Posts
 |
| Photo: Getty Images |
Before we can design
ethical artificial intelligence, regulate AI appropriately or allocate
tasks to the right systems, we need to know what AI is. How do machines
think now and what can we expect in the future? Which tasks are suited
for AI, which ones are not, and why? To answer such questions, we need a nuanced understanding of different kinds of intelligence.
AI’s original take on intelligence can be traced back to Thomas Hobbes’s maxim “Reason ... is nothing but reckoning.” Interpreted as the manipulation of symbolic representations, this idea gave rise to the first generation of AI—dubbed Good Old-Fashioned AI, or GOFAI, by the late philosopher John Haugeland. A different approach to intelligence underlies contemporary deep-learning systems and other forms of second-wave AI—the systems achieving such stunning results in game-playing, facial recognition, medical diagnosis and the like...
AI’s original take on intelligence can be traced back to Thomas Hobbes’s maxim “Reason ... is nothing but reckoning.” Interpreted as the manipulation of symbolic representations, this idea gave rise to the first generation of AI—dubbed Good Old-Fashioned AI, or GOFAI, by the late philosopher John Haugeland. A different approach to intelligence underlies contemporary deep-learning systems and other forms of second-wave AI—the systems achieving such stunning results in game-playing, facial recognition, medical diagnosis and the like...
What, then, of the human case? Will second-wave AI, amplified by faster processors, more data and better algorithms, reach AI’s holy grail of artificial general intelligence, resulting in systems equal to or surpassing humans?
No, it will not.
Source: Scientific American
