AI and the Future of Gig Work: Disruption, Transformation, and the Ethics of Innovation

1. Introduction

The gig economy has seen an exponential growth on the global stage, particularly in India with the expansion of digital platforms and service providers like Ola, Swiggy, Blinkit, Zepto, Zomato, Dunzo, Porter, Rapido, etc. which offer flexible on-demand solutions. The traditional employment model has given way to task-based, algorithmically managed work which is employable with increased flexibility, but often while skirting traditional labour protections. NITI Aayog estimates that the gig workforce will reach 2.35 crore by 2030.

Artificial intelligence (“AI”) is now deeply embedded into these platforms to manage workers, assign task-jobs, assess workers through ratings, optimise delivery routes (factoring in real time traffic, local events and weather), integrate dynamic pricing by predictive modelling, and even to predict worker behaviour and competencies. As AI integration becomes more central to the functioning of these apps, users benefit from faster matching between worker and client, streamlined logistic solutions, improving user experience, and an expansion of freelance opportunities (content creation, coding, digital marketing, etc.). This has left the market more competitive, while broadening access. The benefits of incorporating AI-based tools and solutions into digital platforms, are widely acknowledged – evidenced by the rapidly growing user base on both the demand and supply side. The challenges that AI bring to the gig economy, however, are insidious, often overlooked, and cause for serious concern. These include – opaque algorithmic control which control access to jobs, performance penalties with limited accountability/ oversight or avenues for grievance redressal, erosion of autonomy due to nudges from AI systems, pervasive surveillance, unregulated data collection and displacement of lower-skilled gig workers with the onboarding of wide-scale automation. 

This blog post aims to explore how AI is transforming gig work – albeit creating opportunities, but also deepening concerns around labour rights, privacy, and algorithmic control, and advocates for a more inclusive and ethical worker-centric way forward. 

Image 1          

              Image 2

Caption: Image 1 generated on ChatGPT with the prompt “Develop a picture to describe AI disrupting the gig economy” and Image 2 generated when further prompted to make it a “less negative or neutral” image. The juxtaposition of both AI-generated images is a jarring reminder of the duality perceived or commonly understood, with regards to AI and the gig economy. 

2. Invisible Bosses: How Algorithms Manage, Manipulate, and Marginalise 

Anyone interacting regularly in the digital world and shopping in the online marketplace, can attest to the integration of chatbots in almost every business, at every level. Similarly, increased automation has radically transformed logistics solutions, content moderation, and ride-hailing services. This is a result of the silent, and almost invisible replacement of  swathes of low income, semi-skilled staff and entry-level executives, who relied on such tasks for their livelihood. Further, the digital divide has now widened inequality within this ecosystem wherein highly skilled freelancers who are tech savvy and have digital access (to tools like ChatGPT, Midjourney, Canva, Jasper, etc.), have effectively replaced those with lower skill level, or those who lack the know-how or access to such technology, and the benefits they offer in terms of shortening project turnarounds and overall quality. This inequality of opportunity, is undeniably exacerbated by class, caste, and gender. 

Service providers on these platforms also suffer the insidious effects of the app-based nudges and decisions that are modelled on various algorithms.The app-platform dictates when, where, and how, work can be accessed, thus making the worker reliant on an opaque system that they do not fully comprehend. There is no human manager or boss - merely code. Gig workers complain of opaque automatically enforced penalties for declining jobs, lower visibility if they refuse late night tasks, lower ratings, or cancelled appointments/rides, without any room for challenge or recourse. What is couched as ‘incentives’ for empowerment – star ratings, level ups, penalties, and other gamified elements – are in fact optimising platform efficiency at the cost of worker autonomy. These methods of control are visible on platforms like Urban Company, Uber, Ola, etc. where dynamic and opaque metrics govern worker visibility, performance, and pricing on the app. The stakes are high – one bad review or a missed appointment, could mean a day without income, with no form of recourse. Workers on these platforms are noticing the erosion of any semblance of ‘choice’, with the algorithm auto-assigning tasks or jobs regardless of the worker’s willingness to take it up. Therefore, what was earlier considered ‘freedom’ for flexible work, has now declined to algorithmically compelled work. 

Such AI based pricing and performance models that leave the worker disempowered, and in a state of precarity, have triggered wide protests by workers both in the beauty and cleaning industry, as well as the cab and ride sharing market. Workers are developing collective forms of agency to navigate and strategically resist against algorithmic control. For instance, in various jurisdictions, in a bid to regain control, workers on ride sharing apps are finding ways to game the algorithm– by conducting scheduled en masse log outs to drive up surge pricing, turning off the app to avoid cumbersome rides without affecting their performance metrics, etc. Studies have shown that with such worker-led responses, the algorithmic management that was introduced for increased efficiency and cost-cutting might, in fact, be eating away at the platform’s own profit margins. In other words, systems designed to undermine worker autonomy, and developed without their consultation, are not just ethically flawed and morally in bad taste, but also might be bad for business. 

Beneath this algorithmic control, however, lies another silent erosion of worker rights – unchecked cultivation of personal data, pervasive surveillance, and absence of informed consent. Much like algorithms being the invisible bosses in this economy, data serves as the invisible currency that enables platforms to monitor, predict, and manipulate worker behaviour and decisions without transparency or accountability. 

3. Data as Discipline: how platforms harvest and control workers 

The almost-invasive proliferation of the smartphone, and integration of low-cost internet data in India, has not been accompanied by a corresponding  awareness of digital rights, or entitlements. This is further complicated by barriers of language, and literacy. As a result, smartphone users habitually find themselves accepting verbose and jargon-filled privacy policies – frequently without realising they are formally consenting to data collection, and without understanding what that ‘data’ includes. Location, biometric (face ID logins), app usage, internet activity, phone usage, etc. are constantly harvested for algorithmic modelling. 

For platform-based gig workers, this situation is even more intrusive. Many platforms demand camera and microphone access, enable full-time GPS tracking, and monitor behaviour under the guise of efficiency. Workers are rarely given a clear opt-in or opt-out, and have little to no transparency about what is collected or how it is used. This results in an insidious and pervasive form of AI-based surveillance with round-the-clock tracking of availability, delays, idle time – denuding the worker of their autonomy and dignity.

Based on the behavioural data collected, the platform promotes or demotes workers using the gamified elements with little clarity for the triggering incident or data, without offering any redressal mechanism. The lack of data portability (of ratings, etc.), or ability to contest evaluations or correct false records, leaves the worker completely dependent on the specific platform. In a way, such tracking (read: surveillance) is justified as a means of optimising for efficiency, performance and safety, but is in fact a mode of establishing labour discipline that guarantees unhindered productivity, through data-integrated supervision. 

The inequality in information and access, further entrenches the power imbalance between the app-platform, and worker, Data harvested is used to optimise the platform’s profits without accountability, designedly at the cost of the worker’s welfare and dignity. The Digital Personal Data Protection Act, 2023 (“DPDP”) and its draft rules - already the subject of critical scrutiny on various counts - does not sufficiently address platform accountability or require transparency in algorithmic decision. It further leaves gig workers woefully unprotected, as they remain outside of its scope by way of under-classification, as the Act fails to recognise platform workers as a special or vulnerable class, despite their unique data vulnerabilities. 

In the absence of robust legal frameworks – that protect gig workers, and their data rights by ensuring algorithmic transparency and access to redressal mechanisms – gig workers will continue to suffer, at the altar of the platform’s profit margins. 

4. Regulating AI in the gig economy – legal gaps and the road ahead

The text of the Code on Social Security 2020 (enacted, but not yet in force) recognises gig and platform workers for the first time. Provisions relating to AI governance, automated decision making, and algorithmic bias, however, are conspicuously absent. Without statutory requirement for explanation and appeal mechanisms, automated decisions will continue to be opaque and adversely affect the livelihood of app-based workers. 

While the DPDP Act 2023 attempts to govern data privacy, the legislative framework makes no special accommodation to mitigate the precarity of gig workers, who do not fall within the scope of ‘employees’. Even with regards to employees, the existing regulatory framework allows for non-consensual processing of personal data, “for the purposes of employment”  and towards “safeguarding the employer from loss and liability” [ref: s. 7(i) of the DPDP Act] as a legitimate use. This remains a broadly termed, vague end at best; wherein if data collected and processed can loosely can be connected to ‘employment’, and is in the interest of the employer’s commercial interest, the employee’s privacy concerns become secondary. Certain digital rights afforded to individuals unconditionally, are rendered unavailable to ‘employees’ under the DPDP Act [specifically the right of notification (Section 5), access (Section 11), correction and erasure (Section 12) over such personal data]. Thus, commentators have noted that even bringing gig workers within the scope of the DPDP as ‘employees’ would further imperil them by diminishing their informational control. Further, in the absence of regulatory standards against the perils of automated decision making (as mentioned in Part C of this blog piece), a new digital form of labour discipline has emerged through algorithmic control.

Faced with growing pressure both from civil society organisations, and worker collectives, the government has initiated attempts to address the precarity of gig workers; though not nearly enough. For instance, the 2025 Union Budget expanded the e-Shram registration to gig workers to enable access to health insurance. In 2023, in a pioneering move, the State of Rajasthan, enacted the Rajasthan Platform Based Gig Workers (Registration And Welfare) Act, 2023 to ensure social welfare protections are extended to gig workers. It proposes a unique Gig Welfare Board framework that facilitates worker representation and participation. Similarly, Karnataka proposed its Platform-Based Gig Workers (Social Security and Welfare) Bill in June 2024, which remains to be enacted. This Bill delineates the type of data that workers are entitled to seek, and specifically provides for transparency in data used for algorithmic purposes (such as worker categorisation, rating system, use of personal data) which must be disclosed to the worker, along with an explanation of how the algorithms affect their working conditions. While these are promising developments, the regulatory framework across India still lacks a clear classification of gig workers as ‘employees’ (rather than independent contractors), and fails to mandate mechanisms like algorithmic audits, leaving a gap in addressing the insidious manners in which technology is deepening precarity of gig workers.

Internationally, formal AI ethics codes for platforms are becoming the norm. The G7 countries (i.e., Canada, France, Germany, Italy, Japan, UK, US and the EU), for instance, have agreed on International Guiding Principles on AI and a Code of Conduct for developers. Unlike India, various countries also have national AI strategies and frameworks to guide ethical considerations. Reportedly, the Ministry of Electronics and Information Technology is currently developing ‘voluntary’ ethical guidelines for organisations involved in artificial intelligence and generative AI, which as on date, is yet to be released. Regardless, its voluntary nature merely as a set of guidelines limits its effectiveness. The result is an economy that is able to rapidly automate and algorithmically ensure exploitation for profits, without accountability. 

The DPDP Act requires urgent and necessary amendment [including to s. 7(i) as detailed earlier in this Blog] to provide a principled baseline for collection and use of personal data of employees at large. Further, gig workers, must fall within this purview, by necessary enactment or amendment, recognising them to be ‘employees’ within the scope of protection. The EU’s Platform Work Directive, provides a commendable starting point, by solving the misclassification issue (employee vs. independent contractor) that gig workers globally suffer. Further, the State must also enact a legislative framework specifically for gig workers’ rights, that guarantees transparency in task allocation and performance assessment, mandates a meaningful right to an explanation and appeal process in automated decisions, right to erasure, and correction of data, with the option of data portability. This framework would have to prioritise the consent of workers with regards to data collection, with clear opt-in protocols to limit intrusive surveillance. The legislative framework must mandate third-party algorithm audits and impact assessments, with disclosure requirements of data practices, and notification systems to mitigate the potential for surveillance. Further, it must incentivise ethical use of AI (through certifications or accreditations) for gig platforms by rewarding fairness and transparency. 

Outside the legal landscape, there is an urgent need to digitally empower and train gig workers in understanding how platforms use data and algorithms, and increase awareness to promote collective action and advocacy. Workers must have feedback loops within the platforms, and be at the centre of how AI is designed to optimise performance. 

Ethical platforms, that are worker-centred yet AI powered, are achievable. An example of this is the Namma Yatri cab and auto rickshaw hailing app based in Bangalore, which is powered by ONDC (Open Network for Digital Commerce) network and employs a commission-free approach and subscription fee model for its workers. Launched by the Auto Rickshaw Drivers’ Union in collaboration with a startup, it is built over an open protocol to connect drivers and riders seamlessly, without a profit-driven intermediary, thus disrupting the dominance of players like Uber and Ola in the market. While the future of ONDC in maintaining a democratic space for smaller businesses remains to be seen, initiatives like Namma Yatri offer an encouraging alternative. It demonstrates that AI can either widen inequality in the gig economy, or become a tool for employment – based on how it is designed, regulated, and used.  

Sources and additional references: 

1. Ankit Kapoor & Karthik Rai, 'Gig Economy: A Tale of Algorithmic Control and Privacy Invasion' (NLSIR, 23 March 2023) <https://www.nlsir.com/post/gig-economy-a-tale-of-algorithmic-control-and-privacy-invasion> accessed 7 April 2025.
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