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Psychology and computer science are clearly distinct disciplines. As we have seen, there are obvious differences within the definitions and methodological approaches of the two. Still, despite the differences, there are some interdisciplinary subfields that try to fuse the two.

An interdisciplinary perspective on the two disciplines is cognitive science, wherein the human mind is seen as an information processor, a machine. According to cognitive scientists, the mind sees information in the same manner as computers do. First, it receives ‘input’ from a source. Then, this input is stored on some kind of ‘hard drive’. Finally, the input will be processed. The results of this process is the ‘output’ (Friedenberg, Silverman, 2006: p. 3). The mental representation of information is thus a significant part of cognitive science, which can be compared with information processing on computers.

A field that draws upon this is human-computer interaction (HCI). HCI can be seen as a merge between cognitive psychology and programming aspects of computer science, to create well designed interfaces. According to Carroll, it looks at how humans interact with technology, and how that can be supported through the design. It came into being partly because of “the recognition that computers can be deliberately designed to facilitate human activity and experience only when social and cognitive requirements drive the design process throughout” (Carroll, 1997: p. 62, 79). Therefore, cognitive psychology should be considered for the design of computer systems.

Another example is artificial intelligence (AI), early mentioned as a subset of computer science. AI scientists try to build machines that can automatically make intelligent decisions. They try to do this at the level of intelligence of a human agent, which should lead to the fact that the machine can act in the same manner as humans (Friedenberg, Silverman, 2006: p. 320). The consideration of what this intelligent behaviour is, comes from psychology.

Sources

Carroll, John M. (1997) ‘HUMAN-COMPUTER INTERACTION: Psychology as a Science of Design’, Annual Rev. Psych., 48, pp. 61-83.

Friedenberg, Jay, Gordon Silverman. (2006) Cognitive Science. An introduction to the Study of Mind. Thousand Oaks: Sage Publications Inc.

It is understandable that governments are becoming increasingly interested in the online activity of its citizens. According to Albrechtslund, governments are looking for information about individuals such as “shared activities and circles of friends, as well as personal data about political views, religious beliefs, sexual orientation, and preferences regarding everyday life activities (Albrechtslund, 2008). Social networking sites are for example used to get this information. The information that governments often want can also be stored in email conversations, on personal computers, in the cloud and so on.

Computer science can offer many perspectives on online surveillance. It does not necessarily look at the motives for or consequences of surveillance, like psychology does, but can focus on how surveillance is made possible or can be prevented through a technological perspective. It can address all the different phases in the process of online surveillance from the ‘Big Brother perspective and from the perspective of the person who is being watched. This means that it can look at where to look for useful data, how to retrieve this information, and how to analyze it, but at the same time it can look at how to prevent people spying on ones data.

Examples of where computer scientists thus might look for could be where data is stored on personal computers, how this data can be accessed, how encryptions can be created or cracked, which algorithms represent useful data, and how retrieved datasets can be analyzed. In many possible examples creating programs that can scan large and varying sets of data are important. Also, it is necessary to let these programs find specific words, websites, connections and so on, that might be interesting for the party that is watching.

Next time I will write my last blogpost about how computer science and psychology are related and how they can be bundled to study online surveillance.

Source

Albrechtslund, Anders. (2008) ‘Online Social Networking as Participatory Surveillance’, in First Monday, 13(3), online at: <http://journals.uic.edu/ojs/index.php/fm/article/view/2142/1949>

After looking for a reasonable definition of Computer Science and whether it can be considered a discipline last week, I wanted to focus on the different approaches to study the field this week. Initially I tried to do this with the help of an introductory book to Computer Science: Computer Science. An overview by Brookshear. I found that Brookshear explains more the different aspects of computers that can be studied. Therefore, I also looked at two other texts. Still, approaches in Computer Science do not seem as commonly separated as in Psychology. However, in the end of this post I will look at some approaches.

Brookshear starts in his book with explaining that algorithms are the most fundamental aspect of Computer Science. He defines an algorithm as “a set of steps that defines how a task is performed.” Algorithms are represented in a program. Creating these programs, is called programming (Brookshear, 2007: p. 18). Brookshear explains later in his book that “programs for modern computers consist of sequences of instructions that are encoded as numeric digits (Brookshear, 2007: p. 268).

Fundamental knowledge to understanding problems in Computer Science is to see how data is stored in computers. Computers store data as 0s and 1s, which are called bits. The first represents false, while the latter represents true. According to Brookshear, this true/false values are named Boolean operations (Brookshear, 2007: p. 36). Computers do not just store data, they also manipulate it. The circuitry in the computer that does this, is called the central processing unit (Brookshear, 2007: p. 96). Next to manipulating, data can also be transferred from machine to machine. If computers are connected in that manner, networks, this can happen (Brookshear, 2007: p. 164). The Internet is a famous example of an enormous global network of interconnected computers.

Computer Science has several subfields that are seen as separate studies. An example of this is software engineering. Brookshear claims that it “is the branch of computer science that seeks principles to guide development of large, complex software systems”(Brookshear, 2007: p. 328).  Another example is Artificial Intelligence (AI). Brookshear explains that the field of AI tries to build autonomous machines that can execute complex tasks, without the intervention of a human being. These machines therefore have to “perceive and reason” (Brookshear, 2007: p. 452).

Tedre gives a couple of examples of other subfields in Computer Science, but does not say that those subfields are the only or even most important ones. He sums up complexity theory, usability, the psychology of programming, management information systems, virtual reality and architectural design. Tedre argues that there should be an overarching set of rules for research in these fields. However, later he also argues that computer scientists often need to use approaches and methods from different fields, because this is the only way in which they can deal with the amount of topics in Computer Science (Tedre, 2007: p. 107, 108). Computer scientists thus seem to deal with the difficult task of incorporating many different fields, but at the same time they need to learn how to use a similar set of rules to study these fields.

Denning et al. define the most clear set of subfields in Computer Science: algorithms and data structures, programming languages, architecture, numerical and symbolic computation, operating systems, software methodology and engineering, databases and information retrieval, artificial intelligence and robotics, and finally human-computer communication. They justify their selection, because every one of those subfields has “an underlying unity of subject matter, a substantial theoretical component, significant abstractions, and substantial design and implementation issues” (Denning et al., 1989: p. 16, 17).

Tedre argues, based upon the research of Denning et al., that there have been three ‘lucid’ traditions in Computer Science: the theoretical tradition, empirical tradition and engineering tradition. He argues that because of the adoption of these different traditions, the discipline of Computer Science might have ontological, epistemological and methodological confusion (Tedre, 2007: p. 107).

I can conclusively argue that it is not easy to present a concise image of Computer Science. After having difficulties last week in finding one proper definition for Computer Science, this week I had problems in finding comprehensive ways in which Computer Science is studied. Next time, I will look at how Psychology and Computer Science can be used to study online surveillance. Later, I will also look how the two disciplines overlap.

Sources

Brookshear, J. Glenn. Computer Science. An Overview. Ninth Edition. Harlow: Pearson Education Limited, 2007.

Denning, P. et al. “Computing as a discipline”. Communications of the ACM 32(1), 1989: p. 9-23.

Tedre, Matti. “Know Your Discipline: Teaching the Philosophy of Computer Science”. Journal of Information Technology Education 6(1), 2007: p. 105-122.

When looking into the field of Computer Science, there seem to be many different views on the definition of the discipline. Some authors simply state a definition of the field, others say there is not one coherent definition, and some even argue that Computer Science cannot be considered as proper science. This week I will show some of these different views and herewith try to get an initial understanding of the field of Computer Science.

I will start with considering an author that has written a book to give (Computer Science) students “an overview of what Computer Science is”. Brookshear gives a definition of the discipline in the first line of his book:

“Computer Science is the discipline that seeks to build a scientific foundation for such topics as computer design, computer programming, information processing, algorithmic solutions of problems, and the algorithmic process itself”

(Brookshear, 2012: p. 16)

This definition seems a bit difficult to grasp, because Brookshear explains the field by giving examples of topics that it seeks to build a scientific foundation for. Still, an individual without previous technical knowledge does not necessarily understand what these topics encompass. Tedre says: “it is impossible to characterize the whole academic field of computing by making a list of topics with which all researchers would unanimously agree”. Tedre therefore argues that Brookshear’s definition has little “informational value” (Tedre, 2006: p. 349).

Tedre does not give his own definition of Computer Science, but explains that there have been many debates in the past about what Computer Science is about or should become. He adds that there are still is no complete consensus on the identity of Computer Science these days. The discipline has been diversifying radically since the rise of electronic digital computing, Tedre argues (Tedre, 2006: p. 161-162). This fact may also contribute to the inability in the scholarly world to come to a consensus about a solid definition for the field.

Tedre demonstrates this inability for example by the different opinions of Brooks and Hartmanis. Brooks argued in 1996 that Computer Science is a synthetic, engineering discipline. According to him, “anything which has to call itself a science, isn’t”. Also, he argues that computers are being seen more as tools and not as proper ends. This is led by “the emergence of new topic areas between computer science and many other disciplines” (Brooks in Tedre, 2006: p. 341-342). Hartmanis also thinks that Computer Science differs from other sciences, but he argues that it “is laying the foundations and developing the research paradigms and scientific methods for the exploration of the world of information and intellectual processes that are not directly governed by physical laws” (Hartmanis in Tedre, 2006: p. 346).  Tedre also quotes Minsky, whom in 1979 argued that Computer Science is hard to see as thing in itself, because it has so many relationships with other disciplines (Minsky in Tedre, 2006: p. 347).

Next to authors who simply state definitions of Computer Science or deny that it can be seen as a discipline, some authors explain why Computer Science can be seen as a discipline. The example that I pick here is coming from Dodig-Crnkovic. She argues that Computer Science is based on Logic and Mathematics. Herewith, she argues that there is one important difference, which qualifies Computer Science as a discipline just as well as the previously mentioned ones:

“The important difference is that the computer (the physical object that is directly related to the theory) is not a focus of investigation (not even in the sense of being the cause of certain algorithm proceeding in certain way) but it is rather theory materialized, a tool always capable of changing in order to accommodate even more powerful theoretical concepts.”

 (Dodig-Crnkovic, 2002: p. 7)

According to Dodig-Crnkovic Computer Science thus never has to reach an impasse, because of the ever evolving technology. Herewith, it can be considered as a scientific discipline.

Whereas I now looked at the different ways to define Computer Science, I will look into the different approaches in Computer Science next week.

Sources

Brookshear, J. Glenn. Computer Science. An Overview. Eleventh Edition. Harlow: Pearson Education Limited, 2012.

Dodig-Crnkovic, Gordana. Scientific Methods in Computer Science. Mälardalen University, 2002.

Tedre, Matti. The Development of Computer Science. A Sociocultural Perspective. University of Joensuu, 2006.

This week I have been looking at the basics of psychology. After I talked to a friend in the Netherlands, who studies psychology, I came to the conclusion that the book ‘Psychology’ by Peter Gray would be a solid introduction to the discipline and could introduce me in an appropriate matter to the subject. I scanned over the 654 pages of the book and learned about psychology’s basic methodologies and research fields.

On the first page of his book, Gray states the following:

“Psychology is the science of behavior and the mind. In this definition behavior refers to the observable actions of a person or an animal. Mind refers to an individual’s sensations, perceptions, memories, thoughts, dreams, motives, emotional feelings, and other subjective experiences.”

(Gray, 2007: p. 1)

After this formal definition, Gray continues with explaining that there are three foundation ideas for psychology. The first idea is that behavior and mental experience have physical causes, the second that mind and behavior are shaped by experience, and the last is that the machinery of behavior and mind have evolved through natural selection (Gray, 2007: p. 2).

These foundational ideas are explored by using different research strategies. Gray recognizes three categories in which these strategies can be ordered. The first is research design, wherefore experiments, correlational studies, and descriptive studies are needed. The setting is the second category. Herewith, one must think of either field or laboratory research. Finally, the data-collection method is important. The basic types are self-report and observation (Gray, 2007: p. 29). Another important factor of psychology is the usage of statistical methods to understand the data that has been collected. According to Gray, descriptive statistics are used to summarize sets of data. Inferential statistics help researchers in their confidence about the collected data (Gray, 2007: p. 35).

After the basic methodologies of psychology, Gray goes into more detail and talks about the different fields that are being explored in psychology and have shaped it to what it is now. Human behavior is an important field, that is often being examined  through genetic evolution and the environment around a human being (Gray, 2007: p. 49). Furthermore, cognition and neuroscience are important in studying the shaping of behavior and the mind.

An interesting example in which the field of psychology is particularly relevant to Web Science and the subject that I chose, online surveillance, is through laws of behavior as social facilitation and social interference. These terms are being described by Gray as influential on human behavior, because the individual knows when it is being observed and its behavior is being affected by it (Gray, 2007: p. 502).

This week I wrote on the basic definition of psychology and some of its methodologies. Next week I want to explore in detail which different fields of psychology exist and how they might relate to online surveillance. 

Source

Gray, Peter. Psychology. Fifth Edition. New York: Worth Publishers, 2007.

Back in Amsterdam, I wrote my bachelor thesis on the usage of social media during the so-called ‘new media revolutions’ during the Arab Spring. One of my main conclusions was that social media are not just of use for the oppressed populations to liberate themselves, but are also being used by (authoritarian) governments to track, and often arrest, opponents. While writing my thesis I herewith developed an interest for the ways in which governments all over the world detect, track and eliminate potential ‘enemies’ of the state through the Web.

Online surveillance is for me one of the most interesting subjects when studying the Web. On the one hand it could be used to protect the state by finding criminals, terrorists and other dissidents. At the same time, omnipresent surveillance can affect ‘regular’ citizens. When governments misuse their power in this field, they can become a ‘Big Brother’ that closely tracks everyone in a nation. This may change the way people browse the Web.

Because of this fact, I think that an interesting way of looking at the topic can be through the disciplines of Psychology and Computer Science.

Psychology

Users of the Web might alter their (online) behavior if they have the feeling that they are being constantly ‘watched’. Looking at online surveillance from a psychological perspective may give an explanation why users act differently. Psychology is the study of mind and behavior, and therefore will most likely offer many different theories to analyze web users that have the feeling (or are actually) being watched. I loaned the book Psychology by Peter Gray from the library to start learning about the epistemologies and ontologies in Psychology.

Computer Science

Besides a psychological perspective, it could also be interesting to look at online surveillance from a Computer Science perspective. Through this field it can be analyzed how governments can watch citizens, while at the same time it can look at how the citizens can avoid being watched. I loaned the book Computer Science. An Overview by J. Glenn Brookshear to get some insights in how computers work and how they have been used over the years.

By combining Psychology and Computer Science I hope to get a human perspective with a technological perspective and learn more about how to combine these disciplines.

Sources

Brookshear, J. Glenn. Computer Science. An Overview. Eleventh Edition. Harlow: Pearson Education Limited, 2012.

Gray, Peter. Psychology. Fifth Edition. New York: Worth Publishers, 2007.

Political Science

The book I have been reading this week contains an overview of how political science has evolved in the last decades as a discipline. Entitled Making Political Science Matter (Schram & Caterino, 2006), this edited book builds up on a debate sparked by Flyvbjerg (2001) focused on the limitations of current methodologies –current at that time- in social inquiry. One of the book’s claims is that methodological diversity in this field is somewhat constrained by the pluralism of post-positivism. In other words, positivism in political sciences emulates natural sciences in dividing the discipline in subfields that become isolated one another, each one with their own methodologies. Owing to this division or constrained pluralism, a need of ‘trading zones’ or common understanding between disciplines has been identified.
Also, all essays in the book are highly critical to the application of ‘hard science’ -in which quantitative methods are included-, in political analysis, as this approach seems to be too distant to the object of study, which in this case is the society, composed in turn by people, not objects. This is why hard science cannot fully explain or provide a complete understanding of social phenomena. This limitation is leading to a revolutionary period in which a movement called Perestroika is challenging the current paradigm in social science. Together with Flyvbjerg, Perestroika aims to include –not to switch to- phronesis in the study of politics. Phronesis is a key term in the flyvbjerian debate, meaning that intuition and practical wisdom are critical to the study of social phenomena.
In short, from this book, it seems like political science is distancing from the paradigms of natural sciences, moving towards an approach in which social and political phenomena are approached from a more humanist perspective, in which personal experience gains significance. This shift might be necessary to be considered by other disciplines such as computer science when looking for a common ground , a ‘trade zone’ in which to have a fluid communication.

Unlike the previous post, which briefly showed a couple of works on e-democracy from the perspective a political science specialty, this post is going to explore an overview of the entire discipline of computer science, contained in Brookshear’s Computer Science. An Overview (2009). The aim will be to start establishing initial connections to the topic and problems stated in the first post regarding technical issues in direct democracy.
In his overview, Brookshear claims that computer science has algorithms as their main object of study. More precisely, it is focused on the limits of what algorithms can do and what they cannot. Algorithms can perform a wide range of tasks and solve a wide range of problems, but there are other tasks and problems beyond the scope of algorithms. These boundaries are the area within which theoretical computer science operates. Theory of computation can therefore determine what can and what cannot be achieved by computers.
Among other issues, these theoretical considerations may apply directly to the potential problem of electoral fraud: computer science can seek for answers of whether or not algorithms can be created to alter or manipulate electoral results in a given electoral system. By establishing the limits of algorithms, an electoral system that falls beyond algorithmic capabilities can be devised in collaboration with other fields such as political science.
From the structure of the book, it can be implied that computer science also considers social repercussions in every aspect of the study of computers, as every chapter in the book contains a section of social issues that the use and development of computer technologies entails. Ethical implications are present in every step these technologies make, and computer scientists seem to be sensitive to them. Legal and political considerations are not alien to the scope of computer science. Therefore, finding a common ground with other fields such as political science for addressing certain issues in the use of information and communication technologies for a more direct democracy becomes quite achievable aim, as long as there exist a mutual effort to understand the ways in which these two disciplines deal with the problems they encounter, and the methods they use to try to solve them.
The next post will consist of a brief overview of political science, as it is the discipline that will be finally chosen –sociology will be ruled out– for this interdisciplinary essay.
Reference:
Brookshear, J.G. (2009) Computer Science. An Overview. (10th ed.) Boston: Pearson.

Cyber Warfare, known as the fifth domain, has developed in scale and sophistication. The new US Air Force manual describes it as a “shadowy, fast-changing world where anonymous enemies can carry out devastating attacks in seconds and where conventional ideas about time and space do not apply” (Telegraph, 2010). As never before has the World Wide Web created so much prosperity and opportunity from all echelons of society, but never before have we been exposed to so much risk from anyone, anywhere in the world. 

According to Michael Chertoff, former head of the US Department of Homeland Security, he mentions how it is the least understood threat and the one where our doctrine is least developed”. Therefore, we have only just touched the surface from what is known now, into what is possible. The threat is a real one. Hospitals can be shut down, Power Grids closed and Children targeted. It raises the notion of what is sociologically acceptable within the 21st Century of Cyber Warfare.

Therefore, I hope to find individual ethical stances from governments and societies from different cultures across the world. For example, targeting children at Schools could be deemed unanimously unethical. Similarly, there will be different national stances of perceived legitimacy. Subsequently, this information could be used to help nations understand the repercussions of going against another nations ethical stance, which may be enough to deter the oppressor.

In conclusion, the 21st Century calls for a new multi-lateral agreement, with the unanimous codes of conduct between international communities ratified; similarly, the code of conducts between individual nations could be used as a deterrent if met by a Tit-for-Tat response. Therefore, I plan to understand these existential threats and incorporate them into my study of Moral Philosophy, touching other disciplines such as Sociology and International Relations.

Reading

Tanenbaum, A. (1985) Computer Networks, 4^th Ed. US: Prentice Hall.

Clarke, R. (2010) Cyber War: The next threat to national security and what to do about it.  US: Ecco.

Singer, P. A. (1993) Companion to Ethics. US: Wiley- Blackwell

Williams, B. (1993) Morality: An introduction to Ethics. UK: University Press.