SPICE Professor Raquel Hill Showcases Research at the Cybersecurity Research Acceleration Workshop

When assessing job applications, research data show that recruiters and employers screen applicants based on age, class, personality, and other characteristics that may not be gleaned from a resume. In an ideal situation, one might imagine that employers hire the most skilled applicant, but sociological research shows this is not the case. A job applicant's similarity to the interviewer in class background and class-based leisure activities often matters as much or more to employers than a job applicant's skills or work experience. The ability of a recruiter or employer to learn such information from seemingly unrelated data has led researchers to express concerns about privacy, job relevance, and the potential for illegal discrimination. In the past, these characteristics were usually assessed during the interview phase of a hiring process, but the proliferation of data in online social media sites and discussion boards provide a means for employers to learn this information prior to any face-to-face contact.

Job-seekers often do not realize the extent to which online information may be used in ways that violate their privacy and leave them open to discriminatory practices. Employers can easily gain access to online information or infer from online data much of the information that is prohibited from being asked during a hiring process: religion, marital status, sexual orientation, number of children, etc. While prior research has studied how features like race, age, religion, and sexual orientation affect the initial review of a job applicant, or the applicant’s ability to get a call-back, there is limited understanding of how the web has changed the types of information that employers use to assess an applicant’s employability. In addition, the use of data aggregators for recruiting purposes will also limit the effectiveness of current research methodologies that simulate applicants via constructed resumes and online profiles.

The hiring process is fraught with bias. An employer’s shared culture with applicants often outweighs the employer’s concerns about applicants’ absolute productivity. The proliferation of online data further shifts the focus from assessing applicants’ skills by enhancing employers’ ability to perform cultural matching. Dr. Hill’s research seeks to bring about a paradigm shift in the way that job applicants are evaluated. Her research addresses privacy concerns and limits bias by developing tools for automatically evaluating applicants’ skills that do the following:

  • Enable semantic comparisons between online profiles, offline profiles and job descriptions,
  • Develop means for identifying discrepancies in order to provide better feedback to individuals (applicants and potential employers)

On October 11, 2017, Dr. Hill showcased her research at Cybersecurity Research Acceleration Workshop. SPICE Professors Apu Kapadia and Sameer Patil also presented. The workshop was organized by the NSF Cybersecurity Center of Excellence and Internet2, hosted by the Indiana University Center for Applied Cybersecurity Research. The goal of the workshop was to inform cybersecurity technology adopters of the benefits of adopting cutting edge cybersecurity capabilities into their organizations and matching them with security researchers looking for collaborative partnership.