Artificial Intelligence: A Dabbler’s Approach

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Artificial intelligence or commonly called as AI has been a buzzword which can be heard and seen across various media platforms, technical reports, news, technical sites etc. Even smart phones have AI in form of voice recognition and programs such as Watson, Siri etc which have been addressed by general public and luminaries alike of the advancement that artificial intelligence has made in recent year. But what actually is artificial intelligence, what does it means to be intelligent , what scope and capabilities define a machine to be intelligent. Does having a consciousness necessary for intelligence and where is the future heading toward. All of these questions have been addressed and I have tried to provide a justifiable explanation to the aforementioned questions. This paper dabbles into areas of intelligence, machine learning, defining consciousness, AI used in expressing art, and what future holds in this area.


One of the core aspect of a machine or computer to be considered intelligent is it’s ability to recognize pattern , formally termed as pattern recognition. Pattern recognition has majorly advanced automation industry but Automation i.e the use of robots in industry, has not progressed with the speed that many had hoped it would. The forecasts of twenty years ago are looking fairly silly today: the fact that they were produced largely by journalists for the benefit of boardrooms of accountants and MBA's may have something to do with this, but the question of why so little has been accomplished remains. We are able to create robots who can bolt parts together, paint cars, weld stuff but robots which are able to wash cars, dishes and able to cook for us are still far fetched fantasy, Pattern Classification, more often called Pattern Recognition, is the primary bottleneck in the task of automation. Robots without sensors have their uses, but they are limited and dangerous. In fact one might plausibly argue that a robot without sensors isn't a real robot at all, whatever the hardware manufacturers may say. But equipping a robot with vision is easy only at the hardware level. It is neither expensive nor technically difficult to connect a camera and frame grabber board to a computer, the robot's `brain'. The problem is with the software, or more exactly with the algorithms which have to decide what the robot is looking at; the input is an array of pixels, coloured dots, the software has to decide whether this is an image of a car or table. A task which human beings can master by age eight, when they decode the firing of the different light receptors in the retina of the eye, this is computationally laborious task, and we have only the crudest ideas of how it is done. At the hardware level there are marked similarities between the eye and a camera (although there are differences too). At the algorithmic level, we have only a shallow understanding of the issues, to be able to recognize patterns which human beings intuitively understand is piped dream in current scenario, leaps and bounds of research, observation, trial and error is required to mimic human brain but for now area of pattern recognition is still in its infancy.

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Inductive reasoning is based on the premise of observation. The word itself means your are inducing or drawing conclusion from the evidence that you have gathered or observed in your surrounding area.To formally define it, a logical process in which multiple premises, all believed true or found true most of the time, are combined to obtain a specific conclusion. Inductive reasoning is often used in applications that involve prediction, forecasting, or behaviour.


Deductive reasoning on the other had is going from a generalized viewpoint and then drawing conclusion for a specific case. It is deducing for a specific scenario from the general scenario that has been presented. Formal definition of it is, a logical process in which a conclusion is based on the concordance of multiple premises that are generally assumed to be true. Deductive reasoning is sometimes referred to as top-down logic.


  • A teacher notices that his students learned more when hands-on activities were incorporated into lessons, and then decides to regularly include a hands-on component in his future lessons.
  • An architect discerns a pattern of cost overages for plumbing materials in jobs and opts to increase the estimate for plumbing costs in subsequent proposals.
  • A stockbroker observes that Intuit stock increased in value four years in a row during tax season and recommends clients buy it in March.
  • A recruiter conducts a study of recent hires who have achieved success and stayed on with the organization. She finds that they graduated from three local colleges, so she decides to focus recruiting efforts on those schools.
  • A salesperson presents testimonials of current customers to suggest to prospective clients that her products are high quality and worth the purchase.


  • Premise: Socrates is a man, and all men are mortal. Conclusion: Socrates is mortal.
  • Premise: This dog always barks when someone is at the door, and the dog didn’t bark. Conclusion: There’s no one at the door.
  • Premise: Sam goes wherever Ben goes, and Ben went to the library. Conclusion: Sam also went to the library.

Each of these miniature arguments has two premises (joined by the “and”). These are syllogisms, which provide a model for all deductive reasoning. It is also possible to deduce something from just one statement; but it isn’t very interesting; for example, from the premise “Socrates is a man,” you can certainly deduce that at least one man exists. But most deductions require more than one premise.


Computational art is a creative field that indicates to a futuristic idea of artificial intelligence. Despite the common belief that a machine is unable to create art, current developments and examples in computational art present a new form of art. Reaching to a broad variety of artistic dimensions, artificial intelligence programs are generating poetry, music, visual art, architecture and design. The analysis of computational artworks and the computer programs that generate artworks show that the function of artificial intelligence is far beyond being merely a tool to create art, it is rather an actor that have an artistic and creative agency, which can help to explore the possibilities of a new art genre.

But first let us address the seed of all artistic endeavour, Creativity. It can generally be defined as the ability to come up with new, novel and valuable ideas in a surprising or unfamiliar way. These valuable ideas can have different meanings. An idea can be a concept, theory etc., or an artifact such as a painting, music, architecture, a tool and so on. It is not a mythical thing that is aimed at a certain romantic elite. It is an aspect of human intelligence and we all have it in different levels. It is a marvel of the human mind . Creativity is a concept that refers to various examples in every aspect of life. Therefore, rather than a special faculty, it is a feature of human intelligence in general. Everyone is creative, to a degree. As stated by Sawyer, the modern research on creativity began in the 1950s and 1960s. As the first wave of research on creativity, these studies were focused on the personalities of exceptional creators. In the 1970s and 1980s, by turning their attention into the cognitive approach, the researchers of the second wave focused on the cognitive psychology and the internal mental processes relating to creative behavior. With the emergence of third-wave research in the 1980s and 1990s, researchers extended their focus to the sociological approach, which is an interdisciplinary approach that centers upon the creative social systems . By means of these three waves of creativity research, Sawyer addresses the explanation of creativity by bringing together the personality approach, cognitive approach, and sociocultural approach. For the ‘individual’ definition of creativity, he suggests that ‘creativity is a new mental combination that is expressed in the world’ . In this approach, he describes creativity as ‘Creativity is new’ . As Sawyer suggests, being ‘new, novel or original’ is the fundamental requirement of a creative thought or action. Repeating a previously mastered sequence of behavior is not creative. Therefore, daily activities such as driving to work or walking to school by the same route are non-creative behavioral patterns. Thus, fundamentally the concept of creativity deems newness.

Can AI be Considered as Artistically Creative?

The concept of artistic creativity is a form of creativity that distinguishes itself from everyday life. Being different than problem-solving or crafting, artistically creative products have no function other than pleasure . As stated by Sawyer, the idea that artists have a unique message to communicate is only a few years old . After the word “create” was first used in English in 1589 by George Puttenham to make a comparison between the poetic creation and the divine creation, with the influence of Renaissance, artists began to distinguish themselves from craftsmen. In time, with the influence of the Enlightenment which came up after Renaissance, the intellectuals were attributed something more than just craft or technique, which was the ability to create. Afterward, in the 18th century, the art genres of poetry, music and visual arts were grouped together for the first time, by coining the term “fine arts”. Thus, the word “creative” started to be applied to artists. In regard to the question that whether AI can be artistically creative. We can consider the most common kind of creativeness, which is coined as combinational creativity where we combine previous material and give a twist to make it our own, comedians often use this kind of creativity where they combine different sentences and scenario and create something hilarious. Many type of bots have been built on this concept which can combine different phrases and sentences to create novel or new paragraphs or sentences. The result may or may not be funny. Since machines which will be trained to perform this kind of task and result obtained might not suite human taste. The result can be totally nonsensical since machine cannot recognize what humans find hilarious, what do they find tasteful In short they cannot perfectly predict if the produced outcome is savoury to the human taste or not.

AI and Consciousness

When philosophers ponder whether machines could be conscious, they are generally interested in a particular form of AI: AGI, or artificial general intelligence. AGI doesn’t exist yet, but we now have domain specific intelligences like AlphaGo and Watson, the world Go and Jeopardy! champions, respectively. These systems outperform humans in specific domains, and they are impressive. But AI seems to be developing exponentially, and within the next ten or twenty years there will likely be forms of artificial general intelligence (AGI). AGI is a kind of general, flexible intelligence that can do things like make breakfast without burning the house down, while thinking of mathematics and answering the phone. Its intelligence is not limited to a single domain, like chess. Because AGIs are general, flexible, integrate knowledge across domains, and exhibit human-level intelligence or beyond, AGIs seem like better candidates for being conscious than existing systems. Androids are already under development that are designed to look human, such as the androids intended to take care of Japan’s aging population. Armed with papers about the neuroscience of human empathy, AI researchers will build robots that tug at our heartstrings. So, if and when you first encounter an AGI, will it be conscious? If you like science fiction films then you may be thinking of characters like Roy, Pris and Rachael in Blade Runner, or Eva in Ex Machina -- it seemed to feel like something to be them. What I’m asking is: Will it feel a certain way, from the inside, to be AGI? Will there be a subjective, felt quality to their mental lives? This is the problem of AI consciousness. I believe that it is an open question, First, an AGI may have an architecture that bypasses consciousness altogether. For consider how consciousness works in humans. Only a very small percentage of human mental processing is conscious at any given time. Consciousness is correlated with novel learning tasks that require concentration, and when a thought is under the spotlight of our attention, it is processed in a slow, sequential manner. Now consider that an AGI could be highly advanced, being what is called “super-intelligent AI”. Super-intelligent AI is a hypothetical form of AI that out-thinks humans in every domain – scientific reasoning, social skills, and more. A super intelligence would surpass expert-level knowledge in every domain, with rapid-fire computations ranging over vast databases that could occupy the space of an entire planet or encompass the entire internet. It may not need the very mental faculties that are associated with conscious experience in humans. Consciousness could be outmoded. Indeed, superintelligent AI might rewrite its own code; a self-improving AI may opt to outmode its own consciousness or build other AGIs that are not conscious. And the processing of a superintelligence will likely be beyond the understanding of unenhanced humans in any case. It will be difficult for a human to grasp whether a given AGI system is even conscious. In essence, we can only determine whether a given substrate is capable of conscious processing after detailed investigation of both the substrate and the larger architecture of the AI in question. Since there may be multiple kinds of AGIs (multiple intelligences, if you will), we may need to test each type of system and new substrate independently – some AGIs may be conscious, others may not be. It may be that androids that are designed to tug at the heartstrings, like Eva in Ex Machina, are not conscious, while some bland, unsexy server farm is. Above mentioned consideration suggest that we should regard the problem of AI consciousness as an open ended question, and delve deeper into this issue to reach a deeper understanding of being conscious and if intelligent machines should be considered conscious or not, if yes where do we draw the line?


Areas where AI has become prominent. Expert System: a piece of software programmed using artificial intelligence techniques. Such systems use databases of expert knowledge to offer advice or make decisions in such areas as medical diagnosis and trading on the stock exchange.

Nature Language processing: Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.


To summarize, Artificial Intelligence is still in its infancy, and will require years to reach it’s full potential. The purpose of this paper was to introduce the principle concepts which are basis for a system to be considered intelligent as well as introducing the reader to sub-domains where artificial intelligence can be applied and on what premise. In addition, a brief explanation was presented on consciousness and it’s ramifications for an artificial machine presenting reader with the question of if it should be treated as a machine or another human? This paper introduces reader which few concept and ideas which can be built upon by further reading by reader in his or her own leisure time.


  6. An Introduction to Pattern Recognition - Michael D. Alder
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Artificial Intelligence: A Dabbler’s Approach. (2022, Jun 09). Edubirdie. Retrieved July 19, 2024, from
“Artificial Intelligence: A Dabbler’s Approach.” Edubirdie, 09 Jun. 2022,
Artificial Intelligence: A Dabbler’s Approach. [online]. Available at: <> [Accessed 19 Jul. 2024].
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