10-22-24
This is a question that human kind will ask over and over again. Which is smarter, better and more reliable; the human intellectual capacity, or that of artificial Intelligence or A.I.?
Human intelligence: One-shot
vs. multishot learning
One of the most miraculous qualities of humans is the ability to learn new concepts and ideas from a small number of samples, sometimes from a single one. Most humans are even able to understand and identify a pattern and to use it to generalize and extrapolate. Having been shown one or two images of a leopard, for example, and then being shown images of various types of animals, a human would be able to determine with high accuracy whether those images depicted a leopard. This ability is referred to as one-shot learning.
AI.
One shot learning is a type of machine learning (ML) that involves training a model to perform a task using a small number of examples. It is an important area of research in ML, as it has the potential to significantly reduce the amount of data and computational resources required to train a model. Much more often than not, artificial intelligence systems need copious examples in bulk to achieve comparable levels of learning. An AI system may require millions, even billions, of such samples to learn at a level beyond that of a human of average intelligence. This requirement for multishot learning distinguishes AI from human intelligence. Many researchers feel that this difference is a strong basis for describing humans as being, on average, much more efficient learners than AI systems. Artificial intelligence is humanlike, but there are fundamental differences between natural and artificial intelligence.
Human Flexibility and Creativity.
Human intelligence thrives on flexibility and creativity, allowing us to apply knowledge across vastly different contexts. Its all a part of simply being human. A person can solve problems in novel situations by drawing on past experiences, even if they are unrelated to the immediate problem. For example, a chef may use their expertise in flavor combinations to solve a complex, or simple chemistry culinary problem that is involving reactions, or an artist can transfer their sense of balance and composition to interior design. This creative leap is something AI struggles with, as artificial intelligence relies heavily on predefined rules and algorithms, making it less capable of truly “thinking outside the box” unless specifically programmed to do so. This adaptability in humans, driven by abstract thinking, innovation, and emotional context, underscores our natural intelligence.
Another key difference lies in emotional intelligence and the ability to read and respond to complex social cues. Humans can easily detect and interpret emotions in others, such as recognizing when someone is angry, happy, or upset, even when the cues are subtle or ambiguous. This ability is rooted in empathy and social understanding, allowing us to communicate more effectively and build relationships.
While AI can simulate certain aspects of emotional response through natural language processing and pattern recognition, it lacks true emotional comprehension.
This fact shouild come as no surprise considering the boundless emotional evolution we have developed organically.
AI might process a large dataset on human emotions but does not experience empathy, making it incapable of genuinely understanding the context of human feelings. This limitation creates a distinct boundary between human cognition and artificial intelligence, especially in areas like interpersonal relationships, decision-making, and leadership.
Unlike humans, who navigate relationships with a blend of personal history, emotional nuance, and instinct, AI relies purely on patterns and probabilities to interpret emotions.
Unlike humans, who navigate relationships with a blend of personal history, emotional nuance, and instinct, AI relies purely on patterns and probabilities to interpret emotions. This difference means that while an AI can recognize and even replicate emotional expressions, it lacks the subjective, lived experience that informs true empathy. Humans draw from their own emotional journeys, using them to connect meaningfully with others. An AI's responses, however sophisticated, lack the sincerity that arises from personal understanding, making it inherently limited in offering comfort or compassion in a way that feels authentic to the human experience.
In leadership and decision-making, this absence of empathy presents challenges, as decisions often require more than logic—they call for a deep understanding of team morale, motivation, and unique personal circumstances. Effective leaders don’t simply analyze data; they empathize with their teams, recognizing unspoken cues and adjusting approaches based on the human factors that numbers can't capture. Without the ability to genuinely "read the room" or intuitively gauge an individual's needs, AI remains a powerful tool but cannot fully replace the nuanced judgment that human leaders bring to complex interpersonal dynamics.
Stay in the loop for part 2 and leave a comment with your thoughs. Watch the Youtube channel for the Video episode.
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