COGS assignment 1 Lukas Panos Set 1: (Q1) Symbolic representation involves using symbols—images, objects, gestures, sounds, or signs—to convey meaning or information. These symbols don't necessarily resemble what they represent; their significance is socially agreed upon. For instance, the dollar sign "$" symbolizes money, and the peace symbol represents peace, anti-war movements, and harmony, even though it doesn't directly resemble these concepts. In cognitive science, the concept of symbolism resembles mental representations very closely. Mental representations are internal structures that stand for external objects, events, or ideas. Symbolic representation in the mind employs mental symbols to process information. A comparison can be drawn between symbolism and analogies in cognitive science, where associations between concepts and images aid information processing. Language is a prime example of symbolic mental representation. Words, such as "tree," symbolize physical objects. This interplay between symbols and mental representations is fundamental in human cognition, facilitating abstract thinking, communication, and information processing. (Q3) Concepts and propositions are two distinct forms of mental representations in the field of cognitive science. In a broad sense, a logical proposition is a statement about the world that asserts or denies something and can either be true or false. More specifically, logical propositions are assertions that will express relationships between concepts and through that convey specific information. For example, a logical proposition could be: "Freedom is important in order to be happy.". Logical propositions are more suitable to use when conveying specific information or making statements. We can often see logical propositions being used in language comprehension and communication, enabling the expression of complex ideas through these propositions. On the other hand, a concept is an abstract idea or a general notion of things.They stand for general ideas and usually come from mental representations formed through various experiences. For example, a concept could be "freedom” and “happiness”. Concepts are more suitable when dealing with generalizations or categorizations made in language. They help in simplifying and organizing information. In cognitive science, they are essential for cognitive efficiency, allowing the mind to categorize and recognize patterns in the environment. Both concepts and logical propositions however are fundamental to language and communication. In relation to better understanding the world, concepts help us by providing generalizations and categories whilst propositions help us by enhancing understanding by expressing specific relationships and details. (Q4) The halting problem in relation to the Turing machine is a statement about computational processes in computer science. Through his statement, Alan Turing wondered whether there exists a specific algorithm that will accurately determine whether any arbitrary program will terminate or run indefinitely. This was investigated under the lens of the Turing machine. Alan Turing came to the conclusion that the turing problem was undecided. As Turing stated in his argument ,which was a proof by contradiction, if you had a general algorithm to determine halting, you could construct a specific case where the algorithm would fail to provide the correct answer. (Halting Problem: Turing Theory & Machine | StudySmarter, n.d.) The undecidability of the halting problem had many impacts on the world of computing and artificial intelligence. In a broad sense it showed us that there are problems that computers are not able to solve. It highlighted the limits of tools or systems that can analyze and predict the behavior of other programs. Thus, it demonstrated the fundamental limitation in algorithmic analysis. Moreover, the halting problem has important implications for understanding the boundaries of what algorithms can and cannot calculate. It established limits in computation, affecting diverse fields such as Artificial Intelligence and Cybersecurity and introduced the concepts of “incomputability”. In sum, it allows us to make more reasonable assumptions when creating software and to accept imperfections in our code. Set 2 (Q1) Monism describes that the mental state corresponds to some physical state which implies that the brain and the mind are one entity. Monism states that mental phenomena can be explained through physical processes in the brain. In other words, there is no separate mental substance; mental states are entirely dependent on and determined by the physical processes of the brain. Thus, the brain, a physical substance, will dictate through physical processes what the mind thinks (a mental substance). A counterexample to this was introduced by dualism which states that there exists a separation between the mind and the body, asserting that mental and physical substances interact. This implies that free will and consciousness are solely mental phenomenons. Another counterexample is that there exists the challenge of explaining why and how certain physical processes in the brain give rise to subjective experiences, consciousness and free will. This implies that these phenomenons are caused by the brain processes but cannot completely be reduced to them. (Q4) In the Chinese Room experiment, John Searle aimed to investigate whether computational processes that replicate thinking also imply the replication of consciousness. The experiment's findings led to the argument that the ability to answer questions does not necessarily indicate understanding of the meanings involved. Searle's distinction between syntax and semantics is central to his critique. He asserts that while a computer may proficiently answer questions based on syntactic rules, it lacks true understanding of consciousness. The division between syntax and semantics underscores Searle's contention that intelligent task execution by computers doesn't equate to genuine intelligence or the capacity for true thought. Thus, the Chinese Room experiment goes against the idea that computational processes alone can replicate the depth of human cognition and consciousness. (Q5) Strong AI otherwise known as general artificial intelligence is broadly defined as machines with genuine consciousness and mental states akin to humans. Strong AI tells us that minds that are computable, suggesting that mental processes, including consciousness and intelligence, can be fully replicated and integrated into computers or machines. Machines characterized as strong AI would be able to have free thought, be self aware and have emotion. These machines would also be able to perform certain tasks resembling those that humans can only do. These could be language understanding, expression of emotion,basic reasoning and creativity. Furthermore, the concept of machine consciousness is central to strong AI, suggesting that machines can exhibit mental states and cognitive capacities equal to or surpassing those of humans. The strong AI perspective rejects the notion that there is something inherently unique about biological systems, positing that machines could achieve consciousness without being limited by biological substrates. (Q6) Daniel Dennet addresses the idea that consciousness is too intricate to replicate computationally through a classical or centralized view and a multiple draft model. The centralized or classical view talks about how consciousness can emerge from various information possessing streams of the brain. He makes the comparison of the brain with a theatre where a single person is watching a projection of all the information of the brain on the screen. The person's subjective feelings represent consciousness. However, not all information about an event is not received at the same time. Thus, he states that consciousness does not exist in real time. So, immediate experiences are just an illusion. Afterwards, he proposed an alternative view named the multiple draft model. The argument states that we receive information through various senses like sight, sound, and touch, but these inputs arrive at different times and speeds. (Daniel Dennett’s Been Thinking About Thinking—and AI, 2023) Simultaneously, different mental processes modify this information. Consequently, consciousness is not specific to a single area in the brain; instead, it is distributed. As the information undergoes modifications in different streams, we can observe these changes before or after they occur. An example is our visual perception, involving input from both eyes and processing through multiple streams, resulting in different levels of awareness at different stages. This perspective also clarifies three levels of awareness: conscious, preconscious involving anticipation of events, and subconscious awareness where events are not actively in our awareness but can become conscious later on. Set 3 (Q1) Introspection, as a method of experimentation, faces criticism for being subjective and lacking objectivity, relying on individuals' self-reports that are susceptible to personal biases and influences. Thus, the interpretative aspect of introspection raises concerns about the reliability of the data. Additionally, introspection largely overlooks unconscious processes and influences. Critics argue that many mental phenomenons, including motivations, desires, and certain cognitive processes, occur at an unconscious level and are not always observable from the exterior. (Sze, 2017) Furthermore, the difficulty in verifying and replicating results poses challenges to the scientific credibility of introspection. The private and subjective nature of introspective observations makes obtaining external review difficult. Moreover, the lack of standardized procedures prevents the studies from being consistent and replicable , which undermines the method's reliability. (Q4) A hypothesis is a specific, testable proposition that aims to address a particular aspect of a phenomenon or relationship. It is usually a new idea which has not yet been provided, validated or tested. Once a hypothesis undergoes testing, and the evidence consistently supports it may be implemented to support scientific research and become a theory. Theories, therefore, are hypotheses that were scientifically validated many times and accepted.These provide support to scientific research and help us better understand the world. (Q5) Functionalism is a psychological philosophy that describes the mind as a tool that enables us to adapt to our environments. On the other hand, structuralism is a physiological view that focuses on breaking down the mental processes by the relationships between them rather than by their individual functions. Firstly, these two differ in their focus on mental processes. Structuralism focused on analyzing the structure of conscious experience. It aimed to identify and describe the basic elements or components of the mind, often breaking down mental experiences into their elemental parts. In contrast, functionalism shifted the focus from the structure to the function of mental processes. Rather than solely looking at individual elements, functionalism aimed to understand how mental processes can help individuals adapt to different environments. Secondly, these two differ in their methodology. Structuralism relied on an introspective approach where the individuals would report their thoughts, feelings and emotions in response to stimuli. Functionalism relied more on studying the adaptive functions of behavior. Thus, they did direct observation to understand how mental processes helped individuals adapt to their environments. Lastly, these two psychological approaches differed in their views of consciousness. Structuralism puts emphasis on understanding the basic building blocks of introspective experiences, such as sensations, perceptions, and feelings. In contrast, functionalism states that consciousness is an ongoing and flexible process, highlighting its ability to help us adapt. Work Cited 1. Halting Problem: Turing Theory & machine | StudySmarter. (n.d.). StudySmarter UK. https://www.studysmarter.co.uk/explanations/computer-science/theory-of-computation/ha lting-problem/#:~:text=The%20halting%20problem%20is%20an%20undecidable%20pro blem%20in%20computer%20science,for%20both%20humans%20and%20machines. 2. Daniel Dennett’s been thinking about thinking—and AI. (2023, October 2). Tufts Now. https://now.tufts.edu/2023/10/02/daniel-dennetts-been-thinking-about-thinking-and-ai 3. Sze, D. (2017, December 7). The limits of introspection. HuffPost. https://www.huffpost.com/entry/introspection-research_b_7306546 4. Friedenberg, J., & Silverman, G. (2011). Cognitive Science: An Introduction to the Study of Mind. SAGE.
