By Aya Achkar, Marketing and Communications Intern at Reshaping Work and Marketing Management Masters Student at Rotterdam School of Management
What if your next job, your pay, and even your chance at keeping that job were all determined by an algorithm?
In 2024, as debates over AI governance and the future of work accelerate worldwide, we came together at the Reshaping Work Conference — platform founders, policy researchers, insurance experts, and workers — to discuss one of the most pressing questions in today’s digital labour market:
What happens when algorithms become your manager?
The rapid expansion of AI-driven management systems makes this conversation more relevant than ever, with real implications for fairness, transparency, and the future of work.
Our panel brought together voices from across the platform economy: Axel Dekker (Co-Founder and CEO of What’s Next; former Packaly), Uma Rani (Senior Economist, International Labour Organization), Wendy Liu (CEO Zurich Integrated Benefits & International Life at Zurich Insurance), Shaun Cheah (Gig Worker), and Andrea Herrmann (Innovation Policy Expert, Radboud University), who moderated the discussion. With expertise spanning the insurance industry, the gig economy, academic research, and real-world delivery experience, the panel offered a 360-degree view of how AI is shaping the platform economy.
Algorithms in Platform Work: Invisible, Yet Powerful
From the worker’s perspective, the influence of algorithms can be hard to trace but deeply felt. As Shaun shared, jobs appear (or don’t), bonuses fluctuate, and routes are determined by unseen systems. Platform workers are often left guessing what they did “right” or “wrong”. Algorithms can reward or penalise, but workers rarely get a chance to understand why.
As Uma noted, algorithmic management is increasingly used not only to match workers to tasks but also to monitor, evaluate, and discipline, without human involvement. This undermines the very idea of flexibility that platforms promote. Saying “no” to a job may technically be allowed, but in practice, it can result in fewer assignments, lower pay, or even deactivation.
Algorithms, as we see, are not neutral. They reflect the priorities and design choices of those who build them, and those choices have real consequences.
Transparency by Design: Building a Different Kind of Platform
From a founder’s point of view, it’s possible to do things differently. Axel described how, at Packaly, the team deliberately avoided opaque task assignment. Instead, they used a first-come, first-served system, openly shared our payment logic, and involved riders in decisions through weekly advisory sessions. It wasn’t always easy, especially during high-demand periods, but the trust it built was worth it.
This kind of human-first approach proves that transparency is a design choice. One that more platforms should consider.
Beyond Risk: Using Data to Support Workers
As Wendy shared from the insurer’s perspective, data and AI can also be used to support, not just monitor. With more freelance and gig-based work, Zurich Insurance is rethinking how they deliver benefits, not just to pay out when something goes wrong, but to prevent harm in the first place.
By understanding patterns in behaviour or risk exposure, Zurich can design services that build resilience: from financial planning tools to personalised safety recommendations. Wendy believes benefits in the future should be flexible, personalised, and embedded in the work experience regardless of employment status.
What Needs to Change?
The stakes are high, and the time to act is now.
Algorithms are already reshaping the world of work and without transparency, accountability, and worker voice, we risk reproducing inequality at scale.
Whether through EU directives, ILO conventions, or local initiatives, we need to bring algorithmic management into the scope of labour law and worker protections. And we need more platforms to be transparent, not just because regulators demand it, but because it’s the right thing to do.
Final Thoughts
This discussion made one thing clear: algorithms are here to stay, but how they are designed, deployed, and governed is still up for debate.
As a panel representing workers, researchers, insurers, and platforms, they all brought different experiences to the table, but found common ground in a few key areas:
One of the main conclusions is that algorithmic management should never be a black box, especially when it shapes people’s livelihoods. Moving forward, we need stronger policies, better platform practices, and more inclusive conversations between all stakeholders.
To learn more about the evidence and practical models behind these ideas, listen to the full discussion in Episode 2 of the Work Rewired podcast.