For years philosophers have enquired into the nature of the mind, and specifically the mysteries of intelligence and consciousness. (O’Brien 2017) One of these mysteries is how a material object, the brain, can produce thoughts and rational reasoning. The Computational Theory of Mind (CTM) was devised in response to this problem, and suggests that the brain is quite literally a computer, and that thinking is essentially computation. (BOOK) This idea was first theorised by philosopher Hilary Putnam, but was later developed by Jerry Fodor, and continues to be further investigated today as cognitive science, modern computers, and artificial intelligence continue to advance. [REF] Computer processing machines ‘think’ by recognising information …show more content…
CTM is the school of thought in which our brains are considered as computers and thinking is considered as computations. This thinking, including intelligence, consciousness, thought processes, and essentially everything that makes one’s mind, is often likened to computer software, while the brain is likened to hardware. CLARK. CTM was developed in such a way to explain the mind and mental causation while adhering to the philosophy of materialism, in which the universe is entirely physical. The theory achieves this by explaining that our thinking is a physical process, or communication between the physical parts of our brain. This is because computation in itself is a physical process where decisions are caused or shaped in response to information (O’Brien 2017). The mind receives information, or more specifically input, through our bodies’ senses. This information is recognised and processed by the brain through a corresponding set of instructions, or algorithms, to perform a logical response to the information, or an output. For example, we recognise that a plant is dying (input) and associate this input with corresponding sequence of discrete actions, watering the plant (output). This physical process of computation as thinking LINKY …show more content…
Specifically, in how the theory likens conscious intelligence to a mimicry of consciousness. In Alan Turing’s study of computing and consciousness, he developed the Turing Test, which essentially led to the notion that if a computing machine or artificial intelligence could perfectly mimic human communication, it was deemed ‘conscious’. REF. However, many do not agree and instead argue that while computers may be able to portray consciousness and semantics, it is not commensurable to actual thought and consciousness. Simulation is not the same as conscious thinking, and having a conscious understanding of the sematic properties of the symbols it is manipulating. This flaw was portrayed in John Searle’s thought experiment, ‘The Chinese Room’. Searle places a person who cannot speak Chinese in a room with various Chinese characters and a book of instructions, while a person outside of the room that speaks Chinese communicates through written Chinese message passed into the room. The non-Chinese speaker responds by manipulating the uninterpreted Chinese characters, or symbols, in conjunction with the syntactical instruction book, giving the illusion that they can speak Chinese. This process simulated the operation of a computer program, yet the non-Chinese speaker clearly had no understanding of the messages, or of Chinese, and was still able to produce
Computationalism: the view that computation, an abstract notion of materialism lacking semantics and real-world interaction, offers an explanatory basis for human comprehension. The main purpose of this paper is to discuss and compare different views regarding computationalism, and the arguments associated with these views. The two main arguments I feel are the strongest are proposed by Andy Clark, in “Mindware: Meat Machines”, and John Searle in “Minds, Brains, and Programs.”
In this paper I will evaluate and present A.M. Turing’s test for machine intelligence and describe how the test works. I will explain how the Turing test is a good way to answer if machines can think. I will also discuss Objection (4) the argument from Consciousness and Objection (6) Lady Lovelace’s Objection and how Turing responded to both of the objections. And lastly, I will give my opinion on about the Turing test and if the test is a good way to answer if a machine can think.
One of the major differences between humans and animals is our ability to reason and differentiate our actions from our instincts (Barrett, 2011, p. 3). Justin Barrett further explains this distinction in the first chapter of his book, Cognitive Science Religion and Theology. He explains that cognitive science recognizes the uniqueness of the human mind and focuses on explaining the thinking processes that take place(Barrett, 2011, p. 5). This may seem similar to what the field of neuroscience aims to do but, cognitive science is not as interested with the biological functions of the brain. Instead of looking at physical structures Barrett writes, that cognitive science focuses on broader processes such as perception, attention, memory, reasoning and learning (Barrett, 2011, p. 7). All of these processes interact with each other to create the big questions asked in cognitive science. Some of these big underlying questions of cognitive science are explored in this first chapter, questions such as “What is innate?” or “How are mind and bodies
One of the key questions raised by Rupert Sheldrake in the Seven Experiments That Could Change the World, is are we more than the ghost in the machine? It is perfectly acceptable to Sheldrake that humans are more than their brain, and because of this, and in actual reality “the mind is indeed extended beyond the brain, as most people throughout most of human history have believed.” (Sheldrake, Seven Experiments 104)
Searle's argument delineates what he believes to be the invalidity of the computational paradigm's and artificial intelligence's (AI) view of the human mind. He first distinguishes between strong and weak AI. Searle finds weak AI as a perfectly acceptable investigation in that it uses the computer as a strong tool for studying the mind. This in effect does not observe or formulate any contentions as to the operation of the mind, but is used as another psychological, investigative mechanism. In contrast, strong AI states that the computer can be created so that it actually is the mind. We must first describe what exactly this entails. In order to be the mind, the computer must be able to not only understand, but to have cognitive states. Also, the programs by which the computer operates are the focus of the computational paradigm, and these are the explanations of the mental states. Searle's argument is against the claims of Shank and other computationalists who have created SHRDLU and ELIZA, that their computer programs can (1) be ascribe...
Computers are well known for their ability to perform computations and follow a list of instructions, but can a computer be a mind? There are varying philosophical theories on what constitutes a mind. Some believe that the mind must be a physical object, and others believe in dualism, or the idea that the mind is separate from the brain. I am a firm believer in dualism, and this is part of the argument that I will use in the favor of Dennett. The materialist view however, would likely not consider Hubert to be a mind. That viewpoint believes that all objects are physical objects, so the mind is a physical part of a human brain, and thus this viewpoint doesn’t consider the mind and body as two separate things, but instead they are both parts of one object. The materialist would likely reject Hubert as a mind, even though circuit boards are a physical object, although even a materialist would likely agree that Yorick being separated from Dennett does not disqualify Yorick as a mind. If one adopts a dualism view and accept the idea that the mind does not have to be connected to a physical object, then one can make sense of Hubert being able to act as the mind of Dennett. The story told to us by Dennett, is that when the switch is flipped on his little box attached to his body, the entity that controls Dennett, changes to the other entity. Since the switches are not labeled, it is never known which entity is
I will begin by providing a brief overview of the thought experiment and how Searle derives his argument. Imagine there is someone in a room, say Searle himself, and he has a rulebook that explains what to write when he sees certain Chinese symbols. On the other side of the room is a Chinese speaker who writes Searle a note. After Searle receives the message, he must respond—he uses the rulebook to write a perfectly coherent response back to the actual Chinese speaker. From an objective perspective, you would not say that Searle is actually able to write in Chinese fluently—he does not understand Chinese, he only knows how to compute symbols. Searle argues that this is exactly what happens if a computer where to respond to the note in Chinese. He claims that computers are only able to compute information without actually being able to understand the information they are computing. This fails the first premise of strong AI. It also fails the second premise of strong AI because even if a computer were capable of understanding the communication it is having in Chinese, it would not be able to explain how this understanding occurs.
How can the brain be a mind, a conscious person? Recently, some philosophers have argued that human consciousness and cognitive activity, including even our moral cognition and behavior, can best be explained using a connectionist or neural network model of the brain (see Churchland 1995; Dennett 1991 and 1996). (1) Is this right? Can a mass of networked neurons produce moral human agents? I shall argue that it can; a brain can be morally excellent. A connectionist account of how the brain works can explain how a person might be morally excellent in Aristotle's sense of that term.
Computers are machines that take syntactical information only and then function based on a program made from syntactical information. They cannot change the function of that program unless formally stated to through more information. That is inherently different from a human mind, in that a computer never takes semantic information into account when it comes to its programming. Searle’s formal argument thus amounts to that brains cause minds. Semantics cannot be derived from syntax alone. Computers are defined by a formal structure, in other words, a syntactical structure. Finally, minds have semantic content. The argument then concludes that the way the mind functions in the brain cannot be likened to running a program in a computer, and programs themselves are insufficient to give a system thought. (Searle, p.682) In conclusion, a computer cannot think and the view of strong AI is false. Further evidence for this argument is provided in Searle’s Chinese Room thought-experiment. The Chinese Room states that I, who does not know Chinese, am locked in a room that has several baskets filled with Chinese symbols. Also in that room is a rulebook that specifies the various manipulations of the symbols purely based on their syntax, not their semantics. For example, a rule might say move the squiggly
Davis, Tom. The Theories of the Mind Lectures. Ed. G. Baston. Birmingham University. 9 Nov. 2000
Since antiquity the human mind has been intrigued by artificial intelligence hence, such rapid growth of computer science has raised many issues concerning the isolation of the human mind.
Most of the body’s functions such as, thinking, emotions, memories and so forth are controlled by the brain. It serves as a central nervous system in the human body. The mind is the intellect/consciousness that originates in the human brain and manifests itself in emotions, thoughts, perceptions and so forth. This means that the brain is the key interpreter of the mind’s content. Jackson and Nagel seem to resist identifying what we call “mental events” with brain events, for different reasons, while J.J.C. Smart takes the opposing view.
...lligent, intentional activity taking place inside the room and the digital computer. The proponents of Searle’s argument, however, would counter that if there is an entity which does computation, such as human being or computer, it cannot understand the meanings of the symbols it uses. They maintain that digital computers do not understand the input given in or the output given out. But it cannot be claimed that the digital computers as whole cannot understand. Someone who only inputs data, being only a part of the system, cannot know about the system as whole. If there is a person inside the Chinese room manipulating the symbols, the person is already intentional and has a mental state, thus, due to the seamless integration of their systems of hardware and software that understand the inputs and outputs as whole systems, digital computers too have states of mind.
Speculations on the origin of the mind have ranged from ghosts to society. Each new theory brings about more speculation and disagreement than the last. Where the mind resides, where it came from and if the brain has any involvement with the concept are common questions that fuel theory paradigms. Those questions are also the foundation of the debate about the roll of experience versus the existence of innate capacities. Steven Pinker theorizes the mind as a computing system created by the brain to fill the gap between innate capacities and capacities missing using common sense and learned critical thinking skills.
In the past few decades we have seen how computers are becoming more and more advance, challenging the abilities of the human brain. We have seen computers doing complex assignments like launching of a rocket or analysis from outer space. But the human brain is responsible for, thought, feelings, creativity, and other qualities that make us humans. So the brain has to be more complex and more complete than any computer. Besides if the brain created the computer, the computer cannot be better than the brain. There are many differences between the human brain and the computer, for example, the capacity to learn new things. Even the most advance computer can never learn like a human does. While we might be able to install new information onto a computer it can never learn new material by itself. Also computers are limited to what they “learn”, depending on the memory left or space in the hard disk not like the human brain which is constantly learning everyday. Computers can neither make judgments on what they are “learning” or disagree with the new material. They must accept into their memory what it’s being programmed onto them. Besides everything that is found in a computer is based on what the human brain has acquired though experience.