To paraphrase Ashby's "Design for a brain", it might be asked "How does an institution produce adaptive behaviour?" But of course, institutions often don't produce adaptive behaviour, or their adaptations lead them to adopt patterns of behavior which are more rigid - which is the harbinger of death for an organism, but institutions seem to be large enough to withstand environmental challenges that they continue to survive even without apparently adapting.
One way of answering this problem is to argue that institutions, in whatever form they come, and in whatever state of adaptability, conserve information. An institution might lose a quantity of information in response to an environmental threat, but maintain some stable behaviour despite this. It's internal processes maintain that new set of information. This is, I think, like what happens when institutions are challenged by a complex environment and become more conservative. They discard a lot of information and replace it with rigid categories, often upheld by computer technology and metrics. But the computer-coordinated information-preservation function with a limited information set is surprisingly resilient. However, for human beings existing within this kind of institution, life can be miserable. This is because human beings are capable of far richer information processing than the institution allows - effectively they are suppressed. There may be distinct phases of information loss and preservation.
But if institutions are information-preserving entities, then rigid low-information preserving entities will not be able to compete with richer information-preserving entities. If information preservation is the criteria for "institution-ness", then new ways of preserving information with technology may well be possible which might challenge traditional institutional models. So what is a basic "design for an institution"?
An institution, like a brain, must be a collection of components which communicate - or converse - with one another. In the process of conversation, essential distinctions about the institution are made: what is it, what is it for, what functions must it perform, and so on. Each of these distinctions is essentially uncertain: conversation is necessary to uphold each distinction. Within the conversations there are details about different interpretations of these distinctions. Not all of these differences can be maintained: some must be attenuated-out. So information is lost in the goal of seeking generalisable patterns of practice and understanding to coordinate the whole.
Having said this, the generalisations produced may well be an inadequate representation. So what must be done is that whatever generalisations are produced are used to generate multiple versions of the world as it is understood by these generalisations. The multiplicity of this generated reality and the multiplicity of "actual" reality mus be compared continuously, and the question asked "in what ways are we wrong?" This generation of multiple descriptions is a niche-making function that can generate new information about the world. It is like a spider spinning a web to create a home, but also to detect what is in the environment.
An institution will connect the generalisations it makes with the new information produced through its multiple expressions of its understanding. In traditional institutions, both functions were performed by humans: an "operations" team that identified what needed to be done and did it; and a "research and development" team which looked at the future and speculated on new developments. Technology has shifted the balance between operations and strategy, where research and development is now seen as "operational" in the sense that it has become "data driven". This collapse of distinction-making is dangerous.
But lets say, in a technology-enhanced institution (such as all of ours are now), a clear division could be established between the operational, synergistic parts of the organisation, and the strategic, future-looking parts. We need two kinds of machines. One, the purpose-driven analytical engine that the modern computer is, in order to maintain operations and synergy. The other, a "maverick machine" as Gordon Pask put it, which uses the information it has at its disposal to produce a rich variety of artefacts from paintings and music to usual correlations of data. The maverick machine's purpose (if it can be said to have one) is to stimulate thought and shake it out of the rigid confines of the analytical engine. It presents people with orders of things which are unfamiliar to them, and challenges them to correct it, or embrace a new perspective. By stimulating thought, the maverick machine generates new information to counteract the information that is lost through the analytical engine. The maverick machine is an information-preserving machine because it maintains a living record of human order and distinction-making within the institution.
It is through the stimulation of thought that changes might be made to the analytical engine and new strategic priorities defined, or new orders identified. In this way, an institution must be a collaboration between humans and machines. To think of institutions as essentially human, with technological "support" is a mistake and will not work.
What is particularly interesting about the maverick machine is that it is a creating entity. Not only does that mean that the viable institution maintains its information. It also means that the viable institution is putting stuff out into the environment in the form of new things. This "generous" behaviour will result in patterns of engagement with the environment which will help it to survive. People will support the institution because not only does its information-preserving processes help itself, but helps other things and people in the environment too.
What does this actually look like? Well, imagine two friends who have similar intellectual interests. They meet every now and then and discuss what they are reading and are interested in. But they don't just discuss it, they video their discussions. They process the video to extract text and images. They use machine learning to mine the text and explore new resources, which software is then able to produce new representations of (a maverick machine). A weekly meeting is generative of a rich range of different kinds of things. Others see these things and think "that's cool - how do I get involved?" Using the same techniques, others are able to do similar things, where the software is able to create synergies between them. Slowly an information-preserving "institution" of two friends becomes something bigger.
This is not Facebook: that is an institution which loses vast amounts of information. It is more akin to a university - an institution for preserving information and creating the conditions for conversation.
One way of answering this problem is to argue that institutions, in whatever form they come, and in whatever state of adaptability, conserve information. An institution might lose a quantity of information in response to an environmental threat, but maintain some stable behaviour despite this. It's internal processes maintain that new set of information. This is, I think, like what happens when institutions are challenged by a complex environment and become more conservative. They discard a lot of information and replace it with rigid categories, often upheld by computer technology and metrics. But the computer-coordinated information-preservation function with a limited information set is surprisingly resilient. However, for human beings existing within this kind of institution, life can be miserable. This is because human beings are capable of far richer information processing than the institution allows - effectively they are suppressed. There may be distinct phases of information loss and preservation.
But if institutions are information-preserving entities, then rigid low-information preserving entities will not be able to compete with richer information-preserving entities. If information preservation is the criteria for "institution-ness", then new ways of preserving information with technology may well be possible which might challenge traditional institutional models. So what is a basic "design for an institution"?
An institution, like a brain, must be a collection of components which communicate - or converse - with one another. In the process of conversation, essential distinctions about the institution are made: what is it, what is it for, what functions must it perform, and so on. Each of these distinctions is essentially uncertain: conversation is necessary to uphold each distinction. Within the conversations there are details about different interpretations of these distinctions. Not all of these differences can be maintained: some must be attenuated-out. So information is lost in the goal of seeking generalisable patterns of practice and understanding to coordinate the whole.
Having said this, the generalisations produced may well be an inadequate representation. So what must be done is that whatever generalisations are produced are used to generate multiple versions of the world as it is understood by these generalisations. The multiplicity of this generated reality and the multiplicity of "actual" reality mus be compared continuously, and the question asked "in what ways are we wrong?" This generation of multiple descriptions is a niche-making function that can generate new information about the world. It is like a spider spinning a web to create a home, but also to detect what is in the environment.
An institution will connect the generalisations it makes with the new information produced through its multiple expressions of its understanding. In traditional institutions, both functions were performed by humans: an "operations" team that identified what needed to be done and did it; and a "research and development" team which looked at the future and speculated on new developments. Technology has shifted the balance between operations and strategy, where research and development is now seen as "operational" in the sense that it has become "data driven". This collapse of distinction-making is dangerous.
But lets say, in a technology-enhanced institution (such as all of ours are now), a clear division could be established between the operational, synergistic parts of the organisation, and the strategic, future-looking parts. We need two kinds of machines. One, the purpose-driven analytical engine that the modern computer is, in order to maintain operations and synergy. The other, a "maverick machine" as Gordon Pask put it, which uses the information it has at its disposal to produce a rich variety of artefacts from paintings and music to usual correlations of data. The maverick machine's purpose (if it can be said to have one) is to stimulate thought and shake it out of the rigid confines of the analytical engine. It presents people with orders of things which are unfamiliar to them, and challenges them to correct it, or embrace a new perspective. By stimulating thought, the maverick machine generates new information to counteract the information that is lost through the analytical engine. The maverick machine is an information-preserving machine because it maintains a living record of human order and distinction-making within the institution.
It is through the stimulation of thought that changes might be made to the analytical engine and new strategic priorities defined, or new orders identified. In this way, an institution must be a collaboration between humans and machines. To think of institutions as essentially human, with technological "support" is a mistake and will not work.
What is particularly interesting about the maverick machine is that it is a creating entity. Not only does that mean that the viable institution maintains its information. It also means that the viable institution is putting stuff out into the environment in the form of new things. This "generous" behaviour will result in patterns of engagement with the environment which will help it to survive. People will support the institution because not only does its information-preserving processes help itself, but helps other things and people in the environment too.
What does this actually look like? Well, imagine two friends who have similar intellectual interests. They meet every now and then and discuss what they are reading and are interested in. But they don't just discuss it, they video their discussions. They process the video to extract text and images. They use machine learning to mine the text and explore new resources, which software is then able to produce new representations of (a maverick machine). A weekly meeting is generative of a rich range of different kinds of things. Others see these things and think "that's cool - how do I get involved?" Using the same techniques, others are able to do similar things, where the software is able to create synergies between them. Slowly an information-preserving "institution" of two friends becomes something bigger.
This is not Facebook: that is an institution which loses vast amounts of information. It is more akin to a university - an institution for preserving information and creating the conditions for conversation.
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