Background
Artificial Intelligence (AI) is linked with simulation of human intelligence in the machines which are mostly programmed to think and work like humans With the increase the use of AI, the machines are made to perform several critical tasks including the tasks of a human resource manager (Huang and Rust 2018). Several companies across the globe has invested in automating the repetitive and low value HR tasks to increase the focus on the strategic work process. Thus, it can be said that AI play an integral role in automation of the HR and the workforce thus reducing the human bias to a considerable extent However, the problem arise when there is a situation of bias as a result of machines (Dirican 2015). The report considers a case where an AI enabled machines is used by a company to shortlist the suitable candidates for a job role. The machines was trained using resume of male employees and thus it got the wrong signal and started rejecting female candidates leading to a situation of bias. This situation gives rise to an ethical dilemma linked with the use of machines in performing such tasks.
In the following paragraphs, the background of the case is discussed and case is analyzed on basis of “Doing Ethics Technique” and ACS code of ethics. The analysis will lead to identification of several options that can be implemented to manage this situation of bias.
Leaders across the globe are putting great focus on the advanced technology efforts. One such advancement of technology is in the field of the AI and human resource. Amazon has made use of technology of AI in recruitment process to automate the HR works of shortlisting the profile of the candidates. However, in Amazon, a situation of Bias came to public attention as the automated recruitment engine excluded women from the list. The recruitment engine was prepared with a combination of 500 algorithms so that the resume review process can be automated. However, the problem occurred as the systems were trained with the resumes of the mal employees from the software team and thus the intelligent machine found only the males suitable for the job role thus rejecting the resume of all the female job seeker. Thus a situation of bias was created. If the resume selection process was not automated by the machines this particular situation could have been easily avoided. Use of AI in automation of the HR works is mainly done to reduce the human bias; however, in this case, the machine is found to involve in a situation of bias. The main issue was however, with the training process that was undertaken in this case, which resulted in bias. This particular case is further analyzed in the following paragraphs.
AI in Human Resource Management
In the recent years, there have been an increasing trend of making use of AI in managing the monotonous and the repetitive human resource works (Amritaa and Achwani 2018). The usage and application of AI inhuman resource management play a critical role in transforming the HR workforce, thus reducing the human bias in candidate screening process of job application (Smith and Neupane 2018.). Thus, it can be said that the usage of AI contributes to improving the relationship with the employees and also contributes to the process of workplace learning, which is another significant sustainable benefit that is offered by the technology of AI.
According to Topol (2019), AI reasoning is found to help countries in coordinating the distinctive framework for boosting the critical HR functions. AI is considered to be a perfect insightful machine that is well capable of lessening the work pressures. AI innovation further contributes to effective applicant screening reducing the human bias in the process. AI enabled processes linked with management of human resources is associated with creation of sharp job description that provides a pertinent marker that results in a perfect resume match and it in turn reduces human labor as well (Zel 2019.).
Wisskirchen et al. (2017) indicate that the modern organizations face a number of challenges in bringing new opportunities. The modern organizations generally face a number of challenges in bringing new opportunities, which can be easily tackled by the use of AI. The usage of AI has become mandatory for the business organizations as it helps in increasing the competitiveness in the global market (Hmoud and Laszlo 2019.). Thus, there is no denying the fact that AI has played a critical role in transforming the HR and the workforce, and in turn reducing the human bias (Davenport and Ronanki 2018). The automation of the HR process though AI enabled machines are the future of workforce and therefore, adoption of AI enabled machines in the workplace is an example of tangible sustainable benefit offered by the technology of AI.
The AI in the field of computer science mainly aims in solving the major cognitive problems that are commonly linked with the human intelligence as AI enables the machine to think and perform like humans (Parkes and Wellman 2015). AI is a technology that allows the computers or machines to learn from the actions that are previously performed and thus, the efficiency of the machine increases with performance, which is another sustainable benefit of using AI enabled machines and thus the usage of those types of machine is set to increase in near future.
Case of Bias in Recruiting at Amazon
The technology of AI has considerably changed the traditional HR process as the adoption of modern technology makes the HR practices even more effective and efficient (Maduravoyal 2018). Since good HR practices generally contributes to maximization of the benefits and minimization of the problems, this particular technology mostly works for increasing the tangible sustainable benefits (Jarrahi 2018). With the AI enabled machines, it is possible to improve the HR related functions which include self-service transactions along with recruiting and talent acquisition, reporting, payroll and access policies and procedures. AI has made it possible to automate the human resource functions and increase the speed of completing the monotonous HR tasks, which adds to sustainable benefits of the technology.
On analysis of the recent development in this technological field, it is observed that AI enabled automated HR functions offers clear processes and easier performance management as the human bias is completely reduced in such cases (Russell, Dewey and Tegmark 2015). Therefore, it can be said that AI increases the opportunities and functions related to management of human resources. To summarize, the sustainable benefits offered by the use of AI contributes to enhancement of the business value and agility, speed delivery and digital integration.
The sustainability of any business or technology is measured on basis of the efficiency it offers (Palshikar et al. 2018). The AI in human resource management offers tangible sustainable benefits of enhancing the resource optimization of a particular business by streamlining its processes and increasing its efficiency. Therefore, in future, the adoption of AI in management of human resources is set to increase further.
Doing Ethics Technique is a process that analyses the ethical issues linked with a particular scenario so that an effective solution to a problem can be identified. This particular technique can be useful in having a clear understanding of an ethical issue arising from a particular scenario. To understand and identify the ethical issues linked with the chosen case, the case is analyzed with DET in the following paragraphs.
Q1. What’s going on?
Amazon has automated the recruitment process by adopting advanced technological solution. The company has used more than 500 algorithms to automate the resume review process. This type of HR tasks are mainly automated with an aim of reducing the human bias. However, in this case the machine is found to reject the resumes of the female job seekers. The system learnt to disqualify the female candidates as it was trained with the resumes of the candidates of the software team and all of them were males. Thus the automated resume review process of Amazon proved to be a disaster as although it was aimed in reducing human bias in resume shortlisting process, it resulted in a certain other issues.
Doing Ethics Technique Analysis
Q2. What are the facts?
The primary facts related to the case that is being analyzed are indicated as follows-
- The resume review process in Amazon is automated by AI enabled machines
- Amazon assembled a team who had made use of more than 500 algorithms in automation of the resume review process.
- The system that is developed is trained with the resume of the members who were a part of Amazon software team.
- The Software team had majority of male employees
- The system learnt to disqualify the female participants
Q3. What are the issues?
AI enabled machines are used in automation of HR functions as the risk of facing human bias is reduced in such case. However, the recruitment engine that is developed and trained by Amazon learnt to reject the female candidates as the machine was trained with the resume of male employees.
Q4. Who is affected?
In this particular case, both Amazon and the female job seekers were affected. Amazon suffered a reputational risk of being biased towards the male candidates. The female candidates who listed for the job also suffered as their resumes were rejected without any valid reason
Q5. What are the ethical issues and implications?
The resume review process in a recruitment drive is quite important as it contributes to selection of the most suitable candidate for a job role irrespective of their gender. The different HR functionalities are generally automated with an aim of reducing or completely eliminating the human bias. However, in this case, the bias could not be eliminated due to an inadvertent human error (Fan 2019). An AI enabled machine is capable of learning from previous experience and therefore, when the machine found out that the members of the software team of amazon were mostly males, it started rejecting all the candidates who attended female colleges (Alfawareh and Jusoh 2019). Thus the ethical issue arise in this case which is whether the use of such machines in resume review process is justified or not.
Q6. What can be done about it?
The ethical issue associated with this particular situation is required to be addressed to eliminate this situation of bias that has resulted from making use of an automated machine in the resume review process. The machine is to be re configured so that this error can be eliminated. It is of significant necessity to retrain or reprogram the machine so that the occurrence of similar situation in future can be avoided (Warren and Burmeister 2017). While programming intelligent machines, it is necessary for the developers to evaluate the various aspects where the machine can go wrong. The team working on that software should have used resumes of both male and female employees to train the machines
Q7. What are the options?
There are two option can be identified from this particular situation and these two options are indicated as follows-
- The entire system is to be scrapped and Amazon can go back to making use of traditional form of resume shortlisting.
- The developer of the machine needs to reprogram the machine and retrain it as well so that the machine does not rejects the resume of the female candidates.
Options to Manage Bias in AI-enabled Recruitment
Q8. Which option is best – and why?
The first option is not viable as it will lead to human error or human bias. Therefore, the second option is best as it contributes to development of the machine that will help in addressing the situation of bias (Bhalgat 2019).
The ethical code of “Australian Computer Society” exhibits the code of professional conduct. The ACS ethical code indicate the one should place the interest of public above personal, business or sectional interest and one should work on enhancing the quality of life of those, who are affected by ones work (McDermid 2015). On basis of these principles, the chosen scenario is unethical as the AI enabled machines is not working for enhancing the quality of life. The ACS code of ethics further indicates that one should be honest in representation of skills and should be competent enough to diligently work for the stakeholders (Burmeister 2017.). The code indicates the professional development and the professionalism are the two important need of a professional. Improper training of the machine does not show positive professionalism and therefore the situation is unethical.
In this situation the software developer is to be blamed for developing a machine that has given rise to a situation of bias. It is unethical in terms of ACS code of ethics.
Conclusion
The case of a situational bias by AI enabled machine is analyzed on basis of the DET and ACS code of ethics, the detailed ethical analysis of the case considered indicate that the machine cannot be blamed in this case but the developer who are programmed the machine to function in a particular way should be blamed. A number of options are evaluated in form of the analysis and on basis of the same, certain recommendations are made. The case outlines the negative impact of increase reliance on the machines. Furthermore, it is necessary to appropriately set the program logic so that similar situation of bias can be avoided and therefore the development of the recruitment engine is rightly blamed for the chaos. As per the ACS code of ethics, one should be honest in representation of their skills and in this case, the developer has not been effective enough in their work.
The usage of AI in management of the human resources is expected to increase in future and therefore, it is of foremost necessity to take proper actions in designing such intelligent machines. The situation of bias that is depicted in the report would not have arose if the machine was trained with the profile of both male and the female candidates. Although the intelligent machines exhibits traits linked with human learning and problem solving, proper precautions are required to be taken while training these machines.
The analysis that has been done on basis of ACS code of ethics and DET indicate that it is unethical to make use of a machine that is contributing to gender bias. On basis of the analysis, the following recommendations are made-
- It is recommended that the AI enabled machine is to be retrained using a mix of the resumes of both male and female employees so that similar situation is not faced in future.
- The issues would have been avoided is the recruitment engine was tested prior to its actual usage. It is recommended for the organization that prior to the usage of intelligent machine it is always better to test run the system which can helps in eliminating similar situation of bias.
The above two recommendations if implemented can contribute to addressing the situation of bias.
References
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Amritaa, K.S. and Achwani, S., 2018. A Study on Use of Artificial Intelligence in Human Resource Management. Gavesana Journal of Management, 10(2), pp.45-56.
Bhalgat, K.H., 2019. An exploration of how Artificial Intelligence is impacting Recruitment and Selection process (Doctoral dissertation, Dublin Business School).
Burmeister, O.K., 2017. Professional ethics in the information age. Journal of Information, Communication and Ethics in Society.
Davenport, T.H. and Ronanki, R., 2018. Artificial intelligence for the real world. Harvard business review, 96(1), pp.108-116.
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Wisskirchen, G., Biacabe, B.T., Bormann, U., Muntz, A., Niehaus, G., Soler, G.J. and von Brauchitsch, B., 2017. Artificial intelligence and robotics and their impact on the workplace. IBA Global Employment Institute, pp.2012-2017.
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