How AI Can Help Us Envision More Diverse Intelligence

Key points:

• The notion of intelligence as a linear hierarchy with humans above animals and AI at the top is flawed and limiting. We need to move beyond the idea of an "intelligence staircase."
• Creating AI that simply mimics human intelligence is too narrow a focus. We should broaden our view to consider other forms and manifestations of intelligence beyond just replicating human cognition.
• The "morphospace of cognitive complexity" provides a useful framework for visualizing and exploring the vast landscape of possible intelligences across dimensions of computational complexity, autonomy, and social interaction.
• There is currently a gap between biological and artificial systems in terms of autonomy and social complexity. Biological evolution has driven organisms to increasing levels of independent action, adaptability, and social coordination that most current AI systems lack.
• Humans are cognitively distinct in our highly complex individual and social intelligence, and ability to flexibly shape our environment through culture and technology in an "extended mind." But AI is not bound by biological constraints and could potentially develop radically different forms of alien intelligence.

The notion of intelligence as a linear hierarchy, with humans perched above animals and AI at the summit, is an enduring but flawed vision that has captivated the AI community for far too long. This “intelligence staircase” metaphor simplistically ranks the complexity of cognitive abilities and fails to capture the true essence of intelligence in all its forms. AI luminary Yann LeCun has often spoken about the incremental evolution of machine intelligence, suggesting that before AI can rival human intellect, it must first navigate the more modest cognitive landscapes of a mouse or a rat, much like a child learning to make sense of the world. He envisions a gradual climb, with AI systems developing and refining their capabilities step by step, reminiscent of the natural progression seen in the animal kingdom.

The ladder metaphor of intelligence, while illustrative of cognitive advancements such as planning and problem-solving, might not serve us well in the grand scheme of AI development. Part of this myopia is the idea that the best use of AI is to create AGI. This pursuit is so narrowly focused on emulating and surpassing human intelligence that it’s no wonder people worry about a future where AI reigns supreme.

The bias of re-creating human intelligence is rooted in the very inception of AI. What else is the Turing Test if not an instantiation of machines that outwit humans at being human? Are we too fixated on creating machines that mirror human intelligence? Could this narrow focus limit the potential and scope of what AI can achieve?

How else might we think about intelligence and, by implication, other ways to place the idea of an artificial—or hybrid—intelligence?