As more tools become available at the intersection of recruitment and artificial intelligence (AI) or machine learning (ML), we sometimes get questions about what they are and how to use them. So I wanted to share a little more detail. Over the past few years, we have used AI and ML to guide job seekers throughout the recruitment process, from identifying the right positions to apply to increasing flexibility with online assessments that help engage and evaluate candidates. We’ve built tools to help. While promoting fairness and equity in the hiring process and adhering to legal standards.
Leveraging technology to recruit and develop top talent
At Amazon, we often talk about: Recruit and develop the best talent. it belongs to us leadership principlesIt informs everything we do and is at the core of our culture of continuous growth and innovation.Part of Recruiting and developing top talent We approach the hiring process with the same builder mindset that we use to serve our clients. Our People eXperience and Technology (PXT) team is constantly innovating on behalf of our customers and his Amazon employees. We think deeply about how to build holistic, technology-driven solutions that facilitate scalable hiring processes and impartial candidate experiences, reduce potential bias, and enhance capabilities. Member of our recruitment team.*
Help job seekers discover potential roles
ML helps potential candidates find the most relevant roles to apply for from the very beginning of their search. for example, amazon jobs On the Careers page, candidates can search for roles by title, keywords, and location. As users browse search results, our behavior-driven machine learning algorithms display real-time relevant role recommendations on the job detail page from our complete catalog of open positions.
Identify optimal skills and experience
As candidate engagement progresses, ML will allow us to more quickly identify suitable roles for some candidates. For example, if a new Amazon intern or college graduate is interested in a full-time role, the system automatically recommends roles that match their interests, skills, and experience. These candidates have skills that can be applied to a variety of roles, and we identify interests based on natural language processing of candidate resumes. It then follows a machine learning algorithm to suggest relevant roles to recruiters that match the candidate’s interests. For example, a candidate’s resume may mention an interest in embedded systems, which may suggest a role on the Alexa team.
Our team of scientists continuously monitors recommended matches to ensure fairness, and our hiring team reviews all recommendations to ensure they best reflect the best for long-term success on Amazon. Make sure you are
Make Candidates More Attractive with Online Assessments
We also use online assessments to engage, inform and evaluate candidates in the process. These research-backed assessments are designed to objectively measure key job knowledge, skills, and competencies, and our research suggests that these assessments are more equitable across identity groups. has been shown to promote comprehensive outcomes in This gives candidates greater flexibility as they can take the assessment online instead of waiting for a scheduled phone screen to move through the process. Our research shows that consistent use of online assessments in the hiring process leads to more diverse hires and more efficient and accurate hiring than not using assessments.
Check applications for selected roles
For certain types of roles, machine learning is used to identify candidates who can move through the hiring process based on skills and other qualifications without waiting for resumes to be reviewed by recruiters To do. All other candidate resumes will be referred to our recruiting team for review and next steps will be considered based on the candidate’s likelihood of success. Successful candidates in the hiring process tend to be more diverse when using this tool, and the number of applicants moving on to the next step in the interview process (and ultimately joining Amazon) using this tool increases. The data show an increase. , and do it fairly.
Promote greater equity
Like many Amazon processes, these AI- and ML-based recruiting tools are developed and used responsibly to foster continuous innovation and earn candidate trust. It is especially important that tools used in hiring are developed, implemented and monitored in accordance with legal requirements and scientific and industry best practices. We regularly conduct rigorous analysis of the results of these tools to ensure they provide similar benefits for all demographic groups.
We also exceed legal and industry standards in our commitment to building “naturally inclusive” technology. For us, “Born Inclusive” means focusing on fairness at every stage of product development and examining candidate results across all identity groups.
As part of this process, we start with user research. This means digging deep to understand the context of the tool from diverse and representative perspectives and experiences. Before announcing a new tool, we conduct research to see if it provides similar benefits to individuals from diverse identity groups. And once the tools are in use, we closely monitor their performance to ensure that they deliver comparable results regardless of gender or racial identity.
We believe technology can drive a fairer application process by focusing on the foundations of skills and job requirements, and algorithmically measuring and minimizing bias, and we believe that in this area we We are proud of how we innovate. This, like other Amazon innovations, is part of our commitment to embedding diversity, equity, and inclusion into our hiring tools.
what’s next?
This work is not finished yet. We will continue to raise the bar while making the hiring process even fairer and faster. We are very excited about what lies ahead and continue to be proud of our innovations for our candidates. Recruit and develop top talent.
*These tools are not used in jurisdictions where they are not permitted by local law.
