I have written various articles about artificial intelligence (AI) over recent times, explored different types of AI, its various uses, some potential issues, and how it might all end in tears if we are not careful. What I have not yet properly thought about yet is what we mean when we talk about “intelligence”.
To delve into this, we need to step back and consider the broader concept of intelligence beyond the scope of artificial systems. Intelligence, in its essence, is the ability to learn, understand, and apply knowledge to manipulate one’s environment or to think abstractly as measured by objective criteria such as tests. It encompasses a range of cognitive abilities, including problem-solving, reasoning, planning, abstract thinking, and learning from experience.
Human intelligence, for example, is multifaceted. Psychologists have long debated and studied what constitutes human intelligence. Some theories, like Howard Gardner's theory of multiple intelligences, suggest that intelligence is not a single general ability but a combination of various specific abilities. These include linguistic intelligence, logical-mathematical intelligence, spatial intelligence, and more. Each individual may possess different levels of these intelligences, which collectively define their overall intellectual capabilities.
When we speak of artificial intelligence, we are essentially trying to emulate some aspects of this human-like intelligence using machines and algorithms. However, AI's intelligence is often narrow and specialized. It excels in specific tasks it has been trained for, such as image recognition, natural language processing, or playing chess, but it lacks the general adaptability and cognitive flexibility inherent to human intelligence.
One major area of AI research focuses on developing general artificial intelligence (AGI), which aims to create machines capable of performing any intellectual task that a human can. This goal, however, remains elusive. Current AI systems are predominantly examples of narrow AI or weak AI, designed for specific tasks and lacking the broad, adaptable intelligence of humans.
Understanding the nature of intelligence also means grappling with questions of consciousness and self-awareness. While current AI systems can process information and perform complex tasks, they do so without awareness or understanding. They lack subjective experiences, emotions, and consciousness — elements that are arguably integral to human intelligence.
The quest to define and replicate intelligence raises ethical and philosophical questions as well. As we develop increasingly sophisticated AI, we must consider the implications of creating machines that could potentially match or surpass human cognitive abilities. Issues of control, ethical use, and the potential impact on society are critical considerations.
While artificial intelligence continues to advance and reshape our world, our understanding of intelligence — both human and artificial — remains a work in progress. By deepening our exploration of what intelligence truly means, we can better navigate the challenges and opportunities that lie ahead in the realm of AI. This ongoing inquiry will help ensure that the development and deployment of AI are aligned with human values and (hopefully) societal well-being.
