Rapid advancements in Generative Artificial Intelligence (GenAI) have caught the attention of governments worldwide, with many organizations eager to harness this powerful technology to address complex challenges and improve public services.

However, the complexity and challenges associated with implementing GenAI may hinder government agencies' ability to effectively adopt and leverage this transformative technology.

The economic impact of GenAI is expected to be staggering. McKinsey & Company estimates that by 2030, GenAI could add $26 trillion to $44 trillion to the global economy annually. This transformative potential spans across multiple industries, including manufacturing, finance, healthcare, retail, and many creative industries.

Addressing the Risks of GenAI

GenAI poses significant risks to government agencies, including the risks of political propaganda, compromising national security, leaking confidential data, spreading inaccurate information, lacking transparency, being vulnerable to cyber attacks, and eroding public trust.

Political Propaganda

The ability of GenAI to generate and manipulate information makes it susceptible to being abused for political purposes, such as creating fake news or spreading false information to influence public opinion or sway elections.

Compromising National Security

The ability of GenAI to generate convincingly fake content could be exploited to create deepfakes or manipulate sensitive information, potentially compromising national security and safety measures.

Leaking Confidential Data

The large amount of data required to train GenAI models poses significant security risks. If confidential government information is inadvertently introduced into the training process, it could lead to data leaks or breaches.

Spreading Inaccurate Information

The ability of GenAI to generate seemingly plausible text and images could be used to disseminate false information or fabricate evidence, potentially undermining public trust in government agencies.

Lack of Transparency

The decision-making process of GenAI is often opaque, making it difficult to understand the underlying logic of the model and evaluate the accuracy of its outputs. This lack of transparency can raise concerns about abuse and accountability.

Risk of Cyber Attacks

GenAI relies on complex algorithms and large datasets, making it susceptible to cyber attacks, with potential malicious actors manipulating or controlling GenAI models.

Eroding Public Trust

The misuse or dissemination of inaccurate information by GenAI can erode public trust in government agencies and their ability to provide reliable and trustworthy services.

To address these risks, governments are developing regulations and policy frameworks, conducting awareness campaigns, and providing guidance on security and ethical use.

Developing National-level GenAI Base Models

Developing base models for GenAI is a complex and resource-intensive process. Governments often lack the talent, computing power, and expertise to effectively build and manage these models. As a result, many governments choose to collaborate with private sector companies specializing in GenAI to access and customize models to meet their specific needs.

Base models serve as the foundation for a wide range of applications of GenAI. These models require significant computing resources, expertise, and large amounts of data for training and maintenance, making independent development and management of base models a challenge for governments lacking these resources and capabilities.

An article by McKinsey suggests that public sector organizations entering the GenAI field should start small, establish a risk position, identify and prioritize use cases, select underlying models, and ensure necessary skills and roles. They should also collaborate with end users in developing GenAI applications, maintain human involvement, design comprehensive communication plans, and gradually scale up.