Artificial Intelligence, the Monster we are feeding-outline

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The monster called Artificial Intelligence

Thesis: Major laboratories have been built all over the world to prototype and generate intelligent machines through deep learning. In this paper, I will argue that Artificial Intelligence is a monster that the humans are feeding and it will one day turn and overthrow man, leaving the world in the hands of machines.

I. Introduction

A. Thesis

B. Definition the terms intelligence, deep learning, programing, machine learning

C. History of artificial intelligence.

D. Major scientists who developed AI.

E. Trends in AI

II. Machine learning

A. Supervised learning

B. Non supervised learning

C. Comparison between supervised and non-supervised learning

III. Major advantages of AI

A. Real time assistance

B. In the business field

C. Industrialization

D. Efficiency

E. Accuracy

IV. Limitations of AI

A. Cost implication

B. Threats prevention

C. Loss of metal capability

D. Social factors

E. Ethical factors

F. Men becoming slaves

G. Emotions not guaranteed

H. Rigidity in thinking and execution of instructions

V. Criticism

The divine instruction was for man to steward and subdue the world, such innovations makes the human being achieve the divine instruction. This criticism is worth because it discusses part of the work in AI as divine instruction.

There is power and happiness if a creator creates something more powerful than itself. It is the happiness of a teacher to see their students do well and even pursue a course far much better. With such social theories supporting the work of artificial intelligence, it is making sense that the same AI should not be demonized but rather be seen as a human achievement.

VI. Conclusion

All the sections and subsections are discussed in a brief, precise and clear way ranging from the definitions, the implications and how negative artificial intelligence should be depicted in this section.


Boddington, P. (2017). Towards a code of ethics for artificial intelligence. Cham, Switzerland: Springer.

Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications23(2), 368-375.

Osoba, O. A., & Welser IV, W. (2017). An intelligence in our image: The risks of bias and errors in artificial intelligence. Rand Corporation.

Rosé, C. P. (2017). Artificial intelligence: A social spin on language analysis. Nature545(7653), 166.

Russell, S. (2017). Artificial intelligence: The future is super intelligent. Nature548(7669), 520.

Sandler, R. (Ed.). (2016). Ethics and emerging technologies. Springer.

Strong, A. I. (2016). Applications of artificial intelligence & associated technologies. Science [ETEBMS-2016]5(6).

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