University of TorontoDepartment of Computer Science© Easterbrook 2004-51Lecture 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 behaviourUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-52General 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 pieceUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-53Role of the Observer Achieving objectivity in scientific inquiry1. Eliminate the observer E.g. ways of measuring that have no variability across observers2. 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 perspectivesUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-54The 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/feasibleUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-55So what is a system? Ackoff’s definition: “A system is a set of two or more elements that satisfies the followingconditions: 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 behaviourof 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’)University of TorontoDepartment of Computer Science© Easterbrook 2004-56Elements of a system Boundary Separates a system from itsenvironment Often not sharply defined Also known as an “interface” Environment Part of the world with which thesystem can interact System and environment are inter-related Observable Interactions How the system interacts with itsenvironment E.g. inputs and outputs Subsystems Can decompose a system into parts Each part is also a system For each subsystem, the remainderof the system is its environment Subsystems are inter-dependent Control Mechanism How the behaviour of the system isregulated to allow it to endure Often a natural mechanism Emergent Properties Properties that hold of a system, butnot of any of the parts Properties that cannot be predictedfrom studying the partsUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-57Conceptual Picture of a SystemUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-58Hard vs. Soft SystemsHard Systems: The system is… …precise, …well-defined …quantifiable No disagreement about: Where the boundary is What the interfaces are The internal structure Control mechanisms The purpose ?? Examples A car (?)Soft Systems: The system… …is hard to define precisely …is an abstract idea …depends on your perspective Not easy to get agreement The system doesn’t “really” exist Calling something a system helps usto understand it Identifying the boundaries,interfaces, controls, helps us topredict behaviour The “system” is a theory of howsome part of the world operates Examples: All human activity systemsUniversity of TorontoDepartment of Computer Science© Easterbrook 2004-59Types of System Natural Systems E.g. ecosystems, weather, watercycle, the human body, bee colony,… Usually perceived as hard systems Abstract Systems E.g. set of mathematical equations,computer programs,… Interesting property: system anddescription are the same thing Symbol Systems E.g. languages, sets of icons,streetsigns,… Soft because meanings change Designed Systems E.g. cars, planes, buildings,freeways, telephones, the internet,… Human Activity Systems E.g. businesses, organizations,markets, clubs, … E.g. any designed system when wealso include its context of use
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