University of Toronto Department of Computer Science Lecture 4 What is a system Basic Principles Everything is connected to everything else You cannot eliminate the observer Most truths are relative Most views are complementary Defining Systems Elements of a system description Example systems Purposefulness openness hardness Describing systems Choosing a boundary Describing behaviour Easterbrook 2004 5 1 University of Toronto Department of Computer Science General Systems Theory How scientists understand the world Reductionism break a phenomena down into its constituent parts E g reduce to a set of equations governing interactions Statistics measure average behaviour of a very large number of instances E g gas pressure results from averaging random movements of zillions of atoms Error tends to zero when the number of instances gets this large But sometimes neither of these work Systems that are too interconnected to be broken into parts Behaviour that is not random enough for statistical analysis General systems theory Originally developed for biological systems E g to understand the human body and the phenomena of life Basic ideas Treat inter related phenomena as a system Study the relationships between the pieces and the system as a whole Don t worry if we don t fully understand each piece Easterbrook 2004 5 2 University of Toronto Department of Computer Science Role of the Observer Achieving objectivity in scientific inquiry 1 Eliminate the observer E g ways of measuring that have no variability across observers 2 Distinguish between scientific reasoning and value based judgement Science is supposed to be value free but how do scientists choose which theories to investigate For complex systems this is not possible Cannot fully eliminate the observer E g Probe effect measuring something often changes it E g Hawthorne effect people react to being studied Our observations biased by past experience We look for familiar patterns to make sense of complex phenomena E g try describing someone s accent Achieving objectivity in systems thinking Study the relationship between observer and observations Look for observations that make sense from many perspectives Easterbrook 2004 5 3 University of Toronto Department of Computer Science The principle of complementarity Raw observation is too detailed We systematically ignore many details E g the idea of a state is an abstraction All our descriptions of the world are partial filtered by Our perceptual limitations Our cognitive ability Our personal values and experience Complementarity Two observers descriptions of system may be Redundant if one observer s description can be reduced to the other Equivalent if redundant both ways Independent if there is no overlap at all in their descriptions Complementary if none of the above hold Any two partial descriptions of the same system are likely to be complementary Complementarity should disappear if we can remove the partiality E g ask the observers for increasingly detailed observations But this is not always possible feasible Easterbrook 2004 5 4 University of Toronto Department of Computer Science So what is a system Ackoff s definition A system is a set of two or more elements that satisfies the following conditions The behaviour of each element has an effect on the behaviour of the whole The behaviour of the elements and their effect on the whole are interdependent However subgroups of elements are formed each has an effect on the behaviour of the whole and none has an independent effect on it Or more simply Weinberg A system is a way of looking at the world Systems don t really exist Just a convenient way of describing things like sets Easterbrook 2004 5 5 University of Toronto Department of Computer Science Elements of a system Boundary Separates a system from its environment Can decompose a system into parts Often not sharply defined For each subsystem the remainder of the system is its environment Each part is also a system Also known as an interface Subsystems are inter dependent Environment Part of the world with which the system can interact Observable Interactions How the system interacts with its environment E g inputs and outputs Easterbrook 2004 5 Control Mechanism How the behaviour of the system is regulated to allow it to endure System and environment are interrelated Subsystems Often a natural mechanism Emergent Properties Properties that hold of a system but not of any of the parts Properties that cannot be predicted from studying the parts 6 University of Toronto Department of Computer Science Conceptual Picture of a System Easterbrook 2004 5 7 University of Toronto Department of Computer Science Hard vs Soft Systems Hard Systems The system is Soft Systems precise is hard to define precisely well defined is an abstract idea quantifiable depends on your perspective No disagreement about Not easy to get agreement Where the boundary is The system doesn t really exist What the interfaces are Calling something a system helps us to understand it The internal structure Identifying the boundaries interfaces controls helps us to predict behaviour Control mechanisms The purpose The system Examples The system is a theory of how some part of the world operates A car Examples All human activity systems Easterbrook 2004 5 8 University of Toronto Department of Computer Science Types of System Natural Systems E g businesses organizations markets clubs Usually perceived as hard systems E g any designed system when we also include its context of use Abstract Systems Interesting property system and description are the same thing Similarly for abstract and symbol systems Part of the design includes the representation of the current state of some human activity system Symbol Systems E g MIS banking systems databases Soft because meanings change Designed Systems E g cars planes buildings freeways telephones the internet Easterbrook 2004 5 Information Systems Special case of designed systems E g languages sets of icons streetsigns Human Activity Systems E g ecosystems weather water cycle the human body bee colony E g set of mathematical equations computer programs Control systems Special case of designed systems Designed to control some other system usually another designed system E g thermostats autopilots 9 University of Toronto Department of Computer Science Information Systems Maintains information about Needs information about Subject System Uses Information system Usage System builds
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