Thinking Like a Human or a Machine - The Common and Contrasting Nature of Human and Machine Intelligence

“The Brain—is wider than the Sky—

For—put them side by side—

The one the other will contain

With ease—and you—beside—” Emily Dickson

Understanding Human and Machine Intelligence - A Reciprocal Process

The concept of intelligence remains ambiguous, highlighting the importance of integrating advancements in neuroscience, cognitive science, and artificial intelligence (AI) to solidify our understanding of intelligence. Consequently, the interaction between human and machine intelligence is reciprocal. Initially, neural networks were shaped by our limited knowledge of the brain. Now, the accomplishments of large language models (LLMs) provide an opportunity to enhance our comprehension of cognitive functions, drawing on the successes of AI.

Critics often see LLMs' text generation—one word at a time—as a lack of understanding. Yet, their effectiveness supports modern neuroscience's view of the human mind as practical and efficient rather than profoundly logical. This comparison between LLM operations and brain function makes us rethink our intelligence concepts.

This article examines how human and AI intelligence complement and differ from each other, focusing on their strengths and weaknesses. Understanding these elements allows us to forge synergies that amplify our collective capabilities beyond individual achievements.

The Mind and LLMs Are Flat!

As explored in Nick Chater's "The Mind is Flat," modern neuroscience offers a fresh understanding of the brain that aligns with artificial intelligence's workings, particularly large language models (LLMs). Chater and scientists like Daniel Dennett and Paul Churchland challenge the idea that the mind maintains deep, hidden knowledge. Instead, he suggests that our thoughts and behaviours are spontaneously generated, positioning the mind as a creative improviser.

This concept finds a parallel in the way LLMs function. The brain and LLMs operate seemingly flatly, generating responses and knowledge on the fly without access to a deep reservoir of explicit information. This operation mode reflects Chater's view of the mind crafting narratives and rationalisations in real-time, a perspective supported by the blend of psychology, neuroscience, and behavioural economics.

The similarity between human cognition and AI systems like LLMs, which generate responses from recognised patterns rather than deep understanding, illustrates the practical application of Chater's theory. Both the human mind and LLMs demonstrate remarkable adaptability, tailoring their outputs to fit new contexts without relying on an underlying cache of detailed knowledge.

In conclusion, the insights from Chater, Dennett, Churchland, and the performance of AI systems suggest a shift from the classical notion of a deeply knowledgeable mind to a model that values spontaneous, surface-level cognitive processes. This view emphasises the ability of both human and artificial intelligence to construct narratives and responses at the moment, challenging long-standing beliefs about the nature of cognition.

How do humans differ from AI?

However, the brain differs from AI in many fundamental and profound ways. Modern neuroscience has reframed our conception of the brain, transforming it from the image of a cold calculator to a profoundly complex sensory, emotional, social and cognitive fabric. This shift transcends the classical vision of the brain as a detached logician, operating in a vacuum of rational thought. Instead, we now understand the brain as an embodied entity, its cognitive processes linked to the body's interactions with its biological and the surrounding physical and social environment.

Embodied cognition

The concept of embodied cognition has been particularly significant in our modern understanding, underscoring that the brain does not operate in isolation. Our physical engagement with the world — the touch of a texture, the movement through space, the raw experience of the elements — shapes our cognitive landscape. This intricate dance between sensory input and motor activity is central to how we perceive and understand our world, indicating that cognition is not just a cerebral event but a full-bodied experience.

The concept of embedded cognition goes back very far, although it may not be fully appreciated. Antonio Damasio, one of the most eminent neuroscientists, is known for his work on the brain and emotion. He has written extensively on the importance of the body in cognitive processes. The following quote from his book "Descartes' Error" illustrates the embodied brain hypothesis:

"The mind is embodied, not just embrained, and the body contributes more than life support and modulation to mental functions. The body contributes a content that is part and parcel of the workings of the normal mind."

This quote underscores the principle that cognition is not just a product of the brain in isolation; rather, it arises from integrating brain functions with bodily experiences. Damasio's work, and that of many modern neuroscientists, is crucial to understanding how our physiological state affects how we think, decide, and experience the world.

A bundle of emotions and cognition

The revered split between emotion and reason, a mainstay of lay psychology, has been thoroughly revised by modern neuroscience. It's no longer defensible to view emotions as the adversary of rational thought; instead, they're entwined with it, seamlessly integrated into the fabric of our decision-making. As Luiz Pessoa elaborates in "The Entangled Brain," the amygdala—once pigeonholed as the brain's fear centre—is a crucial node in a network that includes the prefrontal cortex, the command centre for our planning and decision-making. This neural tangle suggests that emotions are not a bug in the system of reason but a feature, imbuing our decisions with vital personal and societal meaning. Pessoa articulates this beautifully: "Emotion and cognition are integrated, and the amygdala plays a high-level cognitive role," underscoring that the brain doesn't strictly segregate feeling from thinking but rather uses emotion to enrich the power of thought.

The social brain

Our brains are fundamentally social organs, deeply wired for connection with others. Matthew D. Lieberman vividly explores this compelling perspective in his insightful book "Social: Why Our Brains Are Wired to Connect." Lieberman poignantly notes, "Our brains are designed to be social. A broken heart or the pain of loneliness are just as real as a broken arm."

This view highlights social connectivity's profound impact on everything from our decision-making processes to overall health and well-being. It's not just that we enjoy social interaction; our brains are shaped by it. The neural pathways that light up in response to physical pain are similarly activated by the pain of social rejection, underlining the deep-seated nature of our social needs. The brain's social wiring is crucial in understanding many aspects of human behaviour and the nature of our mind. Questions like why we seek companionship or why isolation is painful are rooted in our neural architecture. Therefore, in understanding the brain, its social aspect emerges not as a minor detail but as a central feature.

The brain’s plasticity

The notion of the brain as an immutable, purely rational processor has been consigned to the dustbin of scientific history thanks to our growing understanding of neural plasticity. The brain is not a hardwired machine, eternally fixed in its ways; it is a dynamic organ, continually reshaped by experience. Norman Doidge's "The Brain That Changes Itself" back in 2007 offered a compelling testament to this view: "Neuroplasticity contributes to the sculpting of the brain by the environment," he writes, capturing the essence of this transformation. It's a recognition that our brains are far from static entities; they are work-in-progress, moulded by our interactions with our surroundings, capable of remarkable adaptation and learning throughout our lives.

Contrasting AI and the brain

In contrast, AI, like that found in LLMs, operates without this embodied framework. AI does not feel the weight of a book or the warmth of a handshake; it cannot draw from a reservoir of emotions or personal history. It lacks the deep social context that frames human experience, the unspoken understanding that comes from a lifetime of social interaction. AI processes information makes predictions and even simulates conversation, but it does so without the rich, embodied experience that characterises human thought.

The brain is not an island but a peninsula, constantly shaped by the sea of bodily experience, emotional currents, and the social atmosphere in which it resides. This new understanding steers us from viewing the brain as a mere logic machine to unveiling it as a living, feeling, socially attuned organ deeply embedded in the human experience.

The limits of human and artificial intelligence

From the above discussion, we can see that the human brain and AI represent two profoundly different paradigms of intelligence, each with strengths and limitations. The human brain is an organic, evolved structure deeply embedded within a rich tapestry of sensory experiences, emotional responses, and social interactions. Its limits are often tied to these very features: the overwhelming complexity of sensory input can lead to information overload, emotions can skew rational judgment, and the intricate nuances of social contexts can be challenging to navigate. Moreover, the brain's cognitive processes are constrained by the biological need for rest and restoration and by the gradual decline due to aging or disease.

Conversely, AI faces a different set of constraints while free from the need for sleep or the impulses of mood. Its understanding is limited to the data it has been fed; it lacks the ability to truly understand or feel emotions, which are crucial for making complex human decisions. AI cannot draw on a reservoir of personal experiences or cultural context as humans do; it can simulate empathy and understanding but cannot genuinely experience them. Furthermore, while AI can process vast amounts of information with incredible speed, it lacks the human capacity for creativity and intuition that arises from our embodied experiences.

These limitations are, in a sense, complementary. Where humans falter in consistency and the ability to process large datasets, AI excels. Conversely, where AI stumbles in understanding the subtleties of human emotion and experience, the human brain is at its most adept. The human brain can grasp context, infer meaning from a glance, and make leaps of intuition beyond AI's capabilities.

Yet, these mirrored limits also provide opportunities for synergy. AI can augment human capacities by handling data-intensive tasks, providing decision support, and even compensating for cognitive decline. Conversely, human oversight can guide AI, instilling ethical considerations and providing the contextual understanding necessary for appropriate responses.

In contemplating the future of these two forms of intelligence, it is not a matter of competition but instead of collaboration. By recognising and respecting the limits of human and AI intelligence, we can harness their respective strengths, forging a partnership that transcends the limitations of each. This symbiotic relationship promises a future where the sum of human and artificial intelligence is more significant than its parts, where each fills the gaps left by the other, creating a more holistic approach to understanding and interacting with the world.

Towards an Integrative Intelligence

Exploring human and artificial intelligence reveals a landscape rich with limitations and possibilities. While unparalleled in its ability to navigate our world's social and emotional nuances, human intelligence is bound by the constraints of biology and the subjective nature of experience. Artificial intelligence, in contrast, operates with an efficiency and consistency that the human brain cannot match. Yet, it lacks the depth of understanding from embodied experience and emotional insight.

The conclusion we can draw from this is clear: neither form of intelligence is superior in all aspects; instead, they complement each other. The human brain provides what artificial intelligence lacks – the capacity for empathy, creativity, and social intuition. Meanwhile, AI offers tools to extend the reach of human thought, process information at a scale and speed that the human brain cannot achieve, and store knowledge with a precision that our memory cannot guarantee.

This understanding leads us to a call for action: deliberately fostering a symbiotic relationship between humans and artificial intelligence. We must cultivate a culture that acknowledges each other's strengths and weaknesses and actively seeks to integrate them. This might mean redesigning education curricula to include AI literacy, ensuring future generations can partner with AI. In the workplace, it involves creating roles where AI enhances human decision-making rather than replaces it. Research necessitates interdisciplinary collaboration, harnessing AI for breakthroughs in medicine and climate science.

Embracing new insights into human and AI intelligence can lead to transformative outcomes. It is a call to move beyond competition and towards collaboration, to build systems and societies that harness the best of both intelligences. By doing so, we can aim for a future where human potential is not just augmented by artificial intelligence but is also amplified in ways we have yet to imagine fully. The way forward is integrative, inclusive, and innovative – a future where human and machine intelligence merge to address the challenges of the modern world.

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References and Further Readings and Viewings

• The Mind is Flat: The Illusion of Mental Depth and The Improvised Mind , Nick Chater
• Consciousness Explained , Daniel C Dennett
• Descartes' Error: Emotion, Reason, and the Human Brain , Antonio Damasio
• The Entangled Brain: How Perception, Cognition, and Emotion Are Woven Together, Luiz Pessoa