Archive for the ‘Uncategorized’ Category
Initial thoughts on philosophy constitute the subject as a means to question, analyse and assemble thoughts and conceptions of the universe (Nagel, 1987). Furthermore, it has been mentioned that these analyses technically cannot be answered within the current available technology of that particular time. And so, early constructions of the ‘heavens’ and earth, from various religious eras, seemed contradictory to the later findings from scientific studies. Although, from this, further questions can be built upon this to create new philosophies of the universe. This insinuates that the foundations of philosophy stem from an innate human motivation to learn about the world around us and question our very purpose within it. Whether in hindsight that an act of communications hacking is indeed relevant or even significant to the purposes of human beings on planet earth and within the universe.
Not only does philosophy stem from an ideology of ‘nothing is certain’, it also strives to suggest that there are implications and ramifications for such actions associated with what is humanly and technologically possible. Brian Harvey (1985) analyses the ethical consequences of such hacking actions and that the human associated with the action will indeed, over time, become desensitised to the ethical implications as a consequence of their actions. This seems as though it is dependant upon whether they are hacking for the greater good or whether it a simple act of breaking down security systems in order to alter the intended message to its audience.
Furthermore, Harvey (1985) notes that the ethical understanding of a human being is something that is learned, something that is driven from our interaction with the environment and with society, that ethical understanding and awareness are social phenomena that are altered according to variables such as gender, race, religious belief, culture and status. In reference to communications hacking, the ethical implications are based on the judgement from the end-user or the audience of the message and not of the hackers themselves. Although, this begs the question of whether empathy is an emotion on the flipside to perceived ethical discrepancies.
In a news article, the Vatican stated that hackers are subjects associated with a greater good, that they are driving us away from the restrictions and securities of western society and that freedom of speech and the right to know such information is a part of society (Discover Magazine, 2011). In reference to one of my previous posts, this article continues down the route that hacktism is the ideology associated with the freedom of information.
It is clear to see that there is a crossover point between political action and philosophical theory. In my next entry I shall be researching how philosophical theories are represented as political ideologies and how this may affect societies perceptions on communications hacking. Does political reasoning give the hacker the excuse to perform such actions?
In which market structures do web-only firms operate? And what are the implications?
There are many market structures in which firms trade: perfect competition in which many firms sell an identical product; monopolistic competition in which a large number of firms compete with slightly different products, leading to differentiation; oligopoly where a small number of firms compete; and monopoly in which one firm produces a unique good or service, e.g. utility suppliers.
Perfect competition gives rise to a situation in which economic profit induces entry into the market by firms, which in turn eliminates profit. And economic loss induces exit, which in turn eliminates the loss. When profit and loss have been eliminated and entry and exit has stopped, a competitive market is in long-term equilibrium. But this is a rare state to maintain.
Monopolistic competition results in many product innovations, to achieve differentiation, which are cost-efficient to produce so not significant. It differs from perfect competition in that there is excess capacity and the prices are higher.
An oligopoly has a small number of interdependent firms resulting from natural barriers to entry. It is distinguished from monopolistic competition by measuring the market ownership of the 5 largest firms compared to the next 10 largest firms, with 60% market ownership by largest firms giving the oligopoly. It is studied using game theory.
A monopoly has 2 key features: there is no close substitute and there are barriers to entry which deter potential competitors. The 3 types of barrier are: natural in which economies of scale enable one firm to supply the entire market at the lowest cost; the ownership barrier if one firms owns the major portion of a resources; and a legal barrier if a firm is granted a monopoly franchise, government licence, patent or a copyright.
Web-only firms operate in a mix of all 4 market types. There is the monopoly in search services and SEO advertising by Google; the oligopoly-duopoly of Google and Facebook in platforms for user-generated social content and dependent applications; the monopolistic competition of other topic or media based dependent social networks (e.g. SoundCloud, Myspace, Youtube, Vimeo, Goodreads etc); the perfect competition of free knowledge sites with professionally created or user-generated content (e.g. Wikipedia, online periodicals, Quora, Stackoverflow etc).
Are the Freemium business model permutations, including indirect revenue streams, the most economically viable models? Are they supported or undermined by the mixed market environment? The next instalment follows…
 Economics / Parkin, Michael, 1939-
This week I have done some more reading on anthropology’s methods, complementing the findings I wrote about last week. The more I found out about anthropology, the more I wondered how as a discipline it would tackle global issues. Indeed from reading the introductory texts, I got the sense that anthropology (the socio-cultural kind) was concerned with the study of human kind. A priori this doesn’t seem to pose a problem in terms of the globality of the subject matter, but in its approach and even epistemology, anthropology is firmly based on the notion of classification. Indeed its ontologies are cultures, peoples, societies, etc. and its methods are primarily descriptive and comparative, assuming the existence of different ‘things’ to compare. As mentioned in previous posts, an anthropologist looks at a society/community/social group which he/she investigates doing fieldwork, conducting interviews, historical research, etc. But what happens when the group in question is the entire world population, as is often the case with so-called global issues? How then would such a discipline tackle questions that seem to contradict its own epistemological foundations?
Trying to look at the digital divide from an anthropological lens, I have hit what might be the crux of the issue in this assignment – how to let go of my previous assumptions about the world, shaped in large parts by my training in International Relations and instead of re-phrasing the ‘problématique’ I immediately see with the global digital divide in anthropological terminology, attempt to ‘discover’ the problems and ‘frame’ it as an anthropologist would. In order to try and do that, and while I did find some answers in the introductory readings, I decided nevertheless to look for some more targeted articles on the issue.
An article by Kearney (1995) ‘The Local and the Global: The Anthropology of Globalization and Transnationalism’ in Annual Review of Anthropology was particularly helpful. The answers or thinking I considered fall in two broad categories – theoretical and practical.
On the practical side, Peoples and Bailey (2000, p. 5) assert that for global issues, which have admittedly gained importance in the past two decades, anthropologists are often called to consult on specific projects – an emerging sub-field of the discipline referred to as applied anthropology. The idea here is that solutions to global problems often require local knowledge, provided by traditional anthropological research and therefore increasingly useful in the field.
On the theoretical front, Kearney recognises that new thinking is required in ‘anthropological theory and forms of representation that are responses to such nonlocal contexts and influences’ (1995, p. 547). He sees global issues (and globalisation) as having ‘implication for [anthropology’s] theory and methods’ as research which is limited to local units of analysis ‘yield incomplete understandings of the local’ (1995, p. 548). He sees the redefinition of space-time into a multidimensional global space with fluid boundaries and sub-spaces as the most important disruption to anthropological epistemology. He also notes that the notion of ‘progress’ assumed in the discipline and the notion of ‘development’ is and needs to be questioned in the context of globalisation, that is to say that there is no inevitability in the course of global history. Moreover with the ‘deterritorialisation’ of culture, the focus of anthropological study is shifting towards ‘identity’. Underpinning these changes is the fundamental reframing of the concept of classification, no longer considered ‘an invariant subject of investigation in anthropology, but taken instead as a historically contingent world-view category’ (1995, p. 557).
This has given me some interesting avenues to explore so I will conclude my introductory reading on anthropology here. Next week I will start looking at management as a discipline.
Kearney M. (1995) ‘The Local and the Global: The Anthropology of Globalization and Transnationalism’ in Annual Review of Anthropology, Vol. 24, pp. 547-565
Peoples, J. and Bailey, G. (2000) Humanity: An Introduction to Cultural Anthropology, 5th ed., Belmont: Wadsworth/Thomson Learning
Economic theories are constructed using models and data. Models can be described as frameworks which organise how economists think about a problem. Models create a simplified and easier to manage reality with which to test theories. Data is the facts with which the model interacts, therefore the data needs to be relevant.
Data can be;
- Time series – which shows how a variable has changed over time. This is usually graphically represented.
- Cross sectional – shows a fixed point in time how a variable differs between groups or individuals.
Data is represented as;
- Index numbers – this allows the comparison of data without using units and showing any change relative to a base number. Indexes can also be expressed as averages.
- Nominal or real variables – nominal values show the price of things, whereas real values show the price of things taking into account the factors which may influence the price. For instance, a nominal value may have increased, but a real value would show the increase was due to rising labour costs and there was not an increase at all.
Economic models use empirical research to examine the realtionship of interest.
- Construct a theory
- Develop a model to test the theory
- Test the theory with data
This week I had a look at David Bainbridge, Introduction to Computer Law, and Godwin, Cyber Rights. The Bainbridge is terrifically dull – he’s a professor of law and business and it really comes across in the text. I did find this vaguely useful, in the sense that now I realise why I will never be a lawyer. Anyways, he does make some useful commentary on the issue of freedom of expression, which is what I think I am going to be approximately focusing on for my coursework. He goes through a few case studies of real trials and discusses the outcomes which might be interpreted as being problematic in different ways. I think what Bainbridge is saying is that there isn’t really much precedent for questions of freedom on the internet yet – there’s only a limited number of real life trials that have happened and the results aren’t necessarily consistent.
The other book by Godwin, Cyber Rights: Defending Free Speech in the Digital Age, is much better, and I would recommend it. As the title suggests, it is advocationist in nature right from the start. Godwin thinks that freedom on the web is something that should be defended, and we should be much more worried about the consequences of restricting people rather than the consequences of not restricting people. Godwin is himself a lawyer, and discusses a large number of case studies on the issue of rights on the internet, particularly as related to free speech. He also argues that the web is really quite different from the other inventions of communication that came before. On page 75 he says
“The constitutional justification for special regulation of broadcast content – which covers radio, television, and cable and includes regulations like time-based restrictions (such as limiting material for mature audiences to distribution at certain times) -has been twofold. First is the concept of scarcity of resources. There is a notion that broadcasting frequences are so scarce that the government is the only institution with a global enough perspective to step in, allocate them, and govern their use for the public good. Second is the notion that broadcasting is pervasive in some fashion – that it creeps into the home in a way that makes it unique. Regardless of whether you accept these justifications for content control over the airwaves, the fact is that the internet is nothing like broadcasting in either way. Internet communication is not scarce. Every time you add a computer node to the internet, you’ve expanded its size. It is not pervasive because (with the arguable exception of spam…) you don’t have people pushing content into your home; you have people logging on and pulling content from all over the world…It is a fundamentally choice-driven medium for communication…” – p75
Augustine describes the process of learning language and human behaviour as a child; by seeing the words and motions used in the proper place and at the proper time he learned to use them properly himself. Speech software can do something a bit like this? Or whatever. Basically soft AI can learn to manipulate speech, though it has no conscious desires outside of what has been programmed. In mimicking physical human behaviour though we might go into the uncanny valley.
“Every word has a meaning.” p2
Wittgenstein draws up an analogy for the use of language as mental object retrieval in which a shopkeeper is given the instruction to retrieve five red apples. The ‘apples’ are matched to a catalogue, the colour ‘red’ is compared to a colour sample and the cardinal numbers to ‘five’ are listed. For each number, the shopkeeper retrieves one apple of the chosen colour. Following this protocol, the shopkeeper fulfills the instructions and may return to a position of readiness. p3
This is simplification in this example helps to draw aside some of the murkiness which “surrounds the working of language” (p4), and highlights the fact that in the earlier stages of language learning, that is, learning the functions of words, it is not explanation that is imparted, but training.
“In the practice of the use of language on party calls out the words, the other acts on [responds to] them.” -p5
“Naming something is like attaching a label to a thing.” -p7
“What are the simple constituent parts of which reality is composed?” Our conception of things (chairs, trees) is made up of parts, but what is the simplest (ie not composite) form of these parts? The elements? The atoms? We infer lots of stuff from looking at a wooden chair. The wood, and all that this implies (trees, branches, forests, saws, varnish, factories); the paint; how comfortable it may be. This complex web of background knowledge is completely natural in humans but really hard for computers.
“A name signifies only what is an element of reality.” -p29
And as an aside, from the Donna Harraway: “Microelectronics mediates the translations of … mind into artificial intelligence and decision procedures.” -p304
Etymologically, demography comes from the Greek words demos (for population) and graphia (for description or writing).Demography stated informally tries to answer the following questions:
- How many people of what kind are where?
- How did the number of people come about?
- What is the implication of the number derived?
Formally, demography is the scientific study of human population and its dynamics.
Demography deals with aggregates of individuals, it describes the characteristics of population. Most demographic studies employ quantitative and statistical methods, features of population are often measured by counting people in the whole population or sub-populations and comparing the counts.
Population size is a number with absolute and relative connotations. In the absolute sense, human population size quantifies the number of people in a country, region or space. Beyond the numerical quantity is the concern for distribution both within and among country, region, or space, this accounts for the relative connotation. Resulting from the concepts of population size and distribution is population density which is the relationship between population size, distribution, and the space that contains it.
Population density is consequential to the well being of the population. Notably, population density explains the viral spread of disease, knowledge, and ideas; epidemics is most likely to occur in a densely populated space as knowledge and ideas can easily diffuse.
Population study is concerned with the size and distribution of identifiable subgroups within populations. This concern yields information on the structure and composition of population. The characterization (categorization or classification) of population relies on endless list of traits- age, gender, education, religion, income, occupation, language, race, ethnicity etc. However, some traits are more useful; traits that change less frequently or has predictable pattern of change. Age and gender are the basic and most influential characteristics to demographic processes, hence they are known as demographic characteristics.
The dynamics of population is rooted in the basic demographic processes of birth, death, and migration. Basically, population changes can be associated with leaving or entering; to leave means dying or emigrating and to enter means being born or immigrating. This fact can be depicted in the basic demographic equation that follows:
Pt+1 = Pt + Bt ,t +1 – Dt ,t +1 + It ,t+1 – Et ,t+1
where Pt is the number of persons at time t and the number of persons one year later is Pt ,t+1; Bt ,t+1 and Dt ,t+1 are the number of births and deaths that occur between times t and t+1 respectively; It ,t+1 and Et ,t+1 represent the number of immigrants to and emigrants from the population respectively between times t and t+1.
The difference between Bt ,t+1 and Dt ,t+1 is referred to as natural increase (or decrease when the difference is negative) while the difference between It ,t+1 and Et ,t+1 is known as positive net international migration when the difference is positive and negative net international migration otherwise.
Growth in demographic parlance refers to change in population size. From the demographic equation above, growth means the difference between Pt+1 and Pt even though this difference is negative. The interplay of demographic processes results in population growth as well as compositional changes in population.
David Yaukey and Douglas L. Anderton, Demography: The Study of Human Population 2nd ed., 2001
Dudley L. Poston, JR. and Leon F. Bouvier, Population and Society: An Introduction to Demography, 2010
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.
Last week I was very excited to take a look at technoethics and found that the more I read, the more I wanted to read about it. This week, reading around the area of risk management, I have found myself in a similar situation. My mind has been buzzing with ideas about how these fields can contribute in a big way to Web science. Nonetheless, I will briefly introduce the area of risk management at this time and share these potential applications in my future posts.
Brief Overview of Risk
Before talking about managing risks, it is fitting that I define risk. It has been noted that risk is defined differently from one field to the next and there is sometimes contradiction in its definition (Vaughan, 1997). This lack of agreement on definition has been partly attributed to the relatively young age of the field and practitioners adopting definitions of risk from varying fields. However, for the purposes of my adventure in the discipline, I have chosen to define risk as “an event with the ability to impact (inhibit, enhance or cause doubt about) the mission, strategy, projects, routine operations, objectives, core processes, key dependencies and or the delivery of stakeholder expectations.” (Hopkin, 2010, p. 12).
When an organisation employs the Web, it is hoped that it will lead to a favourable outcome (e.g., increased productivity) and not hurt the company (e.g., cause legal troubles) in any way. In many situations within organisations, especially when technology is involved, the result could be uncertain and this constitutes a risk. For example, as the impact of the Web could be different to what is expected, its adoption could be considered as being a control risk.
Types of Risk
There are several ways to classify types of risks and there appears to be no generally accepted classification that is right or wrong. Practitioners often adopt classifications that are appropriate for their circumstances. In addition to the control/uncertainty risks mentioned, texts usually mention two other risks: hazard/pure risks and opportunity/speculative risks. Hazard or pure risks typically refer to things like theft, health and safety risks. Opportunity or speculative risks are usually associated with financial investments, critical business decisions such as moving location or offering a new product, and also, taking or not taking the opportunity.
Not All Risks Are Equal
As you can appreciate, some situations pose a higher degree of risk than others. Situations where there is a high likelihood of a negative outcome occurring or a high probability of loss are usually considered as being riskier than situations at the other end of the spectrum. A good example of this is given by Vaughan (1997). When playing Russian roulette, there is more risk with each bullet loaded into the gun, (until obviously when the barrel is fully loaded – it’ll be certain you’re going to get shot).
Brief Overview of Risk Management
Defining Risk Management
Hubbard (2009) defined risk management as “the identification, assessment, and prioriti[s]ation of risks followed by coordinated and economical application of resources to minimi[s]e, monitor, and control the probability and/or impact of unfortunate events” (p. 10). Simply put, Hubbard believes risk management is “being smart about taking chances.” Having looked at many definitions, one consistent and important characteristic of risk management is that it is a systematic approach to dealing with risk that follows a particular process depending on the risk circumstance.
Some texts (e.g., Scarff, Carty & Charette, 1993) has found it necessary to separate the concepts of ‘management of risk’ and ‘risk management’. The latter refers to the activities of planning, controlling and monitoring, whereas the former includes such activities, as well as those associated with risk analysis.
Dealing with Risk
Risk management aims to eliminate, reduce or control risks and gain enhanced usefulness or benefits from them (Waring & Glendon, 1998). It has been suggested that successful risk management programmes feature a strategy that is:
- proportionate to the level of risk posed;
- aligned with other business activities;
- comprehensive, systematic and structured;
- embedded within business processes;
- dynamic, iterative and responsive to change.
According to Waring and Glendon (1998, p. 9), risk management involves the optimal combination of the following strategic options:
This Week’s Plan
- Reading more about the methodologies associated with the selected disciplines.
- Prepare a blog post that describes the methodologies adopted by the selected disciplines and compare them.
- Explore the contributions these disciplines could make to each other and Web science.
- Publish a blog post that discusses the potential applications of these disciplines to Web science.
Last & Previous Week’s Plan
Identifying the simplest books to read that will give an easy to understand introduction to the disciplines I picked. Making notes on books read. Prepare a blog post that gives an overview of what I want to work on. Publish a blog post that introduces technoethics. Publish a blog post that introduces risk management. Outline a reading plan for moving forward.
Ethics: A Very Short Introduction– Simon Blackburn Handbook fo Research on Technoethics– Rocci Luppicini & Rebecca Adell Managing Risk: Critical Issues for Survival and Success Into the 21st Century– Alan Waring and A. Ian Glendon Introduction to the Management of Risks– Frances Scarff, Andy Carty and Robert Charette Risk Management– Emmett J. Vaughan The Failure of Risk Management: Why It’s Broken and How to Fix It– Douglas W. Hubbard Fundamentals of Risk Management Understanding, Evaluating and Implementing Effective Risk Management– Paul Hopkin
Marketing is a social and manager process whereby individuals and groups obtain what they need and want through creating and exchanging products and values with others. There are five alternative concepts under which organisations conduct their activities, the so-called marketing management philosophies: the production, product, selling, marketing and societal concepts. The production concept holds that consumers favour products that are available and highly affordable; management’s task is to improve production efficiency and bring down prices. The product concept holds that consumers favour products that offer the most in quality, performance and innovative features; thus, little promotional effort is required. The selling concept holds that consumers will not buy enough of the organisation’s products unless it undertakes a large-scale selling and promotion effort. The societal marketing concept holds that generating customer satisfaction and long-run societal well-being are the keys to both achieving the company’s goals and fulfilling its responsibilities.
Most successful and well-known companies have adopted the marketing concept, according to which achieving organisational goals depends on determining the needs and wants of target markets and delivering the desired satisfaction more effectively and efficiently than competitors do. Implementing the marketing concept often means more than simply responding to customers’ stated desires and obvious needs. Customer-driven companies research customers to learn about their desires, gather new product and service ideas, and test proposed product improvements.
The explosive growth in connecting technologies has created a New Economy which provides marketers with new ways to learn about and track customers as well as create product and services tailored to meet customer’s needs. Marketers have redefined how they connect with their customers; in contrast with yesterday’s companies that focused on mass markets, today’s companies are selecting their customers more carefully and developing more lasting and direct relationships with them. Web seems to enable customer relationship building as companies can demonstrate the abovementioned marketing concept on their web sites by including features that are important to consumers; online companies have moved from mass marketing to segmented marketing or one-to-one marketing, in which they target carefully chosen individual buyers.
The New Economy revolves around information businesses; information has the advantages of being easy to differentiate, customize, personalise and dispatch at incredible speeds over networks. With rapid advances in connecting technologies companies have grown skilled in gathering information about individual customers and more adept at individualising their products. Marketing companies go to great lengths to learn about and understand their customers’ needs, wants and demands; they build extensive customer databases containing rich information on individual customer preferences and purchases and then they mine these databases to gain insight by which they ‘mass-customise’ their offerings to deliver greater value to individual buyers. Web enables consumers and companies to access and share an unprecedented amount of information with just a few mouse clicks. In order to be competitive in today’s new marketplace, companies should adopt web technologies or risk being left behind.
Armstrong, G. & Kotler, P. (2003) Marketing: An Introduction. New Jersey: Pearson Education Ltd
Drummond, G. & Ensor, J. (2005) Introduction to Marketing Concepts. Oxford: Elsevier Butterworth – Heineman
Kotler, P., Armstrong, G., Saunders, J., Wong, V. (2001) Principles of Marketing. New Jersey: Pearson Education Ltd
Palmer, A. (2012) Introduction to Marketing: Theory and Practice. Oxford University Press
Masterson, R. & Pickton, D. (2010) Marketing: An Introduction. London: SAGE Publication Ltd