![]() What’s more, AI does not have an ego that needs to be managed. The difference between humans and AI is that the latter can scale, and can be automated. Scanning social data and public data to assess the applicant profileĪI and Machine Learning can help Shutterstock to have access to wider and more diverse talent.ĪI algorithms simply leverage the same cues that humans do. Using technology to create a highly structured and standardized interview experience, every candidate can be presented with the same set questions and given the same opportunity to express their talent, which ultimately improves the video’s predictive utility. The analytics based approach can help in predicting the job performance and areas where HR can focus to improve the employee’s capability and tools that are needed for that. HR managers at Shutterstock can utilize AI and Machine learning systems strength in - mining job applicant’s facial expression, body language, along with the responses he/she provides in the live interview. Scanning through the profiles using Keywords related to the job profileĪI and Machine Learning can help HR managers at Shutterstock to build a reliable connection between what candidates say during the interviews and their personality traits, ability and performance at job. Some of the early opportunities fields where companies are utilizing algorithms for are. Most of the companies at a certain level have already started doing it and Shutterstock is no different. Machine Learning functions in Human Resources Management process Thus lowering the overall cost of running Human Resource Management department.ĪI can help Shutterstock to structure the whole recruitment, selection, and hiring process where each applicant has to go through the same process and judged without human biases of the moment. Machine Learning and Artificial Intelligence can help Shutterstock to significantly reduce the cost of identifying talent by providing better and more comprehensive predictions than human judgment which is influenced by individual heuristics and biases.ĪI and Machine Learning can help Shutterstock to make its internal systems more meritocratic and help individual to better understand their job profiles and what is expected of them.ĪI can help Shutterstock to predict, understand, evaluate, and match people at scale. What Shutterstock can Achieve using AI in Human Resource Management These data driven tools can help Shutterstock to reduce prevalent prejudice in the hiring process, remove interviewer’s biases, and help in reducing discrimination at all level. We at Oak Spring University believe that predictive analytics and assessments tools are underutilized at both organization level and industry level. Management consultants in the Motion Pictures industry calls them – bullshit jobs, where people find no value other and responsibilities that leave a vacuum inside. This mismatch in modern day organizations is resulting into many people ending up in positions and jobs that are at best un-inspiring. Shutterstock is finding it hard to find right people that match both - the vision of the organization and the right attributes needed to be successful at the jobs especially at the highly skills oriented top level positions. Shutterstock like most of the other companies in the Motion Pictures industry is struggling for talent identification. With the advancements of Machine Learning and Artificial Intelligence, the next big question in the field of Human Resource Management is – Should Shutterstock use algorithm to hire employees? Why Shutterstock Needs to Use AI in Hiring Process Introduction to Human Process and Artificial Intelligence
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