The Algorithmic-Human Manager: AI, Apps, and Workers in the Indian Gig Economy

AI systems managing gig work lack transparency: The research found that algorithmic systems used to assign, monitor, and evaluate work for gig workers in India are deliberately opaque, making it difficult for workers to understand how decisions affecting their livelihoods are made.

Algorithmic fairness remains elusive: Despite expanding access to work opportunities, AI-powered management systems produce inequitable outcomes and are not designed to ensure that workers who do more labor receive proportionally higher pay, raising concerns about algorithmic bias in the gig economy.

Worker dignity is compromised by automation: The study reveals that replacing human managers with algorithms introduces significant challenges to worker dignity, suggesting that purely automated management systems may not adequately account for the human dimensions of employment.

A hybrid approach combining AI and human oversight is needed: Rather than choosing between technological efficiency or human accountability, the researchers propose an "Algorithmic Human Manager" framework where AI and human decision-making work together to create more equitable gig work arrangements.

Governance frameworks must be tailored to the Global South: The findings have specific implications for India and other developing economies, suggesting that responsible AI governance for gig work cannot simply adopt models from wealthy nations but must address the unique contexts and vulnerabilities of workers in the Global South.