BMO6630 Business Research Methods For Machine Intelligence

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Answers:

Introduction

Artificial intelligence (AI) also referred to as the machine intelligence (MI) is the intelligent behavior of the machines which make them perform some special functions such as learning and problem-solving which require some level of intelligence. In the modern world, the use of artificial intelligence to solve different complex tasks has become very popular. Many fields such as the medical field, the finance sector, the aviation field, the field of research and many other fields have adopted the use artificial intelligence to help them in solving their problems (Cohen and Feigenbaum, 2014). The business field has not been left behind but has also embraced the technology of artificial intelligence to help in improving the operations. Many businesses are currently using artificial intelligence to perform some of their complex tasks.

In this research, we are going to study the use of artificial intelligence in the modern world. This study will help us to understand how different sectors are using artificial intelligence to improve their performance. It will also help us to predict the future of artificial intelligence in the world. 

Project Objective

The main objective of our research is to determine the major benefits of artificial intelligence in business. We shall also consider some of the major challenges facing artificial intelligence in business. 

Project Scope

justify;">This project covers the use of artificial intelligence in different organizations. We shall give special consideration to the benefits of artificial intelligence in the business sector. We shall also consider some of the major disadvantages facing some industries due to the use of artificial intelligence in their operations.

Literature Review

As we introduced it, artificial intelligence is a modern technology which helps machines to portray some level of intelligence by solving some cognitive functions such as learning and problem solving which used to be solved by animals and people only. In the modern world, the level of intelligence of the people has gone up, and they have developed some intelligent machines which are capable of solving problems on their own without human intervention. Most industries have embraced the technology of artificial intelligence in their operations, and this technology has helped to improve their performance. Among the major industries which use the technology of artificial intelligence extensively include Google, Apple, Uber, and Accenture. Artificial intelligence has also been used extensively by some communication companies such as Facebook and Twitter to aid in voice recognition.

 The use of artificial intelligence has become very common in many other organizations as it has very many benefits to the organizations. Among the major benefits of using artificial intelligence in organizations are

Artificial intelligence can be used for research and exploration in some areas which have some unfavorable conditions for human beings. The knowledge of artificial intelligence has helped in ocean floor exploration which can’t be accessed by human beings easily (Beato, D'Ambrosio, and Rodriguez, 2011, pp.373-403). The knowledge of artificial intelligence has also helped the scientists to explore planet Mars without getting there which could risk their lives.

Artificial intelligence involves the use of machines which can work continuously without getting fatigue like human beings. The machines will provide high-quality work and will work continuously without any breaks which people need to take a rest.

The use of machines in solving problems is better and has fewer errors as compared to the use of human effort. Unlike the human beings who are very prone to errors, the “intelligent” machines will solve the problems more accurately with higher precision with very few chances of making errors. Programming the machines accordingly to solve certain problems will help to achieve very accurate results and the machines will work faster than people.

Another benefit of using artificial intelligence in organizations is the ability of the intelligent machines to perform certain tasks repeatedly without getting bored like the people. According to Fethi and Pasiouras (2010, pp.189-198), the technology of artificial intelligence has helped organizations to deal with tasks which need to be repeated severally. These tasks can be performed by people but their repetitions bore people, and the boredom can compromise the quality of the services offered by people. However, regardless of the number of times repeated by the machines, they won’t get bored but will remain to deliver the original good services.

The knowledge of artificial intelligence can be used to evaluate the health conditions of the patients, and this will enable the doctors to offer the necessary medical care to the patients. For instance, the knowledge of artificial intelligence has helped the doctors to diagnose various liver diseases which has helped the doctors to offer the necessary treatment to the patients (Lin, 2009). Artificial intelligence has played a great role in the medical field and has helped the doctors in offering more efficient services to the patients.

Artificial intelligence can be used to predict the performance of various organizations in the future. According to Bostrom and Muller (2016, pp.555-572), artificial intelligence has helped businesses and other organizations to predict their future performances. This has enabled the businesses to take the necessary actions to evade some losses which might hit them in the future.

Artificial intelligence has many other benefits to the organizations. However, artificial intelligence comes with several challenges to the organizations. The major challenges which face artificial intelligence include the huge capital required to install and implement the technology, increased risks of cyber-attacks, and loss of jobs to most people since the machines do a wide range of jobs which could have been done by people. Organizations which use artificial intelligence have been working hard to look for ways to address these challenges as they can’t afford to miss the many benefits of artificial intelligence.  

Research Design and Methodology

Qualitative research

Qualitative research is a type of research which involves collection and analysis of non-numerical data. The data is collected in terms of words or texts, videos, photographs, sound recordings or other forms (Flick, 2014). The main steps taken in qualitative research are:

Decide on the main topic of research. In this step, we decide the main topic and define the objectives of the research. Our main topic of research is artificial intelligence, and the main objective is to determine the major benefits of artificial intelligence in business.

Carrying out a literature review. This step involves the analysis of the existing systems which help us to understand our research better. In our case, we have done a detailed review of artificial intelligence.

Deciding on the best sampling method and the best sample size. A good sampling method and sample size will help to improve the accuracy of the results obtained in research. In our case, we shall do our research in a hundred randomly selected businesses which use artificial intelligence (sample size=100).

Data collection. This is the step which involves using various methods to collect the required data in the research. To make sure we get valid and reliable data, we should choose good data collection methods which will give the required data. (A questionnaire form which can be used for data collection is shown in the appendix section)

Variable specifications and data analysis. After collecting the data, we should specify all the variables accordingly to help us in the data analysis process. Data analysis helps us to obtain the solutions of our research questions. We can then make the necessary deductions and conclusions of our research.

Preparation of a comprehensive report of the research. This is the last step of qualitative research and involves preparing and documenting a comprehensive report which explains all the outcomes of the research (Rossman, 2014). 

Quantitative research

According to Muijs (2010), quantitative research is research which deals with numerical data. The numerical data is collected and analyzed manually or by using the different mathematical software. Most of the steps used in qualitative research methods are also used in quantitative research, but we have some few differences between the two research approaches. The major steps used in quantitative research are:

Definition of the main problem of research. This is the first step in quantitative research and involves defining the main topic of the research. The objectives, the research questions, and the hypothesis of the research are also developed in this step.

Undertaking a literature review. This is the step where we do a detailed analysis of the existing systems as these systems will always be used as references to our research.

Sampling and sample size. We choose the best sampling methods which will be suitable for our research. On the sample size, we should take a good sample size which will help us to realize good results of our research questions.

The design and preparation of research instruments. The research instruments are the tools which are used in the research. They include the questionnaire or survey forms used in data collection and the computers used in data analysis.

The data collection. After preparing the research instruments, we collect the required data from the relevant resources. For better reliability and validity of the collected data, we should collect our data from trusted sources such as the companies’ websites or countries’ websites.

Data analysis. This is the step which involves analyzing the collected data to help us to answer our research question.

Preparation of the final research report. This is the last step and involves writing a report to summarize the whole research process.

Research limitations

Our research is faced with many limitations. The main limitations of our research include:

The results obtained are just generalized results based on the sample used. We have very many businesses which use artificial intelligence in the world and doing research in all the businesses is very difficult. Therefore, the results obtained are just acceptable approximations but not the actual results.

Another limitation of our research is the complexity of the data. The data of the use of artificial intelligence in some businesses is very complex and may pose a great challenge in the analysis process.

Another limitation of our research is poor cooperation of some businesses. Some businesses may not be willing to disclose their private data of use of artificial intelligence to the researchers. We may also have some cases of incorrect data given by some businesses. 

Time Schedule (Research plan)

The time plan for the research is shown below

Conclusion

Artificial intelligence has been used to improve the performance of many organizations in the world. In the field of business, artificial intelligence has played a great role to help in improving the performance of the businesses. This has encouraged many businesses to embrace the use of artificial intelligence in their services. Artificial intelligence comes with some serious challenges, but the organizations which use AI have come up with some ways to address these challenges. The use of artificial intelligence in business is expected to keep on increasing, and in the future, we may have more than 90% of the big businesses using artificial intelligence. 

References List

Bostrom, V. C. M. a. E. N., 2016. Future Progress in Artificial Intelligence: A Survey of Expert Opinion. Fundamental Issues of Artificial Intelligence, Volume 376, pp. 555-572.

Cohen, E. F. a. P., 2014. The handbook of artificial intelligence. 3 ed. s.l.:Butterworth-Heinemann.

E Turban, R. S. a. D. D., 2011. Decision support and business intelligence systems. 1 ed. s.l.:Pearson Education.

Eugene Charniak, C. K. R. D. V. M. a. J. R. M., 2013. Artificial Intelligence Programming. Second ed. New York: Psychology Press.

Flick, U., 2014. An Introduction to Qualitative Research. 5th ed. London: Sage Publications Ltd.

Józef Korbicz, J. M. K. Z. K. a. W. C., 2012. Fault Diagnosis: Models, Artificial Intelligence, Applications. 1st ed. Warsaw: Springer.

Lin, R.-H., 2009. An intelligent model for liver disease diagnosis. Artificial Intelligence in Medicine, September, 47(1), pp. 53-62.

Muijs, D., 2010. Doing Quantitative Research in Education with SPSS. 2nd ed. London: Sage Publications.

Nicholas Beato, D. B. D. a. A. R., 2011. Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space. The MIT Press Journals, August 8, 19(3), pp. 373-403.

Nilsson, M. K. a. N., 2014. Principles of artificial intelligence. 1st ed. s.l.:Morgan Kaufmann.

Pasiouras, M. F. a. F., 2010. Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operation Research, 2004(2), pp. 189-198.

Rossman, C. M. a. G. B., 2014. Designing Qualitative Research. sixth ed. Carolina: Sage Publications,Inc.

Simari, I. R. a. G., 2009. Argumentation Theory: A very Short Introduction. Argumentation in Artificial Intelligence, pp. 1-22.

Thomas Dyhre Nielsen, F. V. J., 2007. Bayesian Networks and Decision Graphs. 2nd ed. New York: Springer.