The rapid advance of artificial intelligence raises an intriguing question - could machines ever truly think like humans? Google's DeepMind AI recently beat a human champion at the complex game Go, and IBM's Watson defeated Jeopardy champions. Yet some argue that however intelligent machines appear, human cognition remains far too complex to fully replicate. So who's right? Will AIs ever match human intelligence?
Definitions Matter
First, we must define intelligence. General problem-solving ability, creativity, social skills, emotion, self-awareness and other qualities characterize human intellect. But no consensus exists on whether an intelligent machine needs all these attributes.
A more functional definition may suffice: intelligence is achieving complex goals in a wide range of environments. By this standard, AI systems already exhibit intelligence, just not of the human variety.
The AI Approach
Current AI relies on data processing and statistical learning. Given enough data, machine learning algorithms can optimize to incredible levels beyond humans in narrow tasks. AI systems even creatively generate art, music and language.
But this method lacks true comprehension. AI cannot yet common sense, imagine counterfactuals or understand causality like humans can. Their knowledge remains confined to patterns in data.
Some theorists propose that intelligence simply emerges from connecting inputs and outputs through many layers of abstraction. In that model, human-like general intelligence will naturally arise in AI systems as computational power increases.
The Biological Perspective
However, humans exhibit innate abilities that may not emerge through machine learning alone. For example, babies have primitive mental models of objects and forces before any learning occurs. This inborn knowledge scaffolding may bootstrap human cognition.
Additionally, the human brain processes information fundamentally differently than computers. Our brains use slow, analog, massively parallel connections with complex feedback loops. In contrast, AI relies on fast, digital, serial steps in discrete layers.
It remains unclear if intelligence requires our brand of biological computation. Our cognition may depend on our embodiment or evolutionary history as well.
Hybrid Systems
Alternatively, future systems could combine artificial and biological intelligence. Brain-computer interfaces that connect neurons to electronics could achieve new cognitive capabilities.
Uploading human minds to create conscious AI duplicates also remains speculative. But some researchers aim to successfully map detailed connectomes of brain activity.
Testing for True Intelligence
Of course, measuring general intelligence itself poses challenges. An AI that achieves human-level conversational ability provides insufficient evidence by itself. Instead, cognitive scientists propose formal tests to measure abstract reasoning, imagination and social skills.
Examples include:
- Feeling of Life test - can AI make humans empathize with seemingly conscious entities?
- Raven's Progressive Matrices - assess pattern reasoning and novel problem solving.
- Visual Turing Test - evaluate imaginative drawing and visual scene design.
- Winograd Schema Challenge - assess common sense knowledge through language.
Passing these tests robustly would indicate advances toward human-like intelligence.
The Hard Problem of Consciousness
Finally, some posit that no intelligence can be considered human-like without consciousness - the hard problem in neuroscience. We know human brains generate subjective experience. Can silicon chips?
Some argue there is no reason physical computation could not produce consciousness. Others maintain it will only emerge through specific biological mechanisms.
Philosophers continue to debate theories of consciousness and if AI systems could ever experience awareness. This question may remain unresolved until much more advanced AI emerges.
Will AI Match Human Cognition?
Overall, replicating the breadth and fluidity of human intelligence in machines remains a monumental challenge. Truly human-like AI systems likely require uncomputable functions, embodiment, intrinsic motivation and other features mainstream AI research has yet to capture.
But machine intelligence will likely continue advancing in its own direction. And with human guidance, AI may yet solve problems far exceeding our biological brains' abilities.
Though matching our consciousness and general intellect may be tricky, the future of AI remains profoundly promising if we forge the path ahead wisely.