Why we do research
Conducting research on a specific topic assists a researcher to gain knowledge over areas of value and interest, researches then have options to use composed information for further research or benefits to business organisations. The main aim of conducting this research is to understand artificial intelligence and its concept according to the current methods of programming. By conducting this research, the researcher will be able to provide in depth information to large organisations as these companies are the ones mainly showing their interest to adopt this kind of expensive technology (Russell and Norvig, 2016). This case study is based on Amazon, an American electronic commerce company headquartered in Seattle, Washington. The company is availing its services across the world and was founded by Jeff Bezos in 1994. The the owner of the company, Jeff Bezos mainly believes in adopting the latest technology in order to provide quality products as well as extremely effective customer service to its customers. Artificial intelligence could contribute to simplifying the work of employees and delivering more effective services to customers. This research on Artificial intelligence and its usage will be beneficial for Amazon as it will gather data on different opportunities and technologies.
What are the research questions?
Is the development of full Artificial Intelligence effective for working environments?
What is the null hypothesis?
A Null hypothesis simply means that there is no relationship between two available variables. This hypothesis shows that the researcher believes the stated research question does not have any valid point. A Null hypothesis is basically denoted with H0. In relation to the given research, it has been studied that null hypothesis for the research question is defined as below:
H0= No, the development of full Artificial Intelligence is not effective in working environments.
It means development of full Artificial Intelligence does not have an effect on working environment of business organisations like Amazon. It can be said that it does not matter whether Artificial intelligence is developing, or not as human resources still have to place their exact same efforts to monitor work which is performed by machinery (Artificial intelligence). Thus, it does not create any difference at the working environment of Amazon.
What is the alternative hypothesis?
The alternative hypothesis is completely opposite to null hypothesis as it shows that the result is highly effective (Wenger, 2014). An alternative hypothesis is denoted with H1, in context to the research question, it has been analysed that its alternative hypothesis is described as below:
H1=Yes, the development of full Artificial Intelligence is effective in working environments.
As per the above stated Alternative hypothesis, it can be said that development of full Artificial Intelligence is effective in working environment as it completely minimises the work of employees. Along with this, it also reduces chances of conflict which might be occurs at workplace as well as reducing the cost of paying employees.
Resources and Sources
According to the point of view of Baker, (2012). It has been studied that artificial intelligence is also called machine intelligence which is capable of performing activities in similar ways to human beings. These machines include a different learning experience which guides a machine in doing work according to pre-set rules and also ability of correcting the same work at their own level. It can be said that these machines are capable of performing work as a human being by using a similar kind of intelligence. These machineries in which work artificially usually perform work more effectively in comparison to human beings. It has been observed by the author that the development of full artificial intelligence has positive as well as negative outcomes which might enhance profitability of a company or it might also create negative publicity to the company as well. In order to reflect a positive outcome, it has been believed by the author that if artificial intelligence is fully developed then it contributes in creating an effective working environment as there are less employees at workplace which reduces chances of conflicts among employees (LeCun, Bengio and Hinton, 2015). Along with this, Machines also owns more capacity as compared to human beings while performing work in effective manner. It has been observed that increasing usage of artificial intelligence is also contributing in enhancement of sales as large scale companies are using this technology in their working pattern. As a result, these machineries are capable of providing quick services using integrated data on what customer like which corresponds to a customer remaining loyal with the company for long duration of time as the company ‘know them’ so to say. It also helps the company in generating more profit and revenue with the usage of advance and developed technology.
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Apart from this, at the same time it can be said that development of full artificial intelligence is not effective for the working environment. In order to support this statement, it has been investigated that if artificial intelligence will be completely developed then it will directly reduce work of employees (Cohen and Feigenbaum, 2014). As a result, work as well as profitability of the organisation will be depending upon the machinery only which is not good for the company’s growth as well as the profitability of company as this means human skill is lost overtime and the dependence on machinery is prominent. Along with this, it can be said that artificial intelligent systems are only beneficial for the company if they are programmed correctly. As there are very uncertain fragile elements to programming machines artificially it can cause ‘mass destruction’ to equipment and destroy the company’s tools. This may create further problems to the company’s profitability which involves risk as these systems are not yet fully developed and tested.
Chi Square Test
A chi-square test is a test used for statistical hypothesis in a situation where the distribution of sample is chi-squared and the null hypothesis holds true. This method is used for carrying out a comparison between incidence of a characteristic present in one group with the same aspect in relation to another group (Nguyen and Aiello, 2013). It is a commonly used methodology and is often also written as χ2 test. This method is used to ascertain the possibility of probable differences between anticipated and observed frequencies in concern with one or more such classes.
Actual (observed) range Expected (theoretical) range
YES NO YES NO
Agree 28 2 Agree 17 13
Disagree 3 27 Disagree 13 17
Chi square test value = 4.32E-008
Probability of error (refuting null hypothesis) = 4.32E-008
We cannot reject the null hypothesis because the test probability value for refuting H0 is above 0.05
Sources of Data
Researchers are often collecting information from various sources in order to conduct an effective result with true outcomes. This collected data can be termed as qualitative and quantitative in variable form. Basically, qualitative research is based on images, facts, values etc. on the other hand quantitative research mainly covers statistical data which is numbers, figure etc. These methods are used by the researchers according to their feasibility and requirements of the research objective (Nilsson, 2014). Further to this, researchers are using two different methods that is primary and secondary sources for collecting information from the targeted area. In the primary method of data collection researchers gather information directly from the respondent. This includes different sources like interviews, questionnaires, direct observations, surveys etc. In secondary method of data collection researchers find information from research that has been conducted already which may be through books, journals, online articles etc. Information collected from secondary data collection method is second hand and based on finding results of someone else’s findings. In present research, researchers have adopted questionnaires in primary method of data collection.
Questionnaire
Q1) Are you aware of the concept of artificial intelligence?
a) Yes
b) No
Q2) What are the benefits of developing Artificial Intelligence within Amazon?
a) Increases sales
b) Reduces work pressure of employees
c) Delivering quick services
Q3) What are the disadvantages of developing fully Artificial Intelligent systems in Amazon?
a) Enhance dependency of technology
b) Increase chances of fraud
Q4) Does Artificial Intelligence help in growth and development of business organisation?
a) Agree
b) Disagree
Data analysis
Theme 1: Concept of artificial intelligence
Q1) Are you aware of the concept of artificial intelligence?
Frequency
a) Yes
19
b) No
11
Interpretation:
From the above mentioned graph, it has been analysed that artificial intelligence is an advanced form of technology which helps business organisations in achieving their goals and objectives with the help of machinery. These machines have the capability of performing work similar to human beings. As per the evaluation, it has been analysed that among 30 respondents 19 have said that “yes” they agree with the concept of artificial intelligence as they have seen it in many large stores. On the other hand, 11 people have denied to the similar thought as they are not aware about its existence and benefits.
Theme 2: Benefits of developing Artificial Intelligence in Amazon
Q2) What are the benefits of developing Artificial Intelligence in Amazon?
Frequency
a) Increases sales
11
b) Reduces work pressure of employees
9
c) Delivering quick services
10
11
10
9
Interpretation: As per the above stated graph, it has been observed that there are numerous benefits which are gained by large organisations such as Amazon which includes reduced work pressure of employees, increases sales, delivering quick services etc. It has been identified that 11 people have said that main benefit of artificial intelligence is that it increases sales of Amazon as customers will get attracted to use similar kind of advanced technology and will visit more number of stores. Whereas, 9 of them said that artificial intelligence reduces work pressure of employees as they only have to operate and monitor the AI system which can be seen as benefit for Amazon. The remaining 10 respondents have declared that the benefit of developing Artificial Intelligence in Amazon is that it delivers quick services to customers.
Theme 3: Disadvantage of developing fully Artificial Intelligence system in Amazon
Q3) What are disadvantage of developing fully Artificial Intelligence system in Amazon?
Frequency
a) Enhance dependency of technology
12
b) Increase chances of fraud
18
Interpretation:
As per the above-mentioned graph, it can be said that even-though Artificial Intelligence is advance form of technology but it also have some negative impact and disadvantage for Amazon. It has been evaluated that 12 respondent among 30 believes that main disadvantage of Artificial Intelligence for Amazon is that it increases dependency of technology in operational activities which is not right as if someday company faces any issues related to technology then their work will completely stop as they are completely dependent on this form of technology. On the other hand, 18 respondents thinks that main disadvantage of Artificial Intelligence is that it increases chances of fraud. Because there are possible chances that programmer might in built some wrong program which will make this machine work in unethical manner.
Theme 4: Artificial Intelligence helps in growth and development of business organisation
Q4) Does Artificial Intelligence helps in growth and development of business organisation?
Frequency
a) Agree
17
b) Disagree
13
Interpretation:
From the above mentioned graph, it has been realised that Artificial Intelligence is the best technology which contributes in the growth and development of business organisation. In order to support this statement 17 respondents have said that they are agreed to the same thought as they are personally working in some companies which uses the similar technology is growing very faster. Whereas, 13 respondents have stated that does not agreed to the similar thought as they think that even if the technology reduces human efforts but its implementation is itself as expensive method that stops consumes profitability earning of the company.
Results
From the research produced above we can see that the development of full artificial intelligence could be helpful for creating an effective working environment. In order to gain the best results from the research compiled a primary source of data collection method was used.
To do this, questionnaires have been chosen as oppose to interviews as data can be collected relatively quickly due to the fact that the researcher does not need to be present when the questionnaires are completed. This is useful when carrying out research with a large amount of individuals. From carrying out this research, it has been identified that Artificial Intelligent systems are beneficial for large scale organisations but at the same time it also increases huge level of dependency on technology (Michalski, Carbonell and Mitchell, 2013). It can be said that it is important for business organisations to be cautious when choosing a programmer to code in this technology as it can be very precise in the commands that could either be correct or go wrong. It is very important commands are written without mistakes and testing is completed as this execute work in an effective manner similar to human beings.
Explaining how the mechanisms of conducting research work
In this research, the researcher has collected information from the respondents by using primary source of data collection that is questionnaire and also a chi square test. The collected information was then analysed according to the given data of the respondent. This evaluation is helpful in finding out an appropriate outcome for the conducted research.
Reflection
While conducting effective research for Amazon on the topic of Artificial Intelligence I have gained experience which has benefited me and developed my knowledge in this topic. I believe the most effective method of data collection is the primary method of data collection as it provides a high degree of accuracy this is because it’s relevant to the topic of the research study. It is also reliable as the data is collected by the concerned of covered party. A downside to collecting primary data is that it consumes a lot of time. I have also analysed that Artificial Intelligence is only effective technology when the company has reliable programmers. Furthermore, I have noticed that main demerit of this advance technology for Large scale companies is that it enhances dependency of technology over its operational activities.
Legal/Ethical concerns
A good research is required to be well planned, authentic and free from ethical problems. It is important for the researcher to conduct an effective form research in order to find appropriate and relevant outcome for it without compromising with ethical conflict (Russell and Norvig, 2016). In relation to the present research related to the artificial intelligence, the main ethical consideration for the researcher is that they should only use confidential details of respondent for research work only. It should not be used in other work without permission of respondent.
Finding
It has been identified that Artificial Intelligence is a strong and advanced form of technology which helps business organisations to implement their business activities in an effective manner. Along with this, it can be said that if large organisations want to enhance their profitability and reduce their working staff they can adopt this form of technology as it will reduce dependency of employees. As a result, large organisations can easily attain their targeted goals and objectives.
Limitations
While conducting this research, the main limitation that has been identified by the researcher is that the given time for this research was not enough which has interrupted them to find out relevant conclusion. Another limitation for this research was that while collecting information from respondents, they may have not given true information as they were less interested in questions.
Future research
Findings of this research are valuable for the researcher as it will clear their understanding on the same technology more deeply. It can be said if researcher will get chance in future to conduct research over the same topic then they will be easily execute this research in more effective manner.
Books and Journals
Russell, S. J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.
Wenger, E., 2014. Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. Morgan Kaufmann.
Gubbi and et. al., 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future generation computer systems. 29(7). pp.1645-1660.
Burns, H. L. and Capps, C. G., 2013. of Intelligent Tutoring Systems: An Introduction. Foundations of intelligent tutoring systems, p.1.
Lozano-Perez, T., 2012. Autonomous robot vehicles. Springer Science & Business Media.
Delen, D. and Demirkan, H., 2013. Data, information and analytics as services.
Baker, R. S. and Inventado, P. S., 2014. Educational data mining and learning analytics. In Learning analytics (pp. 61-75). Springer, New York, NY.
d Baker and et. al., 2012. Towards Sensor-Free Affect Detection in Cognitive Tutor Algebra. International Educational Data Mining Society.
Russell, S. J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.
Michalski, R. S., Carbonell, J. G. and Mitchell, T. M. eds., 2013. Machine learning: An artificial intelligence approach. Springer Science & Business Media.
Nilsson, N. J., 2014. Principles of artificial intelligence. Morgan Kaufmann.
Nguyen, T.A. and Aiello, M., 2013. Energy intelligent buildings based on user activity: A survey. Energy and buildings. 56. pp.244-257.
Cohen, P. R. and Feigenbaum, E. A. eds., 2014. The handbook of artificial intelligence (Vol. 3). Butterworth-Heinemann.
LeCun, Y., Bengio, Y. and Hinton, G., 2015. Deep learning. Nature. 521(7553). p.436.
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