AI Education: Learning for the Future - Report Sample

Introduction

Artificial intelligence will be useful to learn more about my future educational goal. Artificial intelligence is also known as machine intelligence. It involves having the machines apply both mechanical and programming skills to perform tasks. Learning is multifaceted, and human beings can learn and pally knowledge in cognitive and motor skills. New knowledge is organized into general information by the brain. Man aims to have machines created with such expertise. Machines intelligence is a branch of computer science that expands more into the practical performance of those programs, just like the human brain. That is the motivation behind artificial intelligence.

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Machine Intelligence

Machines have a similarity in functioning like human beings. Artificial intelligence meant to replace social functioning and to perform specific tasks. The simulation of human knowledge in machines is artificial intelligence. Machines are built to use computer programming to perform tasks, just like human beings use brains. They are meant to perform the role of human beings and perform more effectively. Understanding artificial intelligence will help further my education and love for machines that use computer programing.

For a detailed understanding, five books that cover artificial intelligence are analyzed in detail and their relationship to my artificial intelligence academic goal. Artificial intelligence is the future of the industry in the world.

Mitchell, Michalski & Carbonell Book

The book authored by Mitchell, Michalski & Carbonell and published in 2013, covers the theory of computer modeling and the application. It helps understand how scientists use computer modeling to develop intelligent machines that are used to perform tasks similar to human beings. The book ties to my education goal of understanding the basics of artificial intelligence. The aim is to know how the development of a theory that relates to the function of the human brain is one to help build a machine that has a similar role. The book is titled an artificial intelligence approach and provides in-depth insight into the theoretical foundations of artificial intelligence.

Hassabis, Kumaran, Summerfield & Botvinick Book

The book published in 2017 by Hassabis, Kumaran, Summerfield & Botvinick helps breakdown the relationship neuroscience has to artificial intelligence to help the machine function like a normal human being. Neuroscience is related to artificial intelligence. Neuroscience helps in understanding the functioning of the brain. My academic goal is to understand how the functioning of the human brain is made similar to that of the artificial machine. The control of the brain to the human body and the similarity to the control of the machines fascinates students. The authors continue to narrate the historical relationship neuroscience has on artificial intelligence, which is a case of human beings trying to go beyond their limits.

Miller Book

My goal is to understand the algorithm and how it helps the machine work. Miller, who authored the book in 2019 titled, explanation in artificial intelligence: Insights from the social sciences, provides a detailed description of the functioning of the algorithm. The author points out that algorithm are at the Centre of artificial intelligence. It helps predict the behavior of the machine. Miller contends that there is an explainable resurgence of artificial intelligence, which is easy to understand for students. Understanding the artificial intelligence and the functioning of the algorithm is depended on the person explaining and how they perceive their explanation to be according to the author.

Helbing, Frey, Gigerenzer, Hafen, Hagner, Hofstetter & Zwitter Book

Helbing, Frey, Gigerenzer, Hafen, Hagner, Hofstetter & Zwitter, published their book in 2019 in an attempt to understand the impact artificial intelligence has on democracy. Designing and developing artificial intelligence machines need to be recognized by the government. The ability of the government to regulate the use of artificial intelligence is debatable. The goal of artificial intelligence education is to understand the role of government in a digital era.

Kibria Book

Author Kibria, M. G et al. published their book in Big data analytics, machine learning, and covering big data and machine learning. The authors published the book explaining the changes in artificial intelligence and the complexities involved. Next-generation wireless networks Artificial intelligence is fast evolving and becoming more complex. My education goal in artificial intelligence is to understand how the changes impact the functioning of the machine and the level of human help needed. In an era of big data, the authors explain more about the complexities involved in designing advanced artificial intelligence computer programs.

Conclusion

Artificial intelligence is making the digital world more fascinating. The annotated bibliography of the books covering artificial intelligence helps me understand what it is all about and the relationship it has to my academic goal of pursuing artificial intelligence. All five bibliographies provide an in-depth analysis of artificial intelligence, helping look at different aspects of science involved. Artificial intelligence is progressing rapidly, changing all the economic sectors from the traditional ways and doing things. The broader scope analysis is provided by different scholars who see the future of artificial intelligence as just beginning. Artificial intelligence is taking overall tasks that require cognition similar to the human brain, which determines the actions taken. The goal of academic pursuit in machine learning and computer development shows that human ability to innovate is dynamic.

References

Kibria, M. G., Nguyen, K., Villardi, G. P., Zhao, O., Ishizu, K., & Kojima, F. (2018). Big data analytics, machine learning, and artificial intelligence in next-generation wireless networks. IEEE access, 6, 32328-32338.

Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.

Helbing, D., Frey, B. S., Gigerenzer, G., Hafen, E., Hagner, M., Hofstetter, Y., ... & Zwitter, A. (2019). Will democracy survive big data and artificial intelligence?. In Towards digital enlightenment (pp. 73-98). Springer, Cham.

Miller, T. (2019). Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence, 267, 1-38.

Mitchell, R. S., Michalski, J. G., & Carbonell, T. M. (2013). An artificial intelligence approach. Berlin: Springer.