Narrow versus Wide Mechanism by Copeland and Bounded Rationality in Social Science by Simon - Literature review Example

?Mechanism and the Rationality of Human Behaviour and Mind Humans are viewed as creatures that have capabilities of rationalising the events that happen all throughout their lives. Sensible decisions are the products of numerous experiences stored in the human brain, and that these choices are affected by multitudes of if-and-then situations that are constantly firing inside the neurons of the brain. With this in mind, it would seem that the human mind is very much like a supercomputer, making numerous assessments and finding out answers to dilemmas using different analogies, formulae, as well as taking into account which among these options would produce the best result. In B. Jack Copeland’s paper entitled, Narrow versus Wide Mechanism: Including a Re-examination of Turing’s Views on the Mind-Machine Issue (Copeland, 2000), he examines the previous work by Alan Turing on the similarities between his Turing Machine and its similarities to the human brain. Also, the misinterpretations of Turing’s ideas by other theorists were presented in the paper, as well as other theories that either support or debunk them. On the other hand, the rationality of human behaviour in terms of choices and the products of such in the eyes of economists, behavioural analysts and social scientists were presented by Herbert A. Simon in his paper entitled, Bounded Rationality in Social Science: Today and Tomorrow (Simon, 2000). Changes in the trends concerning human choices over several decades as the effect of evolving cultures and ideas was explained and mulled over by seeing human behaviour as the result of decisions, along with theories and models that could possibly explain why recurrences are possible in places where people are expected to be thinking differently from one another. The first paper is Copeland’s views on the connection between the human mind and Alan Turing’s computing machines, as well as the views of narrow and wide mechanisms’ school of thought. Initially, computers are termed as humans who can calculate or perform tasks under specific rules of guidelines and can be considered to be both undisciplined but unintelligently so (Copeland, 2000, p. 11). In building his theory that computing machines can be made to work just as clerks can do numerous tasks at the same time, several connections were made: The theory of mechanism is that the human body is made up of several parts that function as a whole, and much like machines such as clocks, each part has the task of contributing to the movement of the body. However, the human body is capable of self-repair and movement afterwards, while machines such as clocks do not have such capacity (Copeland, 2000, p. 6). The human mind and body are governed by sets of rules that allow it to move accordingly to what is needed, and that the selection of actions is determined by the pre-selected options in the mind, which are in the forms of memories. Much like in computers, problems are solvable only by what functions and options are available in their stored memories (Copeland, 2000, p. 8). Narrow mechanism believes that the mind is a machine that can be strictly simulated by a Turing machine, however, wide mechanism states that there is a strong possibility that although the human mind is indeed a machine, it cannot be imitated by a Turing machine thoroughly, thus dynamic and cognitive behavioural systems of the human mind cannot be calculated by the universal Turing machine (Copeland, 2000, p. 10). The creation of the computer was to make a machine capable of doing the computing work of hundreds to thousands of humans at the same time, proving the notion that similar to humans following a specific set of guidelines, logical computing machines when programmed with the appropriate procedures to do can also do anything that is within the set of instructions, making the process mechanical in nature (Copeland, 2000, pp. 13-14). However, several theorists proposed ideas that not all machines can be programmed to compute everything, and a time may come that some functions or problems would prove to be unsolvable to computing machines. To answer this, Turing was able to introduce a new type of machine called the Oracle or O-machine, which is able to solve mathematical problems that are proven unsolvable by logical or Turing machines (Copeland, 2000, p. 17). Unfortunately, he was not able to prove that the human mind is an O-machine, and his results showed instead that and O-machine works similarly like a Turing machine. This gave other theorists like the Churchlands the idea that the human brain is able to display systematic pattern of responses based on environmental stimuli, thus stipulating that the mind-brain processes are computable based on a “rule-governed” input-output function (Copeland, 2000, p. 22). Narrow mechanists believe that the human mind can be computed and scientifically explained much like Turing machines, and that idea is due to the beliefs that: Thesis M: All functions that can be generated by machines (those that work on finite input in accordance with a finite program of instructions) are Turing-machine-computable (Copeland, 2000, p. 15); and Thesis S: Any process that can be given a systematic mathematical description (a precise characterization of a set of steps, or that which is scientifically describable or explainable) can be simulated by a Turing machine (Copeland, 2000, p. 23). In line with such beliefs, artificial intelligence can thus be simulated by creating a system that consists of physical symbols within a storage system with a large yet finitely-possible capacity, thus asserting the idea that the mind can be simulated by a Turing machine (Copeland, 2000, p. 24). Such ideas make Turing seem that he firmly believes in the programmed and readily-simulated state of the human mind. It must be noted, however that in Turing’s time he was referring to computers as humans that were doing computations for industries or whatever body entails their computing services (Copeland, 2000, p. 27). This resulted in misleading ideas that started from Turing’s original thesis that the universal computing machine is able to do multiple jobs that human computers are capable of doing. He states the importance of the universal computing machine by having a single one that is able to do multitudes of tasks, much like humans, and programming the machine to do different jobs also means that a machine does not need to be limited with doing just one thing (Copeland, 2000, p. 27). In this case, it can be inferred that Turing’s thesis explains that the human mind is a partially random machine, or a machine under a discrete-state, with finite lookup tables or flowcharts instead of singular programs or functions. Such machines are digital in nature, and that the function of the machine is enhanced by an infinite storage capacity, which explains why such machine is different from a Turing machine (Copeland, 2000, p. 28). Thus, Turing’s views on the human mind were; Minds work like O-machines or oracles, in the sense that they have genuinely random output, which follows specific branching actions that result from if-and-then situations (Copeland, 2000, p. 29); Much like the random elements in the human mind, the behaviours of o-machines or discrete-state machines are not completely determinable, thus the random occurrences that seem similar to free will (Copeland, 2000, p. 29); The brain is capable of free will, so in order to make machines that function in the same way as the brain these machines must have an output that makes it produce random results. However, for the maker of such machine the behaviours would not be random since the possible output were already predetermined (Copeland, 2000, p. 30); The paper is concluded that the human mind can be both a discrete-state machine and a Turing machine, given the assumptions that it has both finite but suitable lookup tables, as well as specific functions or programs that are built to adhere to constraints such as resources and options. With this in mind, narrow mechanism alone would not be able to explain fully the processes underlying the human brain, and that wide mechanism offers more by being much more open to other possible models of the human brain. The next paper written by Herbert Simon deals with human rationality, its boundaries based on a person’s capacity, knowledge, and options when used in the setting of economics. Bounded rationality is basically a theory that explains why the products of decisions cannot be predicted without the prior knowledge of the processes behind them (Simon, 2000, p. 26). Such an idea that human rationality is limited is not entirely new, however when economists such as Adam Smith started to analyse human behaviour generally in terms of utilities and practical behaviours, the idea of rationality being bounded by personal choices were pushed aside. Thus the term “reasonable” became equated with people that confide to the rules of utility maximisation, which was able to predict the behaviour of decision-makers (Simon, 2000, p. 27). The predictability of human rationality however was challenged by the proliferation of the principle of uncertainty. This was introduced due to the other events and theories first introduced under the utility theory (Simon, 2000, p. 29): Probability theory – the theory was unable to provide answers regarding as to where the decision makers’ probabilities came from, thus the greater uncertainty for the frequency distribution of future probabilities; Game theory – a theory that is explainable but only under equilibrium, and that the uncertainty only arises due to mutual outguessing of its players. However the theory was unable to explain that in order for the players to come up with similar solutions, there should also have been a need to have factual information in order to react accordingly; Rational expectations – the model assumed that all economic actors were thinking of the same economic model when making decisions. However, not all actors were able to come up with the most effective model, thus accounting for differences in how they think; Experimental economics – some phenomena were unexplained by theories that predicted behaviour, such as boom-bust phenomena in trading. Thus substantive rationality was not able to explain irrational trading behaviours. In order to account for such irrationalities, human decision-making models were made based from the social science disciplines, as well as psychology. This would require economists to devise new methods of research such as using formal methods to build theories and test them, as well as using empirical methods of discovering relevant phenomena to decision-making (Simon, 2000, p. 30). Such social science methods are: Field studies and interview methods; Sample polls; Field and laboratory experiments; Observations of operations in organisations; and Use of qualitative and quantitative data in statistical and regression analyses. The use of psychological theories in assessing decision-making was done due to being able to map how such rationalities happen. There were also empirical data that were generated in the processes that aim to explain such behaviours. The scientists found out that the differences in human behaviour were due to uncertainties that result to deviations in normally-expected results (Simon, 2000, p. 33). Thus it was hard for economists to fully explain such deviations, collect the causes and compress them into one single idea and form the rationality theory in full. Human rationality under the field of economics was further explained under theories formulated by social sciences. Generalisations were: Due to dissatisfactions in the utility theory as the core of human rationality, economists became interested to alternative theories and empirical approaches (Simon, 2000, p. 34); Pragmatic rationality and its effect on economics started to wane, and the new theory on rationality was able to generate new alternative ideas to choose from, which makes for theories that are able to explain long-term economic phenomena (Simon, 2000, p. 35); Organisation and systematisation of economic processes are still needed in reforming the theory on rationality (Simon, 2000, p. 35). In order to fully organise such; methods must be employed in order to develop the rationality theory (Simon, 2000, p. 35): Improvement of data gathering methods (observation, interviewing, information extraction regarding decision-making processes, analysing protocols, trainings in design and conduct of controlled experiments, etc.); Use of appropriate tools in building up the theory (e.g. computer simulations); Use of tools to test theories made (e.g. simulations, experimental work, etc.); Dealing with the uncertainty in different aspects of human decision-making process, taking into account the dynamism of the utility function (the future environment, reactions of all decision-makers at any given situation, changing tastes and values of decision makers). The author was able to enumerate ways in how to deal with the uncertainties of human behaviour with regards to different decision-making processes, and that the rationalities of these people are uniquely bounded by thoughts that were available at the time that the decisions must be made. This explains why some human actions are found to be rather unpredictable based on the existing theories that were supposed to explain general human behaviour. It is suggested that methods normally used in social science studies must also be utilized to further create models that are reliable in shaping a theory or theories that could explain trends in the field of economics. The two papers, while bearing numerous differences were also similar in terms of explaining the way a human mind thinks. The paper about the mind-machine connection is able to show how the human mind can be explained in mechanism terms, thus giving it similarities to computers. The second paper that dealt with the rationality of people as well as the processes of using methods in the social sciences to explain unpredictability in decision-making processes. In a way, the two papers were able to show that decisions made by people are those that were based on available options to them, and are similar to pre-programmed functions in computers. The randomness of human decisions are also accounted to the numerous flowcharts in the human brain as the result of numerous stored memories, making the human brain work very much like modern digital computers. Bibliography Copeland, B. J. (2000) Narrow versus wide mechanism: including a re-examination of turing's views on the mind-machine issue. The Journal of Philosophy, 97(1), pp. 5-32. Simon, H. A. (2000) Bounded rationality in social science: today and tomorrow. Mind & Society, 1(1), pp. 25-39. Read More