See below the assigned area of investigation
Az-zara: AI-Based Hiring Platforms: HireVue
Objective: Research how HireVue uses AI-driven video interviews and facial analysis to assess applicants.
Activity:
- Investigate how the system analyzes speech patterns, tone, and facial expressions.
- Explore ethical concerns related to bias and transparency in AI-driven hiring.
- Identify companies that use HireVue and evaluate the impact on hiring decisions.
- To what extent should Aga Khan Hospital use HireVue for hiring it's workers?
Joshua: AI Resume Screening: Pymetrics
Objective: Examine Pymetrics, an AI-based tool that uses neuroscience and machine learning to evaluate applicants’ cognitive and emotional traits.
Activity:
- Research how Pymetrics replaces traditional CV screening with AI-driven games.
- Analyze the impact on hiring diversity and efficiency.
- Assess whether its machine learning models reduce bias or reinforce existing stereotypes.
- To what extent should the government of Kenya use Pymetrics for hiring government employees?
Divine: Rule-Based Applicant Screening: Holland’s Welfare Fraud Detection
Objective: Analyze the rule-based system used in the Netherlands to detect welfare fraud.
Activity:
- Research how the system used an “if—then—else” approach to classify applicants.
- Investigate the consequences, including legal challenges related to discrimination.
- Compare this system to AI-based fraud detection models in other countries.
- Evaluate the impact and the implications of rule based screening systems in developing countries.
Kin: AI in University Admissions: MyBestScores by TOEFL
Objective: Evaluate how AI-driven screening tools, like TOEFL’s MyBestScores, aggregate test scores for university admissions.
Activity:
- Research how AI selects the best scores from multiple test attempts.
- Investigate whether this system offers a fairer evaluation of applicants.
- Assess its impact on international student admissions.
- To what extent have AI systems used for university admissions impacted students applicants?
Joshua: Automated Employee Screening: LinkedIn Recruiter
Objective: Analyze LinkedIn Recruiter’s AI-driven applicant tracking system.
Activity:
- Investigate how LinkedIn uses AI to rank job candidates based on profiles.
- Evaluate its impact on recruitment efficiency and candidate diversity.
- Identify concerns related to privacy and data security.
- Some companies in the world use LinkedIn recruiter for the initial stages of job recruitment. To what extent should Safaricom a mobile phone company is Kenya use LinkedIn recruiter?
Sinon: Rule-Based Screening in Government Jobs: USAJobs.gov
Objective: Explore the rule-based scoring system in U.S. government hiring.
Activity:
- Research how federal job applications are scored based on pre-set rules.
- Compare the fairness and efficiency of this system against AI-driven hiring tools.
- Assess the impact on inclusivity and accessibility in government hiring.
- To what extent is the rule based scoring system in the US government hiring effective?
Aarav: AI in Financial Sector Hiring: JPMorgan’s AI Screening System
Objective: Investigate how JPMorgan Chase uses AI-driven hiring tools to screen financial analysts.
Activity:
- Research how AI models assess candidates’ experience and risk-taking behavior.
- Analyze the implications for fairness, particularly regarding gender and racial biases.
- Compare JPMorgan’s AI system with traditional human-led hiring practices.
- To what extent would the use of the JPMorgan's AI screening tool impact the screening of financial analysts in Kampala?
