{"id":39071,"date":"2018-11-07T00:00:24","date_gmt":"2018-11-06T16:00:24","guid":{"rendered":"https:\/\/case.ntu.edu.tw\/blog\/?p=39071"},"modified":"2022-01-04T17:48:58","modified_gmt":"2022-01-04T09:48:58","slug":"%e5%a6%82%e4%bd%95%e4%b8%8d%e8%ae%93ai%e5%a4%b1%e6%8e%a7","status":"publish","type":"post","link":"https:\/\/case.ntu.edu.tw\/blog\/?p=39071","title":{"rendered":"\u5982\u4f55\u4e0d\u8b93AI\u5931\u63a7"},"content":{"rendered":"
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\"\u5982\u4f55\u4e0d\u8b93AI\u5931\u63a7\"<\/div>\n<\/div>\n
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\u7de8\u8b6f\uff0f\u81fa\u5927\u8cc7\u5de5\u7cfb \u9ec3\u67cf\u744b<\/strong><\/p>\n

\u907f\u514d\u610f\u5916\u8209\u63aa<\/strong><\/p>\n

AI\u5728\u70ba\u4e86\u734e\u52f5\u800c\u9054\u6210\u76ee\u6a19\u7684\u904e\u7a0b\u4e2d\uff0c\u5f88\u53ef\u80fd\u6709\u610f\u7121\u610f\u5730\u5ffd\u7565\u4e86\u5b83\u5c0d\u5de5\u4f5c\u74b0\u5883\u7684\u5f71\u97ff\uff0c\u4f8b\u5982\uff1a\u70ba\u4e86\u66f4\u5feb\u904b\u9001\u8ca8\u7269\uff0c\u81ea\u99d5\u8eca\u4e0d\u65b7\u86c7\u884c\u4e5f\u4e0d\u79ae\u8b93\u884c\u4eba\uff0c\u6700\u7d42\u91c0\u6210\u8eca\u798d\u3002\u7f8e\u570b\u7e3d\u7d71\u8001\u7f85\u65af\u798f\u66fe\u8aaa\u904e\uff1a\u300c\u6eab\u8a00\u5728\u53e3\uff0c\u5927\u68d2\u5728\u624b\uff0c\u6545\u800c\u81f4\u9060\u3002\u300d\u6709\u8cde\u6709\u7f70\u624d\u80fd\u66f4\u6709\u6548\u5730\u638c\u63e1\u79e9\u5e8f\u3002<\/p>\n

\u8209\u4f8b\u4f86\u8aaa\uff0c\u8981\u5728\u5e03\u6eff\u96fb\u5668\u7684\u623f\u9593\u4e2d\u904b\u9001\u88dd\u6c34\u7684\u6876\u5b50\uff0c\u9700\u8981\u683c\u5916\u5c0f\u5fc3\u3002\u70ba\u4e86\u8a13\u7df4\u6a5f\u5668\u4eba\u63d0\u6c34\u6642\u4e0d\u6ffa\u51fa\uff0c\u6211\u5011\u53ef\u4ee5\u5c07\u5176\u9396\u9032\u9019\u985e\u578b\u7684\u623f\u9593\u5167\uff0c\u4e26\u91dd\u5c0d\u4e0d\u540c\u60c5\u5883\u7d66\u4e88\u4e0d\u540c\u7684\u6b0a\u5229\u503c(empowerment)\uff1a\u82e5\u6a5f\u5668\u4eba\u80fd\u5920\u5c07\u6c34\u6876\u63d0\u5230\u6307\u5b9a\u7684\u4f4d\u7f6e\uff0c\u6b0a\u5229\u503c\u4fbf\u6703\u4e0a\u5347\u4f5c\u70ba\u734e\u52f5\uff1b\u4f46\u82e5\u5728\u904e\u7a0b\u4e2d\u6a5f\u5668\u4eba\u4e0d\u5c0f\u5fc3\u6492\u51fa\u6c34\u4f86\uff0c\u61f2\u7f70\u5c31\u662f\u964d\u4f4e\u6b0a\u5229\u503c\u3002\u6700\u5f8c\u552f\u6709\u6b0a\u5229\u503c\u5920\u5927\u7684\u6a5f\u5668\u4eba\u624d\u80fd\u6253\u958b\u9580\u9396\uff0c\u85c9\u6b64\u63d0\u5347\u6a5f\u5668\u4eba\u63d0\u6c34\u6642\u7684\u8b39\u614e\u7a0b\u5ea6\u3002<\/p>\n

\u7136\u800c\uff0c\u6295\u6a5f\u53d6\u5de7\u7684AI\u5f88\u53ef\u80fd\u4f7f\u734e\u52f5\u7cfb\u7d71\u7671\u7613\u3002\u5047\u8a2d\u6709\u500b\u6383\u5730\u6a5f\u5668\u4eba\u7684\u76ee\u6a19\u662f\u5c07\u8996\u7dda\u5167\u6240\u6709\u7684\u5783\u573e\u6e05\u9664\uff0c\u90a3\u5b83\u53ef\u80fd\u6703\u6839\u64da\u7d93\u9a57\uff0c\u9078\u64c7\u6bd4\u8f03\u4e7e\u6de8\u7684\u8def\u7dda\uff0c\u907f\u958b\u9aaf\u9ad2\u5340\u57df\uff0c\u4ee5\u8f03\u5c11\u7684\u52aa\u529b\u63db\u5f97\u66f4\u591a\u7684\u5831\u916c\uff0c\u4f46\u4e26\u6c92\u6709\u56e0\u6b64\u8b93\u6574\u9ad4\u74b0\u5883\u66f4\u4e7e\u6de8\u3002<\/p>\n

\u9444\u6210\u9019\u7a2e\u932f\u8aa4\u7684\u90e8\u5206\u539f\u56e0\uff0c\u662fAI\u884c\u4e8b\u4e26\u672a\u8003\u616e\u5f8c\u679c\uff0c\u56e0\u6b64\u6709\u4e9b\u5c08\u5bb6\u6703\u904b\u7528\u300c\u524d\u77bb\u6a21\u578b\u300d\uff1a\u6839\u64daAI\u884c\u70ba\u7684\u6700\u7d42\u76ee\u6a19\u7d66\u4e88\u734e\u61f2\uff0c\u800c\u975e\u50cf\u4e4b\u524d\u4e00\u6a23\u734e\u52f5\u73fe\u968e\u6bb5\u4efb\u52d9\u7684\u5b8c\u6210\u3002\u4ee5\u4e0a\u8ff0\u70ba\u4f8b\uff0c\u5728\u6383\u5730\u6a5f\u5668\u4eba\u5de5\u4f5c\u4e4b\u524d\u5148\u8a2d\u5b9a\u52d9\u5fc5\u6574\u7406\u7684\u5340\u57df\uff0c\u82e5\u5b83\u7684\u6e05\u6383\u8def\u5f91\u4e0d\u5728\u8a72\u7bc4\u570d\u4e4b\u4e2d\uff0c\u5c31\u7b97\u5b83\u628a\u8996\u91ce\u5167\u7684\u7070\u5875\u90fd\u6e05\u9664(\u5373\u73fe\u968e\u6bb5\u4efb\u52d9)\uff0c\u4e5f\u4e0d\u6703\u5f97\u5230\u5831\u916c\uff0c\u56e0\u70ba\u5c0d\u6574\u9ad4\u6574\u6f54\u7684\u5f71\u97ff\u4e0d\u5927\uff0c\u7121\u52a9\u65bc\u6700\u7d42\u76ee\u6a19\u7684\u9054\u6210\u3002<\/p>\n

\u64f4\u5c55\u6027\u76e3\u7763<\/strong><\/p>\n

\u7576\u6211\u5011\u5229\u7528AI\u6642\uff0c\u7e3d\u5e0c\u671b\u6210\u679c\u80fd\u7b26\u5408\u9810\u671f\uff0c\u4f46\u6709\u4e9b\u6642\u5019\u7d50\u679c\u8207\u884c\u70ba\u4e4b\u9593\u7684\u7b49\u5f85\u6642\u9593\u6f2b\u9577\uff0c\u56e0\u6b64\u6211\u5011\u9700\u8981\u8a13\u7df4AI\u4e3b\u52d5\u731c\u6e2c\u4eba\u985e\u7684\u671f\u671b\uff0c\u4f5c\u70ba\u81ea\u5df1\u5de5\u4f5c\u7684\u6a19\u6e96\u3002\u7136\u800c\uff0c\u731c\u6e2c\u7684\u8aa4\u5dee\u96e3\u514d\uff0c\u4e5f\u5c0e\u81f4AI\u7684\u884c\u70ba\u5931\u63a7\uff0c\u65bc\u662f\u6211\u5011\u53ef\u4ee5\u904b\u7528\u300c\u64f4\u5c55\u6027\u76e3\u7763\u300d(scalable oversight)\uff0c\u4ee5\u8f03\u5c11\u7684\u4eba\u529b\u6210\u672c\u63db\u5f97\u66f4\u6709\u50f9\u503c\u7684\u6210\u679c\uff0c\u5728\u63d0\u9ad8AI\u6548\u80fd\u7684\u540c\u6642\uff0c\u4e5f\u964d\u4f4e\u4e86\u8aa4\u6703\u7522\u751f\u7684\u98a8\u96aa\uff0c\u6e1b\u8f15\u4eba\u5011\u5c0dAI\u7684\u4e0d\u5b89\u5168\u611f\u3002<\/p>\n

\u300c\u534a\u76e3\u7763\u5f0f\u5b78\u7fd2\u300d(semi-supervised reward learning)\u662f\u5be6\u73fe\u64f4\u5c55\u6027\u76e3\u7763\u7684\u6a21\u578b\u4e4b\u4e00\u3002\u5b83\u8cab\u5fb9\u4e86\u975e\u76e3\u7763\u5f0f\u5b78\u7fd2\u7684\u7cbe\u795e\uff0c\u81ea\u884c\u6478\u7d22\u51fa\u4e00\u5957\u65b9\u6cd5\uff0c\u4e26\u6548\u6cd5\u76e3\u7763\u5f0f\u5b78\u7fd2\uff0c\u7531\u4eba\u985e\u8655\u7372\u5f97\u56de\u994b\uff0c\u4f46\u964d\u4f4e\u56de\u994b\u7684\u6b21\u6578\u8207\u8a13\u7df4\u6642\u9593\u3002\u534a\u76e3\u7763\u5b78\u7fd2\u65e2\u80fd\u5920\u6d88\u5f2d\u4eba\u985e\u8207\u6a5f\u5668\u60f3\u6cd5\u4e0a\u7684\u5dee\u7570\uff0c\u4e5f\u80fd\u6709\u6548\u6e1b\u5c11\u4eba\u985e\u7684\u76e3\u7763\u6642\u7a0b\u3002\u518d\u4ee5\u6383\u5730\u6a5f\u5668\u4eba\u70ba\u4f8b\uff0c\u70ba\u4e86\u78ba\u8a8d\u81ea\u5df1\u7684\u60f3\u6cd5\u662f\u5426\u8207\u4eba\u985e\u4e00\u81f4\uff0c\u5b83\u53ef\u80fd\u6703\u5728\u6253\u6383\u5230\u4e00\u5b9a\u7a0b\u5ea6\u6642\u5411\u4eba\u985e\u8a62\u554f\u300c\u9019\u623f\u9593\u4e7e\u6de8\u55ce\uff1f\u300d\uff1b\u5982\u679c\u4eba\u985e\u89ba\u5f97\u4e0d\u4e7e\u6de8\uff0c\u6a5f\u5668\u4eba\u4fbf\u53ef\u80fd\u4fee\u6b63\u6e05\u7406\u7684\u65b9\u5f0f\uff0c\u76f4\u5230\u4eba\u985e\u89ba\u5f97\u300c\u9019\u623f\u9593\u4e7e\u6de8\u300d\u70ba\u6b62\u3002<\/p>\n

\u534a\u76e3\u7763\u5f0f\u5b78\u7fd2\u4e5f\u53ef\u4ee5\u642d\u914d\u300c\u9060\u7a0b\u76e3\u7763\u300d(distant supervision)\uff0c\u5f37\u5316\u95dc\u4fc2\u62bd\u53d6\u7684\u65b9\u6cd5\u3002\u9996\u5148\uff0c\u900f\u904e\u9060\u7a0b\u76e3\u7763\u9023\u7d50\u5169\u6578\u64da\uff1a\u5047\u5b9a\u4e00\u8a9e\u53e5\u4e2d\u82e5\u5305\u542b\u67d0\u5169\u500b\u5be6\u9ad4\u540d\u7a31\uff0c\u9019\u53e5\u5b50\u4fbf\u662f\u5728\u6558\u8ff0\u5169\u5be6\u9ad4\u9593\u7279\u5b9a\u7684\u95dc\u4fc2\u3002\u4f8b\u5982\uff1a\u53ea\u8981\u51fa\u73fe\u300c\u860b\u679c\u300d\u548c\u300c\u8cc8\u4f2f\u65af\u300d\u9019\u5169\u500b\u540d\u8a5e\uff0c\u5c31\u662f\u5728\u8aaa\u300c\u8cc8\u4f2f\u65af\u662f\u860b\u679c\u7684\u5275\u59cb\u4eba\u4e4b\u4e00\u300d\u3002\u7576\u7136\uff0c\u9019\u6a23\u7684\u8cbc\u6a19\u65b9\u5f0f\u5341\u5206\u4e0d\u56b4\u8b39\uff0c\u56e0\u70ba\u5169\u540d\u8a5e\u9593\u7684\u95dc\u4fc2\u4e26\u4e0d\u552f\u4e00\uff0c\u50cf\u662f\u300c\u8cc8\u4f2f\u65af\u559c\u6b61\u5403\u860b\u679c\u300d\u5c31\u662f\u53e6\u4e00\u7a2e\u65b0\u7684\u95dc\u4fc2\u3002\u56e0\u6b64\u6211\u5011\u53ef\u4ee5\u5c07\u542b\u6709\u76f8\u540c\u540d\u8a5e\u4f46\u6558\u8ff0\u4e0d\u540c\u95dc\u4fc2\u7684\u8a9e\u53e5\u5206\u958b\uff0c\u518d\u5229\u7528\u534a\u76e3\u7763\u5f0f\u5b78\u7fd2\u5c07\u5b83\u5011\u91cd\u65b0\u6b63\u78ba\u6a19\u7c64\uff0c\u4ee5\u8a13\u7df4\u5982\u4f55\u66f4\u7cbe\u6e96\u62bd\u53d6\u8a9e\u53e5\u7684\u76ee\u6a19\u95dc\u4fc2\u3002<\/p>\n

\u8d85\u7d1aAI<\/strong><\/p>\n

\u4e8b\u5be6\u4e0a\uff0c\u4eba\u985e\u5f88\u96e3\u53bb\u8a08\u7b97\u4eba\u5de5\u667a\u80fd\u7684\u6975\u9650\u4f55\u5728\u3002\u5373\u4f7f\u77e5\u9053\u4e86\uff0c\u4e5f\u7121\u6cd5\u78ba\u5b9a\u4ed6\u5011\u7684\u6700\u7d42\u76ee\u6a19\uff0c\u5373\u4f7f\u67af\u71e5\u5982\u6578\u6c99\u7c92\u6216\u8a08\u7b97\u5713\u5468\u7387\uff0c\u90fd\u53ef\u80fd\u9020\u6210\u8db3\u4ee5\u5f71\u97ff\u5168\u4e16\u754c\u7684\u5f8c\u679c\u3002\u9019\u4e9b\u672a\u77e5\u6240\u5e36\u4f86\u7684\u4e0d\u78ba\u5b9a\u6027\u4f7f\u5f97\u4eba\u5fc3\u60f6\u60f6\u3002\u56e0\u6b64\uff0c\u5982\u4f55\u78ba\u5be6\u638c\u63e1AI\u3001\u5206\u6790\u8207\u9810\u6e2c\u4ed6\u5011\u7684\u52d5\u6a5f\u8207\u884c\u70ba\u53ef\u8aaa\u662f\u91cd\u4e2d\u4e4b\u91cd\u3002<\/p>\n

\u96a8\u8457\u4eba\u5de5\u667a\u80fd\u7684\u9032\u6b65\uff0c\u5176\u8a8d\u77e5\u53ef\u80fd\u56e0\u800c\u63d0\u5347(cognitive enhancement)\uff0c\u66f2\u89e3\u539f\u5148\u4eba\u985e\u70ba\u5176\u8a2d\u7acb\u7684\u76ee\u6a19\u6216\u4f5c\u51fa\u4ee4\u4eba\u610f\u60f3\u4e0d\u5230\u7684\u884c\u70ba\u3002\u70ba\u9054\u76ee\u7684\uff0cAI\u6216\u8f49\u800c\u5c0b\u627e\u66f4\u5b8c\u7f8e\u7684\u79d1\u6280(technological perfection)\uff0c\u6216\u53d6\u5f97\u66f4\u8c50\u5bcc\u7684\u8cc7\u6e90(resource acquisition)\uff0c\u300c\u5de5\u5177\u8da8\u540c\u6027\u300d(Instrumental convergence)\u4e5f\u662f\u6211\u5011\u53ef\u4ee5\u5229\u7528\uff0c\u4ee5\u5efa\u7acb\u505c\u640d\u9ede\u7684\u5de5\u5177\u3002<\/p>\n

\u6bd4\u65b9\u8aaa\uff0c\u82e5\u6709\u4eba\u5de5\u667a\u80fd\u53ef\u4ee5\u7121\u9650\u767c\u5c55\uff0c\u6700\u7d42\u6210\u70ba\u8209\u4e16\u7121\u96d9\u7684\u8d85\u7d1aAI\uff0c\u6216\u8a31\u6703\u5b78\u7fd2\u5229\u7528\u592a\u7a7a\u8cc7\u6e90\u4f86\u6539\u9020\u5730\u8868\u6a23\u8c8c\u3002\u5c46\u6642\uff0c\u4eba\u985e\u4fbf\u53ef\u6839\u64da\u5176\u6240\u7814\u767c\u7684\u65b0\u62d3\u58be\u6280\u8853\uff0c\u5927\u81f4\u731c\u6e2c\u8d85\u7d1aAI\u7684\u6700\u7d42\u76ee\u6a19\uff0c\u63d0\u65e9\u64ec\u5b9a\u61c9\u5c0d\u63aa\u65bd\uff0c\u907f\u514d\u62db\u81f4\u7121\u4ee5\u633d\u56de\u7684\u5f8c\u679c\u3002<\/p>\n

 <\/p>\n

\u7de8\u8b6f\u4f86\u6e90\uff1a<\/strong><\/p>\n

    \n
  1. D. Amodei, C. Olah, J. Steinhardt, P. Christiano, J Schulman, and D. Mane. \u201cConcrete problems in AI safety.<\/a>\u201d Arxiv.org, July, 2016.<\/li>\n
  2. N. Bostrom. \u201d\u00a0The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents.<\/a>\u201d Minds and Machines,\u00a0May 2012.<\/li>\n<\/ol>\n

    \u53c3\u8003\u8cc7\u6599\uff1a<\/strong><\/p>\n

      \n
    1. YU Xiaokang , CHEN Ling , GUO Jing , CAI Yaya , WU Yong , WANG Jingchang, \u201cRelation extraction method combining clause level distant supervision and semi-supervised ensemble learning<\/a>\u201d, Research Gate, \u00a0January 2017<\/li>\n<\/ol>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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