7 WAYS TO COMBAT AGE DISCRIMINATION IN HIRING FOR JOB SEARCH

Is Ageism in Hiring Prevalent?

A study from the National Bureau of Economic Research found clear differences in job offer rates based on when a candidate’s age is revealed. When age was not disclosed during early interviews, younger and older candidates had the same chance of receiving job offers. Once age became known, those chances shifted.

AARP reports that one in five adults over age 40 (21%) has experienced discrimination at work. Age bias is often subtle, which makes it difficult to recognize and even harder to address. In this blog, we examine how age bias shows up in hiring, why it exists, and what job seekers can do to limit its impact during a job search.

WHAT ARE YOUR AGE DISCRIMINATION PROTECTIONS?

The Age Discrimination in Employment Act (ADEA) is a federal law that protects workers age 40 and older from discrimination. It makes it illegal for employers to treat employees unfairly because of age. The ADEA applies to hiring, firing, promotions, pay, benefits, and job training.

Key provisions of the ADEA

Examples of Prohibited Behavior

• Not hiring a qualified applicant because they are seen as “too old” for the role.

• Laying off older workers while keeping younger employees with less experience or fewer skills.

• Paying older workers less than younger workers for doing the same job.

• Promoting younger employees instead of older workers who are equally or more qualified.

• Denying training or growth opportunities to older workers.

EEOC Statistics in 2022

• Age discrimination in hiring is the second most common form of employment discrimination, behind sex discrimination.

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• The Equal Employment Opportunity Commission (EEOC) received 14,183 age discrimination complaints related to hiring.

• For these cases, the median settlement amount was $46,698.

EXAMPLE CASES OF AGE BIAS IN HIRING

• EEOC v. UnitedHealth Group, Inc. (2023)UnitedHealth Group discriminated against older applicants applying for customer service roles. The company used a hiring algorithm that screened out older workers at higher rates. UHG did not properly test or validate the tool. The case settled for $2.5 million, paid to affected applicants.

• EEOC v. IBM Corporation (2023)IBM discriminated against older applicants seeking software engineer roles. The EEOC found that IBM relied on a hiring algorithm that had not been validated and disproportionately rejected older candidates. IBM settled the case for $4 million and agreed to change its hiring practices.

• EEOC v. Accenture LLP (2023)Accenture discriminated against older applicants for consulting positions by using an unvalidated hiring algorithm. The settlement provided $3.5 million to impacted applicants, and Accenture was required to update its hiring process.

WHAT IS A HIRING ALGORITHM?

A hiring algorithm is a data-driven method used to review job applicants. It evaluates candidates using set criteria to help predict job performance. The goal is to make hiring faster and more consistent by identifying patterns in applicant data.

Each company may use a different algorithm, which can lead to differences in how candidates are evaluated. Smaller companies may apply these criteria manually, while larger companies often use AI-based tools to support the process.

HOW IS THE HIRING ALGORITHM APPLIED?

Hiring algorithms vary by company and can be used at different stages of the hiring process. The data used to train and run these algorithms is usually stored in one central system, such as an Applicant Tracking System (ATS) or a separate hiring database.

Data Collection and Preparation - The algorithm is trained using data from past job applications. This data may include skills, work experience, and job performance. Before training begins, the data is reviewed and cleaned to make sure it is accurate and consistent.

Algorithm Training - The algorithm analyzes the prepared data to find patterns between applicant traits and job performance. During this step, the system adjusts its settings to improve how accurately it predicts success in the role.

Resume and Application Screening - When a new application is submitted, the algorithm scans the resume and application for key details such as skills, experience, and education. This information is then used to generate a score or ranking for each applicant.

Interview Analysis -In some cases, hiring algorithms review interview notes, transcripts, or video recordings. These tools may evaluate communication skills, problem-solving ability, and overall fit for the role.

Hiring Decisions - Hiring algorithms are meant to support hiring decisions, not replace them. Human review is essential to ensure fairness, reduce bias, and comply with anti-discrimination laws.

For example, Microsoft may require a coding test for a software developer role, while Google may use a different evaluation approach.

A Sample Hiring Algorithm

• Information from resumes, LinkedIn profiles, and social media is used to gather details such as education, degrees earned, work history, skills, recommendations, endorsements, and professional groups. Social media may also reveal a candidate’s online presence, interests, or possible concerns.

• Each piece of information is given a numerical score based on how well it matches the job requirements. For example, experience at Google may result in a higher score than experience at Salesforce.

  The system calculates a total score for each applicant by adding these individual scores together.

  Applicants are then ranked from highest to lowest based on their total score, with the top-scoring candidates listed first.

HOW DOES AN ALGORITHM EVALUATE APPLICANTS FAIRLY?

Here are steps to help make sure algorithm results are fair and free of bias:

• Data Sources – The data used to train and run hiring algorithms should be unbiased and represent a diverse group of applicants.

• Data Predictability – The data must be objective and a reliable predictor of job success. For example, rating someone from 1 to 5 on attractiveness should not be used.

• Human Oversight – Humans must be part of the hiring process. Decisions should consider fairness, equity, legal rules, cultural fit, and soft skills.

• Continuous Monitoring and Improvement – Companies should regularly check and adjust their hiring algorithms to keep results consistent and unbiased.

Most companies work hard to hire qualified candidates fairly. By combining validated algorithms with human judgment, they can make better and more defensible hiring choices.

Can A Single Person be Subject to Age Discrimination in Hiring?

If two candidates have similar experience, as rated by both the company’s algorithm and the interviewer, either candidate—older or younger than 40—can be a valid choice. Applicants usually do not know the exact reason they did not get the job. Because of this, proving individual age discrimination is often difficult.

Examples of inappropriate interview behavior include:

• The interviewer makes age-related comments during the interview or hiring process.

• The interviewer asks questions about the candidate’s age tied to job requirements.

• The company gives a reason for not hiring that is not believable.

• The interviewer assumes the candidate cannot meet the physical requirements of the job.

A CASE STUDY FOR A BIASED HIRING ALGORITHM BE BIASED?

In 2023, the EEOC found Accenture guilty of age discrimination in hiring consultants for these reasons:

• Lack of transparency – Accenture did not share the details of its hiring algorithm with the EEOC. This made it hard to see if the process was fair.

• Use of subjective criteria – The algorithm used factors like “cultural fit” and teamwork skills, which are harder to measure and can carry unconscious bias.

• Failure to validate the algorithm – Accenture did not test its algorithm to make sure it did not unfairly screen out older applicants.

• Lack of human oversight – The company relied too much on the algorithm without enough human checks to catch possible bias.

This case shows why hiring algorithms must be fair, transparent, and checked for bias. Job seekers should ask employers about how hiring decisions are made. Overuse of automated tools or requests for unrelated personal information can be warning signs.

SIGNS OF AGE DISCRIMINATION AND AGE BIAS

Most companies do not publicly share their hiring algorithm. The following are descriptions of how to spot age bias.

Job Posting

• Age Requirements – It is illegal to list an age requirement in a job ad unless it is a bona fide occupational qualification (BFOQ).

• Keywords – Watch for words or phrases that may favor younger applicants, like “recent graduates” or “energetic.” Too many of these can discourage older workers from applying.

• Emphasis on recent graduate roles – Frequent use of entry-level language suggesting younger candidates may be a subtle warning sign.

• Overemphasis on technologies – Candidates should meet the job’s tech requirements, but watch for excessive focus on tools unrelated to the role.

• Narrow salary range – Listing a very low or tight salary range can discourage older applicants, even if it is not illegal.

• Networking – Connect with current or former employees to understand company culture, treatment of older workers, and the overall age diversity in the workplace.

Application Process

• Asking for Date of Birth – Companies can ask for your date of birth, but they cannot use it to decide on hiring. About 50% of companies request this information.

• Requesting Graduation Year – Employers can ask when you graduated, but they cannot use it to make hiring decisions. Avoid giving your graduation year unless needed for onboarding. Some companies may verify degrees if required for the role.

• Family or Marital Status – Asking about your family or marital status is illegal.

• Social Media Profiles – Employers should not require social media accounts if the information could be used to judge your age or lifestyle.

• Company Culture – Research company websites, social media, and news articles to learn about their culture and values. Check for diversity initiatives and any past age discrimination (ADEA) violations before applying.

Interview Process

• Age-Related Comments – It is illegal for interviewers to comment on an applicant’s age, like saying someone looks too old or too young for the job. Watch for hints about age or experience. Prepare answers that focus on your skills and qualifications instead of your age.

• Stereotypical Assumptions – Assuming older applicants are less tech-savvy or cannot adapt to change is discriminatory.

• Retirement Plans – Asking about a candidate’s retirement plans is illegal.

• Physical Agility Tests – Tests that are not directly related to the job can unfairly disadvantage older applicants.

Hiring Decisions

• Favoring Younger Candidates – Choosing younger applicants over older candidates who are equally or more qualified can be discriminatory.

• Lack of Transparency – When employers do not clearly explain hiring decisions, it is harder for older applicants to know if age bias played a role, especially if younger candidates were chosen.

• Keeping Younger Employees During Layoffs – Laying off older workers while keeping younger employees with less experience or fewer qualifications can signal age discrimination.

CONCLUSION

Older workers looking for jobs can face age bias in ways that are obvious or subtle. Here are some strategies to help reduce its impact:

• Know Your Rights – Understand protections under the ADEA.

• Check Job Postings – Look for language that might favor younger candidates.

• Research Companies – Learn about employers before interviews and prepare for vague age-related questions. The Age Friendly Institute has lists of age-conscious companies.

• Update Your Resume and LinkedIn – Remove references that reveal your age and highlight current skills.

• Highlight Adaptability – Emphasize your willingness to learn and achievements in interviews. Avoid mentioning situations that reveal age.

• Do Salary Research – Check what you are worth as an experienced candidate. The Bureau of Labor Statistics government site is a good resource.

• Keep Skills Current – Identify gaps in technical skills and create a learning plan.

With awareness and preparation, older job seekers can navigate hiring more effectively, show their value, and improve their chances of success.

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About the Author:

Lisa Dupras is a LinkedIn Certified Expert and Certified Career Coach who helps tech professionals translate experience into recruiter-ready resumes, optimized LinkedIn profiles, and strategic next-step career moves. With 20+ years in HR and IT, she provides practical guidance rooted in real-world hiring and career strategy.