PERSPECTIVES

Gerrymandering the Résumé: Lights, Camera, Rejection!

Will the Real Applicant Please Stand Up?

By Sally Vazquez-Castellanos
Perspectives | October 29, 2026

An examination of artificial intelligence, employment discrimination, identity theft, and the curious intersection of network news, Hollywood, and the American job market.

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Lights, Camera, Rejection!

Somewhere between the evening news, the Hollywood casting couch of yesterday, and the modern employment algorithm, we appear to have developed a rather peculiar understanding of professional qualifications.

Once upon a time, a person submitted a résumé, interviewed with an employer, and received a decision. There were undoubtedly problems with that system, including discrimination, favoritism, and the occasional executive who believed that being related to the producer constituted a professional qualification.

Today, we have technology.

And technology, we are assured, is objective.

Of course, anyone who has watched a network-news broadcast, followed a celebrity scandal, or listened to a musical artist complain about the entertainment industry knows that the presentation of information can be almost as consequential as the information itself.

A little editing here. A carefully selected photograph there. Perhaps an unfortunate headline.

Suddenly, the person who entered the story is not necessarily the person who emerges from it.

Welcome to the modern employment market, where your résumé may receive more electronic processing than a Hollywood blockbuster, and the final production might bear remarkably little resemblance to the original script.

Humor me. Don’t gerrymander me. And, for heaven’s sake, don’t frame me.

Gerrymandering the Résumé

Gerrymandering is generally associated with the manipulation of electoral district boundaries to produce a political advantage.

In the employment context, the term offers an interesting metaphor.

Imagine an algorithmic screening process that divides applicants into categories based on employment history, educational credentials, geographic location, professional associations, inferred characteristics, or other information.

Some classifications may be entirely legitimate. Others may be inaccurate, poorly validated, or potentially discriminatory.

Now imagine that the system’s boundaries effectively determine which applicants receive meaningful consideration.

The applicant has not necessarily changed.

The boundaries have.

This is not electoral gerrymandering in the legal sense. It is a satirical comparison intended to illustrate how selection criteria can shape outcomes.

Under Title VII of the Civil Rights Act of 1964, a facially neutral employment practice may nevertheless violate federal law when it produces an unlawful disparate impact on a protected group and cannot be justified under the applicable statutory standards.

The Americans with Disabilities Act and the Age Discrimination in Employment Act provide additional protections.

California’s employment regulations expressly address automated-decision systems and discriminatory selection practices.

The legal question is not whether an algorithm draws boundaries. Every screening system applies criteria.

The question is whether those boundaries comply with the law.

And if the criteria were developed using inaccurate information, inappropriate proxies, or inadequately tested assumptions, the consequences deserve examination.

An applicant should not need a political redistricting expert to determine whether her résumé reached the hiring manager.

Network News: Breaking News, Nobody Read Your Résumé

Consider the familiar language of network television.

Breaking news.

Exclusive reporting.

Sources familiar with the matter.

The public receives a carefully organized account of an event, complete with graphics, commentary, and occasionally dramatic music.

Good journalism distinguishes verified facts from allegations, opinion, and speculation. Responsible employment systems should exercise comparable discipline when evaluating people.

Unfortunately, algorithmic systems can create an appearance of precision even when their underlying information is incomplete.

A numerical score may look authoritative.

A ranking may appear objective.

An automated recommendation may seem definitive.

But what happens when the underlying data are wrong?

Suppose an applicant’s employment history has been incorrectly attributed to another person. Perhaps a background report contains an inaccurate credential, a mistaken identity match, or an outdated record.

The employer may receive an assessment that appears technologically sophisticated but rests on unreliable information.

In the language of television news, the problem is not necessarily the anchor.

It may be the source.

Or the editing.

Or the fact-checking that never occurred.

Before broadcasting a conclusion about an applicant, someone ought to verify the story.

Hollywood Casting: The Role Has Already Been Filled

Hollywood provides another useful comparison.

Actors audition for roles. Producers evaluate talent. Casting directors consider experience, availability, contractual requirements, and the needs of a production.

Sometimes the decision is subjective.

Sometimes a recognizable name carries commercial value.

And sometimes an actor discovers that the role was effectively spoken for before the audition began.

Now consider an employment applicant who submits dozens of applications through an online platform.

She meets the advertised qualifications. Her professional experience appears relevant. Nevertheless, she receives automated rejections without an interview.

Perhaps the employer selected stronger candidates.

Perhaps the position was withdrawn.

Perhaps an applicant-tracking system applied legitimate screening criteria.

Or perhaps inaccurate information or an unlawful selection practice affected the result.

An attorney cannot responsibly select among those explanations without evidence.

But the applicant should not be discouraged from asking how the decision was made.

After all, there is a difference between losing an audition and discovering that someone else’s headshot was attached to your résumé.

In Hollywood, they call it casting. In employment law, we call for evidence.

The Musical Arrangement: Will the Real Applicant Please Stand Up?

Musical artists have spent generations exploring questions of identity, authenticity, public image, and creative control.

Eminem famously turned questions of identity and imitation into The Real Slim Shady.

Madonna built a career around reinvention and control of her public persona.

Taylor Swift’s highly publicized efforts to regain control over her musical recordings illustrate a different but related concern: the importance of contractual rights and control over valuable creative assets.

These examples involve different legal interests. None establishes that an employment platform has misused applicant information.

Nevertheless, they offer a useful cultural framework.

In a digital economy, individuals increasingly depend on systems that organize, reproduce, evaluate, and distribute information about them.

An applicant’s professional identity may be represented through a résumé, online profile, employment history, assessment, or third-party report.

The individual may have created some of that information. Other information may have been assembled or inferred by third parties.

When inaccuracies enter the process, identifying the source and obtaining a correction can become difficult.

The practical question is simple:

Will the real applicant please stand up—or has the system already cast someone else in her role?

The CFPB Enters the Production

The Consumer Financial Protection Bureau addressed an important part of this problem in its 2024 Circular 2024-06, Background Dossiers and Algorithmic Scores for Hiring, Promotion, and Other Employment Decisions.

The circular examined circumstances in which third-party employment assessments and algorithmic scores may fall within the Fair Credit Reporting Act.

Its underlying concern was that a company cannot necessarily avoid statutory obligations simply by describing an employment-related consumer report as analytics, artificial intelligence, or another technological service.

There is an important qualification.

The CFPB withdrew Circular 2024-06 on May 12, 2025. It should therefore be identified as withdrawn historical guidance, not current operative agency guidance.

The withdrawal did not repeal the FCRA.

The statute continues to govern covered consumer reporting agencies, consumer reports, and employment-related uses of those reports.

Whether a particular vendor or service falls within the FCRA depends on the statutory definitions and the actual business practices involved.

A professional networking platform is not automatically a consumer reporting agency merely because employers and applicants use it.

Similarly, an employer’s internal algorithm does not automatically produce a consumer report.

The investigation must identify the entities, data flows, and purposes involved.

In other words, before suing the entire production company, counsel should determine who actually wrote the script.

LinkedIn, the Applicant, and the Mystery of the Missing Interview

Consider a hypothetical applicant using LinkedIn to pursue employment opportunities.

She is professionally qualified, maintains an updated profile, and submits applications for positions consistent with her experience.

Nevertheless, she receives no interviews.

She becomes concerned about the integrity of her information and retains employment counsel.

Where should the investigation begin?

Not with an accusation.

With documentation.

Counsel should obtain the relevant job postings, application confirmations, submitted résumés, rejection notices, communications, and any available information concerning third-party screening.

The attorney should determine whether the applicant submitted materials directly through LinkedIn or was redirected to an employer’s separate applicant-tracking system.

That distinction may establish which company possessed the information and which entity controlled the employment decision.

Counsel should also investigate whether the employer used a covered consumer report or an automated assessment and, if so, identify the provider and applicable legal obligations.

Where the FCRA applies, relevant provisions include:

• 15 U.S.C. § 1681a: Definitions governing consumer reports and consumer reporting agencies.
• 15 U.S.C. § 1681b(b): Employment-related disclosure, authorization, and pre-adverse-action requirements.
• 15 U.S.C. § 1681e(b): Reasonable procedures to assure maximum possible accuracy.
• 15 U.S.C. § 1681g: Consumer file disclosures, subject to statutory limitations.
• 15 U.S.C. § 1681i: Reinvestigation of disputed information.
• 15 U.S.C. § 1681m: Applicable adverse-action notice requirements.

Counsel must distinguish the applicant’s statutory rights from voluntary requests and information obtainable only through formal legal process.

The objective is to determine what actually happened.

Not to write a screenplay about what might have happened.

Framing the Applicant: A Legal Problem, Not a Hollywood Plot

The word framing deserves particular attention.

In filmmaking, framing determines what the audience sees.

A camera angle can emphasize one person while excluding another. Editing can change the apparent sequence or significance of events.

In law, deliberately fabricating or misrepresenting evidence to implicate someone in wrongdoing presents a far more serious problem.

These concepts should not be confused.

An algorithm that inaccurately categorizes an applicant has not necessarily participated in deliberate framing.

An unfavorable search result does not establish impersonation.

A rejected application does not prove identity theft.

But where credible evidence indicates that an account was compromised, a person’s identity was misused, or false information was supplied to an employer, counsel should investigate those matters separately.

The investigation may implicate consumer protection, employment law, privacy law, computer crime statutes, or traditional tort principles, depending on the evidence.

Potentially relevant California laws include the California Consumer Privacy Act, the California Comprehensive Computer Data Access and Fraud Act, and applicable identity-theft provisions.

None automatically applies merely because an applicant suspects technological interference.

The evidentiary distinction matters.

A good attorney investigates the facts before deciding whether the case belongs in a courtroom, a regulatory complaint, or the fiction department.

California and New York: Two Different Productions

California and New York have adopted important but distinct approaches to automated employment decision-making.

California’s Civil Rights Council regulations, effective October 1, 2025, expressly address automated-decision systems in employment and clarify the application of existing antidiscrimination principles.

These regulations address matters including discriminatory practices and record retention.

They do not create a universal right to inspect every employer’s proprietary algorithm.

New York City adopted Local Law 144, which imposes specified bias-audit, publication, and notice requirements on employers and employment agencies using covered automated employment decision tools.

A bias audit is not an automatic finding of compliance with all applicable civil-rights laws.

Nor does a statistical disparity, standing alone, establish every element of a discrimination claim.

The analysis requires attention to the particular employment practice, affected population, applicable legal standard, and available evidence.

Both jurisdictions illustrate a larger regulatory challenge.

Technology may change the mechanics of selection.

It does not eliminate the legal responsibilities of employers.

The Red Carpet for Bad Data

Imagine a Hollywood awards ceremony devoted entirely to bad information.

The nominees include:

Best Supporting Error: An outdated employment record that follows an applicant for years.

Outstanding Achievement in Misidentification: A background report that confuses two individuals.

Best Original Algorithm: A screening model that nobody responsible for the hiring decision can adequately explain.

Best Editing: An assessment that omits relevant professional qualifications.

Lifetime Achievement in Bureaucracy: A rejection email informing the applicant that the employer was impressed by her qualifications but has decided to pursue other candidates.

The audience applauds.

The applicant remains unemployed.

Of course, satire is not evidence of unlawful conduct. These examples illustrate potential failures, not findings against any particular employer, platform, or vendor.

Still, the underlying questions deserve serious consideration.

Who supplied the data?

Who verified its accuracy?

Who established the screening criteria?

Was the assessment appropriate for the position?

Did a human decision-maker meaningfully review the result?

And when a mistake was identified, who had authority to correct it?

A system that cannot answer those questions may have an accountability problem, even when a particular legal violation has not been established.

Identity Theft Is Not a Casting Choice

Where an applicant has evidence of identity theft or unauthorized account access, the appropriate response begins with preservation and security.

Relevant records may include login histories, account notifications, unauthorized changes, suspicious communications, and documentation of incorrect personal information.

The Federal Trade Commission’s IdentityTheft.gov resources provide a reporting and recovery framework.

An attorney should also consider whether inaccurate information has been furnished to a covered consumer reporting agency and whether statutory dispute procedures apply.

Importantly, an account compromise and an employment rejection are separate events unless evidence establishes a connection.

That connection should be investigated rather than presumed.

For an applicant concerned about both identity theft and employment discrimination, maintaining separate factual chronologies can help counsel evaluate each potential claim.

The objective is not to produce the most dramatic narrative.

It is to establish the most accurate one.

The Final Cut: Who Controls the Narrative?

The broader concern extends beyond employment.

Modern technology allows information about individuals to be collected, classified, interpreted, and redistributed at extraordinary speed.

News organizations shape public narratives through editorial decisions.

Entertainment companies influence cultural perceptions through storytelling.

Musical artists negotiate control over their recordings, images, performances, and creative identities.

Employers increasingly rely on digital systems to evaluate professional qualifications.

These industries operate under different legal frameworks, but they share a fundamental responsibility to consider the accuracy, legitimacy, and consequences of their information practices.

The analogy becomes especially relevant when artificial intelligence is used to generate inferences about individuals.

An inference is not necessarily a fact.

A prediction is not necessarily an accurate description.

And a computer-generated assessment is not automatically a lawful employment decision.

For employment attorneys, the challenge is to identify the actual decision-making process and determine whether it complies with applicable law.

For regulators, the challenge is to ensure that existing protections remain meaningful when decisions are increasingly mediated by technology.

For applicants, the challenge is often more immediate.

They want to know whether their qualifications received fair consideration.

And whether the information used to evaluate them was accurate.

Closing Credits: Don’t Gerrymander Me, Don’t Frame Me

I have spent enough time around law, entertainment, and technology to appreciate the importance of a good story.

But there is a difference between storytelling and evidence.

There is also a difference between creative license and legal authority.

A news anchor does not acquire the right to invent facts merely because the broadcast is compelling.

A film producer does not acquire unlimited rights to someone’s identity merely because the storyline is entertaining.

A musical artist’s public persona does not place every aspect of that individual’s private life into the public domain.

And an employer does not escape civil-rights obligations simply because an algorithm participates in the hiring process.

Artificial intelligence may be capable of extraordinary things.

It can organize information, recognize patterns, and assist with complex decisions.

It can also reproduce errors, amplify poorly designed criteria, and create an appearance of certainty where meaningful scrutiny is needed.

That is why documentation, validation, and accountability matter.

The future of employment should not resemble an elaborate Hollywood production in which the applicant is simultaneously the star, the understudy, and the person left on the cutting-room floor.

Nor should professional opportunities depend on an invisible redistricting exercise that nobody is prepared to explain.

As for me, I would prefer a little less theatrical editing and a little more due process where the law requires it.

A little less speculation.

A little more evidence.

And perhaps fewer automated rejection notices that sound as though they were written by a publicist managing a celebrity breakup.

Humor me. Don’t gerrymander me. Don’t frame me.

And if the real applicant is still standing somewhere outside the casting office, perhaps someone could finally open the door.

That’s a wrap.

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Sources and Legal Authorities

Federal Law

1. Fair Credit Reporting Act, 15 U.S.C. §§ 1681–1681x.
2. Civil Rights Act of 1964, tit. VII, 42 U.S.C. § 2000e-2.
3. Americans with Disabilities Act of 1990, 42 U.S.C. § 12112.
4. Age Discrimination in Employment Act of 1967, 29 U.S.C. § 623.
5. Consumer Financial Protection Bureau, Background Dossiers and Algorithmic Scores for Hiring, Promotion, and Other Employment Decisions, Circular 2024-06 (Oct. 24, 2024) (withdrawn May 12, 2025).
6. U.S. Department of Justice, Civil Rights Division, Algorithms, Artificial Intelligence, and Disability Discrimination in Hiring (May 12, 2022).
7. Federal Trade Commission & Equal Employment Opportunity Commission, Background Checks: What Employers Need to Know.
8. Federal Trade Commission, IdentityTheft.gov.

California

9. California Fair Employment and Housing Act, Cal. Gov’t Code §§ 12900–12996.
10. California Civil Rights Council, Employment Regulations Addressing Artificial Intelligence and Automated-Decision Systems (effective Oct. 1, 2025).
11. California Consumer Privacy Act of 2018, Cal. Civ. Code §§ 1798.100–1798.199.100.
12. California Comprehensive Computer Data Access and Fraud Act, Cal. Penal Code § 502.
13. Cal. Penal Code § 530.5 (identity theft).

New York City

14. N.Y.C. Admin. Code §§ 20-870–20-874 (Automated Employment Decision Tools).
15. New York City Department of Consumer and Worker Protection, Automated Employment Decision Tools: Frequently Asked Questions.

Cultural References

16. Eminem, The Real Slim Shady, on The Marshall Mathers LP (Aftermath Entertainment & Interscope Records 2000).
17. Madonna, selected recordings and public performances, referenced as cultural examples of artistic reinvention and public-image management.
18. Taylor Swift, public rerecording and master-recording ownership initiatives, referenced as examples of creative ownership and contractual rights.

Cultural references are used for commentary, satire, and illustration. They do not suggest that any named artist, news organization, or entertainment company participated in the hypothetical employment practices discussed.

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Legal Disclaimer

This article is provided for general educational, informational, and commentary purposes only. It does not constitute legal advice or create an attorney-client relationship.

References to employment discrimination, automated decision-making, identity theft, computer intrusion, and other potentially unlawful conduct are intended to illustrate legal issues that may arise under particular factual circumstances.

Nothing in this article establishes that LinkedIn, an employer, a technology provider, a news organization, an entertainment company, or any identifiable individual engaged in unlawful conduct.

Readers should consult qualified legal counsel regarding their particular circumstances, applicable statutes, administrative procedures, and filing deadlines.

ChatGPT and Artificial Intelligence Disclaimer

This article was developed with assistance from ChatGPT, a generative artificial intelligence system, and incorporates the author’s commentary, legal analysis, editorial perspective, and satirical observations.

Generative AI may produce inaccurate, incomplete, or outdated information. Legal authorities and factual assertions should be independently verified before professional reliance or publication.

The use of artificial intelligence in developing this article does not constitute an endorsement of automated employment decisions or a waiver of the author’s intellectual property, privacy, or other applicable legal rights.

Cognitive Liberty and Personal Autonomy Disclaimer

Perspectives recognizes cognitive liberty, personal autonomy, freedom of thought, and individual dignity as important considerations in the development and regulation of emerging technologies.

The author supports responsible technological innovation consistent with constitutional protections, applicable privacy and civil-rights laws, and principles of informed consent and individual autonomy.

Nothing in this publication constitutes consent to unauthorized psychological profiling, intrusive surveillance, impersonation, manipulation, or interference with the author’s or any reader’s personal, professional, or intellectual activities.

This statement expresses the author’s position concerning cognitive liberty and does not independently establish a legal violation or create rights beyond those recognized under applicable law.

Hacker and Unauthorized-Access Disclaimer

Humor me. Don’t hack me.

Publication of this article does not authorize any individual, organization, investigator, technology provider, or other third party to access, monitor, intercept, alter, impersonate, or interfere with the author’s or any reader’s electronic devices, accounts, communications, professional credentials, employment applications, or personal information.

Unauthorized access, identity theft, unlawful interception, and other prohibited conduct may give rise to civil or criminal liability under applicable federal and state law.

Nothing in this article authorizes retaliation, harassment, unauthorized security testing, or interference with any person or organization.

References to hacking, framing, impersonation, and technological manipulation are presented as legal and investigative concerns, not as findings that any particular person or entity committed those acts.

© 2026 Sally Vazquez-Castellanos | Perspectives. All rights reserved.

Editorial note

The revision gives the article three connected satirical themes: gerrymandering as manipulation of selection boundaries, framing as the distortion of an individual’s representation, and Hollywood casting as a metaphor for opaque employment decisions.

The references to network news, Eminem, Madonna, and Taylor Swift provide cultural texture without attributing misconduct to those individuals or to particular media organizations.

For publication, I recommend retaining the legal distinction between documented identity theft, potentially discriminatory screening, and an ordinary rejection. That distinction makes the satire more effective and the legal commentary more defensible.