Are gig workers a part of India’s labour data?

Context & Why in News

• Union Budget 2025 formally recognised gig & platform workers and extended some welfare benefits.
• But the PLFS 2025 (Periodic Labour Force Survey) fails to statistically identify gig/platform workers, undermining data-driven policymaking.

Relevance : GS 2(Governance , Labour Welfare)

Gaps in Labour Classification

• Gig workers defined in the Code on Social Security, 2020, but ambiguously.
• PLFS still classifies them under ‘self-employed’, ‘casual labour’, or ‘own-account worker’ — masking their unique conditions.
• Algorithmic work, multi-platform juggling, no job security, and app-based tasking ≠ traditional employment.

Consequences of Statistical Invisibility

• Gig workers lack social security representation despite legal recognition.
• Policy efforts (e-Shram portal, AB-PMJAY, digital ID cards) lack strong data support.
• Welfare boards rely on PLFS data — flawed classification → exclusionary access to schemes.

Why Gig Work Is Different

• No stable contract or control over work → cannot be equated with self-employment.
• Shaped by algorithms, task-based pay, platform switching.
• Employment volatility, digital reach dependence, and zero benefits not reflected in PLFS.

Policy & Data Disconnect

• MoSPI response in Rajya Sabha: Gig workers are included under ‘economic activity’ — but not separately identified.
• PLFS 2025 changes: More rural representation, monthly estimates — but no changes to capture gig-specific variables.

Way Forward

• Update PLFS classification codes to include gig/platform categories.
• Introduce special survey modules to assess:
  • Number of platforms worked on
  • Nature of algorithmic control
  • Work hours, contracts, pay volatility
• Institutionalise National Social Security Fund (Clause 141) and Welfare Boards (Section 6 of Code) with gig-specific inputs.

Relevant Data Points

• 23.5 million gig workers projected by 2029–30 (NITI Aayog 2022).
• Despite inclusion in Code on Social Security, gig workers remain invisible in core labour statistics.

Additional Dimensions

1. Legal and Policy Recognition

• Code on Social Security, 2020: Defines gig and platform workers but lacks operational clarity.
• No corresponding rules/guidelines yet framed to implement social security benefits.

2. Statistical Gaps

• PLFS 2025: Fails to create a distinct category for gig workers.
• Gig workers merged into ‘self-employed’, ‘casual labour’, causing data invisibility.

3. Economic and Social Security Issues

• No written contracts, volatile incomes, no maternity benefits, or insurance by default.
• e-Shram portal (~30 Cr+ registrations) lacks granularity for gig-specific insights.

4. Algorithmic Control and Digital Governance

• Gig work is governed by platform algorithms, which determine work allocation, pay, and reviews — often without transparency.
• Raises issues of digital rights, data privacy, and worker surveillance.

5. Labour Rights and Unionisation

• Gig workers are not covered under Trade Union Act, limiting collective bargaining.
• Attempts at forming informal unions (e.g., Swiggy delivery agents’ strikes).

6. Gender and Gig Economy

• Low female participation in platform work due to safety, tech access, and lack of flexibility.
• Women gig workers face wage gaps and higher care burden.

7. International Comparisons

• EU passed legislation mandating algorithmic transparency for platform workers.
• UK Supreme Court (2021): Ruled Uber drivers are ‘workers’, not self-employed.

Additional Data and Facts:

Other angles to explore:

• Urbanisation and gig clustering (metro-centric platforms).
• Impact of AI & automation on gig jobs (task elimination, micro-tasking).
• Sustainability concerns — frequent travel by delivery/rideshare gig workers.
• Social audits & grievance redressal in gig platforms — almost non-existent.
• Need for a Unified Labour Market Framework inclusive of informal and gig workers.