“Machines will be capable, within twenty years, of doing any work a man can do.”
So said Herbert Simon, an early artificial intelligence researcher, in 1965.
So said Herbert Simon, an early artificial intelligence researcher, in 1965.
Herb Simon : Earthware Symposium : October 2000 : Carnegie Mellon University
https://www.youtube.com/watch?v=EZhyi-8DBjc
Published on Oct 30, 2014
"...I don't believe that predicting the future is really what we're about. After all, we ourselves, or at least the younger ones among us, are going to be a part of the future. So, being a part of the future, our task isn't to predict it. It is to design it..."
CMU's Herbert A. Simon reflects on how computers will continue to shape the world
October 19, 2000
Interview below By Byron Spice, Post-Gazette Science Editor
A lifelong student of how people make decisions, Simon, 84, has focused on how people use rules of thumb. These mental shortcuts depend on our ability to recognize patterns and associate them with things we have previously experienced. They are essential, he observes, because people rarely have all the time and knowledge necessary to rationally assess situations.
It's an idea at the basis of "bounded rationality" -- the theory that won him the Nobel Prize in economics in 1978. While conventional economists maintained that people make rational choices to obtain the best commodity at the best price, Simon argued that inevitable limits on knowledge and analytical ability force people to choose the first option that "satisfices" or is good enough for them, whether they are buying a loaf or bread or choosing a spouse.
In pursuing these ideas, Simon followed his own rules of thumb. He began as a political scientist, studying how parks department budgets were made in his native Milwaukee, which led him into economics and business administration. At Carnegie Tech in the mid-1950s, he and Allen Newell incorporated a new tool -- the computer -- into the study of decision making. In the process, they invented the first thinking machine and a field that would become known as artificial intelligence.
Simon's continuing interest in how people think landed him in Carnegie Mellon University's psychology department, where he continues his pursuit of cognitive science.
Symposium to explore computers' potential
The potential of computers to make the world a better place or to create problems will be discussed by experts in psychology, artificial intelligence and the arts during a day-long symposium Thursday at Carnegie Mellon University.
Q: Do you consider your Nobel work on bounded rationality to be your most significant contribution to science?
A: Not specifically that, but it really is very closely related to the work I do in computer science. I like to think that since I was about 19 I have studied human decision making and problem solving. Bounded rationality was the economics part of that. When computers came along, I felt for the first time that I had the proper tools for the kind of theoretical work I wanted to do. So I moved over to that and that got me into psychology.
Q: So you have moved from field to field as you could bring new tools to bear on your study of decision making?
A: I started off thinking that maybe the social sciences ought to have the kinds of mathematics that the natural sciences had. That works a little bit in economics because they talk about costs, prices and quantities of goods. But it doesn't work a darn for the other social sciences; you lose most of the content when you translate them to numbers.
So when the computer came along -- and more particularly, when I understood that a computer is not a number cruncher, but a general system for dealing with patterns of any type -- I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer and you didn't have to go through this straitjacket of adding a lot of numbers.
That seemed to me a tremendous breakthrough. And one of the first rules of science is if somebody delivers a secret weapon to you, you better use it.
I've spent a good deal of my last 20 years looking at decision making and problem solving involved in scientific discovery. We took major historical scientific discoveries and we said what would it take to write a computer program that, given no more information than the guy who made the discovery had, would make the same discovery?
CMU's Herbert A. Simon reflects on how computers will continue to shape the world
October 19, 2000
Interview below By Byron Spice, Post-Gazette Science Editor
A lifelong student of how people make decisions, Simon, 84, has focused on how people use rules of thumb. These mental shortcuts depend on our ability to recognize patterns and associate them with things we have previously experienced. They are essential, he observes, because people rarely have all the time and knowledge necessary to rationally assess situations.
It's an idea at the basis of "bounded rationality" -- the theory that won him the Nobel Prize in economics in 1978. While conventional economists maintained that people make rational choices to obtain the best commodity at the best price, Simon argued that inevitable limits on knowledge and analytical ability force people to choose the first option that "satisfices" or is good enough for them, whether they are buying a loaf or bread or choosing a spouse.
In pursuing these ideas, Simon followed his own rules of thumb. He began as a political scientist, studying how parks department budgets were made in his native Milwaukee, which led him into economics and business administration. At Carnegie Tech in the mid-1950s, he and Allen Newell incorporated a new tool -- the computer -- into the study of decision making. In the process, they invented the first thinking machine and a field that would become known as artificial intelligence.
Simon's continuing interest in how people think landed him in Carnegie Mellon University's psychology department, where he continues his pursuit of cognitive science.
Symposium to explore computers' potential
The potential of computers to make the world a better place or to create problems will be discussed by experts in psychology, artificial intelligence and the arts during a day-long symposium Thursday at Carnegie Mellon University.
Q: Do you consider your Nobel work on bounded rationality to be your most significant contribution to science?
A: Not specifically that, but it really is very closely related to the work I do in computer science. I like to think that since I was about 19 I have studied human decision making and problem solving. Bounded rationality was the economics part of that. When computers came along, I felt for the first time that I had the proper tools for the kind of theoretical work I wanted to do. So I moved over to that and that got me into psychology.
Q: So you have moved from field to field as you could bring new tools to bear on your study of decision making?
A: I started off thinking that maybe the social sciences ought to have the kinds of mathematics that the natural sciences had. That works a little bit in economics because they talk about costs, prices and quantities of goods. But it doesn't work a darn for the other social sciences; you lose most of the content when you translate them to numbers.
So when the computer came along -- and more particularly, when I understood that a computer is not a number cruncher, but a general system for dealing with patterns of any type -- I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer and you didn't have to go through this straitjacket of adding a lot of numbers.
That seemed to me a tremendous breakthrough. And one of the first rules of science is if somebody delivers a secret weapon to you, you better use it.
I've spent a good deal of my last 20 years looking at decision making and problem solving involved in scientific discovery. We took major historical scientific discoveries and we said what would it take to write a computer program that, given no more information than the guy who made the discovery had, would make the same discovery?
aau
CMU's Simon reflects on how computers will continue to shape the world
Monday, October 16, 2000
By Byron Spice, Post-Gazette Science Editor
Herbert Simon is the man with the golden thumb.
A lifelong student of how people make decisions, Simon, 84, has focused on how people use rules of thumb. These mental shortcuts depend on our ability to recognize patterns and associate them with things we have previously experienced. They are essential, he observes, because people rarely have all the time and knowledge necessary to rationally assess situations.
 |  |
| Nobel laureate Herbert Simon. (Darrell Sapp, Post-Gazette) |
It's an idea at the basis of "bounded rationality" -- the theory that won him the Nobel Prize in economics in 1978. While conventional economists maintained that people make rational choices to obtain the best commodity at the best price, Simon argued that inevitable limits on knowledge and analytical ability force people to choose the first option that "satisfices" or is good enough for them, whether they are buying a loaf or bread or choosing a spouse.
In pursuing these ideas, Simon followed his own rules of thumb. He began as a political scientist, studying how parks department budgets were made in his native Milwaukee, which led him into economics and business administration. At Carnegie Tech in the mid-1950s, he and Allen Newell incorporated a new tool -- the computer -- into the study of decision making. In the process, they invented the first thinking machine and a field that would become known as artificial intelligence.
Simon's continuing interest in how people think landed him in Carnegie Mellon University's psychology department, where he continues his pursuit of cognitive science.
 | |||
| Symposium to explore computers' potentialThe potential of computers to make the world a better place or to create problems will be discussed by experts in psychology, artificial intelligence and the arts during a day-long symposium Thursday at Carnegie Mellon University. The symposium marks the dedication of Newell-Simon Hall, which is named in honor of Nobel laureate Herbert Simon and the late Allen Newell, winner of the National Medal of Science. The pair were pioneers in artificial intelligence and cognitive psychology and played key roles in developing Carnegie Mellon's computer science program. The speakers at the symposium, "Earthware: A Good World in 2050. Will Computers Help or Hinder?", include Raymond Kurzweil, a leading authority on artificial intelligence; David Gelertner, a Yale University computer scientist who was injured in 1993 by one of the explosive packages mailed by Unabomber Ted Kaczynski; and Alex Singer, a director of "Star Trek" and other film and television programs. Speakers from CMU include robotics visionary Hans Moravec, Internet sociologist Robert Kraut and former computer science dean Raj Reddy. Bill Joy, a co-founder of Sun Microsystems who has warned that genetic engineering, nanotechnology and robotics could pose a threat to mankind, will appear in a "synethic interview," a technology developed at CMU that allows a person's videotaped remarks to be replayed in response to live questions. An interview of science fiction author Arthur C. Clarke, taped at his home in Sri Lanka, also will be presented. Simon will present a concluding talk. The symposium begins at 8:45 a.m. Thursday in University Center's McConomy Auditorium and will conclude with the dedication of Newell-Simon Hall at 5 p.m. The program, which includes lunch, is free to members of the Carnegie Mellon community and $30 for non-campus attendees. For information, call 412-268-8525. | |||
| |||
Simon and the late Newell are the namesakes of the university's newest building, Newell-Simon Hall, which houses computer science offices. Dedication of the $20 million, four-story structure will be marked Thursday by a scientific symposium, "Earthware: A Good World in 2050. Will Computers Help or Hinder?", in University Center.
Last Wednesday, the day when this year's Nobel in economics was awarded to Americans James Heckman and Daniel McFadden, Simon sat down with Science Editor Byron Spice to discuss the nature of scientific discovery and his thoughts about how technology will affect humans in the coming decades.
Do you consider your Nobel work on bounded rationality to be your most significant contribution to science?
A: Not specifically that, but it really is very closely related to the work I do in computer science. I like to think that since I was about 19 I have studied human decision making and problem solving. Bounded rationality was the economics part of that. When computers came along, I felt for the first time that I had the proper tools for the kind of theoretical work I wanted to do. So I moved over to that and that got me into psychology.
Q: So you have moved from field to field as you could bring new tools to bear on your study of decision making?
A: I started off thinking that maybe the social sciences ought to have the kinds of mathematics that the natural sciences had. That works a little bit in economics because they talk about costs, prices and quantities of goods. But it doesn't work a darn for the other social sciences; you lose most of the content when you translate them to numbers.
So when the computer came along -- and more particularly, when I understood that a computer is not a number cruncher, but a general system for dealing with patterns of any type -- I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer and you didn't have to go through this straitjacket of adding a lot of numbers.
That seemed to me a tremendous breakthrough. And one of the first rules of science is if somebody delivers a secret weapon to you, you better use it.
Q: In 1957, you made the famous prediction that a computer would be the world chess champion within 10 years. [IBM's Deep Blue wouldn't beat the human champ until 1997] Do you have a guess when a computer will make a Nobel-worthy discovery?
A: I'm pausing to think if that's already happened.
I've spent a good deal of my last 20 years looking at decision making and problem solving involved in scientific discovery. We took major historical scientific discoveries and we said what would it take to write a computer program that, given no more information than the guy who made the discovery had, would make the same discovery?
We focused on 19th century physics and chemistry. So, for example, we said [17th century mathematician Johannes] Kepler had some data, then available to all astronomers, on the distances of the planets from the sun and the periods of their revolution around the sun. He had that for the five inner most planets. And he started to do whatever he did, and after a while he decided that the periods went up with the square of the distances. And he published that.
The fit isn't very good. So 10 years later, he went back to it. In a couple of months, he said, oh, the period really goes up as a three-halves power of the distance, [the square of the orbital periods are proportional to the cube of their distances from the sun]. That gives you a great fit, so great that we still accept the law, [Kepler's third law of planetary motion].
So we had a little computer program called BACON, named after Sir Francis, and all we gave it were those five data points --five distances and the corresponding periods. And we said to BACON, see if you can find a pattern there. And in a couple of seconds, BACON had it.
So, what did BACON do? Did it try out all possible functions? Well, that's nonsense. No, in fact it got it on the third or fourth try.
Well, Kepler certainly would have gotten a Nobel prize. What about the computer? It didn't know anything Kepler didn't know. So evidently, it had to have similar power. And it didn't do it by brute computer strength. It had a way of generating patterns, it makes a try, it compares the try with reality and then makes an adjustment.
Q: So a computer could someday deserve a Nobel?
A: I see no deep reason why not. We already have a world champion chess player, though that one I would not claim does it in a humanoid way, although it certainly does not do it by brute force. It uses a combination of computer speed and just a load of chess knowledge.
But forget about Nobel prizes; they aren't really very important. One of my former students, Raul Valdes-Perez [a CMU senior research computer scientist] wrote a program called MECHEM. You give it what you know about the inputs and outputs of a chemical reaction but you don't know how the reaction comes about. You ask MECHEM for hypotheses about that reaction and it will give you a set of hypotheses [listing potential steps the reaction may follow]. Its ideas are interesting enough so that its results on several occasions have been published in chemical journals.
Q: Can computers help people act more rationally?
A: Anything that gives us new knowledge gives us an opportunity to be more rational.
Human knowledge has been changing from the word go and people in certain respects behave more rationally than they did when they didn't have it. They spend less time doing rain dances and more time seeding clouds.
But the big thing we have learned is that humans are very good at learning about a lot of patterns that show up in the world and associating what they know about the world with them. It's what a doctor does. He learns what measles looks like so that he can call it measles -- preferably in Latin, though -- and then get access to all that information in his [mental] encyclopedia.
We know people are good at searching for things very selectively, that is, using various rules of thumb to narrow down their searches. One of my big interests has been to see how we can give computers those capabilities. Because I don't care how big and fast computers are, they're not as big and fast as the world.
Q: This week's symposium addresses whether computers will help or hinder efforts to create a "good world." Does that assume a technology can be inherently good or bad?
A: No, not inherently -- inevitably. (Laughs). There are no morals about technology at all. Technology expands our ways of thinking about things, expands our ways of doing things. If we're bad people we use technology for bad purposes and if we're good people we use it for good purposes. That's why I'm less interested in questions of forecasting and more interested in what kinds of decisions we can make so that we do get a positive balance of the good uses of technology.
Q: So what kinds of decisions can we make to achieve that positive balance?
A: Well, first of all, we can do some thinking about what would be a sustainable and acceptable world. Notice I don't say the best of all possible worlds. I wouldn't know how to define it.
| |||
| Simon's name goes on new hallNewell-Simon Hall could be called the building that Lycos built. The $20 million building project was funded largely by Carnegie Mellon University's sale of stock in Lycos Inc., the company founded by CMU researcher Michael Mauldin, who developed the Lycos search engine for the Internet. The project added two stories to two existing buildings -- including the Field Robotics Center -- and connected them together under a single roof with a central atrium. The resulting four-story building encloses 42,000 square feet of renovated space and 65,000 square feet of new space. The building houses elements of the School of Computer Science, including the Robotics Institute, the Language Technologies Institute and the Human-Computer Interaction Institute. | |||
| |||
Q: A good enough world?
A: Yeah, a good enough world -- a satisficing world is my favorite term. And when you begin to think about that, you don't begin by thinking about machines, you think about people in the world. And you decide, well, maybe we better get a world in which we have the resources to keep it going. Maybe we ought to have a world in which things are divided between people kind of fairly.
And then we ask how do we get there? Well, almost any way of getting there involves knowing a lot about the world and how it works. That's a major place where computers come in. They can help us think.
Q: This week's symposium will address some of the ideas of Bill Joy of Sun Microsystems, who says that the combination of genetic engineering, nanotechnology and robotics could create a future in which humans may become expendable. Do you share his concerns about these technologies?
A: Oh, I think they can cause enormous harm. Imagine them in the hands of a group of people who happened to have power and thought they were the hero race. But notice how I put it -- think of them in the hands ofpeople. Again, it's ourselves who are in the center of all this and need to be in the center of our thinking.
Q: If computers can think for themselves, do people become expendable?
A: Computers thinking don't make you expendable. I think the real worry is, does this destroy what's valuable or precious about human beings? And that derives in turn from some idea that to be valuable you have to have a unique property -- you have to be different in some respect -- and that when anybody threatens human difference, whether it's Darwin or Galileo or whoever, there's a very strong reaction.
I think the mistake is in basing one's claim to worth on uniqueness. Most of us really aren't horribly unique. There are 6 billion of us. Put 'em all in one room and very few would stand out as individuals. So maybe we ought to think of worth in terms of our ability to get along as a part of nature, rather than being the lords over nature.
Q: Will machines find us expendable?
A: Well, expendability is a slightly different question. What happens at the time when they can make all the things we want to have made or can afford to have made within the earth's capacity? What do we do about it? Well, first we ought to understand how human beings behave under those circumstances.
There are plenty of historical examples. In every slave civilization there have been a group of people who didn't have to work for a living. So what did they do to make life significant for themselves?
A few of them found very ingenious things to do that really excited them and kept them busy and the fact that they didn't have to do them never bothered them. Science, in England at least, was a gentleman's game as late as the 18th century and some people found it kept them very happy.
And then there are some who focused on the usual verities of life -- family, home, relations with other people -- and when you look at the upper classes of those societies they were about as happy or unhappy as people usually are. Some extravagantly happy, some extravagantly unhappy.
So we're going to have to think about how you grow people up who find exciting things to do when there's nothing that has to be done. We're dangerously close to that for half of our society right now.
But here again, you see, technology may create a condition, but the questions are what do we do about ourselves.
We better understand ourselves pretty clearly and we better find ways to like ourselves.
Q: So, in the next 50 years, we have the potential to create our own utopia or our own hell?
A: More likely a bit of both.
CMU的西蒙反映計算機將如何繼續塑造世界
週一，2000年10月16日，
拜倫香料，郵報科學編輯
西蒙是人與金色大拇指。
人們如何做出決定，西蒙，84終身學生，一直專注於人們如何使用拇指規則。這些心理捷徑取決於我們識別模式，並與我們以前經歷過的事情聯繫起來的能力。他們是必不可少的，他觀察到，因為人們很少擁有所有必要的合理評估形勢的時間和知識。
| |
| 諾貝爾經濟學獎獲得者赫伯特·西蒙。（達雷爾薩普，郵報） |
這是在“有限理性”的基礎上的想法 - 這為他贏得了諾貝爾經濟學獎在1978年雖然傳統經濟學家認為，人們做出理性的選擇，以獲得最好的價格最好的商品理論，西蒙認為，不可避免的限制知識和分析能力迫使人們選擇第一個選項是“satisfices”，或對他們不夠好，無論是買一個麵包或饅頭或選擇配偶。
在追求這些想法，西蒙跟隨著自己的經驗法則。他開始作為一個政治學家，研究公園部門預算是如何在他的家鄉密爾沃基，這導致他進入經濟學和工商管理的。在卡內基技術在50年代中期，他和艾倫紐厄爾成立一個新的工具 - 電腦 - 進入決策的研究。在這個過程中，他們發明了第一台機器的思維和將成為被稱為人工智能的字段。
西蒙的人們是怎麼想的持續的興趣落在他卡內基·梅隆大學的心理學系，在那裡他繼續他的追求認知科學。
| |||
| 研討會探討計算機的潛力計算機的潛力，使世界變得更美好的地方或創建的問題將由心理學，人工智能專家和藝術在卡內基 - 梅隆大學的為期一天的研討會上週四期間進行討論。 本次研討會標誌著紐厄爾西門大廳，這是諾貝爾經濟學獎獲得者赫伯特·西蒙和已故的艾倫紐厄爾，美國國家科學獎章得主的名字命名的奉獻精神。 兩人是在人工智能和認知心理學的先驅，在發展卡內基梅隆大學的計算機科學項目發揮了關鍵作用。 在研討會上的發言，“？陶器：2050年威爾計算機的幫助還是不錯的阻礙世界”，包括雷蒙德·庫茲威爾，人工智能領域的權威;大衛Gelertner，誰是由炸彈客特德·卡欽斯基郵寄爆炸包之一，1993年受傷耶魯大學計算機科學家; 和Alex歌手，“星際迷航”等電影和電視節目的董事。 從CMU演講嘉賓包括機器人有遠見的漢斯·莫拉維克，互聯網羅伯特社會學家克勞特，前計算機科學系主任拉吉·瑞迪。 比爾·喬伊，Sun Microsystems公司的聯合創始人誰警告說，基因工程，納米技術和機器人技術可能對人類的威脅，會出現一個“synethic的採訪，”在CMU開發了一種技術，它允許重播一個人的錄像講話響應於活的問題。 科幻作家阿瑟·克拉克，在他的家在斯里蘭卡錄音的採訪中，也將提交。 西蒙將提出一個結論性的談話。 本次研討會週四開始於上午8:45在大學中心的麥可諾密禮堂大禮堂，將與紐維爾西門大廳下午5時的方案，其中包括午餐奉獻的結論，是免費向卡內基梅隆社區成員和非校園$ 30與會者。有關信息，請致電412-268-8525。 | |||
| |||
西蒙和紐厄爾在後期是大學的最新建築，紐厄爾西門大廳，裡面有計算機科學辦公室的同名。在大學中心：“2050年遺囑計算機幫得佳世或阻礙陶器？”中，$ 20萬元，四層結構的奉獻精神將週四一個科學研討會上作標記，。
上週三，當今年的諾貝爾經濟學被授予美國人詹姆斯·赫克曼和丹尼爾·麥克法登當天，西蒙坐下來與科學編輯拜倫香料來討論科學發現的性質以及他對技術將如何影響人類在未來幾十年的想法。
你認為在有限理性的諾貝爾獎的工作是你對科學最顯著的貢獻？
答：不明確的，但它確實是非常密切相關的計算機科學我做的工作。我這樣想，因為我是約19我研究人的決策和解決問題。有限理性是認為經濟的一部分。當電腦來了，我覺得是第一次，我有合適的工具，什麼樣的理論工作我想做的事。於是我搬了這一點，這讓我進入心理。
問：那麼你從外地遷來字段可以帶來新的工具來承擔你的決策的研究？
答：我開始想，也許社會科學應該有上萬種數學是自然科學的了。這是因為他們談論的成本，價格和數量的貨物工程經濟學一點點。但它不工作的其他社會科學混賬; 當你把它們翻譯成號碼，你失去了大部分內容。
所以，當電腦來了 - 更具體地說，當我明白了一台電腦不是一個數字排排坐，但處理任何類型的模式的通用系統 - 我意識到，你可以制定關於人類和社會現象的理論語言和圖片，無論您想在電腦上，你沒有去通過這個緊箍咒加入了很多數字的。
這似乎給了我一個巨大的突破。而科學的第一個規則是，如果有人提供了一個秘密武器給你，你更好地使用它。
問：1957年，你提出了著名的預言計算機將在10年內的國際象棋世界冠軍。[IBM的深藍不會打的人冠軍，直到1997年]你有猜測當一台計算機將諾貝爾值得發現？
答：我停下來想，如果這是已經發生了。
我花了我近20年來一個很好的協議看著決策和解決問題的參與科學發現。我們採取了重大歷史科學發現和我們說那會是什麼需要編寫，賦予比誰做的已經發現，將做出同樣的發現這個傢伙沒有更多信息的計算機程序？
我們專注於19世紀的物理和化學。因此，例如，我們說[17世紀的數學家約翰]開普勒了一些數據，然後提供給所有的天文學家，從太陽行星的距離和繞太陽公轉的的時期。他有五個最內層的行星。他開始做什麼他做，並在一段時間後，他決定去時段與距離的平方。他出版了。
擬合不是很好。因此，10年後，他又回到了它。在幾個月後，他說，哦，期間真正上升為距離的三個半功率，[軌道週期的平方成正比，從太陽它們的距離的立方。這就給了你一個非常適合，如此之大，我們還是接受法律，[開普勒行星運動第三定律。
因此，我們不得不叫培根有點計算機程序，弗朗西斯爵士的名字命名，而我們給了它是那些五個數據點--five距離和相應的時間段。我們培根說，看你能不能找到一個模式在那裡。並在幾秒鐘，培根它。
那麼，是什麼都做培根？它是否嘗試所有可能的功能？嗯，這是無稽之談。非也，其實它有它的第三或第四次嘗試。
那麼，開普勒肯定會得到一個諾貝爾獎。怎麼樣的電腦？它什麼都不知道開普勒不知道。所以很顯然，它必須有相似的權力。並沒有受到強權的計算機實力做到這一點。它有產生圖案的一種方式，它使一個嘗試，它會比較現實的嘗試，然後進行調整。
問：那麼計算機可能有一天會值得諾貝爾獎？
答：我看不出有什麼深層次原因何樂而不為。我們已經有一個世界冠軍的棋手，雖然那一個，我不會做聲稱它在一個人形的方式，但它肯定不蠻力去做。它使用計算機的速度和只是一個國際象棋知識負載的組合。
但忘了諾貝爾獎; 他們是不是真的很重要。我以前的學生，勞爾巴爾德斯 - 佩雷斯[CMU一個高級研究計算機科學家]寫了一個名為MECHEM程序。你給它，你知道的輸入和化學反應的產出什麼，但你不知道的反應是如何產生的。你問MECHEM有關反應的假設，它會給你一套假說[上市潛力步驟的反應可能跟隨。它的想法是足夠有趣，使得其在多個場合成果已發表在化學期刊。
問：計算機可以幫助人們採取更合理？
答：凡是給我們帶來新的知識，使我們有機會更加理性。
人的認識已經從字去改變，人們在某些方面表現得更加理性比他們時，他們沒有它。他們花更少的時間做雨舞和更多的時間播種雲。
但是，我們所學到的一件大事是，人類是在學習了很多的模式，展現在世人面前和他們聯繫起來了解世界與他們有什麼很好的。這是一個醫生做了什麼。他學會麻疹的樣子，讓他可以稱之為麻疹 - 最好是在拉丁美洲，雖然 - 然後得到他的[精神]百科全書所有這些信息的訪問。
我們知道，人是善於尋找的東西非常有選擇性，即，使用拇指各種規則來縮小他們的搜索。我的一個大的利益，一直看我們如何給電腦的功能。因為我不在乎大，速度快的計算機是如何，他們不是那麼大，那麼快的世界。
問：本週的研討會地址的計算機是否會幫助或阻礙努力營造一個“好世界”。這是否承擔技術可以天生好還是壞？
答：不，不是固有的-必然。（笑）。沒有關於技術道德可言。技術擴展了我們思考的東西的方式，擴大了我們的做事方式。如果我們是壞人，我們用科技壞的 目的，如果我們是好人，我們用它來很好的目的。這就是為什麼我在預測的問題不感興趣，並在什麼樣的決定，我們可以讓我們得到技術的良好應用的一個積極的平衡更感興趣。
問：那麼我們可以做出什麼樣的決定，以實現這一積極的平衡？
答：嗯，首先，我們可以做一些思考，這將是一個可持續的和可接受的世界。請注意，我不說最好的世界中。我不知道如何界定它。
| |||
| 西蒙的名字那張新館紐厄爾西門大廳可以被稱為是Lycos的建造大樓。 在$ 20個萬建設項目，由卡內基梅隆大學的在Lycos的公司，該公司通過CMU研究員邁克爾·莫爾丁，誰開發的上網本Lycos的搜索引擎目前出售股票主要是資助。 該項目增加了兩個故事，兩個現有建築 - 包括外地機器人中心 - 和一個中庭一個屋簷下連接在一起的。由此產生的四層樓房包圍42000平方英尺的裝修空間，65000平方英尺的新空間。 計算機科學學院的建房元素，包括機器人研究所，語言技術研究所和人機交互研究所。 | |||
| |||
問：一個足夠好的世界呢？
答：是啊，一個足夠好的世界-一個令人滿意的世界是我最喜歡的詞。而當你開始思考，你不要想著機開始，你想想人的世界。並決定，好吧，也許我們最好還是在我們擁有的資源繼續下去的世界。也許我們應該有一個世界中，事情人與人之間劃分那種相當。
然後我們問我們如何到達那裡？好了，到那裡幾乎什麼辦法涉及到了解了很多關於世界和它是如何工作。這是一個重大的地方，電腦進來，他們可以幫助我們思考。
問：本週的研討會將解決一些Sun Microsystems公司的Bill Joy，誰說，基因工程，納米技術和機器人技術的結合可以創造一個未來，人類可能成為消耗的想法。你分享他對這些技術的關注？
答：噢，我認為他們可以造成巨大的傷害。想像一下，他們一群人誰碰巧有權力，並認為他們是英雄種族的手中。但是請注意，我是如何把它-在手中覺得他們的人。再次，這是我們自己誰是這一切的中心，需要在我們的思維的中心。
問：如果電腦可以為自己著想，也讓人變得可有可無？
答：計算機的思維不會讓你消耗。我認為真正擔心的是，這也破壞了什麼是關於人類有價值或貴重？而且在一些想法反過來說是有價值的派生你必須有一個獨特的性質-你必須要在某些方面不同-當有人威脅人類的差異，無論是達爾文或Galileo或任何人，有一個很強烈反應。
我認為錯誤是在一個人的主張立足於價值的獨特性。我們大多數人真的是不可怕的是獨一無二的。有6個十億我們。把'時間都在一個房間裡，很少會站出來為個人。因此，也許我們應該在我們相處作為自然的一部分，而不是戰勝自然的能力領主來考慮的價值。
問：機器找到我們消耗？
答：嗯，expendability是一個稍微不同的問題。當時發生什麼時，他們可以使所有我們想要取得或不能提供的是在地球的能力範圍內所做的事情呢？我們該怎麼辦呢？嗯，首先我們應該了解人類在這些情況 下的行為方式。
有很多歷史上的例子。在每一個從文明已經出現了一批誰沒有為生計而工作的人。所以他們做了什麼，使自己的生活顯著？
他們當中有些人發現非常巧妙簡單的事情，真的很激動他們，讓他們忙碌而事實上，他們沒有做他們從來沒有困擾他們。科學，在英國至少是一個紳士的遊戲遲至18世紀，一些人發現它讓他們很開心。
然後還有一些誰專注於生活的平常真理 - 家庭，住宅，與其他人的關係 - 當你在看上層階級，他們即將為快樂或不快樂，因為人們通常是那些社會。一些奢華幸福，有些大手大腳不滿。
因此，我們將不得不考慮如何成長起來的人誰找到有趣的事情時，有沒有什麼有許多工作要做。我們現在正在危險地接近，對於我們社會的一半。
但在這裡，你看，技術可能創造條件，但問題是我們該怎麼做我們自己。
我們更好地了解自己很清楚，我們更好地想方設法喜歡自己。
問：那麼，在未來的50年裡，我們要創造我們自己的烏托邦還是我們自己的地獄的潛力？
答：更可能是兩者兼而有之。
****
HERBERT SIMON v LEWIS CARROLL
Decision making v the cat
思考/數學 錯誤
Foundations: Logic, Language, and Mathematics
https://books.google.com.tw/books?isbn=9401715920
Hugues Leblanc, Elliott Mendelson, A. Orenstein - 2013 - Science
Lewis Carroll, “What the Tortoise Said to Achilles', Mind 4, 1895, 278–280.
7 Cited in note 5. ... say “best” here. Herbert Simon observes 126 GILBERT HAR MAN.
ssatisficeRationality in Action - Page 11 - Google Books Result
https://books.google.com.tw/books?isbn=0262250616
John R. Searle - 2003 - Philosophy
For example, Herbert Simon writes, "Reason is wholly instrumental. ...
Reason in Human Affair pp.7-8
Lewis Carroll, "What Achilles Said to the Tortoise," Mind The Classical Model of Rationality ...
*****
It's always 20 years away... | Alex Knapp
thealexknapp.tumblr.com/post/48917355287/its-always-20-years-away
Apr 26, 2013 - So said Herbert Simon, an early artificial intelligence researcher, in 1965. ... RT @pickover: Lewis Carroll's typewriter, acquired by him in 1888.The Alice Behind Wonderland by Simon Winchester – review | Books ...
www.theguardian.com › Arts › Books › Lewis Carroll
Apr 16, 2011 - There are no simple conclusions about Lewis Carroll's photos of Alice.
沒有留言:
張貼留言