How AI Policy Governance is Affecting Global Ecosystems

Artificial intelligence (AI) is changing many fields with its fast progress, and India is embracing this technological revolution head-on. A NASSCOM report suggested that the nation’s AI market is expected to reach $17 billion by 2027, growing at an annualized rate of 25-35% between 2024 and 2027.

Governments around the world are facing the challenge of creating good policy governance frameworks that can leverage the advantages of AI while reducing any negative impacts.

The importance of transparency, fairness, and accountability

AI has distinctive features, such as its capacity to imitate and surpass human intelligence in difficult tasks that create difficulties for conventional policy and regulatory methods. AI systems can also make decisions that involve moral values, in areas like healthcare, criminal justice, and finance (unlike other digital technologies) and this raises important questions around transparency, fairness, and accountability.

Accordingly, governments are now looking for different ways to guide AI's development and use. National AI strategies show different methods, from the EU's broad rules to the US's more focused ones and the approaches that emphasize innovation in Asia and Africa.

There are several key challenges in implementing effective policy governance frameworks for AI:

• Balancing innovation and regulation: Governments face the challenge of striking a balance between fostering AI innovation and establishing appropriate regulatory oversight. The fast pace of AI development often outpaces the slower process of policymaking, risking either stifling innovation or failing to address emerging ethical and societal concerns in a timely manner.
• Lack of consensus on prioritizing issues: There is little agreement among stakeholders on which AI governance issues should be prioritized. For instance, experts may disagree on prioritisation and focus on long-term existential threats versus concern over immediate harms like algorithmic bias.
• Complexity of dual-use technologies: Many AI technologies have dual-use applications, making it challenging to regulate specific use cases. Banning certain AI applications may not be feasible as the underlying technologies are often used in beneficial applications as well.
•  Adapting existing regulations: While existing regulatory frameworks can be adapted to govern AI, the unique characteristics of AI systems, such as their ability to learn and make autonomous decisions, pose new challenges that require innovative approaches.
• Ensuring accountability and transparency: Policymakers must develop mechanisms to guarantee the accountability and transparency of AI systems, particularly when they are used in high-stakes decision-making domains like healthcare, criminal justice, and finance. In India, for instance, the government has issued an advisory that AI responses to Indian internet users should tag the responses that AI could be unreliable or wrong. It also demands AI developers to prioritize transparency and accountability in their products to protect the consumer from disinformation and harm. 
• Addressing global coordination challenges: Developing a cohesive global policy for AI regulation is complex due to the varying approaches and priorities of different countries and regions. Coordinating international cooperation in AI governance is challenging but crucial.Bridging the gap between industry and government: Fostering effective collaboration between the rapidly innovating AI industry and the slower-moving government policymaking process is essential but difficult to achieve in practice.

Continuous engagement and a multi-stakeholder approach

To address this, some experts have proposed an innovative "dynamic laws" model, where governmental authorities closely collaborate with international organizations and industry players to create more flexible and adaptive regulatory frameworks that can evolve alongside technological advancements. Continuous engagement and a multistakeholder approach are also crucial for developing responsible AI governance frameworks that can keep pace with the rapid technological changes.

Alignment with the private sector

Additionally, the growing involvement of the private sector in AI governance, through self-developed ethical guidelines and industry-led initiatives, raises questions about the effectiveness and alignment of these efforts with broader societal interests – i.e. are the interests of profit-motivated private companies aligned with what is right for the society? Policymakers are grappling with how to ensure that corporate AI governance is accountable and responsive to public concerns.

Further exploration is required

As the landscape of AI policy governance continues to evolve, several key areas require further research and dialogue among stakeholders. These include evaluating the impact of existing AI regulations, exploring international cooperation in AI governance, and assessing the implications of AI regulation on emerging economies.

In conclusion, the age of artificial intelligence has ushered in a new era of policy governance challenges. Governments worldwide are navigating the complexities of balancing innovation, ethical considerations, and societal well-being. The development of flexible, collaborative, and dynamic regulatory models holds promise in addressing the unique characteristics of AI and ensuring that it is deployed responsibly for the benefit of all.

 Authored by Prag Jaodekar, Technology Director in CTO Office, Synechron