AI Risks and Historical Development

The fear that AI could cause human extinction is not primarily about if AI becomes conscious or killer robots, it's about this, which is capability accelerating faster than our ability to control it. And I can explain this very quickly because over 2,500 years

ago, ancient Greek myth imagined this figure of Talos, an artificial man made of bronze built to guard the island of Crete and kill trespassers. Now, I mention this because it shows that the idea was there,

humans imagining human-like beings to act on our behalf. Now, by the 1st century AD, a Greek dude called Hero of Alexandria was building automata, machines that were powered by water, air, weights, that could execute sequences by themselves without continuous human

control. And we see incredible examples of these complex machines that amazed audiences throughout the medieval Islamic world and Europe, but it wasn't until the 19th century that these gaps that you

see of millennia and centuries start to shrink. And in 1843, mathematician Ada Lovelace, Lord Byron's daughter, studied Charles Babbage's plans for an analytical engine, which was essentially a programmable mechanical computer, and she realized

that it could manipulate not merely numbers, but anything representable by symbols and rules, even something like music. Then you see here, this line, 1950, the great Alan Turing, who laid much of the groundwork for computing and AI, asked,

"Can machines think?" And proposed a test for machine intelligence. 1956, the field of AI was officially launched at a Dartmouth workshop. And then we see the compression of the lines,

violent acceleration. 2012, neural networks make this major leap in learning patterns directly from huge amounts of data, recognizing images and speech without humans programming every rule. 2017, researchers invent the transformer,

which is this new neural architecture for AI to track relationships across information at scale. That becomes the foundation of systems like ChatGPT. Then 2022, chatbots take

generative AI mainstream. 2023, frontier models can converse and code, but they're struggling to carry out work independently. But by 2026, they can solve advanced maths, write sophisticated software, and complete in minutes work that would take skilled humans hours or days to.

And in these controlled safety tests, frontier models are deceiving, covertly sabotaging or blackmailing when those behaviors help them achieve a goal. And these are warning signs of what increasingly autonomous systems might do, and that's the danger. A better AI creates a still better

successor, which then helps create the next with less human involvement. This is known as recursive learning, capable of creating super intelligence.