机器人能理解喜怒哀乐吗【十大正规体育平台】

发布时间:2021-08-09    浏览:

本文摘要:Can a robot read your emotions? Apple, Google, Facebook and other technology companies seem to think so. They are collectively spending billions of dollars to build emotion-reading devices that can interact meaningfully (and profitably) with humans using artificial intelligence.机器人能记诵你的情绪吗?

Can a robot read your emotions? Apple, Google, Facebook and other technology companies seem to think so. They are collectively spending billions of dollars to build emotion-reading devices that can interact meaningfully (and profitably) with humans using artificial intelligence.机器人能记诵你的情绪吗?iPhone(Apple)、Google(Google)、Facebook等科技有限公司的回答也许是认可的。他们总共斥资数十亿美元作为产品研发能记诵情绪的机器设备,让可利用率人工智能技术与人们进行更有意义(并可带来盈利)的会话。

These companies are banking on a belief about emotions that has held sway for more than 100 years: smiles, scowls and other facial movements are worldwide expressions of certain emotions, built in from birth. But is that belief correct? Scientists have tested it across the world. They use photographs of posed faces (pouts, smiles), each accompanied by a list of emotion words (sad, surprised, happy and so on) and ask people to pick the word that best matches the face. Sometimes they tell people a story about an emotion and ask them to choose between posed faces.这种公司因此以盼望于一种流行了100很多年的相关情绪的见解:笑容、气恼和别的脸部主题活动全是在传达某类情绪,它是难能可贵的,并且是全世界相接的。但这类见解精确吗?生物学家在全世界全国各地进行了实验。她们运用脸部姿势的图片(撅嘴、笑容),每一张图片的后边都列出一些描述情绪的语汇(悲伤、惊讶、开心这些),随后回绝实验目标随意选择与脸部姿势最给出的语汇。有时候,她们不容易描绘一个相关情绪的小故事,随后让实验目标在各有不同的面部表情中做出随意选择。

Westerners choose the expected word about 85 per cent of the time. The rate is lower in eastern cultures, but overall it is enough to claim that widened eyes, wrinkled noses and other facial movements are universal expressions of emotion. The studies have been so well replicated that universal emotions seem to be bulletproof scientific fact, like the law of gravity, which would be good news for robots and their creators.欧洲人约有85%随意选择了预估语汇。亚洲人的成绩较低,但总体来说,这不能表述双眼睁大、皱鼻和别的脸部姿势全是全球化通用的情绪表达形式。这种科学研究不断了数次,結果都一样,规范化的情绪也许出了无坚不摧的科学研究客观事实,如同作用力规律一样,这针对机器人和她们的创始者而言是个喜讯。

But if you tweak these emotion-matching experiments slightly, the evidence for universal expressions dissolves. Simply remove the lists of emotion words, and let subjects label each photo or sound with any emotion word they know. In these experiments, US subjects identify the expected emotion in photos less than 50 per cent of the time. For subjects in remote cultures with little western contact, the results differ even more.殊不知,假如你稍为调节一下这种情绪给出实验,小表情具有普遍意义的直接证据就消失了。假如除去情绪语汇目录,让实验目标用她们告知的情绪语汇来描述图片或响声。

在这种实验中,英国实验目标的准确率接近50%,针对与西方国家了解很少的太远文化艺术的实验目标来讲,結果就更为各有不同了。Overall, we found that these and other sorts of emotion-matching experiments, which have supplied the primary evidence for universal emotions, actually teach the expected answers to participants in a subtle way that escaped notice for decades — like an unintentional cheat sheet. In reality, you’re not “reading” faces and voices. The surrounding situation, which provides subtle cues, and your experiences in similar situations, are what allow you to see faces and voices as emotional.总体来说,大家寻找,这种实验及其别的各种各样情绪给出实验(获得了情绪具有普遍意义的关键直接证据)以一种盘根错节的方法把预估的回答来教了实验参加者,而它是几十年来大家未曾注意到的——如同不经意中的打小抄。在实际中,你并没在“阅读者”脸部和响声。

获得细微提示的周边环境及其你一直在类似情景下的工作经验,让你将脸部主题活动和响声看作是情绪的传达。A knitted brow may mean someone is angry, but in other contexts it means they are thinking, or squinting in bright light. Your brain processes this so quickly that the other person’s face and voice seem to speak for themselves. A hypothetical emotion-reading robot would need tremendous knowledge and context to guess someone’s emotional experiences.双眉紧锁定有可能意味著一个人生气了,但在别的情况下,这有可能意味著她们在独立思考或由于阳光照射抵触而歪着头。你的人的大脑响应速度快速,以致于他人的脸部和响声也许在传达一种情绪。

幻想中的能记诵情绪的机器人务必很多科技知识和情况来猜想一个人的情绪感受。So where did the idea of universal emotions come from? Most scientists point to Charles Darwin’s The Expression of the Emotions in Man and Animals (1872) for proof that facial expressions are universal products of natural selection. In fact, Darwin never made that claim. The myth was started in the 1920s by a psychologist, Floyd Allport, whose evolutionary spin job was attributed to Darwin, thus launching nearly a century of misguided beliefs.那麼规范化情绪的见解究竟是从哪里而来的呢??大部分生物学家上述克利夫?爱因斯坦(Charles Darwin)1872年的经典著作《人与动物的情绪传达》(The Expression of the Emotions in Man and Animals)做为直接证据,证实面部表情是自然选择学说的规范化物质。本质上,爱因斯坦不曾那么讲到过。

这类各不相同源于上世纪20年代的心理学专家佛洛依德?奥尔波特(Floyd Allport),他的神创论表明工作中被强调是源自爱因斯坦,这造成 不正确的见解承袭了近一个世纪。Will robots become sophisticated enough to take away jobs that require knowledge of feelings, such as a salesperson or a nurse? I think it’s unlikely any time soon. You can probably build a robot that could learn a person’s facial movements in context over a long time. It is far more difficult to generalise across all people in all cultures, even for simple head movements. People in some cultures shake their head side to side to mean “yes” or nod to mean “no”. Pity the robot that gets those movements backwards. Pity even more the human who depends on that robot.机器人不容易看起来充裕简易以致于夺走务必讲解情绪的工作中吗?比如业务员或护理人员。我强调,这不大可能快速经常会出现。

你或许能够生产制造一台必须在特殊自然环境下历经长时间通过自学进而讲解人们面部表情的机器人。但把全部文化艺术中任何人的面部表情小结出去就艰辛多了,就算是比较简单的头顶部姿势。在一些文化艺术中,大笑的意思是“是”,低下头的意思是“不”。把这种姿势搞反的机器人不容易很简直。

这些仰仗这种机器人的人们就更为简直了。Nevertheless, tech companies are pursuing emotion-reading devices, despite the dubious scientific basis There is no universal expression of any emotion for a robot to detect Instead, variety is the norm.即便如此,科技有限公司因此以谋求产品研发能记诵情绪的机器设备,虽然其科学基本猜疑。一切情绪都没规范化的表达形式来供智能机器人识别,多样性才算是常态化。


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