Today’s modular Internet needs a metaphor make-over. The “silo” and “layer” frameworks that have guided are no longer adequate. It’s time to reinvent a well-worn metaphor: the Web as a web. [1], [2]
The silo model divided up the communications business by end-user experiences like telephony, cable and broadcast television, assuming that each experience has its own infrastructure. The distinct experiences with unique public policy aspects remain, but the silos are growing together at the infrastructure level since all media are now moved around as TCP/IP packet flows. The layer model reflects this integration of different media all using the same protocols. It’s relevant when one takes an infrastructure perspective, but doesn’t take into account the very real differences between, say, real-time voice chat, blogs, and digital video feeds. One might say that the silo model works best “at the top” and a layer model “at the bottom”; in the middle, it’s a mess.
Time to revive the web metaphor, with a twist. The “web” of the World Wide Web refers to the network of pointers from one web page to another. [3] The nodes are pages, and the connections between them are hyperlinks. The “info-web” model I’m exploring here proposes a different mapping: the connections in the web represent information flow, not hyperlinks, and the nodes where they connect are not individual pages but rather functional categories, like blogs, social networking sites, search portals, and individuals.
Food webs
It’s a web as in an ecosystem food web, where the nodes are species and the links are flows of energy and nutrients. The simplest view is that of a food chain: in a Swedish lake, say, ospreys eat pike, which eat perch, which eat bleak, which eat freshwater shrimp, which eat phytoplankton, which get their energy from the sun via photosynthesis. A chain is a very simple model which shows only a linear path for energy and material transfer. (The Layers model resembles a food chain, where network components at one layer pass down communications traffic to the layer below for processing.)
A food web extends the food chain concept to a complex network of interactions. It takes into account aspects ignored in a chain, such as consumers which eat, and are eaten by, multiple species; parasites, and organisms that decompose others; and very big animals that eat very small ones (e.g. whales and plankton). The nodes in a food web are species, and the links between them represent one organism consuming another. While the nodes are multiply connected, there is some degree of hierarchy, since in an ecosystem there’s always a foundation species that harvests energy directly from non-organic sources, usually a plant using sunlight. Each successive organism is at a higher trophic level; first the phytoplankton, then the shrimp, then the bleak, etc.
Info-webs
In an eco-based web model for the Internet, the species in a bio-web are mapped to functionality modules as described in my earlier post, A modular net. For example, a YouTube video clip plugged into a MySpace page running on a Firefox browser on a Windows PC might correspond to the osprey, fish, shrimp, plankton in the simple example above. In the same way that there might be other predators beyond ospreys feeding on fish, there might be many other plug-ins on the MySpace page for IM, audio, etc.. In a bio-web, a link between species A and B means “A eats B”. In the info-web model of the Internet, a link means “information flows from A to B.” Value is added to information value in the nodes through processing (e.g. playing a video) or combinations (e.g. a mash-up). For example, a movie recommender embedded in Facebook gets its information from a database hosted somewhere else, and integrates into a user’s page. Therefore, information transport is key. One can think of the links as being many-stranded if there are many alternative ways of getting the relevant information across, or single-stranded if there’s only one or two communications options (e.g. for web search one can use Wi-Fi, 3G data, DSL, cable modem etc, but for high def video on demand there’s many fewer choices.)
The analogy between the info-web and the food web diverges when one considers what flows across the links. In the Internet, information flows around the web; in the biological case, it’s energy and nutrients. Information can be created at any stage in an information web and increases with each step, whereas energy is conserved, and available energy decreases as one moves up the trophic levels of an ecological pyramid. There is a sequence of “infotrophic levels” where information value is added at each step. However, since the amount of information grows with each step, the “information pyramid” is therefore inverted relative to the ecological one: it grows wider from the bottom to the top, rather than narrower.
Implications for policy making
The Internet is complex web of interlocking service, and is approaching the richness of simple biological ecosystems. In the same way that humans can’t control ecosystems, regulators cannot understand, let alone supervise, all the detailed interactions of the Internet. One may be able to understand the interactions at a local level, e.g. how IP-based voice communications plug into web services, but the system is too big to wrap one’s head around all the dynamics at the same time. [4] This is why a market-based approach is advisable. Markets are the best available way to optimize social systems by distributing decision making among many participants. Markets aren’t perfect, of course, and there are social imperatives like public safety and justice that need government intervention. The info-web model suggests ways to find leverage points where regulators should focus their attention, and also provides salutary lessons about the limits of the effectiveness of human ecosystem management.
For example, a keystone species is one that has a disproportionate effect on its environment relative to its abundance. Black-tailed prairie dogs are a keystone species of the prairie ecosystem; more than 200 other wildlife species have been observed on or near prairie dog colonies. Such an organism plays a role in its ecosystem that is analogous to the role of a keystone in an arch. An ecosystem may experience a dramatic shift if a keystone species is removed, even though that species was a small part of the ecosystem by measures of biomass or productivity. Regulators could apply leverage on “keystone species” rather than searching for bottlenecks or abuse of market power. This would provide a basis for both supportive and punitive action. At the moment search engines are “keystone species” – they play a vital role not only in connecting consumers with information, but also in generating revenue that feeds many business models. One might say that Google is the phytoplankton of the Internet Ocean, converting the light of user attention into the energy of money. Local Internet Service Providers may also be keystone species. In earlier phase of the net, portals were keystone species. Keystone services provide a point of leverage for regulators; they can wield disproportionate influence by controlling behavior of these services.
The unintended side effects of intervention in ecosystems stand as a warning to regulators to tread carefully. For example, the Christian Science Monitor reported recently on efforts to eradicate buffelgrass from the Sonoran Desert. It was introduced by government officials after the Dust Bowl in an attempt to hold the soil and provide feed for cattle. It’s unfortunately turned out to be an invasive weed that threatens the desert ecology, choking out native plants like the iconic saguaro cactus. Another example of biological control gone wrong is the introduction of the cane toad into Australia in 1935 to control two insect pests of sugar cane: it did not control the insects and the Cane Toad itself became an invasive species. By contrast, the release of myxomatosis in 1950 was successful in controlling feral rabbits in that country.
The silo model divided up the communications business by end-user experiences like telephony, cable and broadcast television, assuming that each experience has its own infrastructure. The distinct experiences with unique public policy aspects remain, but the silos are growing together at the infrastructure level since all media are now moved around as TCP/IP packet flows. The layer model reflects this integration of different media all using the same protocols. It’s relevant when one takes an infrastructure perspective, but doesn’t take into account the very real differences between, say, real-time voice chat, blogs, and digital video feeds. One might say that the silo model works best “at the top” and a layer model “at the bottom”; in the middle, it’s a mess.
Time to revive the web metaphor, with a twist. The “web” of the World Wide Web refers to the network of pointers from one web page to another. [3] The nodes are pages, and the connections between them are hyperlinks. The “info-web” model I’m exploring here proposes a different mapping: the connections in the web represent information flow, not hyperlinks, and the nodes where they connect are not individual pages but rather functional categories, like blogs, social networking sites, search portals, and individuals.
Food webs
It’s a web as in an ecosystem food web, where the nodes are species and the links are flows of energy and nutrients. The simplest view is that of a food chain: in a Swedish lake, say, ospreys eat pike, which eat perch, which eat bleak, which eat freshwater shrimp, which eat phytoplankton, which get their energy from the sun via photosynthesis. A chain is a very simple model which shows only a linear path for energy and material transfer. (The Layers model resembles a food chain, where network components at one layer pass down communications traffic to the layer below for processing.)
A food web extends the food chain concept to a complex network of interactions. It takes into account aspects ignored in a chain, such as consumers which eat, and are eaten by, multiple species; parasites, and organisms that decompose others; and very big animals that eat very small ones (e.g. whales and plankton). The nodes in a food web are species, and the links between them represent one organism consuming another. While the nodes are multiply connected, there is some degree of hierarchy, since in an ecosystem there’s always a foundation species that harvests energy directly from non-organic sources, usually a plant using sunlight. Each successive organism is at a higher trophic level; first the phytoplankton, then the shrimp, then the bleak, etc.
Info-webs
In an eco-based web model for the Internet, the species in a bio-web are mapped to functionality modules as described in my earlier post, A modular net. For example, a YouTube video clip plugged into a MySpace page running on a Firefox browser on a Windows PC might correspond to the osprey, fish, shrimp, plankton in the simple example above. In the same way that there might be other predators beyond ospreys feeding on fish, there might be many other plug-ins on the MySpace page for IM, audio, etc.. In a bio-web, a link between species A and B means “A eats B”. In the info-web model of the Internet, a link means “information flows from A to B.” Value is added to information value in the nodes through processing (e.g. playing a video) or combinations (e.g. a mash-up). For example, a movie recommender embedded in Facebook gets its information from a database hosted somewhere else, and integrates into a user’s page. Therefore, information transport is key. One can think of the links as being many-stranded if there are many alternative ways of getting the relevant information across, or single-stranded if there’s only one or two communications options (e.g. for web search one can use Wi-Fi, 3G data, DSL, cable modem etc, but for high def video on demand there’s many fewer choices.)
The analogy between the info-web and the food web diverges when one considers what flows across the links. In the Internet, information flows around the web; in the biological case, it’s energy and nutrients. Information can be created at any stage in an information web and increases with each step, whereas energy is conserved, and available energy decreases as one moves up the trophic levels of an ecological pyramid. There is a sequence of “infotrophic levels” where information value is added at each step. However, since the amount of information grows with each step, the “information pyramid” is therefore inverted relative to the ecological one: it grows wider from the bottom to the top, rather than narrower.
Implications for policy making
The Internet is complex web of interlocking service, and is approaching the richness of simple biological ecosystems. In the same way that humans can’t control ecosystems, regulators cannot understand, let alone supervise, all the detailed interactions of the Internet. One may be able to understand the interactions at a local level, e.g. how IP-based voice communications plug into web services, but the system is too big to wrap one’s head around all the dynamics at the same time. [4] This is why a market-based approach is advisable. Markets are the best available way to optimize social systems by distributing decision making among many participants. Markets aren’t perfect, of course, and there are social imperatives like public safety and justice that need government intervention. The info-web model suggests ways to find leverage points where regulators should focus their attention, and also provides salutary lessons about the limits of the effectiveness of human ecosystem management.
For example, a keystone species is one that has a disproportionate effect on its environment relative to its abundance. Black-tailed prairie dogs are a keystone species of the prairie ecosystem; more than 200 other wildlife species have been observed on or near prairie dog colonies. Such an organism plays a role in its ecosystem that is analogous to the role of a keystone in an arch. An ecosystem may experience a dramatic shift if a keystone species is removed, even though that species was a small part of the ecosystem by measures of biomass or productivity. Regulators could apply leverage on “keystone species” rather than searching for bottlenecks or abuse of market power. This would provide a basis for both supportive and punitive action. At the moment search engines are “keystone species” – they play a vital role not only in connecting consumers with information, but also in generating revenue that feeds many business models. One might say that Google is the phytoplankton of the Internet Ocean, converting the light of user attention into the energy of money. Local Internet Service Providers may also be keystone species. In earlier phase of the net, portals were keystone species. Keystone services provide a point of leverage for regulators; they can wield disproportionate influence by controlling behavior of these services.
The unintended side effects of intervention in ecosystems stand as a warning to regulators to tread carefully. For example, the Christian Science Monitor reported recently on efforts to eradicate buffelgrass from the Sonoran Desert. It was introduced by government officials after the Dust Bowl in an attempt to hold the soil and provide feed for cattle. It’s unfortunately turned out to be an invasive weed that threatens the desert ecology, choking out native plants like the iconic saguaro cactus. Another example of biological control gone wrong is the introduction of the cane toad into Australia in 1935 to control two insect pests of sugar cane: it did not control the insects and the Cane Toad itself became an invasive species. By contrast, the release of myxomatosis in 1950 was successful in controlling feral rabbits in that country.
----- Notes -----
[1] Steven Johnson’s Discover essay, republished as “Why the web is like a rain forest” in The Best of Technology Writing, ed. Brendan Koerner, helped inspire this thinking.
[2] This is a rough first draft of ideas. There are still many gaps and ambiguities. The nature of the nodes is still vague: are they applications/services (LinkedIn is one node, Facebook is another), application categories (all kinds of social networking sites are one node), market segments, or something else? How and where does the end user fit in? How can one use this model to address questions of VOIP regulation, accessibility directives, culture quotas for video, and other hot topics in Internet policy? Much work remains to be done. The representation of transport services as links rather than nodes may change. The different in conservation laws needs to be worked out: sunlight, water and nutrients are limited and conserved in the web, rival resources, whereas information is non-rival and can be produced anywhere. Connections need to be made with prior work on metaphors for communications technologies, e.g. Susan Crawford’s Internet Think, Danny Hillis’s Knowledge Web, and Douglas Kellner’s “Metaphors and New Technologies: A Critical Analysis.”
[3] The word web derives from the Old Norse vefr, which is akin to weave. It thus refers to a fabric, or cloth. In many usages, e.g. food webs, there are assumed to be knots or nodes at the intersection of warp and weft, which occur in nets, but not in fabrics.
[4] This is a link to the Hard Intangibles problem more generally, via the limit (about four) on the number of independent variables that humans can process simultaneously.
[2] This is a rough first draft of ideas. There are still many gaps and ambiguities. The nature of the nodes is still vague: are they applications/services (LinkedIn is one node, Facebook is another), application categories (all kinds of social networking sites are one node), market segments, or something else? How and where does the end user fit in? How can one use this model to address questions of VOIP regulation, accessibility directives, culture quotas for video, and other hot topics in Internet policy? Much work remains to be done. The representation of transport services as links rather than nodes may change. The different in conservation laws needs to be worked out: sunlight, water and nutrients are limited and conserved in the web, rival resources, whereas information is non-rival and can be produced anywhere. Connections need to be made with prior work on metaphors for communications technologies, e.g. Susan Crawford’s Internet Think, Danny Hillis’s Knowledge Web, and Douglas Kellner’s “Metaphors and New Technologies: A Critical Analysis.”
[3] The word web derives from the Old Norse vefr, which is akin to weave. It thus refers to a fabric, or cloth. In many usages, e.g. food webs, there are assumed to be knots or nodes at the intersection of warp and weft, which occur in nets, but not in fabrics.
[4] This is a link to the Hard Intangibles problem more generally, via the limit (about four) on the number of independent variables that humans can process simultaneously.
2 comments:
You might find Mark Buchanan's book Nexus useful, as he covers some of the same territory of web metaphors and link/node relationships. But your extension that using keystone species as the ones regulators should watch is new (and valuable) to me.
Thanks for the recommendation and the comment, Suze; I'll follow up.
I think networking is the most powerful metaphor around today, on a par with “clockwork” in the 17th century, and “engines” in the 19th. No surprise, given that the internet is the current dominant technology.
It turns out that the "keystone species" idea isn’t new; Tren told me yesterday that Cusumano analysed Microsoft as a keystone species during the anti-trust case. I couldn’t find that reference; the closest I came was Iansiti and Levien’s paper “Strategy as ecology,” HARVARD BUS REV 82 (3): 68 Mar 2004, originally titled “Keystones and Dominators: Framing the Operational Dynamics of Business Ecosystems.” Iansiti & Levien refer to Gawer and Cusumano’s “Platform Leadership: How Intel, Microsoft, and Cisco Drive Industry Innovation," Harvard Business School Press, 2002.
The ecosystem metaphor is pervasive in ICT. The novelty (if any) in my claim is that the species analogs are the functional modules of the internet/web , rather than companies; and that the ecology analogy breaks down in some important ways, e.g. the inverted "info-trophic pyramid" I mention in the post. But I wouldn't be surprised to find that this is well-tilled ground; my "if I can think of it, someone else has already done it" rule governs.
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