best ai for dissertation writing

best ai for dissertation writing

The Role of Artificial Intelligence in Dissertation Writing

1. Introduction

The power of computers and software in mathematics is nowhere more apparent than in the area of mathematical research. As a case study, let’s look at the field of computational algebraic geometry and algebraic topology. In the past thirty years, these seemingly disparate fields have been strongly influenced by developments in computer programming. This began with the creation of computer software able to illustrate and plot solutions to various algebraic equations. This was a very crude tool, but was quickly recognized as a potentially powerful way to gain intuition and understanding of algebraic objects. Gradually, the software became more sophisticated, essentially performing complicated algorithms and often generating whole new theories and subfields within algebra and topology. A good example is the theory of Groebner bases, an essentially computational method for solving systems of polynomial equations. Since its inception in 1965, it has exploded into a huge area of research with wide-ranging applications in mathematics and computer science. Computers have validated and explored many other areas of mathematics, and the influence of computation is only going to increase in the future.

Nowadays, it is impossible to imagine our life without computers and their powerful software. No wonder, those influential and versatile technologies have already started to influence and dictate the way we conduct our scientific experiments, research and even the way we teach. This document primarily focuses on the influence of computer technologies on the field of mathematics and consists of two main parts. The first part gives an overview of how technology has influenced mathematical research, focusing on the impact of computation in various mathematical fields. The second part gives a brief introduction on how technology has influenced mathematics teaching. This is a rapidly changing area, affected by changes in technology at all levels, from primary schools to universities. While the overall outcome of the influence of technology on this field is positive, there are potentially disturbing issues raised by the changing educational landscape.

2. Benefits of AI in Dissertation Writing

When a student starts out on a dissertation, they are usually struggling just to get something down on paper. It isn’t for lack of good ideas or motivation. Many take long breaks in the early stages, leaving too big a gap between those first bursts of productivity and the next time they sit down to write. Or, if they try to follow through, they get writer’s block, not knowing how to move their ideas forward in ways that will result in a first-rate dissertation. In both cases, students could benefit from using AI as a tutor at this initial stage. AI can help students to generate ideas for their dissertation. Some programmes (again, including Dr. Daedalus) ask students questions that prompt them to think in new ways about their topic. Luc Stake 7 recalls: “I asked a question about the feasibility of using a particular approach to data analysis, and the computer asked me why it mattered… I ended up having to think much more carefully about the connection between my method and the significance of the analysis.” So here AI is seen not just automating a task, but facilitating a process of learning and discovery.

3. Limitations of AI in Dissertation Writing

Whilst some of the previous suggestions sound appealing, caution should be used to ensure that AI is not abused and relied on too much. Remember that dissertation writing is a very personal journey and it will be crucial to maintain a balance between it being an interesting experience and simply punching into a computer what is needed to achieve desired results. Allow the AI model to spit out some regression analysis is fine these days given any large data set this is the go-to test, but the autonomy to decide exactly what type of analysis is best suited for the question and what to do with the obtained results will always belong to the student and is what separates a great dissertation from a poor one.

AI is not capable of writing a dissertation. What it will be capable of is doing a lot of the donkey work involved in research and preparation for a dissertation. Mankind has made great strides in how to ask the right research question and the computer algorithms which will be developed should be capable of refining the question to produce results which will be defined as desirable. Once this stage has been achieved then AI can be let loose to scan the countless online academic journals and other resources where at the click of a button it will be able to harvest all the relevant data. Another aspect where AI could be very useful is in the ability to run hypothesis tests. Through machine learning algorithms, it could be possible to write a program which will take data and subject it to a certain statistical test. If the data meets the requirements of the test, it will be able to make a valid conclusion.

4. Best AI Tools for Dissertation Writing

a) Automated Machine Learning (AutoML) Machine Learning, also known as ML, is an AI system that has the ability to learn from data and to enhance its accuracy without being programmed explicitly. Machine learning has been applied to various tasks, and one of them is to assist humans in building software or systems. However, building a machine learning model also requires data science expertise and consumes a lot of time. Now with AutoML, it’s possible to automate building a machine learning model without any data science expertise and it’s the best affordable option for small businesses. It can help automate model selection, feature engineering, and algorithm selection to ease the machine learning process at a lower cost. Step-by-step guidelines are provided in order to build a model with minimal steps. Post-modeling tasks like model validation and optimization are greatly enhanced because AutoML systematically automates the whole machine learning process and results in higher accuracy of the machine learning model. Through automation, AutoML will reduce the overall cost for machine learning development. There are several AutoML software/tools available with some provided paid service and some are open source; TensorFlow, H2O.ai, and auto-sklearn are a few examples to name.

AI has both a high and low cost, high range and accuracy. AI is defined as a system that has the ability to perform a task that would normally require human intelligence. AI systems can execute tasks, which normally require human intelligence, for example visual perception, speech recognition, decision-making, and translation between languages. In order to know more about AI and its categorization, the figure 1.1 below shows the categorization of AI based on cost and range. High cost and range of AI are always related to strong AI and weak AI. Strong AI, also known as true AI, is a system that has the ability to understand, learn, and apply its intelligence to surpass human intelligence. There are only a few systems that are categorized as strong AI and are still in the development process. On the other hand, weak AI or form of AI today is designed to accomplish a narrow task or to simulate the human’s method to do the particular task. Weak AI highly depends on the intelligence applied by humans to develop the ability of machines to carry out the task in a natural intelligence.

5. Conclusion

In conclusion, AI is now beginning to play a significant role in a student’s dissertation. Tools such as BERT are greatly advancing natural language processing and the capabilities of this have been seen in the latent Dirichlet allocation algorithm. This has both positive and negative effects. Work can be indexed and searched easily; however, the computer’s ability to process information and categorize it assumes patterns and relationships in the data that aren’t there – this is dangerous. The aim of a dissertation is to produce new findings to the academic world, and if a computer makes assumptions on the data and indexes it in a certain way, the student’s work may get overlooked compared to another’s because it is not in line with the indexation process. With all of this in mind, the continually growing capabilities of AI look to only increase the extent to which it can aid a student in their dissertation. And ensuring the academic integrity of the dissertation is maintained will be an issue that will have to be addressed further down the line.