Investors are essential for successful fund management.
In the rapidly evolving world of work, Artificial Intelligence (AI) is playing a significant role, particularly in the Gig Economy. This economic model, characterized by flexible contractual relationships and algorithmic management, is seen as the cradle of this innovative approach to work management.
Algorithmic Management, using algorithms for hiring, scheduling, surveillance, and evaluation, has expanded beyond gig platforms and into traditional workplaces globally. A large majority of firms now use software for managerial tasks, indicating that gig economy challenges mirror broader labor market trends in automation of management.
However, this revolution comes with implications and controversies. One of the primary concerns is the precarious livelihoods and lack of safeguards faced by workers. Algorithm-driven decisions often determine job assignments, pay rates, and deactivation with little transparency or recourse, reinforcing income instability and precarious work conditions.
Moreover, women and marginalized groups face exacerbated challenges due to algorithmic management, including lower earnings, limited upward mobility, safety concerns, and restricted access to opportunities because of embedded social norms and digital divides. In Asia, where large portions of the workforce engage in gig work across various sectors, algorithmic management shapes millions of workers’ experiences, raising concerns about sustainability and fairness on a massive scale.
Transparency and accountability are other significant issues. Algorithms operate with limited explanation, leaving workers in the dark about how decisions affecting their livelihoods are made. This opacity raises ethical concerns about fairness and undermines trust. Academic research reveals multi-billion-dollar economic benefits accruing to platforms and firms through algorithmic exploitation of workers, who bear risks without protections or voice.
Regulatory challenges also arise due to the opacity of these business models. While new regulations aim to mitigate negative impacts of algorithmic management by enforcing fairness and worker protections, their implementation is complex, and their effectiveness remains to be seen.
The impact on worker well-being is another concern. Constant monitoring and automated performance evaluation can generate stress and reduce worker autonomy, affecting mental health and job satisfaction.
Companies such as Uber, Lyft, Yandex, Didi, Doordash, Just Eat Take Away, and Deliveroo are known to use Algorithmic Management in their operations. Ride prices can be dynamically adjusted during peak demand periods to incentivize drivers in the ride-hailing sector. Customers in the ride-hailing sector can evaluate their drivers independently of any management supervision, and some companies encourage users to write reviews to gain a higher status.
AI enables the optimized matching of individual work or delivery orders with the availability of independent employees in the Gig Economy. Algorithmic Management uses electronic or algorithmic platforms to manage employee teams based on data models. AI can support the evaluation of freelance employees, as they perform their services outside the company and are less easily supervised.
However, it's essential to note that AI is not typically used as an addition to classical methods of employee management, but as a replacement. The use of objective decisions based on data models instead of intuition is a characteristic of Algorithmic Management.
These issues highlight the urgent need for thoughtful algorithm design, increased transparency, stronger labor protections, and inclusive policies to ensure the gig economy is fair, sustainable, and equitable for all participants. The future of work lies in striking a balance between technological advancement and human welfare.
Other technology like artificial-intelligence is expanding beyond the gig economy and influencing traditional workplaces, as a large majority of firms now use it for managerial tasks. This shift towards algorithmic management raises concerns about fairness and transparency, as opaque decisions made by AI can impact workers' livelihoods with little recourse or explanation.
