The End-Game of Artificial Intelligence: The Characteristics of Artificial General Intelligence
Overview of the DefinitionsIt is important to note that AGI is a hypothetical future artificial intelligence system that is deemed to have close to human-like intelligence and capabilities. Advances in the subfields of artificial neural networks, machine learning and deep learning, computer vision, robotics, and natural language processing via large language models and multimodal language models have been pushing the field of AI toward achieving AGI. Some sources and commentators use the terms AGI and strong AI interchangeably. However, in other sources, strong AI is reserved for computer programs that experience sentience or consciousness, as opposed to weak AI which is only capable of solving one specific problem and lacks general cognitive abilities. It is in this regard that AGI is more about intelligent systems that can perform a wide range of cognitive tasks while strong AI is about systems that can perform on par with humans or even surpass human intelligence. Cognitive abilities are central to the imagined or assumed capabilities of artificial general intelligence. A particular AGI system would have the ability to perform intellectual tasks that a human being can do, including reasoning, problem-solving, learning, perception, and natural language processing, among others. It will also be capable of planning, exhibiting common sense, and unsupervised or autonomous actions and behaviors.
Main Characteristics of AGIUnderstanding better what AGI is and what it can do requires understanding its specific traits or characteristics. Various criteria for intelligence have been proposed to help in determining whether a particular AI system has reached AGI. There is still no universal test but some of the notable ones include the Turing test and the Coffee test. The following are the specific concepts for testing human-level artificial general intelligence:
• Turing Test: This test involves a human evaluator who assesses the responses of both a machine or system and a human in a conversation. The evaluator is unaware of which participant is a human or if an AI system is involved. The system needs to convince the evaluator that it is a human in order to pass the Turing test.
• Coffee Test: Stephen Wozniak, the co-founder of Apple, introduced the Coffee Test. It centers on requiring a machine entering an average home and figuring out how to make coffee. This involves finding the coffee machine and then the coffee, adding water, finding a mug, and brewing the coffee by pushing the proper buttons.
• Robot College Test: Another test is called the Robot College Test which requires a machine or an AI system to take college admission tests, get admitted to a particular institution, enroll in that institution, take and complete the same classes that a human would, pass the relevant tests and requirements, and receive a degree.
• Employment Test: Computer scientist Nils Nilsson proposed the Employment Test as part of the criteria for evaluating a supposed AGI system. This is similar to the Robot College Test and but it specifically involves a machine or an AI system performing an occupation at least on the same level as humans in the same occupation.
• Automated Reasoning: An AGI system is capable of complex and sophisticated reasoning using different reasoning skills with minimal to zero human intervention. These include deductive, inductive, and abductive reasoning.
• Perception and Representation: It should also be able to perceive and interpret the world and also represent information about the world in a form that other artificial intelligence systems or computer systems and humans can understand.
• Automated Planning: The system should also be capable of developing and implementing strategies or action sequences on its own based on human-provided tasks or other tasks emerging from its generative activities.
• Learning: An AGI system makes use of advanced techniques in machine learning and deep learning. It should be capable of self-improvement through unsupervised learning to adapt from experience and improve its performance.
• Natural Language Communication: It should be able to communicate in natural language through advanced natural language processing. This includes generating and interpreting written and spoken communication.
• Creativity Thinking: The system should also be capable of creative thinking and demonstrating creative pursuits as demonstrated through generative outputs and the generation of novel ideas and creative solutions to complex problems.
• Complex Movements or Mobility: Some researchers also suggest that an AGI should have the ability to act through the performance of complex movements. This includes moving and manipulating objects or changing locations to explore.The aforementioned intelligence traits suggest that the characteristics of artificial general intelligence are a collective or culminated realization and application of the different subfields of and techniques in artificial intelligence which include machine learning and deep learning, artificial neural networks, natural language processing, knowledge representation and reasoning, computer vision, scheduling and planning, and robotics. Nevertheless, based on the discussions above, an AGI system is capable of performing a wide range of cognitive tasks, exhibiting creativity and problem-solving abilities, and learning and adapting to new situations. This is the reason why advances or developments remain a significant challenge, and much research and pursuits are required before this hypothetical future artificial intelligence system becomes a reality and widely available.