Why are algorithms considered as literal?

Discuss about the Use Of The Application Algorithm.

Use of the algorithms has been increasing rapidly in the recent years to predict things more accurately. However, the business organizations use an algorithm to strengthen their business predictions (Luca et al. 2016). Application of computer algorithm is beneficial for the business owners to identify the distribution channel and to understand the customer preferences. However, use of algorithm often creates risk if the users do not understand the process of computer algorithm. As for example, Netflix has invested million dollars to develop the algorithm in order to understand the customer preferences but often the viewer’s preferences do not match with algorithm predictions. Therefore, often the social media sites use an algorithm that maximizes the rate of pay per click, which dissatisfies the customers (Kotthoff 2016). This current study deals with the application algorithm, its limitations and accessing issues.

Why are algorithms considered as literal?

Literature shows that humanizing algorithms makes human being more comfortable while they are using the algorithm. As for example, when an individual is designing automated call functions then humanizing algorithm is effective. The behavior of algorithm is different from the human. It can be said that the human being treats the algorithm and the machines that are involved in algorithm process also treat the employees and the supervisor (Kleinberg et al. 2017). Algorithm can be literal if humans are not able to use this algorithm carefully. However, it can be said that algorithm is a computer programming in order to solve issues and it serves as the blueprint. Hence, it can be said that the user needs to apply the algorithm by using proper. Any error during the application of algorithm may create issues as algorithm is a literal process. If the human being ignores any consideration during the use of algorithm then they may face trouble while accessing the algorithm process. The instruction should follow properly during the application of algorithm. Algorithm may operate the task literally, which will create a big trouble for the human being.

What are the major issues of algorithm use?

Computer algorithm includes various programming. This is considered as the effective predictive tool. However, this system may create problem if they are not applied in a proper manner (Zhang et al. 2018). Often technical issues arise while computing the program. The source of data needs to access in a proper manner otherwise the system can be damaged. As for example, the social media sites often affected due to the use of algorithm.

What are the major issues of algorithm use?

It has been seen that many sites prefer to use the algorithm to select the ads and news in order to attract the users. On the other hand, many websites deploy algorithms to choose the links and ads for the users. These algorithms are associated with the enhancement of user click-throughs, as a result, the sites become choked with poor quality click bait. As a result, the rate per click becomes increased, which hampers the customer satisfaction level. Hence, the missteps occur in algorithm process that is a big issue of algorithm use to carry out business predictions. Apart from this often the business organization uses a computer algorithm to predict the customer preferences. However, often mismatch occurs between the customer preference and the algorithm prediction (Kleinberg et al. 2017). Hence, it has been found from the studies that operating process of the algorithm is crucial to reduce issues regarding it. On the other hand, data should be accessed properly otherwise the issues can occur in algorithm system. Therefore, a computer algorithm is a time-consuming process and big tasks are difficult to put into the computer algorithm process. Hence, it has been found that computer algorithm is beneficial for business prediction if the process is carried out properly. Any misuse of this process may create a big error in the system, which can hamper the customer satisfaction in the context of any business.

What is the importance of right data input during the application of algorithm?

In order to use the algorithm right data input is necessary for an organization. Based on the literature review it has been received that the healthcare organizations are trying to measures the forborne disease in restaurants. For this purpose, the healthcare organization uses online reviews to understand which restaurant is violating the local health code. They create an algorithm to collect this data. Use of algorithm the healthcare organizations are able to review the large amount data. Algorithm is associated with the computer system thus right data input is necessary. If the data is not given properly then expected outcome cannot be got (Ding et al. 2015). Firstly right data needs to input in algorithm process then it should be processed and finally the outcome is got. To apply the algorithm process for a business purpose proper data resource need to choose for the organization. However, it is important for the organization to organize the data in a proper way to get expected outcomes from the algorithm process. Increased length of data is helpful to improve the prediction trough algorithm process.

What is the importance of right data input during the application of algorithm?

What are the limitations of algorithm use?

Algorithm process is beneficial for business prediction, however; it has some limitations that often hamper the effectiveness of this process. Based on the given literature it has been found that algorithm generates predictions based on the existing data and it is not transferable to a new issue and assesses the problem. One of the major limitations of algorithm process is the formal system. It is often difficult to make a connection with the informal world and the computer world. On the other hand, algorithms are considered as the black box. Maximum business platforms are owned by the private owners and they do not want to expose their internal working process by computer algorithm to the end users. As a result, complexity occurs in the system and the user faces difficulties to comprehend this system (Xue et al. 2017). Therefore, machine learning algorithm is used in high dimensional space to access millions of parameters. This leads human being to comprehend this system.

The first key question refers that algorithm process is considered as the literal process. This fact is also found in core article based on which the question is generated. From the supportive journal it has been received that proper accessing is mandatory during the application of algorithm otherwise issues will be generated in this system. Human operates algorithm and due to an error in this process leads algorithm to monitored human. The second key question refers to the issues related to algorithm application. From the supportive journal it has been received that technical issue is a major issue of algorithm and poor accessing may create customer dissatisfaction through the algorithm process. This issue is also found in the core journal. The third question is related to the necessity of right data input in algorithm process. It has been received from the supportive journal proper input of data is necessary to get expected outcome from the algorithm process, which is also supported by the core article. The last key question focuses on the limitations of algorithm process. It has been received that algorithm is considered as the black box which is a major limitation among the other limitations of algorithm process. Due to complexity in comprehending algorithm process, it is considered as the black box that also found in the core article. Hence, it can be said that each article related to the four key questions support the information of core article.

Conclusion

The above piece of work reveals the advantages and limitations of the algorithm process in business predictions. It has been received that algorithm process needs proper input of data. Any error during the data input may create complexity in the algorithm process. Due to the complexity algorithm is considered as the black box, which is the major limitation of this process. Often the prediction of the algorithm process does match with the customer perception. It is considered as the linear process. Despite these limitations algorithm is beneficial for business prediction as it helps the user to review the large data quickly.

References

Ding, S., Zhao, H., Zhang, Y., Xu, X. and Nie, R., 2015. Extreme learning machine: algorithm, theory and applications. Artificial Intelligence Review, 44(1), pp.103-115.

Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J. and Mullainathan, S., 2017. Human decisions and machine predictions. The Quarterly Journal of Economics, 133(1), pp.237-293.

Kotthoff, L., 2016. Algorithm selection for combinatorial search problems: A survey. In Data Mining and Constraint Programming (pp. 149-190). Springer, Cham.

Luca, M., Kleinberg, J. and Mullainathan, S., 2016. Algorithms need managers, too. Harvard business review, 94(1), p.20.

Xue, J., Wu, P., Kryger, M., Wang, W., Cheng, P., Das, I.J. and Hu, K.S., 2017. Limitations of Optimization Algorithm With Volumetric Modulated Arc Technique for Head and Neck Cancer Radiation Therapy. International Journal of Radiation Oncology• Biology• Physics, 99(2), p.E741.

Zhang, Y., Ye, P., Wu, J. and Zhang, H., 2018. An optimal curvature-smooth transition algorithm with axis jerk limitations along linear segments. The International Journal of Advanced Manufacturing Technology, 95(1-4), pp.875-888.