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"It can be expected that supercomputers will soon surpass human capabilities in almost all areas—somewhere between 2020 and 2060...Is this alarmism?" Short ans

"It can be expected that supercomputers will soon surpass human capabilities in almost all areas—somewhere between 2020 and 2060...Is this alarmism?" Short answer: Yes. What is the evidence for this claim, upon which the premise of this article rests? The existence of algorithms that simulate human game play today is hardly it. The authors have fallen into the trap of accepting the nomenclature of "artificial intelligence" without further questions. There is nothing "artificial" nor "intelligent" about it. Rather, machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases. The danger is in their human programmers being non-introspective of those biases, not in the algorithms themselves. Thus I personally am much more fearful of human-made decisions than non-human ones. Don't hate the player, hate the game.

hacker_9 10y ago
Glad your reply is top. To be honest we could do with less of these fluff pieces on HN, leave them to Reddit and Facebook.
j2kun 10y ago
Or, as it stands today, human decision makers using the output of these algorithms as a signal, without understanding the potential flaws of that signal. "I just did what the computer recommended" Someone (can't remember who) said it better: "You don't want to be an edge case in this brave new world."
- ams6110 10y ago
  "I was just following orders" the excuse for most of the worst behavior of humans.
  - chronicx0 10y ago
    As long as I get paid my immensely large machine learning salary, I will follow orders all year.
  - j2kun 10y ago
    The difference is they have the power to make a decision.
- narrator 10y ago
  "Why did the computer recommend that?" "No one knows, not even the programmers who wrote it! Deep learning is a black box!"
  - jodrellblank 10y ago
    https://en.wikipedia.org/wiki/The_Machine_That_Won_the_War_(short_story) https://en.wikipedia.org/wiki/The_Machine_That_Won_the_War_(... - Asimov, 1961
Houshalter 10y ago
There's this: http://www.nickbostrom.com/papers/survey.pdf http://www.nickbostrom.com/papers/survey.pdf >We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. This survey is a few years old. Discussion and knowledge about AI risk has increased considerably since then. And AI itself has made remarkable progress in that time as well. It's amazing how much progress there has been in AI in just the last 5 years. Who knows where it will be in 40 years. Look where computer technology was 40 years ago.
- j2kun 10y ago
  Is there an established, rigorous definition of "high level machine intelligence"? Or even a concrete list of sufficient criteria? Every single discussion I've encountered leaves the notion undefined, or just "I'll know it when I see it"
  - Houshalter 10y ago
    Artificial General Intelligence is roughly defined as a machine that can do all the things a human can do. For example, an AI capable of doing AI research and programming computers, would be AGI. The Turing test (as Turing originally described it, not garbage like chatbot competitions) is the most widely accepted standard of AGI. Superintelligence goes well beyond that. A machine with cognitive abilities far beyond humans. I don't think such a machine is very unlikely even in the near future. It's unreasonable to believe that humans are the pinnacle of intelligence. We are just the very first intelligent creature to evolve. Our brains are heavily resource constrained by size and energy. And neurons are many orders of magnitude slower than transistors. And also far larger and less compact.
    - rtx 10y ago
      So how will this intelligent thing come about.
Cybiote 10y ago
Without disagreeing (nor agreeing), what do you mean by intelligence? A lot of the disagreements I see is from people disbelieving that "mere" math and algorithms can exhibit intelligence. A mystical sort of Intelligence of the Gaps. I don't think that is your stance but I'd be interested in clarification.
joshmarlow 10y ago
> Rather, machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases. Maybe we shouldn't call Supervised learning techniques "Artificial Intelligence", but instead "Memoized Intelligence"? Then again, it's probably a spectrum from memoized intelligence to "true" intelligence.
- kochthesecond 10y ago
  Fuck, I am also trained on a set of human derived data and past experiences. What even is intelligence?
  - joshmarlow 10y ago
    Totally agreed; intelligence (IMHO) is all about using pattern matching to model and reason about a domain. Social things like us get some of that acquired pattern matching knowledge from other social things. I guess the difference is that supervised learning systems can't yet make an autonomous effort to acquire new knowledge from other social things.
F_J_H 10y ago
I think you've missed the point of the article. It's not completely about AI per se, but about the broader issue of technology in general bringing us to new territory with respect to the ability to control and/or manipulate society, which could have disastrous unintended consequences. Therefore, we need to be proactive about policies that would protect against unfettered influence by those controlling the technology. You've said the equivalent of "guns don't kill people. People kill people".
- jkestelyn 10y ago
  There are numerous historical examples of societal manipulation (of the most extreme kind) that had little to do with technology. I don't disagree about the need for policies; I just think those policies need to be directed toward humans as the weak link in the chain, not machines. This is not like gun control where a single person with a weapon can do a lot of unchecked damage, and thus access to guns needs to be controlled. Very few have access/can do damage with an algorithm.
  - intended 10y ago
    Which is the meat of the article. This is definitely the point to make a "did you read the full article" check. My reading of it was that people were clearly seriously concerned about the current state of the art. The article also considered Future possibilities.
xbmcuser 10y ago
We don't need true artificial intelligence. Just pseudo intelligence will kill off a lot of jobs. The most hurt will be the developed countries. Let just say a few million driving jobs go because of Ai. That will snowball and remove millions of other supporting jobs. Billions of dollars will stop circulating in the economy as most of it will go into the pockets of corporations and rich people who can afford to owns stocks of these companies. Instead of being used.
tastythrowaway2 10y ago
"...machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases." This one point simply cannot be stressed enough.
george_ciobanu 10y ago
I agree with you on the first points. We don't know how soon computers will match us in intelligence and they're still underpowered but 2 things might accelerate their rise: 1. GPU computing. Much more similar to the brain. 2. IoT - it might bring computers the senses humans have today. A self-correcting ML system with access to broad sensors, huge computing resources and the Internet is starting to look surprisingly similar to our abilities and data access.
narrator 10y ago
>Rather, machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases The AI that plays Go is now better than all Go Players and it trains by playing itself. It was bootstrapped by analyzing human games, but now it's past that. Theoretically reinforcement learning AIs could have access to deeper levels of understanding than just by copying humans because they can build upon experience. These are limited domains for now, but I think the first startling AI will come from chatbots that can come up with novel arguments. Watch the chatbot space. When someone comes up with a really good chatbot that can come up with creative responses, that will really be an AI turning point. All the deep learning ones I've seen so far are like talking to someone with moderate dementia. They forget things from earlier in the conversation and go into conversational loops.
- dragonwriter 10y ago
  Go is an objectively defined game; anything dealing with the real world is going to involve subjective human biases in the criteria.
  - 1MM1 10y ago
    AI beat humans at poker, which is a game with incomplete information. https://www.theguardian.com/technology/2017/jan/30/libratus-poker-artificial-intelligence-professional-human-players-competition https://www.theguardian.com/technology/2017/jan/30/libratus-... "The algorithms that power Libratus aren’t specific to poker, which means the system could have a variety of applications outside of recreational games, from negotiating business deals to setting military or cybersecurity strategy and planning medical treatment – anywhere where humans are required to do strategic reasoning with imperfect information. “Poker is the least of our concerns here,” said Roman V Yampolskiy, a professor of computer science at the University of Louisville. “You have a machine that can kick your ass in business and military applications. I’m worried about how humanity as a whole will deal with that.”
    - lsy 10y ago
      Poker may have incomplete information, but it's still an objectively-defined game. The cards, the "win" state, all of that stuff is trivially encodable and well-defined.
make3 10y ago
the thing is that deep learning is like 3 years old. I'm 28 years old and even I have seen the world without the internet, forget about cellphones and smartphones What I mean to say is, progress is incredibly, impossibly blazingly fast. 2060 is extreeeemely far away.
- rgbrenner 10y ago
  Deep learning is at least 50 years old, depending on when you want to start counting. Take a look at Ivakhnenko and Lapa's paper "Cybernetic predicting devices" from 1965, that had the first algo. There's been a lot of work since then during the 70s, 80s, 90s, through today. In fact the idea goes back even further to the 1940s, when the first papers were published about how NNs could possibly work. Edit: found this page that has the history: http://www.scholarpedia.org/article/Deep_Learning http://www.scholarpedia.org/article/Deep_Learning

hacker_9 10y ago

Glad your reply is top. To be honest we could do with less of these fluff pieces on HN, leave them to Reddit and Facebook.

j2kun 10y ago

Or, as it stands today, human decision makers using the output of these algorithms as a signal, without understanding the potential flaws of that signal. "I just did what the computer recommended" Someone (can't remember who) said it better: "You don't want to be an edge case in this brave new world."

ams6110 10y ago
"I was just following orders" the excuse for most of the worst behavior of humans.
- chronicx0 10y ago
  As long as I get paid my immensely large machine learning salary, I will follow orders all year.
- j2kun 10y ago
  The difference is they have the power to make a decision.
narrator 10y ago
"Why did the computer recommend that?" "No one knows, not even the programmers who wrote it! Deep learning is a black box!"
- jodrellblank 10y ago
  https://en.wikipedia.org/wiki/The_Machine_That_Won_the_War_(short_story) https://en.wikipedia.org/wiki/The_Machine_That_Won_the_War_(... - Asimov, 1961

Houshalter 10y ago

There's this: http://www.nickbostrom.com/papers/survey.pdf http://www.nickbostrom.com/papers/survey.pdf >We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that high-level machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity. This survey is a few years old. Discussion and knowledge about AI risk has increased considerably since then. And AI itself has made remarkable progress in that time as well. It's amazing how much progress there has been in AI in just the last 5 years. Who knows where it will be in 40 years. Look where computer technology was 40 years ago.

j2kun 10y ago
Is there an established, rigorous definition of "high level machine intelligence"? Or even a concrete list of sufficient criteria? Every single discussion I've encountered leaves the notion undefined, or just "I'll know it when I see it"
- Houshalter 10y ago
  Artificial General Intelligence is roughly defined as a machine that can do all the things a human can do. For example, an AI capable of doing AI research and programming computers, would be AGI. The Turing test (as Turing originally described it, not garbage like chatbot competitions) is the most widely accepted standard of AGI. Superintelligence goes well beyond that. A machine with cognitive abilities far beyond humans. I don't think such a machine is very unlikely even in the near future. It's unreasonable to believe that humans are the pinnacle of intelligence. We are just the very first intelligent creature to evolve. Our brains are heavily resource constrained by size and energy. And neurons are many orders of magnitude slower than transistors. And also far larger and less compact.
  - rtx 10y ago
    So how will this intelligent thing come about.

Cybiote 10y ago

Without disagreeing (nor agreeing), what do you mean by intelligence? A lot of the disagreements I see is from people disbelieving that "mere" math and algorithms can exhibit intelligence. A mystical sort of Intelligence of the Gaps. I don't think that is your stance but I'd be interested in clarification.

joshmarlow 10y ago

> Rather, machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases. Maybe we shouldn't call Supervised learning techniques "Artificial Intelligence", but instead "Memoized Intelligence"? Then again, it's probably a spectrum from memoized intelligence to "true" intelligence.

kochthesecond 10y ago
Fuck, I am also trained on a set of human derived data and past experiences. What even is intelligence?
- joshmarlow 10y ago
  Totally agreed; intelligence (IMHO) is all about using pattern matching to model and reason about a domain. Social things like us get some of that acquired pattern matching knowledge from other social things. I guess the difference is that supervised learning systems can't yet make an autonomous effort to acquire new knowledge from other social things.

F_J_H 10y ago

I think you've missed the point of the article. It's not completely about AI per se, but about the broader issue of technology in general bringing us to new territory with respect to the ability to control and/or manipulate society, which could have disastrous unintended consequences. Therefore, we need to be proactive about policies that would protect against unfettered influence by those controlling the technology. You've said the equivalent of "guns don't kill people. People kill people".

jkestelyn 10y ago
There are numerous historical examples of societal manipulation (of the most extreme kind) that had little to do with technology. I don't disagree about the need for policies; I just think those policies need to be directed toward humans as the weak link in the chain, not machines. This is not like gun control where a single person with a weapon can do a lot of unchecked damage, and thus access to guns needs to be controlled. Very few have access/can do damage with an algorithm.
- intended 10y ago
  Which is the meat of the article. This is definitely the point to make a "did you read the full article" check. My reading of it was that people were clearly seriously concerned about the current state of the art. The article also considered Future possibilities.

xbmcuser 10y ago

We don't need true artificial intelligence. Just pseudo intelligence will kill off a lot of jobs. The most hurt will be the developed countries. Let just say a few million driving jobs go because of Ai. That will snowball and remove millions of other supporting jobs. Billions of dollars will stop circulating in the economy as most of it will go into the pockets of corporations and rich people who can afford to owns stocks of these companies. Instead of being used.

tastythrowaway2 10y ago

"...machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases." This one point simply cannot be stressed enough.

george_ciobanu 10y ago

I agree with you on the first points. We don't know how soon computers will match us in intelligence and they're still underpowered but 2 things might accelerate their rise: 1. GPU computing. Much more similar to the brain. 2. IoT - it might bring computers the senses humans have today. A self-correcting ML system with access to broad sensors, huge computing resources and the Internet is starting to look surprisingly similar to our abilities and data access.

narrator 10y ago

>Rather, machine-learning algorithms are trained on a diet of human-derived data that is simply a reflection of existing human biases The AI that plays Go is now better than all Go Players and it trains by playing itself. It was bootstrapped by analyzing human games, but now it's past that. Theoretically reinforcement learning AIs could have access to deeper levels of understanding than just by copying humans because they can build upon experience. These are limited domains for now, but I think the first startling AI will come from chatbots that can come up with novel arguments. Watch the chatbot space. When someone comes up with a really good chatbot that can come up with creative responses, that will really be an AI turning point. All the deep learning ones I've seen so far are like talking to someone with moderate dementia. They forget things from earlier in the conversation and go into conversational loops.

dragonwriter 10y ago
Go is an objectively defined game; anything dealing with the real world is going to involve subjective human biases in the criteria.
- 1MM1 10y ago
  AI beat humans at poker, which is a game with incomplete information. https://www.theguardian.com/technology/2017/jan/30/libratus-poker-artificial-intelligence-professional-human-players-competition https://www.theguardian.com/technology/2017/jan/30/libratus-... "The algorithms that power Libratus aren’t specific to poker, which means the system could have a variety of applications outside of recreational games, from negotiating business deals to setting military or cybersecurity strategy and planning medical treatment – anywhere where humans are required to do strategic reasoning with imperfect information. “Poker is the least of our concerns here,” said Roman V Yampolskiy, a professor of computer science at the University of Louisville. “You have a machine that can kick your ass in business and military applications. I’m worried about how humanity as a whole will deal with that.”
  - lsy 10y ago
    Poker may have incomplete information, but it's still an objectively-defined game. The cards, the "win" state, all of that stuff is trivially encodable and well-defined.

make3 10y ago

the thing is that deep learning is like 3 years old. I'm 28 years old and even I have seen the world without the internet, forget about cellphones and smartphones What I mean to say is, progress is incredibly, impossibly blazingly fast. 2060 is extreeeemely far away.

rgbrenner 10y ago
Deep learning is at least 50 years old, depending on when you want to start counting. Take a look at Ivakhnenko and Lapa's paper "Cybernetic predicting devices" from 1965, that had the first algo. There's been a lot of work since then during the 70s, 80s, 90s, through today. In fact the idea goes back even further to the 1940s, when the first papers were published about how NNs could possibly work. Edit: found this page that has the history: http://www.scholarpedia.org/article/Deep_Learning http://www.scholarpedia.org/article/Deep_Learning