Presentation for Hybrid Days, making the point that we are part of technologies rather than them being part of us, so our technologies (at least the softer and collective ones) are cyborgs.
Presentation from JTEL WinterSchool in Innsbruck, 2010, taking as a starting point that soft technologies such as pedagogies, institutional rules, timetabling methods and so have to be considered as integral to assemblies of learning technologies. This perspective has many interesting consequences.
Brittany Ransom is an artist exploring how technology, nature and social creatures (like people, insects, and dogs) co-exist in today's world, and what we can learn from each other. By using insects, people and their pets, software, electronics and social media, she helps us all explore what it means to be a human in a multi-species world.
In this Hands-On Ideas session, she shares her inspiration, how she goes about her work, what it's revealed, and how you can build on it to explore these ideas more deeply.
The Rise Of Us: Dynamics of Smartmobs (Fall 2008)Kevin Lim
Presented at the University at Buffalo, for "The Wisdom (and Vicissitudes) of Crowds: Web 2.0, Social Networking, and Higher Education" at http://ubtlc.buffalo.edu/workshops/workshop.asp?EventID=776
Presentation from JTEL WinterSchool in Innsbruck, 2010, taking as a starting point that soft technologies such as pedagogies, institutional rules, timetabling methods and so have to be considered as integral to assemblies of learning technologies. This perspective has many interesting consequences.
Brittany Ransom is an artist exploring how technology, nature and social creatures (like people, insects, and dogs) co-exist in today's world, and what we can learn from each other. By using insects, people and their pets, software, electronics and social media, she helps us all explore what it means to be a human in a multi-species world.
In this Hands-On Ideas session, she shares her inspiration, how she goes about her work, what it's revealed, and how you can build on it to explore these ideas more deeply.
The Rise Of Us: Dynamics of Smartmobs (Fall 2008)Kevin Lim
Presented at the University at Buffalo, for "The Wisdom (and Vicissitudes) of Crowds: Web 2.0, Social Networking, and Higher Education" at http://ubtlc.buffalo.edu/workshops/workshop.asp?EventID=776
Marshal McLuhan said that we shape our tools and then they shape us. This is the imperative for attending to information literacy and technology fluency in education.
A presentation given at the conference on international media at Fachhochschule St Pölten in Austria on 25 March 2013. It's inspired by and based on this RSA Animate video of a talk by Manuel Lima:
https://www.youtube.com/watch?v=nJmGrNdJ5Gw
After Gutenberg: The Tradition of Authenticity in a New Agecgering
The shift from an oral to a written tradition also created a shift from the synchronous to the asynchronous. What if our reliance on the reproduction of written (and recorded) communication really was just a technologically-informed meander—the "Gutenberg Parenthesis"—a necessary diversion on the way to a whole new tradition that demands a new kind of literacy? The popularity and availability of cell phones, iPods, and internet access, combined with social tools like facebook, mySpace, and YouTube have resulted in a Renaissance…full of opportunity and danger that make it more critical than ever that we not forget the past while we forge this new future.
How to Prevent & Overcome Digital Extinction - Digital EvolutionAndrea Vascellari
5 practical tips on how to prevent and eventually overcome 5 of the most frequent causes of digital extinction that brands, organizations and at times also individuals are facing today.
120 9The Language of Internet MemesPat r i c k DCicelyBourqueju
120 |
9
The Language of Internet Memes
Pat r i c k D av i s o n
In The Future of the Internet—and How to Stop It, Jonathan Zittrain
describes the features of a generative network. A generative network encour-
ages and enables creative production and, as a system, possesses leverage,
adaptability, ease of mastery, accessibility, and transferability.1 Notably absent
from this list of characteristics, however, is security. Many of the character-
istics that make a system generative are precisely the same ones that leave it
vulnerable to exploitation. This zero-sum game between creativity and secu-
rity implies a divided Internet. Those platforms and communities which value
security over creativity can be thought of as the “restricted web,” while those
that remain generative in the face of other concerns are the “unrestricted web.”
The restricted web has its poster children. Facebook and other social net-
working sites are growing at incredible speeds. Google and its ever-expand-
ing corral of applications are slowly assimilating solutions to all our com-
puting needs. Amazon and similar search-based commerce sites are creating
previously unimagined economies.2 Metaphorically, these sites, and count-
less others, make up the cities and public works of the restricted web. How-
ever, the unrestricted web remains the wilderness all around them, and it is
this wilderness that is the native habitat of Internet memes.
The purpose of this essay is twofold. The first is to contribute to a frame-
work for discussing so-called Internet memes. Internet memes are popular
and recognizable but lack a rigorous descriptive vocabulary. I provide a few
terms to aid in their discussion. The second purpose is to consider Foucault’s
“author function” relative to Internet memes, many of which are created and
spread anonymously.
What Is an Internet Meme?
In 1979 Richard Dawkins published The Selfish Gene, in which he discredits
the idea that living beings are genetically compelled to behave in ways that
are “good for the species.” Dawkins accomplishes this by making one point
The Language of Internet Memes | 121
clear: the basic units of genetics are not species, families, or even individuals
but rather single genes—unique strands of DNA.3
At the end of the book, Dawkins discusses two areas where evolutionary
theory might be heading next. It is here that he coins the term “meme.” He
acknowledges that much of human behavior comes not from genes but from
culture. He proposes that any nongenetic behavior be labeled as a meme and
then poses a question: can the application of genetic logic to memes be pro-
ductive? To make the differences between genes and memes clear, I offer a
short example of each.
Genes determine an organism’s physical characteristics. A certain gene
causes an organism to have short legs, or long, for instance. Imagine two
zebra. The first has the short-leg gene, and the second the long. A lion attacks
them. The shor ...
120 9The Language of Internet MemesPat r i c k DBenitoSumpter862
120 |
9
The Language of Internet Memes
Pat r i c k D av i s o n
In The Future of the Internet—and How to Stop It, Jonathan Zittrain
describes the features of a generative network. A generative network encour-
ages and enables creative production and, as a system, possesses leverage,
adaptability, ease of mastery, accessibility, and transferability.1 Notably absent
from this list of characteristics, however, is security. Many of the character-
istics that make a system generative are precisely the same ones that leave it
vulnerable to exploitation. This zero-sum game between creativity and secu-
rity implies a divided Internet. Those platforms and communities which value
security over creativity can be thought of as the “restricted web,” while those
that remain generative in the face of other concerns are the “unrestricted web.”
The restricted web has its poster children. Facebook and other social net-
working sites are growing at incredible speeds. Google and its ever-expand-
ing corral of applications are slowly assimilating solutions to all our com-
puting needs. Amazon and similar search-based commerce sites are creating
previously unimagined economies.2 Metaphorically, these sites, and count-
less others, make up the cities and public works of the restricted web. How-
ever, the unrestricted web remains the wilderness all around them, and it is
this wilderness that is the native habitat of Internet memes.
The purpose of this essay is twofold. The first is to contribute to a frame-
work for discussing so-called Internet memes. Internet memes are popular
and recognizable but lack a rigorous descriptive vocabulary. I provide a few
terms to aid in their discussion. The second purpose is to consider Foucault’s
“author function” relative to Internet memes, many of which are created and
spread anonymously.
What Is an Internet Meme?
In 1979 Richard Dawkins published The Selfish Gene, in which he discredits
the idea that living beings are genetically compelled to behave in ways that
are “good for the species.” Dawkins accomplishes this by making one point
The Language of Internet Memes | 121
clear: the basic units of genetics are not species, families, or even individuals
but rather single genes—unique strands of DNA.3
At the end of the book, Dawkins discusses two areas where evolutionary
theory might be heading next. It is here that he coins the term “meme.” He
acknowledges that much of human behavior comes not from genes but from
culture. He proposes that any nongenetic behavior be labeled as a meme and
then poses a question: can the application of genetic logic to memes be pro-
ductive? To make the differences between genes and memes clear, I offer a
short example of each.
Genes determine an organism’s physical characteristics. A certain gene
causes an organism to have short legs, or long, for instance. Imagine two
zebra. The first has the short-leg gene, and the second the long. A lion attacks
them. The shor ...
An overview of current Augmented Reality (AR) technology and potential future applications in libraries. Researched and presented to 9410: Emerging Technologies in Fall 2012 at the University of Missouri School of Information Science and Learning Technologies (SISLT).
Slides from the 3rd International Seminar on Online Higher Education in Management, Santiago, Chile, October 2016. A 20 minute presentation intended to end in questions, the biggest of which being, in an age of plenty, with options for distributed content, distributed connections, distributed accreditation, and tools for personal sense making, whether there is a need for universities and other formal educational institutions any more. Unsurprisingly, the consensus among participants was a slightly equivocal 'yes'. However, thinking more deeply about the nature of those institutions, participants considered ways institutions can become network hubs with blurred boundaries, ways they might continue to preserve/transform culture, and ways they might focus more deeply on values, creativity, meaning, critical thinking, etc. Some great dialogues emerged.
Marshal McLuhan said that we shape our tools and then they shape us. This is the imperative for attending to information literacy and technology fluency in education.
A presentation given at the conference on international media at Fachhochschule St Pölten in Austria on 25 March 2013. It's inspired by and based on this RSA Animate video of a talk by Manuel Lima:
https://www.youtube.com/watch?v=nJmGrNdJ5Gw
After Gutenberg: The Tradition of Authenticity in a New Agecgering
The shift from an oral to a written tradition also created a shift from the synchronous to the asynchronous. What if our reliance on the reproduction of written (and recorded) communication really was just a technologically-informed meander—the "Gutenberg Parenthesis"—a necessary diversion on the way to a whole new tradition that demands a new kind of literacy? The popularity and availability of cell phones, iPods, and internet access, combined with social tools like facebook, mySpace, and YouTube have resulted in a Renaissance…full of opportunity and danger that make it more critical than ever that we not forget the past while we forge this new future.
How to Prevent & Overcome Digital Extinction - Digital EvolutionAndrea Vascellari
5 practical tips on how to prevent and eventually overcome 5 of the most frequent causes of digital extinction that brands, organizations and at times also individuals are facing today.
120 9The Language of Internet MemesPat r i c k DCicelyBourqueju
120 |
9
The Language of Internet Memes
Pat r i c k D av i s o n
In The Future of the Internet—and How to Stop It, Jonathan Zittrain
describes the features of a generative network. A generative network encour-
ages and enables creative production and, as a system, possesses leverage,
adaptability, ease of mastery, accessibility, and transferability.1 Notably absent
from this list of characteristics, however, is security. Many of the character-
istics that make a system generative are precisely the same ones that leave it
vulnerable to exploitation. This zero-sum game between creativity and secu-
rity implies a divided Internet. Those platforms and communities which value
security over creativity can be thought of as the “restricted web,” while those
that remain generative in the face of other concerns are the “unrestricted web.”
The restricted web has its poster children. Facebook and other social net-
working sites are growing at incredible speeds. Google and its ever-expand-
ing corral of applications are slowly assimilating solutions to all our com-
puting needs. Amazon and similar search-based commerce sites are creating
previously unimagined economies.2 Metaphorically, these sites, and count-
less others, make up the cities and public works of the restricted web. How-
ever, the unrestricted web remains the wilderness all around them, and it is
this wilderness that is the native habitat of Internet memes.
The purpose of this essay is twofold. The first is to contribute to a frame-
work for discussing so-called Internet memes. Internet memes are popular
and recognizable but lack a rigorous descriptive vocabulary. I provide a few
terms to aid in their discussion. The second purpose is to consider Foucault’s
“author function” relative to Internet memes, many of which are created and
spread anonymously.
What Is an Internet Meme?
In 1979 Richard Dawkins published The Selfish Gene, in which he discredits
the idea that living beings are genetically compelled to behave in ways that
are “good for the species.” Dawkins accomplishes this by making one point
The Language of Internet Memes | 121
clear: the basic units of genetics are not species, families, or even individuals
but rather single genes—unique strands of DNA.3
At the end of the book, Dawkins discusses two areas where evolutionary
theory might be heading next. It is here that he coins the term “meme.” He
acknowledges that much of human behavior comes not from genes but from
culture. He proposes that any nongenetic behavior be labeled as a meme and
then poses a question: can the application of genetic logic to memes be pro-
ductive? To make the differences between genes and memes clear, I offer a
short example of each.
Genes determine an organism’s physical characteristics. A certain gene
causes an organism to have short legs, or long, for instance. Imagine two
zebra. The first has the short-leg gene, and the second the long. A lion attacks
them. The shor ...
120 9The Language of Internet MemesPat r i c k DBenitoSumpter862
120 |
9
The Language of Internet Memes
Pat r i c k D av i s o n
In The Future of the Internet—and How to Stop It, Jonathan Zittrain
describes the features of a generative network. A generative network encour-
ages and enables creative production and, as a system, possesses leverage,
adaptability, ease of mastery, accessibility, and transferability.1 Notably absent
from this list of characteristics, however, is security. Many of the character-
istics that make a system generative are precisely the same ones that leave it
vulnerable to exploitation. This zero-sum game between creativity and secu-
rity implies a divided Internet. Those platforms and communities which value
security over creativity can be thought of as the “restricted web,” while those
that remain generative in the face of other concerns are the “unrestricted web.”
The restricted web has its poster children. Facebook and other social net-
working sites are growing at incredible speeds. Google and its ever-expand-
ing corral of applications are slowly assimilating solutions to all our com-
puting needs. Amazon and similar search-based commerce sites are creating
previously unimagined economies.2 Metaphorically, these sites, and count-
less others, make up the cities and public works of the restricted web. How-
ever, the unrestricted web remains the wilderness all around them, and it is
this wilderness that is the native habitat of Internet memes.
The purpose of this essay is twofold. The first is to contribute to a frame-
work for discussing so-called Internet memes. Internet memes are popular
and recognizable but lack a rigorous descriptive vocabulary. I provide a few
terms to aid in their discussion. The second purpose is to consider Foucault’s
“author function” relative to Internet memes, many of which are created and
spread anonymously.
What Is an Internet Meme?
In 1979 Richard Dawkins published The Selfish Gene, in which he discredits
the idea that living beings are genetically compelled to behave in ways that
are “good for the species.” Dawkins accomplishes this by making one point
The Language of Internet Memes | 121
clear: the basic units of genetics are not species, families, or even individuals
but rather single genes—unique strands of DNA.3
At the end of the book, Dawkins discusses two areas where evolutionary
theory might be heading next. It is here that he coins the term “meme.” He
acknowledges that much of human behavior comes not from genes but from
culture. He proposes that any nongenetic behavior be labeled as a meme and
then poses a question: can the application of genetic logic to memes be pro-
ductive? To make the differences between genes and memes clear, I offer a
short example of each.
Genes determine an organism’s physical characteristics. A certain gene
causes an organism to have short legs, or long, for instance. Imagine two
zebra. The first has the short-leg gene, and the second the long. A lion attacks
them. The shor ...
An overview of current Augmented Reality (AR) technology and potential future applications in libraries. Researched and presented to 9410: Emerging Technologies in Fall 2012 at the University of Missouri School of Information Science and Learning Technologies (SISLT).
Slides from the 3rd International Seminar on Online Higher Education in Management, Santiago, Chile, October 2016. A 20 minute presentation intended to end in questions, the biggest of which being, in an age of plenty, with options for distributed content, distributed connections, distributed accreditation, and tools for personal sense making, whether there is a need for universities and other formal educational institutions any more. Unsurprisingly, the consensus among participants was a slightly equivocal 'yes'. However, thinking more deeply about the nature of those institutions, participants considered ways institutions can become network hubs with blurred boundaries, ways they might continue to preserve/transform culture, and ways they might focus more deeply on values, creativity, meaning, critical thinking, etc. Some great dialogues emerged.
Keynote slides from Segundo Coloquio Nacional de Educación Media Superior a Distancia, in Mexico, 2011, discussing the dance and coevolution of technologies (including pedagogies) that has led to the emerging connectivist model of distance learning. The presentation looks beyond this to a holist model of distance learning that embodies collective and set entities as well as networks and groups.
Revealing the elephant in the online classroomjondron
Pedagogies as technologies, soft and hard technologies, benefits of soft technologies for learning (spoiler - the elephant is the teacher, not the technical process of teaching)
Presentation for TENCompetence Winter School 2009 looking at principles for creating social software to support learning, using collective processes to take on some teacher roles.
4. cyborg
“creatures simultaneously
animal and machine, who
populate worlds ambiguously
natural and crafted” (Donna
Haraway, A Cyborg Manifesto)
5. everything you need to know about this presentation,
for the time-poor
(most) humans are not part-
technology
(most) technology is part-human
(literally, not metaphorically)
12. Collective types
e.g. ant nest tidying
e.g. termites, ant trails,
money markets
Wikipedia edits
e.g. flocks, shoals, herds, direct stigmergic
e.g. 2nd Life
crowds mediated e.g., tag clouds, Google Search
e.g.reputation systems, rating systems, collaborative filters
13. Control in social
systems
Collective control
Individual Negotiated Publisher
control control control
Ownership, collaboration, hierarchies,
autonomy dialogue structure
Cooperation, sharing
22. Effective collectives
1. Adaptability
6. Sociability
2. Stigmergy 7. Constraint
3. Evolvability 8. Context
4. Parcellation 9. Connectivity
10. Scale
5. Trust
Dron, J. (2007). Control and Constraint in E-Learning: Choosing When to Choose. Hershey, PA: Idea Group International.
26. technology
“the orchestration of phenomena for some
use”
(W. Brian Arthur)
Arthur, W. B. (2009). The Nature of Technology: what it is and how it evolves. New York, USA: Free Press.
28. All technologies
are assemblies
http://upload.wikimedia.org/wikipedia/commons/a/a1/Heath_Robinson_WWI.png
By W. Heath Robinson, via Wikimedia Commons
39. Artificial apes
Our technologies are not just reflections of us or
things that we use. They are, in part or in whole,
made of us
40. Good cyborg/bad
cyborg
• humans are part of technologies
and humans are in control
• humans are part of
technologies and technologies
are in control
41. some danger signs that a
technology is too hard
• rules that cannot be broken
• easy paths
• ‘the computer says no’
42. some danger signs that a
technology is too soft
• repetition of boring tasks
• the need for skill
• complexity and puzzlement
Technologies, as W. Brian Arthur observes, involve the orchestration of phenomena to some use. Sometimes that orchestration is pre-decided and embedded in the technology itself, being built into the fabric of physical machines, software, rules and laws: factories, legal systems, and railways for example. These I describe as hard technologies. Sometimes, the orchestration is more like a jazz improvisation that we, to a greater or lesser extent, make up as we go along: language, computers, wikis and screwdrivers, for example, can be used for myriad purposes and orchestrate myriad phenomena. These I describe as soft technologies.\nSoftness and hardness depends upon your point of view and the context in which you view the technology. A computer is soft for a programmer, hard for the user of an ATM, for example. Neither is suitable in all cases. Soft technologies give creativity and flexibility, but at the cost of effort and active invention: soft approaches to washing clothes, for example, mean that it takes a day to do what it would take a few minutes to do with a washer-dryer. Hard technologies give efficiency, speed, and freedom from error, but at the cost of creativity and flexibility. Soft is hard, hard is easy. Ideally, we should be able to choose how soft or hard our technologies are depending on our contextual needs.\nAll technologies are assemblies and almost all, in a given context, contain a mixture of soft and hard. Humans are not just users of soft technologies but are a part of them: they are the orchestrators who play an active and continuing role in their creation. In a sense, therefore, almost all technologies are cybernetic organisms, cyborgs, a blend of human and machine.Meanwhile, through applications of collective intelligence such as Google Search's PageRank, tag clouds, wikis or collaborative filters that recommend things to us based on the actions of the crowd, the actions of people are combined with algorithms in order to create a single actor, an entity that does work and that influences how individuals behave. Thus we are not only parts of machines as individuals but also as collectives. But, depending on algorithms and interaction designs, collectives are as likely to embody stupid mobs as they are wise crowds.This cyborg amalgam of human and technology is as old as humanity itself: from the moment we began to talk or extract grubs with sticks, we have been a part of technology and it has been a part of us. However, thanks to the efflorescence of adjacent possibilities that emerge with each new technology, the technological assemblies of which we are a part inevitably become more complex and interconnected at an ever-increasing speed. Our potential for good and our potential for bad increases at the same rate, and the ways we exist as humans can become more machine or more human. Unless we are in control of the softness and hardness of our cyborg bodies and unless we design the collectives of which we are a part to be wise, we can become either cogs in a machine or victims of emergence in which we are the unconscious and unwilling creators of our own nightmares. In this conference we will be exploring ways to enable our inevitable and unstoppable co-evolution as cybernetic organisms that enhance and enable control of our own destinies.\n
\n
a useful fact to remember\n
\n
\n
examples of collectives. note not all involving computers\n recommender systems\n voting in elections\n crowds gathering on the street\n social navigation and stigmergy\n termites\n
collectives in the sense of the borg - set of agents linked that act in some ways as single entity. \n
a closer look. \ne.g. crowd: sees other crowd - if there is a crowd, join it - be part of crowd - others join\ne.g. tag cloud: collect tags for group - aggregate and normalise weights - weed out the old ones - display in different font sizes\ne.g. CF: collect user behaviour re resources - identify similarities - display recommendations\nnote feedback loop - may be mined by different crowd or individual but most interesting when affects the original crowd\nnote collective is entity: may be part of the crowd\n
\n
\n
\n
\n
\n
\n
\n
\n
flickr 2 years apart. almost the same\nbut note temporal parcellation - hot tags\nThe rich get richer while the poor get poorer\n
simpy and del.icio.us - note enormous similarity of tags - even down to weighting\nactually, simpy users are often disaffected delicious users but - uncanny\ninsufficient parcellation\n
Still a big issue: this is from FLickr top tags from last 24 hours - seems to be spam-ads - note different user names. note bizarre sponsored results!\n
how much do I want to share?\n need for fine-grained control over what i reveal of myself to who and when\n
Technological...\n RSS\n JSON\n RLOs\n ELF/OKI\nlearn from the learners\nprepare for change\n\nit will happen - use it\nsignposts, not fenceposts\n\ndeferred design\nexaptions\nreplication and variation\ndeath as a teacher\n\nscale\nislands and isthmuses\n\nsoft and hard security\ntechnical reliability\ncontrollable access\ntransparency\nidentity\n\nawareness of others\nmultiple channels\ndialogue\n\nwhat shape is a learning environment? What rules?\nmeaningful signposts\n\nself-organising - only a learning environment if it contains motivated learners\nlarge and slow moving provide constraint\n\n\neverything and everyone connected\n\n\nmultiple scales - large and slow influence small and fast\nhierarchies\n
\n
a screwdriver is a single tool, but it can be many technologies. This is an important distinction. \n
the same tool can be many technologies. The screwdriver is a different technology if it is used to stir pain than if it is used to tighten a screw\nto a computer programmer, a sales terminal is a soft device that can become whatever he or she wants it to be. for a sales assistant, it is a hard technology that forces one kind of behaviour (‘the computer says no’). The same tool is orchestrating different phenomena for different purposes \n
\n
ursula franklin notes there are as much technologies of prayer as of electronics and metallurgy. it aint what you do it’s the way that you do it. Laws and legal systems are technologies.\n
and that’s how they evolve - not so much adaptation and new innovation (though that happens) but mainly by mixing and mashing. So technologies are made of technologies - again, it depends on your point of view which level you look at things. A transport system is a technology, as is a car, as are rules of the road, as is a car radio. All are part of a whole.\n
soft technologies are flexible, allowing people to be creative. paint brushes and paint are soft technologies that can be used in many ways.\n
hard technologies reduce choices \n\norchestration of phenomena embedded in rules, laws, physical parts etc - e.g. automatic transmission vs manual transmission\n
hard technologies have their processes embedded - may be laws or rules or part of the software or hardware - \nnotably, LMSs embed implicit pedagogies\n\nhard technologies tell us what to do - they reduce choices. So, they make things easy. and reliable, fast, free from error\n
the orchestration is part of the technology so a hard technology is complete\n
\n
by which I mean soft technologies are more difficult (and unreliable, slow)\n\nWe have to invent social technologies and to literally be a part of them\n\nSofter technologies increase the adjacent possible by enabling and/or making more likely new choices to be made. They enable creativity\n\nMore choices come at a price - we have to make them. That is one thing that makes them difficult or hard.\n\n
we have to find ways to use soft technologies - without the parts we add, they are not technologies at all, just tools waiting for something to happen\n
because many different things can happen, we can orchestrate phenomena in many ways, so soft technologies are flexible\n
people do. it’s a dance, and we are the partners to technologies\n
The general principles of softening involve making things adaptable, using signposts rather than fence posts, opening up new uses and, above all, aggregating: adding new technologies to increase the adjacent possible. These may involve automation but, if so, not involving the loss of previous capacities.\nTo harden typically involves automation of things that were formerly manual but not just automation per se - it has to replace something softer. Automation that forces a particular way of doing things is hard. Filtering means removing of possibilities (good example: adaptive systems that only show what they think is relevant, rather than those that suggest possible alternatives or highlight things of value). Hard technologies explicitly limit choices.\n
\n
\n
\n
\n
\n
Mashing up is the most effective method of making systems as hard or soft as needed\n