Although we are mostly interested in the politics of AI, there is also a reverse way of understanding how people form political opinions, using principles from AI. Neuroscientists have been building interesting bridges.
There are many techniques used for building AI systems. But the recent spectacular success of AI is mainly due to advances in artificial neural networks. We will try to understand the concepts behind them.
The most powerful model of intelligence is the human brain. How much of this power do we understand? How does the brain compute? Will we ever be able to design computations that will match all that complexity?
Social networks are large graphs of data. Your digital twin is a node in these graphs. Could all these graphs be connected into one massive graph and also connected to the graph of all human knowledge?
So far, we have built our knowledge of AI upwards. Now it's time to go back and ask foundational questions. Do we really understand what we are building? Are we setting the correct initial conditions for safe AI systems?
We can now put together ideas from the preceding articles. If you have powerful neural networks working on large graphs and adapt them to quantum computing, it is natural to envisage that an intelligence explosion will happen.