Research Paper
reddygs17
AnnotatedBibliography.docxReading Head: ANNOTATED BIBLIOGRAPHY 1
ANNOTATED BIBLIOGRAPHY 5
Annotated Bibliography for Research Paper
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University of the Cumberlands
Pasquale, F., & Cashwell, G. (2018). Prediction, persuasion, and the jurisprudence of behaviorism. University of Toronto Law Journal, 68(supplement 1), 63-81.
http://eds.a.ebscohost.com/eds/detail/detail?vid=1&sid=80a53932-b932-4bf6-926e-093727bceef6%40sessionmgr4007&bdata=JkF1dGhUeXBlPXNoaWImc2l0ZT1lZHMtbGl2ZQ%3d%3d#db=edspmu&AN=edspmu.S1710117418000033
In the above article, Pasquale and Cashwell show how big data and artificial intelligence is used in the judicial system for prediction and persuasion of behavior. The authors point out how decision-makers are using data algorithms to help in predicting whether judges will take cases and if so, the merits they will use to reach a decision. The employment of natural language and machine learning (ML) techniques has become a trend in the twenty-first century. The authors also state in their article how big data could also be used to predict certain natural phenomena such as the weather. The use of algorithmic predictions is an emerging jurisprudence of behaviorism in the context of judicial law. The article looks at the issues that are associated with analytic data predictions as used by judges. It also tries to answer questions such as the use and purpose of predictive software, whether artificial intelligence is a valuable tool for highlighting violations of human rights (in court cases), and whether elements of bias could be possible when using ML techniques. The article analyses the use of predictive data technology on specific aspects of ordinary life, and whether such artificial intelligence and trends in data analytics could be of more benefit than the pullback in society. The authors focus their argument on the judicial system.
Predictive analytics is essential when it comes to the business world. Most businesses that use software to predict, persuade consumer behaviors are always successful in terms of sales and revenues and consumer loyalty. Unlike traditional intelligence approaches to data, behavioral predictive, and persuasive data analytics help determine how a customer might behave in the future situation and how they may react to certain aspects a business share with them. Such predictive analytics can discover patterns and identify opportunities or problems in a market. Predictive analytics also allows companies to plan, thus avoiding certain uncertainties concerning their consumers. A good example is a clothing store that gathers consumer behavior data. The store can use the data to predict what a consumer will buy in the future and thus be well-stocked with what the consumers need beforehand.
Guha, S., & Kumar, S. (2018). Emergence of big data research in operations management, information systems, and healthcare: Past contributions and future roadmap. Production and Operations Management, 27(9), 1724-1735.
According to Guha and Kumar, in their article 'Emergence of big data research in operations management…', there are various changing trends in data collection and management. The authors believe that in the new century, data is generated whenever we use the Internet and that aside from the information that we make, interconnected devices on the Internet of things also collect data. The information is having a considerable amount about the environmental factors of this present reality and the requirement for extensive information examination in the specialized viewpoint just as the individual component of data use. In the article, the authors discuss the contributions of big data to various domains such as healthcare, information systems and operations, and supply management.
The report also touches on the sub-areas of the stated areas and ways in which big data techniques lead to improvements. The authors even discuss cloud computing, the Internet of things (IoT), smart health and predictive manufacturing, and how such an area has the potential of growth and exploration.
Big data is applied important to a business and can be used in various ways. It can be used for social listening. The availability of vast waves of data makes it possible for businesses to determine the word going around in society about the company. Business owners also use big data to make comparative and market analysis.
Business owners can compare their products and services with competition through analysis of user behavior. Big data also allows for real-time monitoring of consumer engagement in the business sector. Information from marketing analytics helps in promote and get new audiences for new products in the market. Big data thus helps businesses utilize outside intelligence in the process of decision making, improve customer care, create operational efficiency, and identifying risks in products and services a company offers. An excellent example of the benefits of big data is when a business uses information about consumer purchasing behavior to target a tailored advertisement to such a segment market.
Akl, S. G., & Salay, N. (2019). Artificial Intelligence A Promising Future? Queen's Quarterly, 126(1), 6-20.
Aki and Salay discuss artificial intelligence in their article on 'Artificial Intelligence A Promising Future.' In their research, they view AI having a bright future and shaping the way human beings carry on their day to day activities. The authors talk of how artificial intelligence has developed over the years, citing examples of developments such as Deep Blue, Watson, Project Debate, and AlphaGo, among many others. The article talks of how Artificial Intelligence as a science has become a social phenomenon. The authors point out that artificial intelligence and machine learning serve a great purpose in the modern-day world. The use of data and deep learning algorithms are to extract features that are in artificial intelligence technology. AI's future is bright, and the authors feel that such a positive trend will see the use of technology hugely benefit the life of a human being.
In business, artificial intelligence is to automate tasks that would otherwise be manual and time-consuming. Technological development can be used by companies to create a competitive advantage and to increase efficiency. AI also ensures that tasks are done efficiently with minimal errors as when compared to human efforts. Artificial intelligence can also be to detect fraud, improve data security, and ensure proper marketing and security screening.
