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      Software: These are the few software being used in HR based on the AI automation algorithm.

      Myinterview: It is cloud-based interview platform for the interview that brings the candidates and the employees together. The prescreening of the candidates is done by one way interview. It has different features which include customized questions, managing candidate applications, and reviewing and providing a comment upon them. It helps to make the recruitment process more effective affordable and efficient. It brings the personality of the candidates in the forefront of the employer and ensures a best fit to the company.

      Talla: Talla is an AI auto med platform to help the customer support. It automates the answering of the queries, provides the reports when needed, and maintains the accuracy of the report.

      Saberr: The creator believes that development of the technology should promote and automate a meaning full relationship between people and technology. AI should help the human rather than replace them. The software helps the team member and candidate to receive an individual report which shows the value based on the values and personality based on Schwartz and Big 5 personality. The report helps to increase the selfawareness and helps the teams to understand about type values and personality and tells that how the act at work.

      Hemingway App: This app uses a primitive AI that recognizes writing by NLP and polishes the writing structure. It helps in saving the time and increases the readability.

      Skype Translator: It reduces the language barrier as it works on eight languages and the text translator helps in more than 500 languages for prompt messaging.

      Google smart reply: It uses the machine learning to analyze the emails and suggests a quick response the person wants to send. It helps the employee to save the time in deciding the response for the mail and keeps the mails updated and well answered.

      Paradox: With the help of AI assistant, it focuses on the entire candidate Management. With the help of VCV it helps to search the candidates: it calls them with the questions by using the voice recognition and invites them for the video interview.

      So, it can be said that AI can be effectively intertwined into the complete life cycle of the employee; it starts with recruitment and selection, to HR service delivery and career designing, along with the personalized experience, and ends with the succession planning. HR agility has emerged as a critical theme for organizations in the war for talent.

      “Bad implementation of AI is a bias itself”

       “You can have data scientists, but the ability to translate that to actual AI has become a struggle in HR.”

      –Sonny Tambe [8]

      Like a fairy tale dream, the life is always not a fancy land where all wishes comes true with a spiral of magic band. There always lies a bad in between the good and an evil between the boons, so is the case of AI in HR. As it is said that all the coins have two sides, so the AI is likewise among perusing resumes to grab best applicants more accurately by using the data to have a detailed discussion with the applicant. These are the positivity of the Big Data and AI technology in the HR department. But as the coin has two sides, so is the AI.

      Between good and bad, there is a managerial conflict going on in totally believing a machine for “devolving” people management tasks as an HR function or to took up a strategic challenge by totally believing upon it [9]. However, it is debatable issue that can be argued over time (e.g., Wood [10]) that AI proposes a real opportunity for HR to make its mark.

      In terms of ethics of organization, the point arises in terms of permission in regard to the use of AI in organizations. The question pertains in terms of the use of machines in selecting the future success of any organizations. The issue of the trust rises. It is also difficult to judge the ill effects of AI in terms of errors, as in contrast to a human being, so to use the AI, new methodology ought to be determined for AI.

      From an organizational psychology viewpoint, there are lots of issues to be handled before implementing the AI in HR In particular, the loss or the gain has to be carefully calculated before the inclusion. Researchers are expecting that, in the next 10–20 years, around 40%–50% of jobs in Germany could be computerized and round 12 % of all the employees will be substituted by means of machines technology like AI, where selection of the employees would also be greatly affected. It would certainly cause fear of job security result in lack of task interest under performance. It would also result in mental stress and negative fitness and poor outcome for the organizations.

      In addition, from an economic point of view, AI calls for a big deal of training and skill updating before using it have to be taken care of, and lots of cost involve in regard to most of the companies having a big population of employee.

      It would additionally result in mainstream bias via incorrect training. There are various threats, and significant changes also would not take place and loop holes in the transparency can also become a disadvantage. After all, at some factors, the companies may not recognize how constantly and continuously self-schooling AI makes its selections or recommendations.

      3.10.1 Technical Requirements and Acceptance

      Currently, there also are various questions in regard to technical competency. The quality and advancement of the machine may give varied results in interpretation of data. For example, the speech conception tool of AI may give wrong result based on the poor quality of the machine or poor algorithm. The technological structure and the essential resource needs also are still unclear at this time.

      Applicants face the threat of being misjudged by the use of AI, in which it can bring the image of the company down in the eyes of the other applicants. Furthermore, because of the specialized process of application, the handling of AI can be in particular intricate for managers.

      Finally, the legal component is likewise imperative. Some of the dark side of AI in HR is as follows:

       “There is a central idea in machine learning: the data you use to teach a machine learning algorithm can significantly influence its behavior.”

       – Pinar Yardage, Manuel Cambrian, and Iyad Rahwan, MIT

      3.10.2 Cost Involvement

      As per the comments from the several HR professionals, HR is still considered as the traditional department and the backbone of any organization; hence, it is necessary to update the work methodology of the HR with the new technology. But in order to gain the initiative, cost is implied and so in the case of AI. As per the report of TATA [12], implementing AI in HR involves two types of cost: fixed cost and variable cost. Fixed cost deals with the machinery purchase, software automation, and the software implementation, while variable cost deals with training of the employees in reference to AI in terms of adoptability and functioning. It may be a huge investment for an organization in comparison to the traditional method of HR. So, most of the organization may retain itself from it.

      3.10.3 Machine Biases

      It is found that danger from

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