As humans, when we encounter concepts or phenomena that we don’t fully understand, we create new disciplines to study and comprehend them. Emergent behaviors, in particular, often baffle us – these are instances where the whole is drastically different from its individual building blocks. We might comprehend the blocks fairly well, but the complex constructs they form can be mystifying. Economics, as an example, is a field established to decipher the collective outcomes of numerous interacting individuals.
Today, we are witnessing similar emergent behaviors in the realm of artificial intelligence. Large language models like ChatGPT are demonstrating capabilities that we can’t entirely explain, other than acknowledging that they’ve emerged from tools we thought we knew well. As AI systems become more complex and demonstrate capabilities resembling cognition, we may need to extend our methods of understanding and investigating them. In this context, it could be beneficial to consider the creation of new fields: “AI Neuroscience” and “AI Psychology.”
AI Neuroscience
AI Neuroscience would be a discipline focused on understanding the ‘mechanics’ of AI – the intricate layers of artificial neural networks, how they interact, and how they produce the outputs that they do. This field would delve into the structure and interconnections of AI models, much like how neuroscience studies the brain’s physical structure and the neural networks within it.
AI neuroscientists would investigate the detailed workings of AI models, looking into how information flows through the network, how weights and biases change during learning, and how different architectures impact the model’s behavior. They would strive to map the AI’s “connectome” and understand how various components contribute to the overall functionality.
AI Psychology
On the other hand, AI Psychology would be more concerned with the ‘behavior’ of AI – its outputs, interactions, and ‘decisions.’ Rather than focusing on the AI’s internal structure, AI psychology would look at how AI perceives its inputs, responds to different scenarios, and changes its behavior over time.
AI psychologists would develop tests and experiments to probe AI behavior, much like how psychologists use various tests to study human cognition, personality, and behavior. They would analyze how AI systems learn over time, how they generalize from past experiences, and how they respond to novel situations.
Why do we need them?
Splitting AI research into these two fields could provide a more nuanced understanding of AI systems. AI Neuroscience would help us understand what’s happening ‘under the hood’ of AI systems, while AI Psychology would give us insights into their behavior and interactions with the world.
This division mirrors the dichotomy in human cognition research, where neuroscientists study the physical brain, and psychologists study behavior and mental processes. Both perspectives are crucial for a full understanding of cognition, whether in humans or AI.
As AI systems continue to grow in complexity and importance in our lives, developing a more sophisticated understanding of how they work and how they behave becomes increasingly important. The creation of AI Neuroscience and AI Psychology could be a significant step in that direction, fostering a more nuanced understanding of AI and enabling us to use, regulate, and improve these systems more effectively.
——————-
PS from Gu: this was written by GPT 4, using my previous blog post as a prompt. I largely agreed with the points here and admired GPS4’s ability to organize language.