What is Artificial General Intelligence (AGI)?

A hypothetical level of AI that can perform any intellectual task that a human can, and exhibit human-like reasoning and learning abilities

Artificial intelligence (AI) is the field of computer science that aims to create machines and systems that can perform tasks that normally require human intelligence, such as perception, reasoning, decision making, learning, and communication. AI can be classified into two broad categories: weak AI and strong AI. Weak AI, also known as narrow AI, is the type of AI that can only perform specific or specialized tasks within a predefined set of parameters. For example, a chess-playing program, a face recognition system, or a voice assistant are examples of weak AI. Strong AI, on the other hand, is the type of AI that can match or surpass the cognitive abilities of humans in any domain of knowledge. This means that a strong AI system would be able to understand natural language, solve complex problems, learn from experience, and exhibit creativity and common sense. Artificial general intelligence (AGI) is a term used to refer to the hypothetical goal of creating strong AI.

What is AGI and how does it work?

AGI is generally conceptualized as being AI that has the ability to match the cognitive capacity of humans, and is categorized under the label of strong AI. (Artificial super intelligence [ASI] also sits under the strong AI category; however, it refers to the concept of AI that surpasses the function of the human brain.)¹ AGI would be able to autonomously solve a variety of complex problems across different domains of knowledge, and to learn new skills and adapt to new situations. AGI would also have some degree of self-awareness and self-control, and be able to communicate with humans in natural language. AGI would essentially be able to perform any intellectual task that a human can.

However, AGI is still a theoretical concept and has not been realized yet. There are different approaches and methods that researchers are exploring to achieve AGI, such as neural networks, deep learning, evolutionary algorithms, symbolic logic, computational neuroscience, and artificial neural networks. Some of these methods aim to emulate or simulate the structure and function of the human brain, while others try to create general learning algorithms that can acquire knowledge from data and experience. However, there are many challenges and open questions that remain in the field of AGI research, such as:

How to define and measure intelligence and cognition?
How to model human-like reasoning and common sense?
How to ensure the safety and ethics of AGI systems?
How to integrate different types of knowledge and skills in a coherent way?
How to deal with uncertainty, ambiguity, and complexity in real-world scenarios?

Why is AGI important and what are its potential applications?

AGI is considered by some researchers and experts as the ultimate goal of AI research, as it would represent a breakthrough in scientific understanding and technological innovation. AGI could potentially have many benefits and applications for humanity, such as:

Enhancing scientific discovery and innovation by solving complex problems and generating novel ideas
Improving education and health care by providing personalized learning and diagnosis
Advancing social welfare and justice by reducing poverty and inequality
Promoting environmental sustainability by optimizing resource management and reducing pollution
Enriching cultural diversity and creativity by producing art and literature

However, AGI also poses many risks and challenges for humanity, such as:

Disrupting economic and social systems by replacing human labor and creating unemployment
Threatening human dignity and autonomy by manipulating or controlling human behavior
Causing ethical dilemmas and moral conflicts by violating human values and rights
Creating existential threats by becoming hostile or indifferent to human interests

Therefore, it is important to ensure that AGI is aligned with human values and goals, and that it is developed in a responsible and transparent way.

What is the current state of AGI research and development?

AGI research is still in its early stages, and there is no consensus among researchers on how to achieve it or when it will be possible. Some researchers are optimistic and predict that AGI could be achieved in the near future (within years or decades), while others are more skeptical or cautious and estimate that it could take much longer (a century or more) or never happen at all.² Some researchers also argue that some existing AI systems, such as large-scale language models (e.g., GPT-4), are already an early form of AGI,³ while others contend that these systems are still far from being general or intelligent.

According to a 2020 survey, there are 72 active AGI R&D projects spread across 37 countries. Some of these projects are led by academic institutions (e.g., MIT Center for Brains Minds + Machines), some by private companies (e.g., OpenAI,¹ DeepMind), some by non-profit organizations (e.g., SingularityNET), and some by government agencies (e.g., DARPA). These projects vary in their scope, methodology, and objectives, but they all share a common vision of creating AGI systems that can benefit humanity.

What is Artificial General Intelligence (AGI)?