Existential risk from advanced artificial intelligence | Wikipedia audio article
Channel: wikipedia tts
Date: 14/01/2019

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Existential_risk_from_artificial_general_intelligence


00:03:29 1 Overview
00:07:01 2 History
00:12:03 3 Basic argument
00:17:26 4 Sources of risk
00:17:36 4.1 Poorly specified goals: "Be careful what you wish for" or the "Sorcerer's Apprentice" scenario
00:22:44 4.2 Difficulties of modifying goal specification after launch
00:23:34 4.3 Instrumental goal convergence: Would a superintelligence just ignore us?
00:26:49 4.4 Orthogonality: Does intelligence inevitably result in moral wisdom?
00:31:26 4.4.1 "Optimization power" vs. normatively thick models of intelligence
00:33:28 4.4.2 Anthropomorphism
00:36:37 4.5 Other sources of risk
00:37:40 5 Timeframe
00:41:46 6 Scenarios
00:47:03 7 Reactions
00:51:25 7.1 Endorsement
00:52:15 7.2 Skepticism
00:55:29 7.3 Indifference
00:56:44 8 Consensus against regulation
00:59:52 9 Organizations
01:00:30 10 See also



Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago.

Learning by listening is a great way to:
- increases imagination and understanding
- improves your listening skills
- improves your own spoken accent
- learn while on the move
- reduce eye strain

Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone.

Listen on Google Assistant through Extra Audio:
https://assistant.google.com/services/invoke/uid/0000001a130b3f91
Other Wikipedia audio articles at:
https://www.youtube.com/results?search_query=wikipedia+tts
Upload your own Wikipedia articles through:
https://github.com/nodef/wikipedia-tts
Speaking Rate: 0.7118829956764858
Voice name: en-GB-Wavenet-B


"I cannot teach anybody anything, I can only make them think."
- Socrates


SUMMARY
=======
Existential risk from artificial general intelligence is the hypothesis that substantial progress in artificial general intelligence (AGI) could someday result in human extinction or some other unrecoverable global catastrophe. For instance, the human species currently dominates other species because the human brain has some distinctive capabilities that other animals lack. If AI surpasses humanity in general intelligence and becomes "superintelligent", then this new superintelligence could become powerful and difficult to control. Just as the fate of the mountain gorilla depends on human goodwill, so might the fate of humanity depend on the actions of a future machine superintelligence.The likelihood of this type of scenario is widely debated, and hinges in part on differing scenarios for future progress in computer science. Once the exclusive domain of science fiction, concerns about superintelligence started to become mainstream in the 2010s, and were popularized by public figures such as Stephen Hawking, Bill Gates, and Elon Musk.One source of concern is that a sudden and unexpected "intelligence explosion" might take an unprepared human race by surprise. For example, in one scenario, the first-generation computer program found able to broadly match the effectiveness of an AI researcher is able to rewrite its algorithms and double its speed or capabilities in six months of massively parallel processing time. The second-generation program is expected to take three months to perform a similar chunk of work, on average; in practice, doubling its own capabilities may take longer if it experiences a mini-"AI winter", or may be quicker if it undergoes a miniature "AI Spring" where ideas from the previous generation are especially easy to mutate into the next generation. In this scenario the system undergoes an unprecedently large number of generations of improvement in a short time interval, jumping from subhuman performance in many areas to superhuman performance in all relevant areas. More broadly, examples like arithmetic and Go show that progress from human-level AI to superhuman ability is sometimes extremely rapid.A second source of concern is that controlling a superintelligent machine (or even instilling it with human-compatible values) may be an even harder problem than naïvely supposed. Some AGI researchers believe that a superintelligence would naturally resist attempts to shut it off, and that preprogramming a superintelligence with complicated human values may be an extremely difficult technical task. In contrast, skeptics such as Facebook's Yann LeCun argue that superintelligent machines will have no desire for self-preservation.