创新背景

有证据表明，目前的招聘流程受到任人唯亲和偏见的困扰。因此，可以将人工智能应用于招聘流程。

创新过程

研究人员已经系统地回顾了考虑人工智能在招聘过程中的有效性的学术文献。他们的研究结果表明，人工智能招聘通过更快，提高空缺职位的填补率，并在面试后推荐更有可能被雇用的候选人，从而提高了招聘效率。他们的审查表明，虽然人工智能在被雇用后预测员工结果的能力有限，但它对人类来说是一个实质性的进步。作者还评估了人工智能是否可以减少有偏见的决策并改善所选候选人的多样性。总体而言，人工智能招聘比人工招聘带来了更多样化的结果。

最后，作者研究了候选人和招聘人员对人工智能招聘的反应。他们的分析显示，人们对人工智能招聘的反应绝大多数是负面的。他们发现，人们对人工智能招聘的信任程度低于人类招聘，因为他们有隐私问题，他们发现人工智能的风度较低，他们认为部署人工智能招聘的组织不如那些通过人类招聘的组织有吸引力。

总的来说，这些发现导致了人工智能的表现与感知方式之间的差距。虽然人工智能招聘实践平均显示出对人类方法的改进，但人们对此反应消极。这对于采用人工智能招聘方法具有重要意义，并且可能会阻碍更好的招聘技术的实施。

媒体通常对人工智能招聘进行负面描述，并强调人工智能如何歧视候选人并使他们处于不利地位。然而分析表明，即使人工智能并不完美，它也比人类招聘人员更公平、更有效。与其孤立地关注人工智能，不如将其与其他招聘实践进行比较，以了解它为招聘过程带来的价值。

嵌入算法中的偏见可以通过编写算法的人更加小心地得到缓解，并且在招聘过程中合规人员可以监控该过程，以减少对公平性的任何担忧。让我们同时在招聘和工作场所包容性方面推进人工智能。

创新价值

人工智能招聘通过更快，提高空缺职位的填补率，并在面试后推荐更有可能被雇用的候选人，从而提高了招聘效率。

创新关键点

将人工智能应用于招聘流程中，增加了公平性，提高了招聘效率。

Using artificial intelligence for job recruitment

Researchers have systematically reviewed the academic literature considering the effectiveness of artificial intelligence in the recruitment process. Their research results show that artificial intelligence recruitment improves the recruitment efficiency by faster, improving the filling rate of vacant positions and recommending candidates who are more likely to be employed after the interview. Their review shows that although AI has limited ability to predict employee outcomes after being employed, it is a substantial progress for mankind. The authors also assessed whether artificial intelligence could reduce biased decisions and improve the diversity of selected candidates. In general, AI recruitment brings more diversified results than manual recruitment.
Finally, the author studies the responses of candidates and recruiters to AI recruitment. Their analysis shows that people's reaction to AI recruitment is mostly negative. They found that people's trust in artificial intelligence recruitment was lower than that of human recruitment because they had privacy problems. They found that the demeanor of artificial intelligence was low. They thought that the organizations deploying artificial intelligence recruitment were less attractive than those recruiting through human.
Overall, these findings led to the gap between the performance and perception of AI. Although AI recruitment practices have on average shown improvements in human methods, people have reacted negatively to this. This is of great significance for the adoption of artificial intelligence recruitment methods and may hinder the implementation of better recruitment techniques.
The media often give a negative description of AI recruitment and emphasize how AI discriminates against candidates and puts them at a disadvantage. However, the analysis shows that even if artificial intelligence is not perfect, it is fairer and more effective than human recruiters. Rather than focusing on artificial intelligence in isolation, it is better to compare it with other recruitment practices to understand the value it brings to the recruitment process.
The bias embedded in the algorithm can be mitigated more carefully by the person who wrote the algorithm, and the compliance personnel can monitor the process during the recruitment process to reduce any concerns about fairness. Let's promote AI in both recruitment and workplace inclusion.