BEHAVIOURAL SEGREGATION OF EMPLOYEES BASED ON CONFLICT PREDICTION: LEGAL FRAMEWORK AND JUDICIAL ANALYSIS

1. INTRODUCTION

Behavioural segregation of employees based on conflict prediction refers to the practice of using artificial intelligence, behavioural analytics, personality assessments, workplace communication records and predictive algorithms to identify employees who are considered likely to create workplace disputes. Employers may use these predictions to separate employees into different teams, restrict professional interactions, deny leadership opportunities or isolate individuals perceived as potential sources of organisational conflict.

Although preventing workplace disputes is a legitimate managerial objective, predictive segregation raises serious legal concerns involving privacy, equality, discrimination, procedural fairness, freedom of association and employee dignity. An employee should not suffer adverse treatment merely because an algorithm predicts future disagreement or interpersonal incompatibility.

2. LEGAL FRAMEWORK GOVERNING BEHAVIOURAL SEGREGATION

A. CONSTITUTIONAL EQUALITY AND NON-ARBITRARINESS

In India, Articles 14 and 16 of the Constitution provide important protections against arbitrary treatment and discrimination, particularly in public employment. Predictive systems that disproportionately disadvantage employees because of caste, religion, gender, disability, trade-union participation or other protected characteristics may raise constitutional concerns.

B. PRIVACY AND PERSONAL DATA PROTECTION

Article 21 protects personal liberty and privacy. The Digital Personal Data Protection Act, 2023, where applicable, establishes obligations concerning the processing of digital personal data. Employers must consider lawful processing, applicable notice and consent requirements, security safeguards and statutory rights.

C. EMPLOYMENT AND INDUSTRIAL RELATIONS

The Industrial Disputes Act, 1947, and the Industrial Relations Code, 2020, subject to applicable commencement and transitional arrangements, provide relevant protections concerning industrial disputes, unfair labour practices and employment relationships. Segregation intended to discourage collective representation or suppress legitimate employee grievances may attract legal scrutiny.

3. MAJOR LEGAL RISKS

Discriminatory classification: Predictive systems may indirectly disadvantage employees belonging to protected or vulnerable groups.

Privacy intrusion: Analysing private communications, behavioural patterns and interpersonal relationships may exceed legitimate workplace monitoring.

Professional exclusion: Employees may lose promotions, collaborative assignments and leadership opportunities because of unverified predictions.

Retaliatory segregation: Employees raising complaints, reporting misconduct or participating in union activities may be classified as conflict-prone.

Procedural unfairness: Automated classifications without disclosure, explanation or an opportunity to challenge the assessment undermine natural justice.

Psychological harm: Isolation and reputational labelling can create hostile working conditions and damage professional dignity.

4. IMPORTANT JUDICIAL DECISIONS

1. K.S. Puttaswamy v. Union of India (2017) — DIRECT CONSTITUTIONAL PRINCIPLE

The Supreme Court recognised privacy as a fundamental right under Article 21. The judgment establishes constitutional principles relevant to intrusive employee surveillance and excessive behavioural profiling.

2. Maneka Gandhi v. Union of India (1978) — ANALOGOUS AUTHORITY

The Supreme Court established that state action affecting personal liberty must satisfy fairness, reasonableness and non-arbitrariness. These principles are relevant when public employers impose adverse consequences through predictive classifications.

3. E.P. Royappa v. State of Tamil Nadu (1974) — DIRECT EQUALITY PRINCIPLE

The Supreme Court connected arbitrariness with inequality under Article 14. Arbitrary segregation of public employees based on unsupported behavioural predictions may therefore invite constitutional scrutiny.

4. Air India v. Nergesh Meerza (1981) — ANALOGOUS AUTHORITY

The Supreme Court examined discriminatory and unreasonable service conditions affecting women employees. Its reasoning supports scrutiny of unequal employment classifications and arbitrary workplace policies.

5. Vishaka v. State of Rajasthan (1997) — ANALOGOUS AUTHORITY

The Supreme Court recognised the importance of workplace dignity and protection against sexual harassment. Behavioural segregation must not become a mechanism for victimising complainants or isolating employees who report misconduct.

6. Apparel Export Promotion Council v. A.K. Chopra (1999) — ANALOGOUS AUTHORITY

The Supreme Court emphasised workplace dignity and protection against sexual harassment. Employers must ensure that behavioural management practices do not undermine employee dignity or discourage legitimate complaints.

7. District Registrar and Collector v. Canara Bank (2005) — ANALOGOUS AUTHORITY

The Supreme Court examined privacy protections against intrusive access to personal records. Its reasoning is relevant when employers collect and analyse sensitive employee information without adequate legal justification.

5. EMPLOYER COMPLIANCE AND PREVENTIVE SAFEGUARDS

Organisations should adopt the following safeguards:

Establish a legitimate and documented purpose before implementing conflict-prediction systems.

Prohibit segregation based solely on algorithmic predictions.

Conduct discrimination and privacy impact assessments.

Provide employees with meaningful explanations of consequential classifications.

Introduce human review and accessible grievance procedures.

Protect whistleblowers and trade-union representatives against retaliatory profiling.

Restrict access to behavioural information and establish appropriate retention periods.

Conduct independent audits to identify inaccurate predictions and discriminatory outcomes.

6. CONCLUSION

Behavioural segregation based on conflict prediction creates a significant intersection between employment governance, algorithmic accountability, privacy and equality law. Although employers may legitimately prevent workplace conflicts, predictive classifications cannot justify arbitrary exclusion, discriminatory treatment or suppression of employee rights. Indian constitutional principles, employment legislation and judicial decisions collectively support fairness, dignity, proportionality and accountability. Consequently, behavioural prediction should assist responsible workplace management rather than become an instrument for isolating employees or punishing individuals for conflicts that have not actually occurred.