cloud”
  • licenses would cease to matter
  • Since no code changed hands
  • So what did matter about open source? Not “freedom”
  • O’Reilly cared for only one type of freedom: the freedom of developers to distribute software on whatever terms they fancied.
  • the freedom of the producer
  • who must be left to innovate, undisturbed by laws and ethics.
  • The most important freedom,
  • is that which protects “my choice as a creator to give, or not to give, the fruits of my work to you, as a ‘user’ of that work, and for you, as a user, to accept or reject the terms I place on that gift.”
  • O’Reilly opposed this agenda: “I completely support the right of Richard [Stallman] or any individual author to make his or her work available under the terms of the GPL; I balk when they say that others who do not do so are doing something wrong.”
  • The right thing to do, according to O’Reilly, was to leave developers alone.
  • According to this Randian interpretation of open source, the goal of regulation and public advocacy should be to ensure that absolutely nothing—no laws or petty moral considerations—stood in the way of the open source revolution
  • Any move to subject the fruits of developers’ labor to public regulation
  • must be opposed, since it would taint the reputation of open source as technologically and economically superior to proprietary software
  • the advent of the Internet made Stallman’s obsession with licenses obsolete
  • Many developers did stop thinking about licenses, and, having stopped thinking about licenses, they also stopped thinking about broader moral issues that would have remained central to the debates had “open source” not displaced “free software” as the paradigm du jour.
  • Profiting from the term’s ambiguity, O’Reilly and his collaborators likened the “openness” of open source software to the “openness” of the academic enterprise, markets, and free speech.
  • “open to intellectual exchange”
  • “open to competition”
  • “For me, ‘open source’ in the broader sense means any system in which open access to code lowers the barriers to entry into the market”).
  • “Open” allowed O’Reilly to build the largest possible tent for the movement.
  • The language of economics was less alienating than Stallman’s language of ethics; “openness” was the kind of multipurpose term that allowed one to look political while advancing an agenda that had very little to do with politics
  • highlight the competitive advantages of openness.
  • the availability of source code for universal examination soon became the one and only benchmark of openness
  • What the code did was of little importance—the market knows best!—as long as anyone could check it for bugs.
  • The new paradigm was presented as something that went beyond ideology and could attract corporate executives without losing its appeal to the hacker crowd.
  • What Raymond and O’Reilly failed to grasp, or decided to overlook, is that their effort to present open source as non-ideological was underpinned by a powerful ideology of its own—an ideology that worshiped innovation and efficiency at the expense of everything else.
  • What they had in common was disdain for Stallman’s moralizing—barely enough to justify their revolutionary agenda, especially among the hacker crowds who were traditionally suspicious of anyone eager to suck up to the big corporations that aspired to dominate the open source scene.
  • linking this new movement to both the history of the Internet and its future
  • As long as everyone believed that “open source” implied “the Internet” and that “the Internet” implied “open source,” it would be very hard to resist the new paradigm
  • Telling a coherent story about open source required finding some inner logic to the history of the Internet
  • “If you believe me that open source is about Internet-enabled collaboration, rather than just about a particular style of software license,”
  • everything on the Internet was connected to everything else—via open source.
  • The way O’Reilly saw it, many of the key developments of Internet culture were already driven by what he called “open source behavior,” even if such behavior was not codified in licenses.
  • No moralizing (let alone legislation) was needed; the Internet already lived and breathed open source
  • apps might be displacing the browser
  • the openness once taken for granted is no more
  • Openness as a happenstance of market conditions is a very different beast from openness as a guaranteed product of laws.
  • One of the key consequences of linking the Internet to the world of open source was to establish the primacy of the Internet as the new, reinvented desktop
  • This is where the now-forgotten language of “freedom” made a comeback, since it was important to ensure that O’Reilly’s heroic Randian hacker-entrepreneurs were allowed to roam freely.
  • Soon this “freedom to innovate” morphed into “Internet freedom,” so that what we are trying to preserve is the innovative potential of the platform, regardless of the effects on individual users.
  • Lumping everything under the label of “Internet freedom” did have some advantages for those genuinely interested in promoting rights such as freedom of expression
  • Forced to choose between preserving the freedom of the Internet or that of its users, we were supposed to choose the former—because “the Internet” stood for progress and enlightenment.
  • infoware
  • Yahoo
  • their value proposition lay in the information they delivered, not in the software function they executed.
  • The “infoware” buzzword didn’t catch on, so O’Reilly turned to the work of Douglas Engelbart
  • to argue that the Internet could help humanity augment its “collective intelligence” and that, once again, open source software was crucial to this endeavor.
  • Now it was all about Amazon learning from its customers and Google learning from the sites in its index.
  • The idea of the Internet as both a repository and incubator of “collective intelligence”
  • in 2004, O’Reilly and his business partner Dale Dougherty hit on the idea of “Web 2.0.” What did “2.0” mean, exactly?
  • he primary goal was to show that the 2001 market crash did not mean the end of the web and that it was time to put the crash behind us and start learning from those who survived.
  • Tactically, “Web 2.0” could also be much bigger than “open source”; it was the kind of sexy umbrella term that could allow O’Reilly to branch out from boring and highly technical subjects to pulse-quickening futurology
  • O’Reilly couldn’t improve on a concept as sexy as “collective intelligence,” so he kept it as the defining feature of this new phenomenon.
  • What set Web 2.0 apart from Web 1.0, O’Reilly claimed, was the simple fact that those firms that didn’t embrace it went bust
  • find a way to harness collective intelligence and make it part of their business model.
  • By 2007, O’Reilly readily admitted that “Web 2.0 was a pretty crappy name for what’s happening.”
  • O’Reilly eventually stuck a 2.0 label on anything that suited his business plan, running events with titles like “Gov 2.0” and “Where 2.0.” Today, as everyone buys into the 2.0 paradigm, O’Reilly is quietly dropping it
  • assumption that, thanks to the coming of Web 2.0, we are living through unique historical circumstances
  • Take O’Reilly’s musings on “Enterprise 2.0.” What is it, exactly? Well, it’s the same old enterprise—for all we know, it might be making widgets—but now it has learned something from Google and Amazon and found a way to harness “collective intelligence.”
  • tendency to redescribe reality in terms of Internet culture, regardless of how spurious and tenuous the connection might be, is a fine example of what I call “Internet-centrism.”
  • “Open source” gave us the “the Internet,” “the Internet” gave us “Web 2.0,” “Web 2.0” gave us “Enterprise 2.0”: in this version of history, Tim O’Reilly is more important than the European Union
  • For Postman, each human activity—religion, law, marriage, commerce—represents a distinct “semantic environment” with its own tone, purpose, and structure. Stupid talk is relatively harmless; it presents no threat to its semantic environment and doesn’t cross into other ones.
  • Since it mostly consists of falsehoods and opinions
  • it can be easily corrected with facts
  • to say that Tehran is the capital of Iraq is stupid talk
  • Crazy talk, in contrast, challenges a semantic environment, as it “establishes different purposes and assumptions from those we normally accept.” To argue, as some Nazis did, that the German soldiers ended up far more traumatized than their victims is crazy talk.
  • For Postman, one of the main tasks of language is to codify and preserve distinctions among different semantic environments.
  • As he put it, “When language becomes undifferentiated, human situations disintegrate: Science becomes indistinguishable from religion, which becomes indistinguishable from commerce, which becomes indistinguishable from law, and so on.
  • pollution
  • Some words—like “law”—are particularly susceptible to crazy talk, as they mean so many different things: from scientific “laws” to moral “laws” to “laws” of the market to administrative “laws,” the same word captures many different social relations. “Open,” “networks,” and “information” function much like “law” in our own Internet discourse today.
  • For Korzybski, the world has a relational structure that is always in flux; like Heraclitus, who argued that everything flows, Korzybski believed that an object A at time x1 is not the same object as object A at time x2
  • Our language could never properly account for the highly fluid and relational structure of our reality—or as he put it in his most famous aphorism, “the map is not the territory.”
  • Korzybski argued that we relate to our environments through the process of “abstracting,” whereby our neurological limitations always produce an incomplete and very selective summary of the world around us.
  • nothing harmful in this per se—Korzybski simply wanted to make people aware of the highly selective nature of abstracting and give us the tools to detect it in our everyday conversations.
  • Korzybski developed a number of mental tools meant to reveal all the abstracting around us
  • He also encouraged his followers to start using “etc.” at the end of their statements as a way of making them aware of their inherent inability to say everything about a given subject and to promote what he called the “consciousness of abstraction.”
  • There was way too much craziness and bad science in Korzybski’s theories
  • but his basic question
  • “What are the characteristics of language which lead people into making false evaluations of the world around them?”
  • Tim O’Reilly is, perhaps, the most high-profile follower of Korzybski’s theories today.
  • O’Reilly openly acknowledges his debt to Korzybski, listing Science and Sanity among his favorite books
  • It would be a mistake to think that O’Reilly’s linguistic interventions—from “open source” to “Web 2.0”—are random or spontaneous.
  • There is a philosophy to them: a philosophy of knowledge and language inspired by Korzybski. However, O’Reilly deploys Korzybski in much the same way that the advertising industry deploys the latest findings in neuroscience: the goal is not to increase awareness, but to manipulate.
  • O’Reilly, of course, sees his role differently, claiming that all he wants is to make us aware of what earlier commentators may have overlooked. “A metaphor is just that: a way of framing the issues such that people can see something they might otherwise miss,
  • But Korzybski’s point, if fully absorbed, is that a metaphor is primarily a way of framing issues such that we don’t see something we might otherwise see.
  • In public, O’Reilly modestly presents himself as someone who just happens to excel at detecting the “faint signals” of emerging trends. He does so by monitoring a group of überinnovators that he dubs the “alpha geeks.” “The ‘alpha geeks’ show us where technology wants to go. Smart companies follow and support their ingenuity rather than trying to suppress it,
  • His own function is that of an intermediary—someone who ensures that the alpha geeks are heard by the right executives: “The alpha geeks are often a few years ahead of their time. . . . What we do at O’Reilly is watch these folks, learn from them, and try to spread the word by writing down (
  • The name of his company’s blog—O’Reilly Radar—is meant to position him as an independent intellectual who is simply ahead of his peers in grasping the obvious.
  • “the skill of writing is to create a context in which other people can think”
  • As Web 2.0 becomes central to everything, O’Reilly—the world’s biggest exporter of crazy talk—is on a mission to provide the appropriate “context” to every field.
  • In a fascinating essay published in 2000, O’Reilly sheds some light on his modus operandi.
  • The thinker who emerges there is very much at odds with the spirit of objectivity that O’Reilly seeks to cultivate in public
  • meme-engineering lets us organize and shape ideas so that they can be transmitted more effectively, and have the desired effect once they are transmitted
  • O’Reilly meme-engineers a nice euphemism—“meme-engineering”—to describe what has previously been known as “propaganda.”
  • how one can meme-engineer a new meaning for “peer-to-peer” technologies—traditionally associated with piracy—and make them appear friendly and not at all threatening to the entertainment industry.
  • O’Reilly and his acolytes “changed the canonical list of projects that we wanted to hold up as exemplars of the movement,” while also articulating what broader goals the projects on the new list served. He then proceeds to rehash the already familiar narrative: O’Reilly put the Internet at the center of everything, linking some “free software” projects like Apache or Perl to successful Internet start-ups and services. As a result, the movement’s goal was no longer to produce a completely free, independent, and fully functional operating system but to worship at the altar of the Internet gods.
  • Could it be that O’Reilly is right in claiming that “open source” has a history that predates 1998?
  • Seen through the prism of meme-engineering, O’Reilly’s activities look far more sinister.
  • His “correspondents” at O’Reilly Radar don’t work beats; they work memes and epistemes, constantly reframing important public issues in accordance with the templates prophesied by O’Reilly.
  • Or take O’Reilly’s meme-engineering efforts around cyberwarfare.
  • Now, who stands to benefit from “cyberwarfare” being defined more broadly? Could it be those who, like O’Reilly, can’t currently grab a share of the giant pie that is cybersecurity funding?
  • Frank Luntz lists ten rules of effective communication: simplicity, brevity, credibility, consistency, novelty, sound, aspiration, visualization, questioning, and context.
  • Thus, O’Reilly’s meme-engineering efforts usually result in “meme maps,” where the meme to be defined—whether it’s “open source” or “Web 2.0”—is put at the center, while other blob-like terms are drawn as connected to it.
  • The exact nature of these connections is rarely explained in full, but this is all for the better, as the reader might eventually interpret connections with their own agendas in mind. This is why the name of the meme must be as inclusive as possible: you never know who your eventual allies might be. “A big part of meme engineering is giving a name that creates a big tent that a lot of people want to be under, a train that takes a lot of people where they want to go,”
  • News April 4 mail date March 29, 2013 Baffler party March 6, 2013 Žižek on seduction February 13, 2013 More Recent Press I’ve Seen the Worst Memes of My Generation Destroyed by Madness io9, April 02, 2013 The Baffler’s New Colors Imprint, March 21, 2013
  • There is considerable continuity across O’Reilly’s memes—over time, they tend to morph into one another.
Tiberius Brastaviceanu

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

  • 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
       
      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
       
      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
       
      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
Kurt Laitner

Owning Together Is the New Sharing by Nathan Schneider - YES! Magazine - 0 views

  • VC-backed sharing economy companies like Airbnb and Uber have caused trouble for legacy industries, but gone is the illusion that they are doing it with actual sharing
  • Their main contribution to society has been facilitating new kinds of transactions
  • The notion that sharing would do away with the need for owning has been one of the mantras of sharing economy promoters. We could share cars, houses, and labor, trusting in the platforms to provide. But it’s becoming clear that ownership matters as much as ever.
  • ...30 more annotations...
  • Whoever owns the platforms that help us share decides who accumulates wealth from them, and how
  • Léonard and his collaborators are part of a widespread effort to make new kinds of ownership the new norm. There are cooperatives, networks of freelancers, cryptocurrencies, and countless hacks in between. Plans are being made for a driver-owned Lyft, a cooperative version of eBay, and Amazon Mechanical Turk workers are scheming to build a crowdsourcing platform they can run themselves. Each idea has its prospects and shortcomings, but together they aspire toward an economy, and an Internet, that is more fully ours.
  • Jeremy Rifkin, a futurist to CEOs and governments, contends that the Internet-of-things and 3-D printers are ushering in a “ zero marginal cost society“ in which the “collaborative commons” will be more competitive than extractive corporations
  • once the VC-backed sharing companies clear away regulatory hurdles, local co-ops will be poised to swoop in and spread the wealth
  • People are recognizing that doing business differently will require changing who gets to own what.
  • “We’re moving into a new economic age,” says Marjorie Kelly, who spent two decades at the helm of Business Ethics magazine and now advises social entrepreneurs. “It needs to be sustainable. It needs to be inclusive. And the foundation of what defines an economic age is its form of ownership.”
  • It’s a worker-owned cooperative that produces open-source software to help people practice consensus—though they prefer the term “collaboration”—about decisions that affect their lives.
  • From the start Loomio was part of Enspiral, an “open value network“ of freelancers and social enterprises devoted to mutual support and the common good.
  • a companion tool, CoBudget, to help them allocate resources together
  • The team members recently had to come to terms with the fact that, for the time being, only some of them could be paid for full-time work They called the process “participatory downsizing.”
  • And they can take many forms. Loomio and other tech companies, for instance, are aspiring toward the model of a multi-stakeholder cooperative—one in which not just workers or consumers are voting members, but several such groups at once.
  • Loconomics is a San Francisco-based startup designed, like TaskRabbit, to manage short-term freelance jobs
  • “People who have been without for a long time,” she says, “often operate with a mindset that they can’t share what they have, because they don’t know when that resource will come along again.”
  • As Loconomics prepares to begin operations this winter, it’s running out of the pocket of the founder, Josh Danielson
  • The ambition of a cooperative Facebook or Uber—competitive, widespread, and owned by its community—still seems out of reach for enterprises not willing to sell large parts of themselves to investors. Organizations like 
  • His fellow OuiShare founder Benjamin Tincq is concerned that too much fixation on a particular model will make it hard for well-meaning ventures to be successful. “I like the idea that we don’t need to have a specific legal status,” he says. “It’s more about hacking an existing legal status and making these hacks work.”
  • Fenton’s new undertaking, Sovolve, proposes to “create innovative solutions to accelerate social change,” much as CouchSurfing did, but it’s doing the innovating cautiously. All work is done by worker-owners located around the world. Sovolve uses an internal platform—soon to become a product in its own right—through which contributors decide how much they want to be paid in cash and how much in equity. They can see how much others are earning. Their virtual workplace is gamified, with everyone working to nudge their first product, WonderApp, into virality
  • Loomio’s members use a similar system, which they call Loomio Points. But Sovolve is no cooperative; contributors are not in charge.
  • Open-source software and share-alike licenses have revived the ancient idea of the commons for an Internet age. But the “ commons-based peer production“ that Sensorica seeks to practice doesn’t arise overnight. Just as today’s business culture rests on generations of accumulated law, habit, and training, learning to manage a commons successfully takes time
  • It makes possible decentralized autonomous organizations, or DAOs, which exist entirely on a shared network
  • The most ambitious successor to Bitcoin, Ethereum, has raised more than $15 million in crowdfunding on the promise of creating such a network.
  • all with technology that makes collective ownership a lot easier than a conventional legal structure
  • A project called Eris is developing a collective decision-making tool designed to govern DAOs on Ethereum, though the platform may still be months from release.
  • For now, the burden of reinventing every wheel at once makes it hard for companies like Sensorica and Loomio to compete
  • For instance, Cutting Edge Capital specializes in helping companies raise money through a long-standing mechanism called the direct public investment, or DPO, which allows for small, non-accredited investors.
  • Venture funding may be in competition with Dietz’s cryptoequity vision, but it provides a fearsome head start
  • Co-ops help ensure that the people who contribute to and depend on an enterprise keep control and keep profits, so they’re a possible remedy for worsening economic inequality
  • Sooner or later, transforming a system of gross inequality and concentrated wealth will require more than isolated experiments at the fringes—it will require capturing that wealth and redirecting its flows
  • A less consensual strategy was employed to fund the Catalan Integral Cooperative in Spain; over the course of a few years, one activist borrowed around $600,000 from Spanish banks without paying any of it back.
  • In Jackson, Mississippi, Chokwe Lumumba was elected mayor in 2013 on a platform of fostering worker-owned cooperatives, although much of the momentum was lost when Lumumba died just a few months later.
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