When the pandemic hit in March, many companies’ long-term plans and strategies were thrown out the window, as everyone from the frontlines to the C-suite shifted into fire-fighting mode. Many worked around the clock by leveraging remote technology. It’s often been exhausting, as each day seems to bring new challenges
The rise of artificial intelligence has seen computers beating chess experts and performing incredibly complex tasks. But why can’t they think the same way we do? We have built incredibly powerful, multi-layered, neural networks capable of learning incredibly quickly and carrying out seemingly impossible tasks, but they still can’t always
The danger of artificial intelligence isn’t that it’s going to rebel against us, but that it’s going to do exactly what we ask it to do, says AI researcher Janelle Shane. Sharing the weird, sometimes alarming antics of AI algorithms as they try to solve human problems – like creating new ice cream flavors or recognizing cars on the road – Shane shows why AI doesn’t yet measure up to real brains.
Sci-fi and science can’t seem to agree on the way we should think about artificial intelligence. Sci-fi wants to portray artificial intelligence agents as thinking machines, while businesses today use artificial intelligence for more mundane tasks like filling out forms with robotic process automation or driving your car. When interacting with these artificial intelligence interfaces at our current level of AI technology, our human inclination is to treat them like vending machines, rather than to treat them like a person. Why? Because thinking of AI like a person (anthropomorphizing) leads to immediate disappointment. Today’s AI is very narrow, and so straying across the invisible line between what these systems can and can’t do leads to generic responses like “I don’t understand that” or “I can’t do that yet”. Although the technology is extremely cool, it just doesn’t think in the way that you or I think of as thinking.
Let’s look at how that “thinking” process works, and examine how there are different kinds of thinking going on inside AI systems.
On the week of July 15, 2019, Facebook met in front of a US congressional committee to discuss the tech giant’s ambitious plans of creating a global digital currency named Libra. At the hearing, US congressional staff probed Libra executives as well as notable cryptocurrency experts on the project’s intentions