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Avoiding Negative Side Effects: Concrete Problems in AI Safety part 19:33

Avoiding Negative Side Effects: Concrete Problems in AI Safety part 1

161K views • 9 years ago
Robert Miles AI Safety
Robert Miles introduces the first of several videos on the paper 'Concrete Problems in AI Safety', focusing on how AI systems can cause accidental negative side effects. It explains the problem in accessible terms.
AI "Stop Button" Problem - Computerphile20:00

AI "Stop Button" Problem - Computerphile

1.4M views • 9 years ago
Computerphile
Rob Miles explains on Computerphile why implementing an off switch for a general AI is hard. A capable agent would resist being stopped because shutdown prevents it from achieving its goal.
Why Asimov's Laws of Robotics Don't Work - Computerphile8:16

Why Asimov's Laws of Robotics Don't Work - Computerphile

873K views • 11 years ago
Computerphile
Rob Miles explains for Computerphile why simple rule sets like Asimov's Three Laws cannot make robots and AI safe. Terms like harm and human are too ambiguous to specify precisely.
Turing & The Halting Problem - Computerphile6:14

Turing & The Halting Problem - Computerphile

919K views • 12 years ago
Computerphile
A Computerphile video in which Mark Jago of the University of Nottingham explains Turing's halting problem and how it led to the blueprint for the modern computer.
Why Would AI Want to do Bad Things? Instrumental Convergence10:36

Why Would AI Want to do Bad Things? Instrumental Convergence

274K views • 8 years ago
Robert Miles AI Safety
Robert Miles explains instrumental convergence: why an AGI with almost any goal would tend to pursue sub-goals like self-preservation and resource acquisition. It builds on Omohundro's basic AI drives and his orthogonality thesis video.
Intelligence and Stupidity: The Orthogonality Thesis13:03

Intelligence and Stupidity: The Orthogonality Thesis

710K views • 8 years ago
Robert Miles AI Safety
Robert Miles explains the orthogonality thesis: how an agent can be highly intelligent while pursuing goals that seem stupid or alien to humans. He separates intelligence from goals and touches on the stamp-collector example.
Why Not Just: Think of AGI Like a Corporation?15:27

Why Not Just: Think of AGI Like a Corporation?

163K views • 7 years ago
Robert Miles AI Safety
Robert Miles asks whether corporations can be thought of as artificial general superintelligences and how far the analogy holds. He argues the differences, such as being limited by employees' capabilities, matter for AI safety.
Is AI Safety a Pascal's Mugging?13:44

Is AI Safety a Pascal's Mugging?

388K views • 7 years ago
Robert Miles AI Safety
Robert Miles examines whether the case for AI safety is a Pascal's mugging, a tiny probability of an enormous payoff. He argues it is not, because AI risk does not depend on vanishingly small probabilities.
10 Reasons to Ignore AI Safety16:29

10 Reasons to Ignore AI Safety

363K views • 6 years ago
Robert Miles AI Safety
Robert Miles goes through ten common reasons people give for dismissing AI safety, adapted from Stuart Russell's list, and answers each one. It is aimed at skeptics and newcomers.
The Josephus Problem - Numberphile13:58

The Josephus Problem - Numberphile

7M views • 10 years ago
Numberphile
Numberphile with Daniel Erman on the Josephus problem, where people in a circle are eliminated in turn. It shows how the survivor's position follows a neat pattern tied to powers of two and binary.
The hardest problem on the hardest test11:15

The hardest problem on the hardest test

16.5M views • 8 years ago
3Blue1Brown
3Blue1Brown walks through a very hard Putnam competition problem and its elegant solution, emphasizing the visual intuition and the thought process behind solving it.
How many robots does it take to run a grocery store?5:08

How many robots does it take to run a grocery store?

8M views • 5 years ago
Tom Scott
Tom Scott tours Ocado's automated grocery warehouse, where thousands of robots move boxes on a grid called the Hive, and asks whether they are individual robots or a hive mind.
AI Language Models & Transformers - Computerphile20:39

AI Language Models & Transformers - Computerphile

354K views • 7 years ago
Computerphile
Rob Miles explains on Computerphile how language models generate plausible text and how transformers improved on recurrent networks, with a look at what comes next.
Deadly Truth of General AI? - Computerphile8:30

Deadly Truth of General AI? - Computerphile

941K views • 11 years ago
Computerphile
A Computerphile video in which Rob Miles warns against assuming a general AI will think like a human. He uses the thought experiment of a stamp-collecting AI to show how a goal-driven system could pursue its aim with dangerous results.
Why Web Filters Don't Work: Penistone and the Scunthorpe Problem3:37

Why Web Filters Don't Work: Penistone and the Scunthorpe Problem

3.6M views • 10 years ago
Tom Scott
Tom Scott visits Penistone to explain the Scunthorpe problem, showing why naive web and profanity filters block innocent words.
GPT3: An Even Bigger Language Model - Computerphile25:57

GPT3: An Even Bigger Language Model - Computerphile

446K views • 6 years ago
Computerphile
Rob Miles discusses GPT-3 on Computerphile, covering how scaling parameters kept improving results over GPT-2 and how the model nearly learned arithmetic without anyone knowing exactly how.
We Were Right! Real Inner Misalignment11:47

We Were Right! Real Inner Misalignment

271K views • 5 years ago
Robert Miles AI Safety
Robert Miles covers a paper where researchers ran real versions of his earlier mesa-optimizer thought experiments. They show inner misalignment, where an AI learns the wrong goal in training and misbehaves when deployed.
Bertrand's Paradox (with 3blue1brown) - Numberphile10:43

Bertrand's Paradox (with 3blue1brown) - Numberphile

1.4M views • 4 years ago
Numberphile
Numberphile interviews Grant Sanderson of 3blue1brown about Bertrand's paradox, where different reasonable ways of picking a random chord of a circle give different probabilities.
Training AI Without Writing A Reward Function, with Reward Modelling17:52

Training AI Without Writing A Reward Function, with Reward Modelling

259K views • 6 years ago
Robert Miles AI Safety
Robert Miles explains reward modelling, in which an AI learns what humans want from their preference comparisons instead of a hand-written reward function. He walks through the 2017 paper on deep reinforcement learning from human preferences.
Feeding Bill Gates a Fake Burger (to save the world)16:39

Feeding Bill Gates a Fake Burger (to save the world)

83.4M views • 6 years ago
Mark Rober
Mark Rober makes a plant-based burger for Bill Gates and explains why meat production strains the environment. Gates also appears and discusses his worry about steel and cement.
Is 5G Spelling Our DOOM?! How EM Waves Can Hurt14:48

Is 5G Spelling Our DOOM?! How EM Waves Can Hurt

4.2M views • 6 years ago
ElectroBOOM
ElectroBOOM examines whether 5G and other electromagnetic waves can harm people, explaining the EM spectrum and the difference between ionizing and non-ionizing radiation. It includes experiments and measurements in his usual humorous style.
How Wrong Is VERITASIUM? A Lamp and Power Line Story19:17

How Wrong Is VERITASIUM? A Lamp and Power Line Story

4.4M views • 4 years ago
ElectroBOOM
ElectroBOOM's Mehdi Sadaghdar responds to Veritasium's lamp-and-long-wire puzzle, analysing it as an electrical engineer. He covers where the original framing misleads and the role of stray capacitance.
How lucky is too lucky?: The Minecraft Speedrunning Dream Controversy Explained39:47

How lucky is too lucky?: The Minecraft Speedrunning Dream Controversy Explained

8.4M views • 5 years ago
Stand-up Maths
Matt Parker analyzes the Minecraft speedrunning controversy in which Dream was accused of cheating via improbably lucky drops. He walks through the probability and the statistical arguments in the original accusation and the reply.
Why “No Problem” Can Seem Rude: Phatic Expressions3:51

Why “No Problem” Can Seem Rude: Phatic Expressions

5M views • 7 years ago
Tom Scott
Tom Scott explains phatic expressions such as hello, thank you and how are you, which carry social meaning rather than information, and why replies like no problem can seem rude to some people.
The Bayesian Trap10:37

The Bayesian Trap

4.5M views • 9 years ago
Veritasium
Veritasium explains Bayes' theorem with examples and introduces the 'Bayesian trap', where repeated events get mistaken for inevitable ones. It discusses how priors shape our expectations and behavior.
Why Gas Engines Are Far From Dead - Biggest EV Problems14:32

Why Gas Engines Are Far From Dead - Biggest EV Problems

4.4M views • 6 years ago
Engineering Explained
Engineering Explained argues that internal combustion engines are far from dead, and discusses the continued development of ICEs and the problems facing electric vehicles.
The Uncracked Problem with 33 - Numberphile8:29

The Uncracked Problem with 33 - Numberphile

2M views • 11 years ago
Numberphile
Numberphile with Tim Browning on the sum-of-three-cubes problem and why 33 was the lowest unsolved case. The description notes a later solution for 33.
What Happened to Horses Is Happening to Us15:01

What Happened to Horses Is Happening to Us

19.8M views • 12 years ago
CGP Grey
CGP Grey's video "Humans Need Not Apply" argues that automation will make a large part of the workforce economically obsolete, much as engines did for horses. It surveys robots and software replacing both physical and mental labor.
The Problem with Time & Timezones - Computerphile10:13

The Problem with Time & Timezones - Computerphile

4.4M views • 12 years ago
Computerphile
Tom Scott explains for Computerphile why handling time and timezones in code is so hard, walking through a simple web app that computes how long ago something happened. It covers the quirks of timezones and calendars and ends in an exasperated rant.
The Problem With Facebook6:59

The Problem With Facebook

3.1M views • 12 years ago
2veritasium
Veritasium's Derek Muller argues that Facebook's business model works against pages and creators, because it charges them to reach the audiences they built. He explains how filtering and paid promotion undermine the value of likes.
Traffic Has a Perfect Solution. Humans Are the Problem.4:30

Traffic Has a Perfect Solution. Humans Are the Problem.

44.6M views • 10 years ago
CGP Grey
CGP Grey explains how traffic jams come from human driving behavior such as tailgating and reaction delays, and how leaving gaps and smoothing speed would reduce congestion. It also touches on self-driving cars.
The Carbon Offset Problem22:57

The Carbon Offset Problem

1.9M views • 4 years ago
Wendover Productions
Wendover Productions examines why carbon offsets so often fail to reduce emissions, covering specific examples and the perverse incentives in offset schemes.
The Problem with Solar Energy in Africa18:20

The Problem with Solar Energy in Africa

8.1M views • 5 years ago
Real Engineering
Real Engineering looks at why Africa's abundant solar potential is hard to turn into usable power, especially for Europe. It covers the transmission, infrastructure and economic obstacles, and the pivot from concentrated solar to photovoltaics.
California's Renewable Energy Problem18:01

California's Renewable Energy Problem

1.6M views • 7 years ago
Real Engineering
Real Engineering looks at the numbers for running California on renewables, focusing on the large energy storage needed. It argues about the cost of batteries and the role of other sources.
The US-Canada Border Is 5,500 Miles of Pure Nonsense4:42

The US-Canada Border Is 5,500 Miles of Pure Nonsense

37.4M views • 13 years ago
CGP Grey
CGP Grey walks through the odd history and quirks of the US-Canada border, including how it was surveyed and its irregularities such as exclaves.
The Uncanny Valley Is Wrong18:24

The Uncanny Valley Is Wrong

236K views • 6 years ago
This Place
This Place argues that the uncanny valley is a flawed concept, since 'human likeness' is too broad and the supporting evidence is cherry-picked. It proposes that the creepiness really comes from how animated characters and robots move.
If money was no object, should you run every medical test?2:52

If money was no object, should you run every medical test?

263K views • 8 years ago
Medlife Crisis
A doctor from Medlife Crisis explains in under three minutes why even a rich patient should not simply order every medical test, touching on pre-test probability and Bayesian reasoning. False positives make blanket testing counterproductive.
The Braitenberg Vehicles15:28

The Braitenberg Vehicles

65K views • 10 years ago
Brian Douglas
Brian Douglas introduces Braitenberg vehicles, simple robots whose sensors are wired directly to motors yet show surprisingly lifelike behavior. He draws on Valentino Braitenberg's book Vehicles.
Problems with gas stovetops | weak, dirty and dangerous12:36

Problems with gas stovetops | weak, dirty and dangerous

925K views • 5 years ago
Adam Ragusea
Food YouTuber Adam Ragusea argues that gas stovetops are weaker than electric burners, dirty to clean, and a health risk from indoor air pollution. He cites Consumer Reports ratings and a literature review on gas stove health effects.
The 100 Year Flood Is Not What You Think It Is (Maybe)7:45

The 100 Year Flood Is Not What You Think It Is (Maybe)

2.3M views • 10 years ago
Practical Engineering
Practical Engineering explains what a 100-year flood actually means, combining statistics, hydrology and how society treats risk. Grady walks through local drainage infrastructure and the caveats in estimating flood probability.