AI’s Impact on the Future of Work

By Andeed Ma, President of the Risk and Insurance Management Association of Singapore (RIMAS); Partner of the Artificial Intelligence International Institute (AII); Author of AI for Humanity: Building a Sustainable AI for the Future

From privacy concerns to the development of AI governance standards, the convergence of technology and ethics presents both challenges and opportunities. As AI continues to rapidly reshape industries, the critical intersections of AI, privacy, governance, and ethics must be explored.

Human-AI Symbiosis - Collaboration, Not Replacement

AI is not just automating routine tasks; it’s creating a new paradigm of work where humans and machines collaborate. In this emerging landscape, we see the concept of "human-AI symbiotic intelligence," where AI augments human capabilities rather than replacing them. This dynamic is particularly relevant to data protection professionals, who must oversee the ethical and responsible use of AI.

While some jobs may diminish due to AI's ability to automate repetitive tasks, new roles are emerging—particularly in AI oversight, risk management, and ethics. The future of work in AI-driven industries is one of collaboration, not replacement. Future workers must adapt by embracing AI literacy, which will enable them to understand AI's role and its limitations. This literacy is not solely technical but also involves industry-specific knowledge and the ability to navigate AI's ethical challenges.

For DPOs, AI literacy means understanding how AI can help with compliance, risk mitigation, and policy implementation while protecting data privacy. As AI reshapes industries, those tasked with safeguarding data privacy are in a unique position to lead in ensuring that AI systems are transparent, accountable, and ethical.

Adapting to AI Disruption – Education and Opportunity

The disruption caused by AI is not unlike previous technological shifts, from the steam engine to cloud computing. History teaches us that while some jobs may be displaced, new opportunities always emerge for those who adapt. In the data protection and governance sectors, AI will automate some tasks but create new demands for oversight and ethical governance.

Ongoing education and adaptability is key. Just as workers in past eras had to upskill for new technologies, today’s professionals must acquire new skills to thrive. As AI becomes more integrated into business processes, the demand for professionals who can oversee and govern AI systems responsibly will only increase. This ongoing evolution will require data professionals to remain adaptable, proactive, and committed to continuous learning.

Balancing Innovation with Privacy and Governance

As organisations implement AI, they face new challenges—particularly around privacy, governance, and bias. One notable example involved a research project in New Zealand that sought to develop AI models without compromising privacy by studying the social behaviours of meerkats. This demonstrates that innovation and privacy can coexist, provided organisations approach AI development thoughtfully.

In another example, Amazon’s AI-driven recruitment system initially showed bias against female candidates. To correct this, Amazon employed adversarial learning and privacy-enhancing techniques like data masking to reduce bias. 

The lesson is clear: AI audits, fairness checks, and privacy-enhancing technologies are crucial for mitigating bias and ensuring ethical AI deployment. Human oversight remains essential to safeguarding fairness, especially in sensitive areas like recruitment and education.

The Need for Governable AI and Evolving Standards

The complexity of AI governance increases as AI systems become more autonomous and integrated into everyday processes. The rise of "governable AI," where AI systems become more advanced, they could generate insights that may surpass human understanding. To address this, organisations must develop AI systems with embedded control mechanisms to monitor and manage risks dynamically, while remaining under human oversight.

One of the most significant developments in AI governance is the emergence of international standards, such as ISO/IEC 42001. These standards emphasise responsible AI development and integrate data protection into the governance framework. The collaboration between AI governance standards and data protection laws, such as Singapore's PDPC and the EU’s AI Act, provides a unified approach to AI accountability. Organisations must stay informed about these evolving standards and incorporate them into their AI governance practices.

This article was first published on The Governance Age on 26 Aug 2024.