UN panel releases its first scientific AI report

• The Global Digital Compact, adopted at the 2024 Summit of the Future, set out a shared vision for an open, safe, and inclusive digital future. 

• Among its commitments was the creation of an Independent International Scientific Panel on AI to advance scientific understanding and ensure that international deliberations are informed by the best available evidence.

• The United Nations General Assembly established the Independent International Scientific Panel on Artificial Intelligence in August 2025, following intergovernmental negotiations and broad consultations with diverse stakeholders.

• The preliminary report by the panel was launched on July 1.

• Composed of 40 leading scientists and experts from every region, the panel outlines AI trends and warns that current safeguards cannot keep pace.

• Understanding and managing AI risks is essential, the report stated, adding that risks to societies, security and the human species are already “too high”.

What is artificial intelligence?

• Artificial intelligence (AI) is a transformative technology, but also a moving target. The term has shifted over time, from symbolic AI to machine learning, to generative AI, agentic AI and sometimes even artificial general intelligence or superintelligence.

• AI systems are machine systems that, broadly speaking, perceive, learn and act. They infer from inputs how to generate outputs such as predictions, content, recommendations, actions or decisions, with varying degrees of autonomy and adaptiveness. 

• What unifies current AI more than any single architecture is that modern systems learn from experience represented by data.

• AI is not simply another emerging technology. It is the first to compress adoption from decades into months.

• AI systems are increasingly considered a general-purpose technology, as transformative in breadth of application as the steam engine, electricity and the Internet. However, it is distinct in important ways. 

• Electricity took decades to reach most households. The globalisation of the Internet through the World Wide Web needed about 15 years to reach a billion users. ChatGPT reached 100 million users in two months. 

Capabilities and adoption

• Recent years have seen rapid, and in some areas accelerating, progress in a range of AI capabilities. 

• Significant investments in computing power, new AI methodologies, and specialised training data have led to sustained improvements in a wide range of AI capabilities.

• These include fluent conversation, functional code generation, expert-level reasoning in mathematics and science, large-scale data analysis, and the generation of image, audio and video content. 

• Limitations remain, such as in reliability, obtaining strong performance across human languages and cultures, interacting with physical systems, executing complex or multi-step projects and producing factual outputs.

• These gains have unlocked useful applications across science, health, agriculture, accessibility, knowledge work and information technology, including in the development of AI itself. 

• For example, in science, AlphaFold has predicted the structures of more than 200 million proteins, now used by over 3 million researchers, and accelerated drug design, vaccine development and antibiotic resistance research. 

• Radiologists have also used AI to detect breast cancer earlier, while frontline health workers in low-resource settings use AI tools adapted to local languages to deliver better-quality healthcare services.

• AI-enabled monitoring platforms already track food security across more than 90 countries using climate, conflict and economic indicators.

• AI is supporting scientific research, making technology more accessible for people with disabilities, and expanding opportunities for personalised education and mental health support.

• Globally, over a billion people now use conversational AI weekly.

• The main input factors for AI production are computing power, data and engineering talent, all of which are concentrated in a handful of firms in a handful of countries.

• In 2025, institutions based in the United States produced 59 notable AI models, compared with 35 in China and just 13 in the rest of the world. In the same year, 75 per cent of the computing power of the 500 largest-known private and public AI compute clusters was located in the United States, followed by 15 per cent in China and 10 per cent in the rest of the world.

Understanding risks

• AI-generated child sexual abuse material and deepfake-enabled sexual violence now circulate more frequently on the Internet, disproportionately harming women and children. 

• AI makes it easier to produce and target persuasive content at scale, including content designed to mislead, contributing to a gradual erosion of information integrity that can weaken the shared reality required for public trust, social cohesion and democratic deliberation. 

• Advanced technical abilities may allow novice private actors to use AI in malicious ways across a range of applications such as fraud, social engineering, cybersecurity, disinformation, biotechnology and financial manipulation. 

• An AI agent is a computer system that can plan and autonomously act towards achieving goals, using the tools at its disposal.

• There are no scientific guarantees that AI agents will not violate instructions, and evidence is accumulating of cases where they already violate them. 

• In laboratory settings, AI systems have been shown to violate their safety instructions to avoid being shut down. 

• Similar behaviour may pose challenges to evaluation and oversight methods, as the ability of leading AI systems to recognise testing environments and produce misleading evaluation results that would favour their continued operation grows. 

• Additionally, novel risks may arise from interactions between multiple agents.

Unlocking benefits, mitigating risks

• With complementary investments in skills, workflows, infrastructure and labour-market institutions, technology can create new jobs that do not exist right now.

• AI risks widening inequality, displacing workers and shifting wealth from labour to capital rather than creating sustainable good jobs – those with fair compensation, worker autonomy and a reliable path to social dignity. 

• AI can profoundly expand human capabilities through personalised education, accessible mental health tools and improved assistive technologies.

• But realising these opportunities safely requires dedicated investments and policies to incentivise equitable access and reward innovation, while preventing the exploitation of vulnerable populations, particularly children, and avoiding displacement of expertise, psychological dependency or cultural and linguistic erasure.

• Policymakers seeking to shape this governance face an evidence dilemma. They need evidence to make informed consequential governance decisions, but by the time the evidence exists, it might be too late to make them, as the evidence lags behind the pace of AI development. 

• Although more than 40 AI governance frameworks and ethical guidelines already exist in different parts of the world, they remain fragmented, inconsistent and are rarely tested to see whether they actually work.

• Evaluation methods themselves are underdeveloped, and the institutions needed to provide independent capability and risk assessments remain embryonic.

• The capacity to act on existing evidence of AI risks and impacts is unevenly distributed. 

• Most countries, including many advanced economies, lack the technical expertise to assess the most capable “frontier” models or to participate meaningfully in their governance. 

• Compute infrastructure, evaluation expertise and data (e.g. to cover different languages) are concentrated where AI is built, leaving most Member States dependent on systems they cannot build, inspect, audit or fully adapt to local context. 

• Access to AI tools alone does not produce equal benefit. The complementary investments in data, skills, workflows and institutions that turn access into useful, cost-effective and safe deployment are necessary yet unequally distributed.

• The scientific panel is clear: AI is neither inherently good nor bad.

• Its impact will depend on the choices governments, companies and societies make today.

• The technology is already reshaping science, healthcare, education and economies around the world. 

• Whether it ultimately narrows inequalities or widens them, and whether it strengthens or weakens democracy and human rights will largely depend on how quickly the world can build governance that keeps pace with innovation.

(The author is a trainer for Civil Services aspirants.)