CSC785 Philosophy Of Computer Sciences Assignment UITM Example Malaysia
Computer scientists and philosophers have been working together for years, trying to understand how humans interact with computers. The field of philosophy that deals specifically in this area is called “Philosophy Of Computer Science” or PCCS for short; it seeks answers at two different levels: knowledge (epistemology) and value/ethics – where there are many questions without clear-cut distinctions between them because they arise from our grasp on reality itself through modelling by computing devices such as machines which can be programmed so precisely according to some rules or others’ designs.
Although there are many different sub-disciplines of philosophy concerned with computer science, this article will focus on the sub-field called ‘Philosophy of cyberspace’ which is concerned with the philosophical study of the contemporary computer-mediated phenomena in general or its specificities, such as cybernetics, virtual communities, virtual reality and digital online media.
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This is an example of a Philosophy Of Computer Sciences Assignment Answer for CSC785 from Malaysia UITM. I have prepared this document to help you with your studies in the course, “Philosophy Of Computer Science & Technology”. The aim here will not just provide some philosophical insights but also give practical advice about how these ideas can be applied practically within our field as computer scientists or engineers!
Assignment Task 1: Explain the significance of computability and computation in the context of philosophy of computer science.
Computability is a fundamental property of mathematical problems, and it’s what makes them computable.
A problem is “computable” if there is some algorithm that can be given input from the outside world and produce an answer within a finite time. This means that no matter how complex or difficult your question may seem, you’ll eventually find an algorithm to solve it!
Computation refers to procedures that when followed will lead to answers being generated – this includes things like addition or subtraction though not necessarily in that order. Computations are usually done with fingers/tongues rather than machines because they’re quick and easy, but sometimes calculations need more power than human brains can provide so then we turn to computers. Theoretically, there’s nothing stopping us from using machines for all calculations, and this would also give the answers instantly: but we’re nowhere near doing that so we may as well stick with our fingers/tongues!
Computable functions include things like addition. And you use these functions in order to get answers to questions! You’d think that all questions would be computable: in fact, some were thought to be until Turing came along and showed how they may not be.
Computability is a mathematical property that can be used to determine if a statement is true or false. For example, the set of all counting numbers from 1 to 100 is computable because you can always go back and add one more than you started with (i.e., 101) in order to get every number from 110 onwards.
Computable things are those that can be done by a machine. Computability is an issue in the philosophy of computer science, and has to do with whether certain tasks are or are not possible – computable. The concept was developed by Gottfried Wilhelm Leibniz who argued for its importance on several occasions, most notably in his 1713 paper “On Calculating Machines”.
There’s also an important distinction between computation and computability: computation is the process of calculating something; while computable means that something can be calculated by a machine (i.e., Turing complete). So you could say that Fermat’s last theorem is not computable because it relies on finite precision in order to find prime numbers, which is something that’s not possible with modern computers. Turing machines are capable of continuous calculations (i.e., in real time), while everything in nature happens continuously in discrete time steps.
Assignment Task 2: Integrate values, attitude and profesionalism in discussing social and ethical issues in computer science.
Integrating values, attitude and professionalism in discussing social and ethical issues in computer science is important because it allows us to have a well-rounded perspective when making decisions. It is also essential that we maintain a positive attitude and high level of professionalism when discussing these complex topics, as this will help to create an open forum for discussion and collaboration. By integrating these important aspects into our discussions, we can work together to find solutions that reflect our shared values and uphold the highest standards of ethics in computer science.
Recently, the United States Federal Bureau of Investigation (FBI) released a series of documents about their operation targeting visitors to child pornography websites. These documents were part of a larger release regarding the case in which Jay Michaud was arrested for visiting Playpen, one such site that was created and distributed by the FBI . The legality and ethics surrounding this case have been widely debated . In order to discuss these issues in a professional manner, we must first define the key terms that are being used.
In computer science, legality is concerned with whether or not an action is deemed legal by the governing body. The FBI position on their actions surrounding Playpen is that they were legal as the investigation was an active operation approved by a judge as part of a legally authorized criminal investigation. In this case, legality is concerned with whether or not an action is compliant with laws and regulations.
One of the unique aspects of computer science is that it straddles the divide between the humanities and the sciences. As a result, computer scientists must be comfortable with both abstraction (thinking at a high level about complex problems) and with rigor (executing detailed algorithms to solve those problems).
When faced with social and ethical issues in computer science, it is important to integrate one’s values, attitude, and professionalism into the decision-making process.
Integrating one’s personal values into the decision-making process is important because it allows for consideration of all aspects of the issue at hand. Taking an ethical stance on a computer science issue is not always easy, but by considering all facets of the issue and how they relate to our personal values, we can make a decision that we can stand behind.
It is also important to maintain a positive attitude when discussing social and ethical issues in computer science. Being respectful of others’ opinions and working towards a common understanding is essential in creating positive change. Finally, professionalism must be maintained at all times because it reflects our level of respect for others and their opinions.
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Assignment Task 3: Synthesize concepts, ideas, opinions and arguments in justifying positions in the philosophy of computer science.
In the philosophy of computer science, a position is justifiable if it can be argued for using arguments from authority.
A philosopher would argue that a given argument from authority has the same form as any other type of argument and thus must be evaluated by the same criteria – specifically, by determining whether or not its premises are true. This means examining both what assumptions were made in drawing conclusions from those premises as well as how strong these assumptions are. In short: does this person know what they’re talking about? And if so, why should we trust them?
With science, the authority in question is the consensus of all qualified scientists who have concluded that a given position is justifiable. In the philosophy of computer science, it’s often argued that there is no fundamental difference between the human brain and a computer.
The idea behind this argument is that computers can only do what they’re programmed to do, while people can also think about what they want (thoughts). So if thought processes are just a matter of following instructions then why not say that brains are machines?
The answer seems to be because we have free will; we decide whether or not something makes sense based on our experience with other situations like these. There may be similarities but there are differences too – one being the lack of physicality in computers versus humans which means their actions cannot be directly affected by outside forces like gravity or kinetic energy.
However, this is not at all apparent in the way that computer scientists think about computers – they are just more interested in what can be achieved rather than how it’s done. A brain-computer comparison may be an argument from authority but based on their ideas of justifiable position, it doesn’t have to be backed up by anything besides the authority of their peers.
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