The Lift Line
No one is sacked. Ratings fall, incentives stop, the app locks the id. Removal without a remover is the gig economy’s founding trick.
Why This Editorial Matters for Your Exam
Gig economy questions are usually answered with two memorised props: the NITI Aayog projection and the Code on Social Security definition. Both are necessary; neither is an argument.
This piece gives you the argument. Its opening is a reported scene, an exhausted mehndi artist at the author’s own door, afraid of a bad rating, declining dinner because company policy forbids it, and the analysis converts that scene into a structural claim: the algorithm has replaced the employer, and the law only knows how to regulate employers. That reframing, employment law built for an identifiable employer meeting a labour market run by unaccountable software, is the analytical core that lifts a GS2 social justice answer or a GS3 employment answer above the standard recitation. The piece also gives you the federalism hook, Rajasthan legislating first, and the comparative hook, Europe.
Background and Context
The author and the scene. Shashi Shekhar, editor-in-chief of Hindustan, opens with a henna artist booked through an app arriving two hours late before Rakshabandhan: clients ran late all day, he could not object because a complaint or a bad rating could get him blocked, and his next booking was 8.30 the following morning. His own summary: in the village he earned less but had respect; now he has become a machine.
The numbers carried in the piece. On NITI Aayog’s count there were 77 lakh gig workers in 2021; the workforce has grown 55 per cent in four years; NITI estimates it will reach 2.3 crore, about 6.7 per cent of the non-agricultural workforce, within the next four years. Nearly 23 per cent is concentrated in the National Capital Region. 27 per cent of gig workers have faced accidents. Festive-season hiring of 2.5 to 3 lakh workers, an 8 to 15 per cent increase, was being reported the same week.
The legal landscape, for context. The Code on Social Security, 2020 defines gig and platform workers for the first time in Indian law and provides for a social security fund with aggregator contributions of 1 to 2 per cent of turnover, but awaits full operationalisation. Rajasthan’s Platform Based Gig Workers (Registration and Welfare) Act, 2023, the country’s first state law, creates registration, a welfare board and a cess-funded welfare fund; the piece points to Rajasthan by name as having shown the way. The European Union’s Platform Work Directive, 2024 is the piece’s other benchmark: “tough laws and regulations to safeguard gig workers’ economic and social security, like Europe has”.
The Analysis
Use and throw, stated as a principle. Companies hiring gig workers, the piece argues, operate on “use and throw”. The festive surge makes the mechanism visible: hiring expands 8 to 15 per cent for the season, and when demand subsides nobody is sacked; incentives are discontinued and apps block ids using technical jargon. The moment of dismissal, the event on which the whole of labour law hangs, never occurs.
The illusion of formalisation. Sparkling uniforms, clean bikes and direct bank transfers look like formalisation from a distance. The piece’s claim is that they are its illusion: the personal cord between employer and employee has been severed, and labour management has been hijacked by opaque algorithms. Registration without rights is legibility, not protection.
The body as the shock absorber. With 27 per cent facing accidents, treatment long and costly, and a prolonged absence from the app risking a lockout, the worker’s rational choice is to ride injured and exhausted. The app’s punctuality demands sit on top of traffic and waterlogging the worker cannot control. Risk has been transferred downward to the person least able to carry it.
Two second-order effects, and they are the piece’s most original claims. First, gig work hides unemployment: degree-holders take platform work rather than carry the label of being unemployed, flattering the statistics. Second, it is draining agriculture and small industry of workers, because the young will not do small jobs near home and migrate instead to inhuman conditions in big cities. Both effects run through status and visibility, not wages, which is what makes them hard to see in the data.
The closing standard. A progressive society runs on policies and regulations, not on algorithms. Rajasthan has shown the way; the Centre and the other states must carry the baton.
Data and Institutions Vault
Prelims-grade facts:
The workforce:
- NITI Aayog counted about 77 lakh gig workers in India in 2021.
- The gig workforce has grown about 55 per cent in the four years since, per the piece.
- NITI Aayog projects about 2.3 crore gig workers, near 6.7 per cent of the non-agricultural workforce.
- Nearly 23 per cent of India’s gig workforce is concentrated in the National Capital Region.
- NITI Aayog data cited in the piece: 27 per cent of gig workers have faced accidents.
- Festive-season hiring was projected at 2.5 to 3 lakh workers, an 8 to 15 per cent increase.
The legal architecture:
- The Code on Social Security, 2020 gave gig and platform workers their first statutory definitions.
- The Code provides for aggregator contributions of 1 to 2 per cent of turnover to a social security fund.
- Rajasthan’s Platform Based Gig Workers (Registration and Welfare) Act, 2023 was India’s first state gig-worker law.
- The Rajasthan Act creates worker registration, a welfare board and a cess-funded welfare fund.
- e-Shram is the national registration portal for unorganised workers, under the Ministry of Labour and Employment.
- The EU’s Platform Work Directive, 2024 creates a presumption of employment and rights over algorithmic management.
⚠️ Watch the trap: A gig worker and a platform worker are related but not identical categories under the Code on Social Security, 2020. A gig worker is anyone earning outside a traditional employer-employee relationship; a platform worker is the subset working through an online platform. Every platform worker is a gig worker; the reverse is not true, and Prelims options exploit exactly this nesting.
The Debate
Regulate hard. Removal by algorithm with no appeal is a due-process vacuum no other part of the labour market would tolerate. Accident rates above a quarter of the workforce, with cover absent and recovery unpaid, price human injury into delivery times. And a model that both hides unemployment and drains local economies is imposing social costs it does not pay for. Rajasthan and the EU prove regulation is drafttable, not utopian.
Regulate lightly. Platforms created income at a speed no factory model matched, for migrants the old informal economy exploited invisibly and worse. Entry is instant, hours are flexible, payment is direct and traceable, which is more formal than the labour chowk it replaced. European-style employment presumptions raise platform costs and shrink the jobs being protected; a young labour market frozen into permanent-employment templates would serve incumbents, not workers.
Where the truth likely sits. The binary is false: the choice is not between employment law and nothing. The instruments that fit gig work are registration, portable aggregator-funded benefits, insurance tied to the work’s actual risks, and due process over the algorithm, none of which requires converting every rider into a permanent employee. That is roughly the layered position India’s framework is groping toward, a central Code for social security, state welfare boards for delivery, and the piece’s contribution is the demand that it move from statute to operation.
How to Think About This
When technology restructures a labour relationship, ask three questions in order.
Who decides, and can the decision be seen? In gig work, assignment, rating, pay and removal are algorithmic. The first regulatory demand is therefore transparency and human review, before any welfare economics.
Where did the risk go? Follow injury, income volatility and idle time. In platform work all three moved from the firm to the worker. Social security design is the routing of that risk back, via aggregator contributions, insurance and floors.
What does the arrangement hide? Here, unemployment among the educated and the drain from agriculture and small industry. Second-order effects decide whether a labour-market innovation is absorbing slack or disguising it.
The same three questions organise answers on AI in hiring, on contractualisation in manufacturing, and on the platformisation of care work.
Diagram-in-Words
Takeaway Box
Lift line: No one is sacked; ratings fall, incentives stop, the app locks the id. Removal without a remover.
Prelims hooks: NITI Aayog: 77 lakh gig workers in 2021, projection near 2.3 crore and 6.7 per cent of the non-agricultural workforce, 23 per cent in the NCR, 27 per cent facing accidents; Code on Social Security, 2020 defines gig and platform workers, aggregator contribution 1 to 2 per cent of turnover; Rajasthan Platform Based Gig Workers Act, 2023 the first state law; e-Shram under the Ministry of Labour and Employment; EU Platform Work Directive, 2024.
Mains hook: The algorithm replaced the employer and labour law only knows employers: no dismissal event, no accountable decision-maker, risk transferred to the worker. Correctives: operationalise the Code, aggregator-funded welfare boards on the Rajasthan model, explainable and appealable algorithmic decisions, portable benefits.
Interview hook: If a deactivation is produced by a rating model no human reviewed, who is accountable for an unfair removal, and what would an appeal even look like?
Sources: Hindustan Times, NITI Aayog, Ministry of Labour and Employment
Source: The Algorithm at the Society Gate: What Gig Work Has Done to Labour — Ujiyari.com | Free UPSC & State PCS Editorial Analysis
