The race towards achieving artificial general intelligence (AGI) has captured the attention of AI developers globally, from small startups to big tech companies like DeepSeek in China. AGI is seen as a critical threshold where machines will be able to outperform humans in various tasks, leading to major societal transformations, job displacement, and advancements in technology. However, the definition and practical utility of AGI remain unclear and contentious, with no clear consensus on what AGI entails and how to measure its progress.
Despite efforts to define AGI more precisely, including developing benchmark tests like the Abstract Reasoning Corpus for Artificial General Intelligence (ARC-AGI), the evaluation of AI’s general intelligence remains challenging. Tests like ARC-AGI, while aimed at assessing flexible reasoning and problem-solving skills in AI models, have their limitations and do not capture the real-world complexity of human intelligence and problem-solving abilities.
While AI models like OpenAI’s o3 have shown promising results in benchmark tests, the challenges lie in how these models perform in real-world scenarios. AI tests often focus on specific tasks or problems with known solutions, failing to capture the broader context and variability of real-world challenges. Moreover, the lack of detailed information provided by AI developers makes it difficult to assess the true capabilities and limitations of AI models beyond benchmark results.
Even if AI models excel in specific tests, such as medical diagnosis or legal brief writing, their performance in real-world conditions may not align with expert human performance. AI models still struggle with tasks that require contextual understanding, critical thinking, and decision-making in uncertain situations. Achieving AGI is not solely about intelligence but also about practical utility, scalability, and affordability of AI tools, which current models may lack despite advancements in machine learning and neural networks.
The impact of AI on society, ranging from creating new molecules to facilitating cheating in education, highlights the broad implications of AI beyond achieving AGI. While AGI is seen as a milestone that could revolutionize society, the focus on achieving AGI may overshadow the current societal impacts, ethical concerns, and practical applications of AI technology. The path to AGI is complex and requires a deeper understanding of the limitations, challenges, and societal implications of artificial intelligence. Ultimately, achieving AGI is not the end goal but rather a part of a larger conversation about the responsible development and deployment of AI technology.
