• Collect, analyse, present and comment upon business data.
• Identify the relationship between computer hardware and software.
• Describe the most common types of software programmes and explain how they may be used to enhance management functions.
Various actants, including both non-technical and technical, comprises the theory of computing. In a computing network, changes occur in a network when any actants connect to or act upon another actant.
This specific statement reveals the significant role and relationship between the different actants in modern computing. The applications the Actor Network Theory in computing helps in understanding the interconnection and relationship between the human and non-human actants acting within a network. The approach of actor-network theory helps in appreciating the complexity existing in an organization or reality (Liebenberg, 2012). Furthermore, the application of the Actor Network Theory helps in understanding the social effects that are promoted as the result of the association of different actants in the network.
This particular assignment focuses on evaluating the two modern computing stories “IBM is one step closer to mimicking the human brain” and “Google wants to stop you entering passwords” with the application of Actor Network Theory.
Relevancy of Actor Network Theory for understanding computing
Actor-Network Theory is one of the most influential theories in the theory of modern computing. Michel Callon, Bruno Latour, and John Law first developed the Actor Network Theory in the early 1980’s for exploring the structure and growth of information. Bajde, (2013) has defied ANT as a computing approach for practicing sociology. The actor-network theory does not only limit to the social science but comprises the science and criteria of association between the actants. The relevant reasons for applying the Actor Network Theory for studying computing are as follows:
The ANT allows identifying the interconnection between the human and non-human actants acting upon a network;
ATN analyzing the relationship between the actants while hiding the individual characteristics of the connected actants;
iii. ATN reveals the technological influence on society and human actants that possess the potential for changing the social interactions and interconnections between the actants;
Story Description
Imitation of the human brain is the focus of research for the last decades. Recently, the scientists of IBM were successful in mirroring the biological function of human brain. The creation of randomly spiking artificial neurons can thoroughly process a huge amount of data and store them (Bell, 2016). The artificial neurons have made a breakthrough in cognitive computing and development of neuromorphic, energy efficient and ultra dense technologies. The artificially developed neural brain has shown influential phase-change characteristics and computations primitives while using very less energy similar to the human brain. In addition to that, the artificial brain has been able to react to the external stimulation (electrical pulse) causing a phase- change material to crystallize.
For categorizing, the various actants in the story the theory of ANT has been applied. In this particular story, the artificial neural brain, Internet of Things, neuromorphic technologies and neuron are the digital actants. While on the other hand, the computers and Blue-ray are defined as the hardware actants that acts on the network. The technology and algorithms used in developing the artificial neural brain are considered as the software actants and the scientist, and IMB team is defined as the human actants in the current story. The software actants pull on the software actants in this story that has brought significant changes in the artificially designed neural network.
In this contemporary computing story, the application of the Actor Network Theory reveals the relationship and interconnection between the identified actants in the network. The development of the artificial neural brain network has provided the scientist with the imitation of the human brain that also shows computation problems like data correlations (Horowitz, 2012. Mimicking the activities of the human brain is one of the critical tasks that have resulted in hundreds of research and theoretical study previously. The practical application of the artificial neural networks still required more demonstration. The result in of experiment has provided sustainable switching cycles and complex signals. There remains an area of management functionalities to improve the computation performance of the artificial neural brain that can be used for high volume and velocity of information processing.
With the interconnection of thousands of devices on the internet, a high volume of data is being generated at high velocity. It is difficult to control and process the huge volume of information. Pollack, Costello, and Sankaran, (2013) cited that the time and power required for processing the huge volume of information are much higher that affordable. The use of artificial neural network was able to compute multiple easy of data processing with the frequency of mere 100Hz. The high processing speed and less power consumption significantly impact the human actants and neuromorphic technologies in this story.
With the recent trends, Goggle is currently supporting its users to use YOLO attitude for managing password. The YOLO (You Only Login Once) allows the users to online to devices only once. Google has teamed up with the Dashlane and Android developers to allow access using third party software. The open source YOLO API stores all the user id and password for all the applications for easy management (Reynolds, 2016). Currently, the application is developed only for the Android Operating System. The use of password management system allows the users for easy access and managing password of different applications at the same time.
The application of the Actor-Network Theory has revealed the different actants and network in the current story. Android Operation systems, YOLO software, Dashlane, YOLO API are identified as the software actants in the computing story. The tangible mobile devices like mobile phones and tablets are considered as the hardware actants. On the other hand, the people using the Android devices are the human actants in the current contemporary story. The software and hardware actants in the story significantly impact the human actants with its interconnections.
Google and Android system has together connected millions of people together with different applications and services. Every application uses its specialized user id and password for login. It’s become very difficult for the users to remember all the password of the different applications and log-in every time to use the applications (Bueger, 2013). The open source YOLO API allows the users to store and manage the password for all the applications. The linking of the different applications and websites through the YOLO third party software only needs the users to log in once with the password and user-id. Currently, the YOLO application is only developed for the Android devices. There remains a scope of management functionalities of developing the YOLO system independent of the operating system.
In linking to the second contemporary story about the Google’s encouragement of password management system using YOLO, there lay significant issues (Wissink, 2013). The YOLO application stores the user id and password for a variety of applications and websites. Being an open source application on the android system, the YOLO has faced various password leaks and hacks currently. Although the system provides an easy login to the different applications with one click fails to ensure safety and security of the user data (Vezyridis, and Timmons, 2014). The larger issue is to ensure the data integrity and security of the users of Android devices. Moreover, since a massive number of data is being generated nowadays, is required to control the security of the information.
Long Term Effect of Computing: The use of computing for a long time results in the generation of the huge volume of structured and unstructured data (Durepos, and Mills, 2012). Understanding the impact of the data to the human actants is much required for analyzing the relation between the human and non-human actants in any network.
Problems of ANT: The utilization of the Actor Network Theory is not possible in every case. The use of ANT in research study causes more time and financial resource (Fioravanti, and Velho, 2016). In the research study, if there is efficient time, the number of cases to analyze ANT is not sufficient. Dwiartama, and Rosin, (2014) have stated that ANT is useful in providing social interconnections between the actants but fails to produce any statistical data to the applications.
Conclusion
The application of the Actor Network Theory in the two modern computing theories has identification of the actants and network in the computing stories successfully. The selected stories have provided in-depth analyzing of the modern computing with the application of ANT. In the first story “IBM is one step closer to mimicking the human brain” the analyzing with the Actor-Network Theory has revealed the impact of artificial neural network in big data and data processing. In the second story “Google wants to stop you entering passwords”, the ANT has revealed the different underlying relations between the human actants and security of data. Therefore, the applications of the ANT in the computing stories have provided connections between the actants and its impact on the social environment.
References
Bajde, D., (2013). Consumer culture theory (re) visits actor–network theory Flattening consumption studies. Marketing Theory, 13(2), pp.227-242.
Bell, L. (2016). IBM is one step closer to mimicking the human brain. [online] WIRED UK. Available at: https://www.wired.co.uk/article/cientists-mimicking-human-brain-computation [Accessed 7 Aug. 2016].
Bueger, C., (2013). Actorâ€ÂNetwork Theory, Methodology, and International Organization. International Political Sociology, 7(3), pp.338-342.
Durepos, G. and Mills, A.J., (2012). Actor-network theory, ANTi-history and critical organizational historiography. Organization, 19(6), pp.703-721.
Dwiartama, A. and Rosin, C., (2014). Exploring agency beyond humans: the compatibility of actor-network theory (ANT) and resilience thinking. Ecology and Society, 19(3), p.28.
Fioravanti, C. and Velho, L., (2016). Let’s follow the actors! Does Actor-Network Theory have anything to contribute to science journalism?. Transcultural, 6, p.04.
Horowitz, L.S., (2012). Translation Alignment: Actorâ€ÂNetwork Theory, Resistance, and the Power Dynamics of Alliance in New Caledonia. Antipode, 44(3), pp.806-827.
Liebenberg, J., (2012), October. Unravelling the Text Book as Embodied Curriculum: An Actor-Network Theory View of an Android-based eBook Implementation in a South African Secondary School. In M. Specht, M. Sharples and J. Multisilta eds.,, mLearn (pp. 302-307).
Pollack, J., Costello, K. and Sankaran, S., 2013. Applying Actor–Network Theory as a sensemaking framework for complex organisational change programs. International Journal of Project Management, 31(8), pp.1118-1128.
Reynolds, M. (2016). Google wants to stop you entering passwords. [online] WIRED UK. Available at: https://www.wired.co.uk/article/google-dashlane-password-manager-openyolo [Accessed 5 Aug. 2016].
Vezyridis, P. and Timmons, S., (2014). Implementing an Emergency Department Information System: An Actor-Network Theory Case Study. International Journal of Actor-Network Theory and Technological Innovation (IJANTTI), 6(1), pp.17-30.
Wissink, B., (2013). Enclave urbanism in Mumbai: An actor-network-theory analysis of urban (dis) connection. Geoforum, 47, pp.1-11.
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