This book-length article combines several peer reviewed papers and new material to analyze the issues of ethical artificial intelligence (AI). The behavior of future AI systems can be described by mathematical equations, which are adapted to analyze possible unintended AI behaviors and ways that AI designs can avoid them. This article makes the case for utility-maximizing agents and for avoiding infinite sets in agent definitions. It shows how to avoid agent self-delusion using model-based utility functions and how to avoid agents that corrupt their reward generators (sometimes called "perverse instantiation") using utility functions that evaluate outcomes at one point in time from the perspective of humans at a different point in time. It argues that agents can avoid unintended instrumental actions (sometimes called "basic AI drives" or "instrumental goals") by accurately learning human values. This article defines a self-modeling agent framework and shows how it can avoid problems of resource limits, being predicted by other agents, and inconsistency between the agent's utility function and its definition (one version of this problem is sometimes called "motivated value selection"). This article also discusses how future AI will differ from current AI, the politics of AI, and the ultimate use of AI to help understand the nature of the universe and our place in it.
CHENNAI: Google DeepMind's AlphaGo, an artificial intelligence programme developed using deep neural networks and machine learning techniques, hit global headlines last year when it beat South Korean Go grandmaster Lee Sedol to win the series 4-1. However, not many know that AlphaGo has consumed a whopping 30,000 watts of power to complete the task, while the human brain consumes around 20 watts! What gives the human brain such efficiency has so far proven elusive to replicate in computers. Not surprisingly, man's most defining organ is also the least understood. Although an adult human brain weighing 1.4 kg is made up of close to 100 billion neurons, scientists do not know how many different kinds of human neurons exist.
Science-fiction can sometimes be a good guide to the future. In the film Upgrade (2018) Grey Trace, the main character, is shot in the neck. His wife is shot dead. Trace wakes up to discover that not only has he lost his wife, but he now faces a future as a wheelchair-bound quadriplegic. He is implanted with a computer chip called Stem designed by famous tech innovator Eron Keen – any similarity with Elon Musk must be coincidental – which will let him walk again.
One balmy May evening, thirty of Silicon Valley's top entrepreneurs gathered in a private room at the Berlinetta Lounge, in San Francisco. Paul Graham considered the founders of Instacart, DoorDash, Docker, and Stripe, in their hoodies and black jeans, and said, "This is Silicon Valley, right here." All the founders were graduates of Y Combinator, the startup "accelerator" that Graham co-founded: a three-month boot camp, run twice a year, in how to become a "unicorn"--Valleyspeak for a billion-dollar company. Thirteen thousand fledgling software companies applied to Y Combinator this year, and two hundred and forty were accepted, making it more than twice as hard to get into as Stanford University. After graduating thirteen hundred startups, YC now boasts the power--and the peculiarities--of an island nation. At the noisy end of the room, Graham was cheerfully encouraging improbable schemes. At the quiet end, Sam Altman was absorbed in private calculations. When founders came over to ...