Newmedia6

Lecture 6

Embodied cogni1on in digital ecosystems

If we described liquid architecture as a symphony in space, this descrip5on should s5ll fall short of the promise. A symphony, though it varies within its dura5on, is s5ll a fixed object and can be repeated. At its fullest expression a liquid architecture is more than that. It is a symphony of space, but a symphony that never repeats and con8nues to develop. If architecture is an extension of our bodies, shelter and actor for the fragile self, a liquid architecture is that self in the act of becoming its own changing shelter.

Marcos Novak

Topics

•  How ecology concepts may be used in new media environments?

•  Func1oning of digital ecosystems

•  Embodied cogni1on in digital ecosystems

Essay topics

•  Digital ecosystem – a fer1le metaphor or the new type of ecosystem that uses ecological principles?

•  In this empirical essay you should describe how you conceptualize digital ecosystem concept using the examples from new media environments.

Ecologies and ecosystems

•  The terms of “ecology” (a discipline) and “ecosystem” (a system) are oGen misused as synonyms of each other to describe such knowledge building that is facilitated by new media technologies.

•  Another issue is ‐ can we use these terms merely as metaphors taken from biological systems, or are the ecological principles fully applicable to the new media systems?

Informa1on ecology ‐ metaphorical

•  The biological human‐centred understanding of informa:on systems, (Davenport and Prusack, 1997, p. 11) has primarily used the informa:on ecology as a metaphorical term to capture holis:c and human‐centred management of informa:on.

•  The term “ecology” is used because it is one of the most expressive language currently has to indicate the massive and dynamic interrela:on of processes and objects, beings and things, pa@erns and ma@er (Fuller, 2005, p.2).

Knowledge ecology ‐ metaphorical

•  The knowledge ecology term marks the rapidly developing area that binds knowledge crea:on and u:liza:on with the social and management aspects in human networks (Pór & Malloy, 2000; Pór & Spivak, 2000).


•  G. Siemens published a book “Knowing Knowledge” (2006) captures a new knowledge ecology vision.

•  Siemens (2006) wrote in his book Knowing Knowledge that Connec1vism is a staged view of how individuals encounter and explore knowledge in a networked/ecological manner.


•  The central concepts Siemens discusses are: knowledge, learning, spaces, networks and knowledge ecologies.

•  However, the Connec:vism framework is inconsistent in elabora:ng the ecological role of tools, ac:vi:es, and communi:es in the forma:on and evolvement of knowledge ecologies.

Knowledge ecology ‐ metaphorical •  Ecology is a knowledge‐sharing environment (p. 87).

•  Networks occur within ecologies. Ecology is a living organism. It influences the forma5on of the network itself. (p. 92).

•  Ecologies and networks provide the solu5on to needed structures and spaces to house and facilitate knowledge flow (p. 86).

G. Siemens, book “Knowing Knowledge” (2006)

Knowledge ecology ‐ metaphorical •  Our mind is a network… and ecology. It adapts to the environment (p. 27).

•  Individuals are ac5ve in the learning ecology/space in terms of consuming or acquiring new resources and tools (2006, p. 45)

•  The health of each personal learning network is influenced by the suitability of the ecology in which the learner exists (p. 92).



•  The ecology fosters connec5ons to original and knowledge sources, allowing for currency.

•  The ecology fosters rich interac8on between disparate fields of knowledge, allowing growth and adapta8on of ideas and concepts.

•  Each par5cipant in the ecology pursues his/her own objec5ves, but within the organized domain of knowledge of a par5cular field (p. 117).



•  Ecologies permit diverse, mul5‐faceted concepts… and meanings to emerge based on how items are organized or self‐organize (p. 87).

•  Ecologies are nurtured and fostered…instead of constructed, organized and mandated (p. 90).

•  Ecologies are: loose, free, dynamic, adaptable, messy, and chao5c (p. 90).

•  Ecology is a living organism (p. 92).


Media ecology ‐ metaphorical •  Book “Media Ecologies” is an analysis of the determinates of radio, telephones, cameras, surveillance, computa1onal media, and networks.

•  Media ecology term refers to the business‐oriented discussions of media and informa:on management (e.g. 1me management processes, intellectual property regimes, database and soGware design, content control, access structuring, metadata, archiving, and the use and genera1on of new document and informa1on types).

•  “Media ecology” describes a kind of environmentalism: using a study of media to sustain a rela1vely stable no1on of human culture.

Fuller, Ma`hew. Book (2005). Media ecologies : materialist energies in art and technoculture

Can we use ecology principles explaining new media systems?

Transla1ng from ecology concepts

Personal environment

Community as a kind of species

Personal network

Associa1ons of communi1es

Digital ecosystem = technology, people, ar1facts

Person as an individual of a community

System levels in digital ecologies

Interac1ons of individuals and environments

Learner and personal places

Learner and PLE

Learner and network

Learner and community

Learner and digital ecosystem

Interac1ons of a community and its

environment

Interac1ons in the community

Community and its digital habitat

Community and its niche

Interac1ons in associated

communi1es and ecosystems

Self‐organiza1on in associated

communi1es and digital ecosystems

Interac1ons between

communi1es in associated communi1es

I. Behavioral digital ecology

•  Studies: –  interac1ons of individuals with digital habitats For example the PLE studies.

– adap1veness of digital behavior •  Niche crea1on •  Fitness to the niches •  Naviga1on in niches such as swarming

PLEs in digital ecosystem

•  Personal learning environments (PLEs) that people construct and use in their daily ac1vi1es are not merely the mediators, ‘the inac1ve pipes’ that enable knowledge flow.

•  PLEs are dynamically evolving ac:vity systems in which the personal objec:ves and human and material resources are integrated in the course of ac1on.

•  PLE is also distributed ecologically, integra:ng our minds with the environment.

PLE as our way for taking ac1on

Ecological ac1on control •  Hommel (2003), has wrièn that ac:on control to all behavioral acts is ecologically delegated to the environment ‐ when planning ac1ons in terms of an1cipated goals, the sensory‐motor assemblies needed to reach the goal are simultaneously selec:vely ac:vated in the environment, and bind together into a coherent whole that serves as an ac:on‐plan, facilita1ng the execu1on of the goal‐directed ac1ons through the interac1on between the environment and its embodied sensory‐motor ac1va1ons.

An embedded ac1on cue delegated to the environment

PLE as our way for taking ac1on

•  We actualize certain dimensions from the environment around us integra:ng it to the ac:on‐plans, and simultaneously the environment extends certain dimensions to us changing and shaping our inten:ons.

•  The “network” (as referred by Siemens, 2005) in the ecological framework may be interpreted as a distributed system con:nuously constructed of our minds and the environment components.

Embodied cogni1on

•  Varela, Thompson & Rosch (1991, p. 149) wrote that knowledge is the result of ongoing interpreta:on that emerges from our capaci:es of understanding.

•  These capaci1es are rooted in the structures of our biological embodiment but are lived and experienced within a domain of consensual ac:on and cultural history.

Varela, F. J., Thompson, E. & Rosch, E. (1991) The Embodied Mind. Cambridge, MA: MIT Press.

Embodied cogni1on

•  Using the term enac5on they focused on two points: – 1) percep1on consists of perceptually guided ac1on, and

– 2) cogni1ve structures emerge from recurrent sensory‐motor paèrns that enable ac1on to be perceptually guided (Varela et al., 1991, p. 173).

Embodied cogni1on

•  They coined the term embodied ac:on to transmit the idea that cogni:on depends upon the kinds of experience that come from having a body with various sensory‐motor capaci:es, and second that these individual sensory‐motor capaci1es are themselves embedded in a more encompassing biological, psychological, and cultural context.

Ecological cogni1on

•  Ecological psychologists locate meaning and intelligent ac:on into coupling of individual and environment

•  Ecological approach aims at understanding cogni:ve systems in terms of their environmental situatedness (Magnani, 2005).

We are eco‐cogni1ve engineers

•  Humans are powerful eco‐cogni:ve engineers.

•  Humans use the environment itself as a representa:on by manipula:ng and even crea:ng it so as to find room for new cogni:ve chances not immediately available.

Bardone, 2010

Crea1ng and ac1ng upon ecological chances

•  Humans turn environmental constraints into ecological chances when facing the challenges posed by the environment itself.

•  Human cogni:on is chance‐seeking system that is developed within an evolu1onary framework based on the no1on of cogni:ve niche construc:on.

•  We build and manipulate cogni:ve niches so as to unearth addi:onal resources for behavior control.

Bardone, 2010

Eco‐cogni1ve engineering

•  Humans constantly delegate cogni:ve func:ons to the environment

•  Human beings overcome their internal limita:ons by (1) disembodying thoughts and then (2) re‐projec:ng internally that occurring outside

•  to find new ways of thinking. Bardone, 2010

Eco‐cogni1ve engineering

•  Human cogni1ve behavior consists in ac:ng upon anchors – the affordances ‐ which we have secured a cogni:ve func:on to via cogni1ve niche construc1on.

•  Affordances can be related to the variable (degree of) abduc:vity of a configura:on of signs.

Bardone, 2010

Interac1onal affordance concept

•  Gibson (1979) originally defined affordances as opportuni:es for ac:on for an observer, provided by an environment.

•  Gaver (1996) emphasized that affordances emerge in human ac:on and interac:on and, thus, go beyond mere percep1on.

•  Affordances are the perceived possibili:es for both thinking and doing, what learners evoke and signify during their actual interac:on with an ar:fact or tool and with each other.

•  Michaels (2003) claimed that perceiving affordances is more than perceiving rela1ons, but it brings a@en:on to the ac:on‐guiding informa:on and sets up ac:on systems to act.

Affordance networks

•  Barab and Roth (2006) have noted that connec:ng learners to ecological networks, where they can learn through engaged par1cipa1on, ac:vates the affordance networks.

•  Barab and Roth (2006) assumed that affordance networks are not read onto the world, but instead con:nually “transact” (are coupled) with the world as part of a percep:on‐ac:on cycle in which each new ac:on poten:ally expands or contracts one’s affordance network.

Affordance networks

•  Learning is a process of becoming prepared to engage dynamic networks in the world in a goal‐directed manner (Hoffmann & Roth, 2005).

•  affordance networks are dynamic sociocultural configura1ons

•  include sets of perceptual and cogni1ve affordances that collec1vely come to form the network for par1cular goal sets

•  affordance networks are extended in both 1me and space

Cultural affordances as an ecological knowledge

•  Vyas and Dix (2007) dis1nguished 3 levels of affordances: personal, organiza:on/community, and culture level, which differ also on the level of how rapidly they can change.

•  HeG (2001) wrote that: “…we engage a meaningful environment of affordances and refashion some aspects of them… These laYer constructed embodiments of what is known – which include tools, ar8facts, representa8ons, social paEerns of ac8ons, and ins8tu8ons – can be called ecological knowledge”.

embodied simula1on

•  Discoveries in cogni1ve and neuroscience about the func1oning of mirror‐neuron systems (Gallese et al., 1996), claim, that cogni:on is embodied through grounding knowledge directly in sensory‐motor experiences without the media:on of symbolic representa:ons (Pecher & Zwaan, 2005).

Embodied simula1on •  Research indicates that –  from observa:on of others and the environment (Rizzolap et al., 2001),

–  from listening narra1ves (Rizzolap & Arbib, 1998; Iaccoboni, 2005) or

–  from reading narra:ves (Scorolli & Borghi, 2007) and

–  from looking everyday images of objects or works of art (Gallese & Freedberg, 2007)

•  we perceptually ac:vate certain mul:‐modal ac:on‐poten:alites of embodied symbols that mediate our purposeful and goal‐directed ac:ons (see Gallese & Lakoff, 2005).

Embodied symbols evoke ac1on

Smile and the world will smile back:)

Besides possibili1es of organizing meanings with various ways in social learning environments, much more a@en:on needs to be put on these ac:on‐related cues individuals and communi:es interact with in the environment.

Embodied simula1on

•  When ac1ng in social learning environments not only the meanings are newly created from found informa1on, but also the emo:on and ac:on‐related cues are picked up from different narra:ves and from the whole systems, and they are integrated into our ac:on plans.

•  Embodied simula1on may be how storytelling works as a personal “tool” for placement in hybrid ecosystems

•  It is the source of ecological inheritance that may be used as a naviga:onal “tool” for interac:on in community niches (as an intersubjec:vity)

Social ecology of iden1ty identity

structure

negotiability identification

communities economies of meaning

Forms of membership Ownership of meaning

Mode of belonging

engagement

imagination

alignment

Identities of participation

Identities of non-participation

Identities of participation

Identities of non-participation

Close circle of friends doing

everything together

Experience of boundaries through

a faux-pas

Having one’s ideas adopted

Marginality through having one’s ideas

ignored

Affinity felt by the readers of the

newspaper

Prejudice through stereotypes

Vicarious experience

through stories

Assumption that someone else understands what is

going on

Allegiance to a social movement

Submission to violance

Persuasion through directed experience

Literal compiliance as in tax returns

Wenger, 1998. Social ideology of iden1ty

Community niches

•  People with various perspec:ves are simultaneously at present in ecosystems and influencing them.

•  Many abstract subspaces can be formed within ecosystems.

•  Such spaces emerge when parts of the environment are embodied and used similar way by many people.

•  Groups of individuals who have something in common in their iden:ty create abstract learning spaces in the ecology ‐ niches.

Community niches

•  Hutchinson (1957) defined a niche as a region (n‐dimensional hypervolume) in a mul:‐dimensional space of environmental factors that affect the welfare of a species.

•  Niches have been conceptualized as the environmental gradients with certain ecological amplitude, where the ecological op:mum marks the gradient peaks where the organisms are most abundant.

•  Each niche gradient defines one dimension of the learning space.

•  All niche gradients are situated and establish a mul:‐dimensional hyper‐room, which axes are different environmental parameters.

Niche gradients

•  Any niche gradient is a peak of the fitness landscape of one environmental characteris:c (Wright, 1931), which can be visualized in two‐dimensional space as a graph with certain skew and width, determining the ecological amplitude.

•  The shape of the fitness graph for certain characteris1c can be ploèd through the abundance of certain specimen benefipng of this characteris1c.

Defining community niches by affordances

•  People determine the personal learning affordances within their PLEs.

•  Any individual conceptualizes affordances personally, but the range of similar learning affordance conceptualiza1ons may be clustered into more general affordance groups eg. ‘pulling social awareness informa1on’ or ‘searching ar1facts by social filtering’ etc.

•  These affordance clusters may be interpreted and used as the abstract learning niche gradients.

Affordances of social tools in a community

Community niche guides naviga1on of individuals

Community niche2 Community niche1

My ini1al place

The community space

Naviga1ng in community niches

•  Ecologies integrate many niches of different communi1es.

•  Niches enable to enact knowledge and influence personal networks because of ecological inheritance leG as feedback to the social soGware systems.

Adapted from: Technical and Design Considera1ons for a Mobile Informa1on System. Mark Bilandzic & Marcus Foth (2009).

Niche construc1on as an ecological factor

•  A recent literature in evolu1onary theory emphasizes the idea of niche construc:on (Odling‐Smee et al., 2003) as an ecological factor.

•  It is argued, the organism has a profound effect on the very environment as a feedback loop.

•  Organisms have influence on their environment, and the affected environment can have a reciprocal effect on other organisms of this species or on other species, crea1ng an environment different from what it would have been before it was modified.

Niche construc1on as an ecological factor

•  Ecological inheritance, however, does not depend on the presence of any environmental replicators, but merely on the persistence, between genera:ons, of whatever physical changes are caused by ancestral organisms in the local selec:ve environments of their descendants.

Ecological inheritance

•  People create a feedback loop to hybrid ecosystem that influences the evolu:on of communi:es and determines their individual interac:on with the ecosystem.

•  This feedback loop is an ecological inheritance created by organisms themselves into their environment, which has influence on their evolu:on (Odling‐Smee et al., 2003)

Odling‐Smee, F.J., Laland, K.N., & Feldman, M.W. (2003). Niche Construc1on: The Neglected Process in Evolu1on. Monographs in Popula1on Biology, 37, Princeton University Press.


Community iden1ty

t

t + 1

Time

Niche crea1on

Adapta1on to the niche Culturally defined

affordances of the digital

ecosystem

Adapted from Odling‐Smee, F.J., Laland, K.N., & Feldman, M.W.


Ecological inheritance is the par1cular set of culturally defined affordances and meanings leG into the systems by various communi1es in the form of meaning‐ and ac1on‐relevant cues.

“Ecosophy” ‐ the cross‐fer:liza:on of the three modes: “mental,” “natural,” and “social” means that any of these modes of an ecology always demand carrying over into another mode, another universe of reference in order to have any func:on (Felix Guaàri)

Naviga1ng in community niches

Pata, 2009

II. Digital popula1on ecology

•  Studies abundance and distribu1on of digital (species) communi1es

•  Deals with the popula1on dynamics in communi1es and their interac1ons with the environment

III. Ecology of associa1ons of digital communi1es

•  Studies the composi1on and organiza1on of the associated digital communi1es

III. Ecology of associa1ons of digital communi1es

•  Ecosystems grow and develop in four progressive growth forms reflected in boundary, structure, network, and informa1on rela1onships. –  Boundary growth brings the input of low‐entropy (ordered) material into the system. Entropy is essen1ally a measure of how organized or disorganized a system is, of the number of ways in which a system may be arranged, oGen taken to be a measure of “disorder” (the higher the entropy, the higher the disorder).

–  Structural growth occurs when the physical quan:ty of biomass in the system increases, oGen as a result of the increase in the amount, number, and size of components in the ecosystem.

More ar1facts are imported to the digital ecosystem

Communi1es grow bigger. More communi1es with par1cular iden1ty are associated into digital ecosystem.

II. Ecology of associa1ons of digital communi1es

•  Network growth is growth in connec:vity of the system through addi:onal energy–ma@er transac:ons, which results in pathway prolifera1on and more cycling of maèr and energy. Network growth deals specifically with the internal organiza1on of the system.

•  Informa:on growth is qualita:ve growth in system behavior from exploita:ve pa@erns to more conserva:ve pa@erns, which are more energe:cally efficient. Informa1on growth deals with the development of ecosystem compartments themselves, as they tend to increase their own performance within the system.

More network connec1ons and ar1fact and knowledge transac1ons

Conserving informa1on

Knowledge ecosystem •  A knowledge ecosystem comprises: –  (a) a human network of produc:ve conversa:ons designed to create

–  (b) a knowledge network of ideas, informa:on, and inspira:on, supported by

–  (c) a technological network consis:ng of knowledge bases and communica:on links that altogether generate value and intelligence for the whole ecosystem.

Pór, G., & Molloy, J. (2000). Nurturing Systemic Wisdom Through Knowledge Ecology. Systems Thinker, 1 (8), 1–5.

Digital ecosystem •  Digital ecosystem (DE) is an

–  open, –  self‐organizing agent environment, –  containing human individuals, –  informa1on services, –  network interac1on, –  knowledge sharing tools, and –  resources

•  that help maintain synergy among human beings or organiza1ons, where –  each agent of each species is proac1ve, –  responsive regarding its own benefit/profit and –  responsible to its system.

Boley, H., & Chang, E. (2007). Digital Ecosystems: Principles and Seman1cs, published at the 2007 Inaugural IEEE Interna1onal Conference on Digital Ecosystems and Technologies. Cairns, Australia. February 2007. NRC 48813.

Ar1fact ecology •  Ar:fact ecologies refer to a system consis1ng of – different digital and physical ar:facts, – people, –  their work prac:ces and values, and –  their emerging and dynamic rela:onships.

Vyas, D.M., & Dix, A. (2007). Artefact Ecologies: Suppor1ng Embodied Mee1ng Prac1ces with Distance Access. In Proceedings of UbiComp 2007 Workshops, Sept 2007, Innsbruck, Austria (pp. 117‐122). University of Innsbruck.

Compare previous knowledge ecosystem terms with the ar5fact ecology term! How is the ecology term different of the ecosystem term, or is it a synonym?

Example: social media marke1ng ecosystem

Hybrid ecosystem

•  “Hybrid” refers to the structural property of the world that is achieved by deliberate blending of geographical spaces with content elements of social environments, such as blogs, microblogs, wikis, social repositories and ‐networks, using mobile and web applica1ons.

•  Ar1facts (eg. digital narra1ves, images, real‐world objects), soGware (eg. social soGware tools), language (eg. user‐created ontologies such as tags), other actors, and geographical loca1ons all serve as mediators of ac:on.

Hybrid ecology

•  Hybrid ecologies rely on the ar:cula:on of ‘fragments of embodied virtuality’ or fragmented interac:on.

Crabtree, A., & Rodden, T. (2007). Hybrid ecologies: understanding interac1on in emerging digital‐physical environments. Personal and Ubiquitous Compu1ng

Hybrid digital ecosystem •  Social media environments together with geographical loca1ons can be conceptualized as a “hybrid ecosystem”, provided that par:cipants of social media have ecological dependence of the par:cular set of mediators that they use as their niche for taking ac:on.

IV. Digital community ecology

•  Studies interac1ons between the (species) communi1es of digital associa1ons of communi1es: – Food networks such as artefact‐actor networks John Seeley Brown (1999; 2002), and George Siemens (2005; 2006) related knowledge ecology and knowledge ecosystem terms with weaving informa:on and artefacts, meanings and knowledge, networks and connec:ons.

Engineering web

•  Jones et al. (1997) highlights the indirect interac1ons between species and the organism connec:vity by the engineering web and not by the food web: The ecosystem engineers can regulate energy flows, mass flows, and trophic paYerns in ecosystems to generate an “engineering web”—a mosaic of connec8vity comprising the engineering interac8ons of diverse species.

•  Can co‐exis1ng human communi1es in social soGware environments or hybrid environments engineer their niches so that this niche starts to constrain or facilitate other community?

Does such engineering web exist in digital ecosystems?

Jones, C. G., Lawton, G. H., & Shachak, M. (1997). Ecosystem engineering by organisms: Why seman1cs maèrs. Trends in Ecology & Evolu1on, 12, 275.

IV. Digital community ecology

•  Some communi1es benefit from the niches of other communi1es. – Commensalism

– Symbiosis – Parasi1sm

IV.Digital community ecology

•  Vandermeer (2008) dis1nguishes between obligate and faculta:ve organisms and niches, formula1ng assump1ons how these organisms are influenced by niche construc1on: –  a) In an obligate construc:ve niche the organism dies in the absence of niche construc:on; Example: Wikis and microblogging environments can be considered obligate construc1ve niches, where single person without the community has very li`le benefit of the system


– b) In a faculta:ve construc:ve niche the organism survives even in the absence of niche construc:on, nevertheless it will benefit further from the construc:on Example: Blogs or social bookmarking systems may be seen as faculta1ve construc1ve niches, in which keeping individual diary or collec1ng bookmarks gives some addi1onal value even without sharing it with the community


•  c) A faculta:ve organism survives even in a non‐construc:ve niche, but benefits further from the construc:on Example: A faculta1ve user of social web systems does not rely on its’ ac1vi1es on the niche construc1on of the other users


•  d) An obligate organism does not survive unless a constructed niche becomes available. Example: An obligate web user has constructed its personal learning environment of community tools and services eg. of ‘pulling feeds’, and cannot func1on effec1vely without this niche construc1on.


1.  The community as a system increases by the input of low‐entropy energy (ideas?) or maèr (people, ar1facts?) across the system boundary.

2.  During the next growth and development system connec1vity and cycling increases through addi1onal network transac1ons. This retains the energy–maèr within the system boundaries for a longer 1me. As a result, system entropy produc1on decreases (system is more ordered).

Networks and connec1vity

People, ar1facts

•  Succession in digital communi1es


h`p://www.geog.mcgill.ca/faculty/peterson/susfut/adap1veCycle/index.html

Release, or crea5ve destruc5on ‐ tightly bound accumula1on of ar1facts and ideas and people are suddenly released

System can easily be reorganized by small inputs as actors or ideas begin to capture opportunity

V. Digital ecosystem ecology

•  Studies how ma@er (such as ar:facts and ideas) circulates in ecosystems – Mul1plica1on such as embedding or copying –  From some ar1fact types to another types (blog ‐> twièr) so that informa1on can move across systems and communi1es

–  Deriva1on such as referring in new context, elabora1ng, summarizing, mixing etc.

–  Evalua1ng such as commen1ng, ra1ng –  Sharing in community databases (community browsing) –  Annota1ng (tagging) to make shortcuts, redistribu1ng across users, spaces

V. Digital ecosystem ecology •  Studies: – How energy circulates in ecosystems

An energy in ecosystems allows the interac1on and exchange of maèr (ideas?) between its animate and inanimate components.

Energy is ability to do work. Can the new media system architecture, the networks (bounds, kine1c energy), or the “cultural interface” create this “energy”?

h`p://000fff.org/the‐power‐of‐digital‐ecoystems/

Does energy get released in the representa1on process? Does semiosis, the crea1on of meanings release, energy?

Can extra “energy” be created in new media environments?

ar1facts

people

The kine1c energy of a moving object depends on its mass (think "weight") and its speed.

V. Digital ecosystem ecology •  Studies: –  Entropy rela:onships in ecosystems Entropy is a measure of how evenly energy is distributed in a system. Entropy serves as a measure of how close a system is to equilibrium — that is, to perfect internal disorder.

Shannon's entropy represents an absolute limit on the best possible lossless compression of any communica1on, under certain constraints.

–  One of the most important features of biosystems is how they are able to maintain local order (low entropy) within their system boundaries. At a steady state, specific entropy produc1on is minimized.

Low entropy High entropy

Entropy in open and closed digital ecosystems

•  A closed system has no interac1on with anything outside it, to and from it no energy or maèr can flow.

•  The second law of thermodynamics says that a closed system always tends towards achieving a state with a maximum of entropy (disorder).

•  The entropy of an open system is low.

•  Example: Open digital ecosystems (if we consider for example one certain social soGware system) seem to be possessing low entropy, and higher orderliness.

h`p://www.informa1onphilosopher.com/solu1ons/scien1sts/layzer/

Education

Newmedia6