Ethics and Governance of Generative AI Systems
The rapid development and deployment of Generative Artificial Intelligence (AI) systems, such as large language models (LLMs) and image generators, present both transformative opportunities and profound ethical challenges. The core difficulty lies in aligning these powerful new systems with human intent—making them reliably do what we want and, crucially, avoid what we don't.
A fundamental technical challenge is recognizing that an LLM is not inherently designed to produce truth or factual accuracy. Its design goal is to predict the most probable next word or token based on its training data, which often results in highly plausible but factually incorrect outputs.
The need for proactive governance is urgent and recognized globally. For example, the government of Nepal has officially approved a National AI Policy. This initiative acknowledges the technology’s potential to accelerate development in key sectors like education, health , disaster management and agriculture while simultaneously establishing the necessary legal and institutional frameworks for its ethical, safe, and transparent use. Specifically, the policy should guide the deployment of such technology in Nepal’s rural communities to accelerate the rapid development of society and the country.
The Values Embodied in Technology
Ethical considerations for Generative AI must move beyond simply focusing on how we use the systems. There is a deep and constant connection between technology, ethics, and values that requires us to ask: "Whose values are being advanced by which uses?"
This perspective demands looking beyond the code to consider the people who benefit from the technology, ensuring that its advantages are broadly distributed rather than accruing only to a select few. Current safety rules in these systems are often superficial. They rely on simple keyword and phrase pattern matches, which are easily bypassed (e.g., by framing a forbidden request as a fictional story). The conditions of deployment and access to these systems also inherently establish a set of value criteria.
Benefits of Generative AI
Despite the ethical and safety challenges, the technology offers significant societal and economic benefits. Generative AI is a powerful tool for artists and creators, enabling them to rapidly explore vast possibilities and generate numerous ideas. The human role shifts to one of discernment—judging which generated ideas are truly exceptional. The systems are already proving useful for tasks like proofreading, editing, summarizing, and helping non-native speakers quickly craft professional-sounding communication. Like earlier technologies such as spell-checkers, AI can eliminate or reduce labor in routine or undesirable tasks. A crucial, often-undiscussed benefit is the ability to generate realistic, simulated data about non-existent people or systems. This allows researchers in healthcare, finance, disaster management and other sectors to make advances without ever requiring access to sensitive, real-world private data, thereby enhancing privacy protection.
Massive Ethical and Societal Risks
The unchecked deployment of Generative AI introduces severe ethical and societal risks: The systems have the capability to massively increase the scale and magnitude of misinformation and disinformation. Experts warn that the coming information chaos, especially around future elections, is something for which society is largely unprepared. Even unintentionally, these systems can generate and present harmful misinformation as fact. Many of the most powerful systems are highly closed and opaque (a major concern given the name of a company like "OpenAI" is now a misnomer). This lack of transparency means users have no way to understand how the systems operate or seek recourse when errors occur. The threat of job displacement is real, as illustrated by companies publicly stating their intention to drastically reduce staff (e.g., from a team of 50 to 5). It is vital to identify and preserve the skills we cannot afford to lose—skills that are critical for safety, such as a pilot's ability to land a plane if the autopilot fails. The deployment of these systems often uses the public as unwitting and unconsenting subjects of a massive experiment. Every prompt and interaction collects user data, and fixes are often rapid, backend changes in response to public notice rather than planned, transparent updates. Significant questions abound regarding the ethical use of publicly available data for training, particularly in cases involving artists and image generation, and who ultimately owns the output created by these systems.
Conclusion and Outlook
Unlike some technologies where ethical challenges took years to fully materialize, the harms of Generative AI were identified within months of its public release. The academic and professional communities working on these systems have the opportunity to make real progress in minimizing harms while maximizing benefits as the technology continues to mature. The core takeaway is a call for a continuous and critical examination of whose values are being advanced by the code, the uses, and the deployment of this powerful new technology.