iVOD / 155400

Field Value
影片長度 771
委員名稱 沈發惠
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/d4cdf32868ad364baaca075a0f8d4ddb768d2097a9b873f67579206f6b0958272dfc6c4b509e5c9c5ea18f28b6918d91.mp4/playlist.m3u8
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 7.03409375
transcript.pyannote[0].end 7.72596875
transcript.pyannote[1].speaker SPEAKER_03
transcript.pyannote[1].start 7.72596875
transcript.pyannote[1].end 7.74284375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 8.13096875
transcript.pyannote[2].end 10.96596875
transcript.pyannote[3].speaker SPEAKER_03
transcript.pyannote[3].start 12.97409375
transcript.pyannote[3].end 13.98659375
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 14.12159375
transcript.pyannote[4].end 15.03284375
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 16.04534375
transcript.pyannote[5].end 24.06096875
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 24.73596875
transcript.pyannote[6].end 29.88284375
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 30.65909375
transcript.pyannote[7].end 63.81846875
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 63.86909375
transcript.pyannote[8].end 71.56409375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 71.90159375
transcript.pyannote[9].end 78.09471875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 79.24221875
transcript.pyannote[10].end 87.86534375
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 88.37159375
transcript.pyannote[11].end 100.03221875
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 100.74096875
transcript.pyannote[12].end 105.06096875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 105.58409375
transcript.pyannote[13].end 106.22534375
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 107.28846875
transcript.pyannote[14].end 112.82346875
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 113.22846875
transcript.pyannote[15].end 118.34159375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 118.98284375
transcript.pyannote[16].end 122.00346875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 122.71221875
transcript.pyannote[17].end 125.04096875
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 125.34471875
transcript.pyannote[18].end 126.99846875
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 127.25159375
transcript.pyannote[19].end 129.41159375
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 130.10346875
transcript.pyannote[20].end 136.16159375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 136.56659375
transcript.pyannote[21].end 142.65846875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 142.99596875
transcript.pyannote[22].end 146.26971875
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 146.94471875
transcript.pyannote[23].end 148.73346875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 148.93596875
transcript.pyannote[24].end 153.77909375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 154.30221875
transcript.pyannote[25].end 156.02346875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 156.44534375
transcript.pyannote[26].end 157.22159375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 157.39034375
transcript.pyannote[27].end 166.01346875
transcript.pyannote[28].speaker SPEAKER_03
transcript.pyannote[28].start 166.08096875
transcript.pyannote[28].end 166.36784375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 166.77284375
transcript.pyannote[29].end 167.12721875
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 167.78534375
transcript.pyannote[30].end 168.42659375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 169.28721875
transcript.pyannote[31].end 170.77221875
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 171.19409375
transcript.pyannote[32].end 184.45784375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 184.62659375
transcript.pyannote[33].end 188.33909375
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 188.89596875
transcript.pyannote[34].end 190.11096875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 191.17409375
transcript.pyannote[35].end 199.24034375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 199.52721875
transcript.pyannote[36].end 199.99971875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 202.93596875
transcript.pyannote[37].end 204.57284375
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 209.41596875
transcript.pyannote[38].end 209.56784375
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 209.56784375
transcript.pyannote[39].end 210.27659375
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 209.70284375
transcript.pyannote[40].end 217.38096875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 210.90096875
transcript.pyannote[41].end 211.15409375
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 217.71846875
transcript.pyannote[42].end 232.65284375
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 232.85534375
transcript.pyannote[43].end 235.21784375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 235.45409375
transcript.pyannote[44].end 247.06409375
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 247.45221875
transcript.pyannote[45].end 255.65346875
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 253.64534375
transcript.pyannote[46].end 256.05846875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 256.51409375
transcript.pyannote[47].end 257.18909375
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 258.23534375
transcript.pyannote[48].end 260.04096875
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 260.42909375
transcript.pyannote[49].end 271.34721875
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 272.03909375
transcript.pyannote[50].end 277.27034375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 278.08034375
transcript.pyannote[51].end 278.70471875
transcript.pyannote[52].speaker SPEAKER_03
transcript.pyannote[52].start 278.70471875
transcript.pyannote[52].end 283.31159375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 283.04159375
transcript.pyannote[53].end 286.46721875
transcript.pyannote[54].speaker SPEAKER_03
transcript.pyannote[54].start 284.15534375
transcript.pyannote[54].end 287.51346875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 287.51346875
transcript.pyannote[55].end 301.84034375
transcript.pyannote[56].speaker SPEAKER_03
transcript.pyannote[56].start 287.53034375
transcript.pyannote[56].end 288.17159375
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 302.48159375
transcript.pyannote[57].end 303.02159375
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 304.32096875
transcript.pyannote[58].end 305.58659375
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 306.31221875
transcript.pyannote[59].end 311.83034375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 312.62346875
transcript.pyannote[60].end 316.90971875
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 317.46659375
transcript.pyannote[61].end 319.94721875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 320.67284375
transcript.pyannote[62].end 322.14096875
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 322.61346875
transcript.pyannote[63].end 323.42346875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 324.97596875
transcript.pyannote[64].end 326.19096875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 326.71409375
transcript.pyannote[65].end 334.07159375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 334.61159375
transcript.pyannote[66].end 337.12596875
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 338.44221875
transcript.pyannote[67].end 345.52971875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 345.76596875
transcript.pyannote[68].end 351.60471875
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 366.10034375
transcript.pyannote[69].end 367.12971875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 367.82159375
transcript.pyannote[70].end 368.71596875
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 369.22221875
transcript.pyannote[71].end 369.69471875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 370.40346875
transcript.pyannote[72].end 374.28471875
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 374.63909375
transcript.pyannote[73].end 376.12409375
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 377.17034375
transcript.pyannote[74].end 379.98846875
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 380.86596875
transcript.pyannote[75].end 385.94534375
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 386.51909375
transcript.pyannote[76].end 390.06284375
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 390.45096875
transcript.pyannote[77].end 393.87659375
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 394.48409375
transcript.pyannote[78].end 402.02721875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 402.17909375
transcript.pyannote[79].end 411.03846875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 411.10596875
transcript.pyannote[80].end 412.65846875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 412.91159375
transcript.pyannote[81].end 415.78034375
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 416.01659375
transcript.pyannote[82].end 422.78346875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 422.96909375
transcript.pyannote[83].end 424.80846875
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 425.01096875
transcript.pyannote[84].end 436.72221875
transcript.pyannote[85].speaker SPEAKER_03
transcript.pyannote[85].start 437.63346875
transcript.pyannote[85].end 439.08471875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 439.37159375
transcript.pyannote[86].end 442.54409375
transcript.pyannote[87].speaker SPEAKER_00
transcript.pyannote[87].start 443.50596875
transcript.pyannote[87].end 451.80846875
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 452.44971875
transcript.pyannote[88].end 458.01846875
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 458.27159375
transcript.pyannote[89].end 459.14909375
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 459.72284375
transcript.pyannote[90].end 464.75159375
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 465.29159375
transcript.pyannote[91].end 466.42221875
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 466.64159375
transcript.pyannote[92].end 468.04221875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 468.61596875
transcript.pyannote[93].end 473.57721875
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 473.64471875
transcript.pyannote[94].end 476.39534375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 476.53034375
transcript.pyannote[95].end 477.35721875
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 477.79596875
transcript.pyannote[96].end 481.08659375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 481.15409375
transcript.pyannote[97].end 482.47034375
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 482.68971875
transcript.pyannote[98].end 489.70971875
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 490.85721875
transcript.pyannote[99].end 492.08909375
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 492.40971875
transcript.pyannote[100].end 493.32096875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 493.75971875
transcript.pyannote[101].end 496.30784375
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 496.74659375
transcript.pyannote[102].end 497.75909375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 499.54784375
transcript.pyannote[103].end 502.12971875
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 501.74159375
transcript.pyannote[104].end 511.10721875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 502.16346875
transcript.pyannote[105].end 502.18034375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 502.19721875
transcript.pyannote[106].end 502.31534375
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 511.88346875
transcript.pyannote[107].end 512.44034375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 512.91284375
transcript.pyannote[108].end 517.08096875
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 517.70534375
transcript.pyannote[109].end 524.35409375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 526.02471875
transcript.pyannote[110].end 527.84721875
transcript.pyannote[111].speaker SPEAKER_03
transcript.pyannote[111].start 529.07909375
transcript.pyannote[111].end 531.47534375
transcript.pyannote[112].speaker SPEAKER_03
transcript.pyannote[112].start 531.66096875
transcript.pyannote[112].end 533.12909375
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 532.67346875
transcript.pyannote[113].end 535.05284375
transcript.pyannote[114].speaker SPEAKER_03
transcript.pyannote[114].start 535.69409375
transcript.pyannote[114].end 548.63721875
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 535.76159375
transcript.pyannote[115].end 536.33534375
transcript.pyannote[116].speaker SPEAKER_00
transcript.pyannote[116].start 548.14784375
transcript.pyannote[116].end 549.09284375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 551.86034375
transcript.pyannote[117].end 554.99909375
transcript.pyannote[118].speaker SPEAKER_03
transcript.pyannote[118].start 551.92784375
transcript.pyannote[118].end 552.04596875
transcript.pyannote[119].speaker SPEAKER_00
transcript.pyannote[119].start 555.21846875
transcript.pyannote[119].end 556.99034375
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 558.07034375
transcript.pyannote[120].end 559.03221875
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 559.53846875
transcript.pyannote[121].end 566.45721875
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 566.45721875
transcript.pyannote[122].end 573.44346875
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 572.11034375
transcript.pyannote[123].end 579.72096875
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 580.00784375
transcript.pyannote[124].end 582.42096875
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 580.81784375
transcript.pyannote[125].end 590.47034375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 590.82471875
transcript.pyannote[126].end 592.00596875
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 592.03971875
transcript.pyannote[127].end 592.05659375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 592.10721875
transcript.pyannote[128].end 597.96284375
transcript.pyannote[129].speaker SPEAKER_00
transcript.pyannote[129].start 594.97596875
transcript.pyannote[129].end 595.36409375
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 596.25846875
transcript.pyannote[130].end 600.37596875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 600.96659375
transcript.pyannote[131].end 602.51909375
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 602.90721875
transcript.pyannote[132].end 604.05471875
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 604.22346875
transcript.pyannote[133].end 628.87784375
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 629.43471875
transcript.pyannote[134].end 645.80346875
transcript.pyannote[135].speaker SPEAKER_00
transcript.pyannote[135].start 645.87096875
transcript.pyannote[135].end 646.09034375
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 646.09034375
transcript.pyannote[136].end 646.37721875
transcript.pyannote[137].speaker SPEAKER_00
transcript.pyannote[137].start 646.37721875
transcript.pyannote[137].end 646.41096875
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 646.73159375
transcript.pyannote[138].end 662.13846875
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 662.54346875
transcript.pyannote[139].end 665.41221875
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 665.41221875
transcript.pyannote[140].end 672.87096875
transcript.pyannote[141].speaker SPEAKER_01
transcript.pyannote[141].start 665.42909375
transcript.pyannote[141].end 665.53034375
transcript.pyannote[142].speaker SPEAKER_00
transcript.pyannote[142].start 673.17471875
transcript.pyannote[142].end 677.76471875
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 676.58346875
transcript.pyannote[143].end 695.58471875
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 682.48971875
transcript.pyannote[144].end 685.07159375
transcript.pyannote[145].speaker SPEAKER_00
transcript.pyannote[145].start 695.58471875
transcript.pyannote[145].end 704.71409375
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 705.65909375
transcript.pyannote[146].end 706.84034375
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 707.19471875
transcript.pyannote[147].end 712.96596875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 712.96596875
transcript.pyannote[148].end 725.14971875
transcript.pyannote[149].speaker SPEAKER_00
transcript.pyannote[149].start 724.54221875
transcript.pyannote[149].end 726.44909375
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 726.14534375
transcript.pyannote[150].end 726.36471875
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 726.44909375
transcript.pyannote[151].end 726.85409375
transcript.pyannote[152].speaker SPEAKER_00
transcript.pyannote[152].start 726.85409375
transcript.pyannote[152].end 732.37221875
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 726.90471875
transcript.pyannote[153].end 728.25471875
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 730.21221875
transcript.pyannote[154].end 730.29659375
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 732.47346875
transcript.pyannote[155].end 741.41721875
transcript.pyannote[156].speaker SPEAKER_00
transcript.pyannote[156].start 741.41721875
transcript.pyannote[156].end 745.43346875
transcript.pyannote[157].speaker SPEAKER_00
transcript.pyannote[157].start 745.50096875
transcript.pyannote[157].end 748.67346875
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 749.33159375
transcript.pyannote[158].end 751.62659375
transcript.pyannote[159].speaker SPEAKER_01
transcript.pyannote[159].start 749.85471875
transcript.pyannote[159].end 750.51284375
transcript.pyannote[160].speaker SPEAKER_00
transcript.pyannote[160].start 752.26784375
transcript.pyannote[160].end 764.72159375
transcript.pyannote[161].speaker SPEAKER_00
transcript.pyannote[161].start 765.05909375
transcript.pyannote[161].end 769.21034375
transcript.pyannote[162].speaker SPEAKER_01
transcript.pyannote[162].start 766.37534375
transcript.pyannote[162].end 768.16409375
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 768.16409375
transcript.pyannote[163].end 769.26096875
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 769.26096875
transcript.pyannote[164].end 769.34534375
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 770.22284375
transcript.pyannote[165].end 771.97784375
transcript.whisperx[0].start 7.328
transcript.whisperx[0].end 27.743
transcript.whisperx[0].text 主席有請我們人事長請說人事長委員長人事長早我想今天我們主席安排這個議程有關政府機關導入AI提升效能的這個議程這個如果人事長的印象這是在兩個禮拜前9月30
transcript.whisperx[1].start 30.694
transcript.whisperx[1].end 56.477
transcript.whisperx[1].text 我們這個人事總處的業務報告的時候本席在這裡花了10分鐘的時間整個質詢的時間就在跟這個人事長討論有關政府使用AI的所以可能是我跟主席的所見略同或者是主席受到本席的啟發知道說這個我們人總在這個政府導入這個AI裡面扮演的核心角色核心角色
transcript.whisperx[2].start 57.489
transcript.whisperx[2].end 77.68
transcript.whisperx[2].text 那這個上次我花了10分鐘也提出了三個要求那這個是不是人事長會擔心說那我是不是上個禮拜兩個禮拜前全部都問完了今天不知道問什麼了不過其實10分鐘是只短情長我們有關AI的部分我今天還是有很多要請教人事長
transcript.whisperx[3].start 81.199
transcript.whisperx[3].end 104.493
transcript.whisperx[3].text 主席安排這樣的議程很重要也是因為本屆的內閣在520成立的時候就宣示本屆的內閣就是一個行動AI創新內閣也就是說換句話說從剛剛講到現在我們人事總處就是在本屆內閣裡面扮演最核心的角色也就是我們政府使用設成是AI的核心角色
transcript.whisperx[4].start 108.115
transcript.whisperx[4].end 126.503
transcript.whisperx[4].text 這個所以在520宣誓之後呢在6月6號我們行政院也核定了有關提升行政院公務人員人工智慧智能實施計畫對不對對6月6號核定了齁其中有五大內容這五大內容裡面有三大內容是我們人事總處的職責兩大內容是出發部的職責對不對
transcript.whisperx[5].start 130.205
transcript.whisperx[5].end 145.712
transcript.whisperx[5].text 所以上一次的質詢裡面我就針對這個三這個我們人總的這個三大這內容的業務提出三個要求第一個就是把AI計畫要這個他的成果要定期盤點
transcript.whisperx[6].start 146.992
transcript.whisperx[6].end 162.84
transcript.whisperx[6].text 成果的部分要定期盤點,要檢討。第二個,把AI列入公務人員學習必修課程,這個人事長記得吧。第三,把AI納入115年度原額評鑑計畫當中,這個人事長也承諾了,對不對?是。好,那這個
transcript.whisperx[7].start 169.332
transcript.whisperx[7].end 189.775
transcript.whisperx[7].text 也就是說我們這個這次那個編列的這個號稱編列百億AI預算並且合訂了這樣子的一個實施內容但是我們知道說除了這個AI的這個業務除了我們人種以外我們其他速發部我們的速發部跟國科會也扮演重要的角色了
transcript.whisperx[8].start 191.206
transcript.whisperx[8].end 191.907
transcript.whisperx[8].text 請國科會副主委
transcript.whisperx[9].start 210.031
transcript.whisperx[9].end 234.388
transcript.whisperx[9].text 副主委我時間有限所以要趕快講我們這個AI基本法草案我們在7月15號預告開始預告60天應該是在9月13完成預告了那期間呢也有許多這個民間團體包括市改會包括跆拳會都對我們這個AI基本法的草案在預告期間提出了一些建議
transcript.whisperx[10].start 235.569
transcript.whisperx[10].end 254.664
transcript.whisperx[10].text 包括個人隱私的問題、數位落差的問題等等這些部分請問一下副主委我們接下來這個草案送冤我們有沒有會針對這些部分再做檢討報告委員這個部分我們已經納入這個考量當中那也修正在我們的基本法草案裡面有修正嗎?很好很好那這個
transcript.whisperx[11].start 258.614
transcript.whisperx[11].end 269.284
transcript.whisperx[11].text 我們在AI基本法在立法以前還沒有完成立法之前我目前行政院是使用行政指導原則在進行有關AI使用的管控
transcript.whisperx[12].start 278.355
transcript.whisperx[12].end 301.493
transcript.whisperx[12].text 我們在上一年有一個AI的使用的一個所屬機關使用生成式AI的參考指引有第一個參考指引對參考指引這個是行政指導原則行政指導原則那另外有關操作的部分有操作的指導也有這個各項AI管理指引技術指南就技術的部分有這個技術指南那這個
transcript.whisperx[13].start 305.049
transcript.whisperx[13].end 323.061
transcript.whisperx[13].text 這個我看了這個國科會的基本法草案齁在公告預告期間的看了這個草案齁總共內容18條啦齁18條裡面呢我們盤點這18條裡面總共有13條他開頭三個字都一樣是哪三個字 主委欸副主委來
transcript.whisperx[14].start 325.017
transcript.whisperx[14].end 351.432
transcript.whisperx[14].text 政府應也就是說在基本法裡面這個18條裡面有13條都是政府應幹嘛政府應該幹嘛政府應該幹嘛總共13條都是規範政府的啦那這個有這麼多政府應應做的事情這個我就要請問人事長這個我們最核心的角色我們這裡人工智慧法裡面這麼多政府應作為的事項我們的人力足夠嗎現有的人力
transcript.whisperx[15].start 366.139
transcript.whisperx[15].end 379.229
transcript.whisperx[15].text 好好沒有關係這個這個人事長未來這個基本法通過之後政府應該作為的事情有這麼多了以現有的人力來講我認為這個人力一定的調整是勢在必行
transcript.whisperx[16].start 381.319
transcript.whisperx[16].end 393.147
transcript.whisperx[16].text 不管是公務人員的緣額也好不管是約聘僱人員也好你未來政府有這麼多政府應作為的事項我們應該提早就我們的這個中央機關總緣額法應該要提早做這個檢討還有我們有關這個約聘僱人員我們本會
transcript.whisperx[17].start 405.655
transcript.whisperx[17].end 412.441
transcript.whisperx[17].text 本委員會在這個今年5月的時候有提出一個臨時提案請我們人總提出有關這個有關AI的這個約聘僱人員人力使用檢討結果我看了你們檢討的書面報告基本上是沒有檢討只是把現狀列出來而已沒有檢討未來的做法
transcript.whisperx[18].start 425.171
transcript.whisperx[18].end 436.456
transcript.whisperx[18].text 所以這部分請我因為時間關係我請請這個人事長我們這個人事緣和調整在這個基本法架構之下絕對是勢在必行的所以請我們人總提早因應好不好謝謝謝謝委員那接下來另外一個比較比較這個我個人認為是不是應該政府應該考慮的這個我不曉得是國科會的職權還是人總的職權這是有關這個美國
transcript.whisperx[19].start 452.506
transcript.whisperx[19].end 463.342
transcript.whisperx[19].text 美國在這個今年的這個3月28號由這個賀錦麗副總統他提出了而且已經開始實施就是每個政府機關都必須設置AI長
transcript.whisperx[20].start 465.373
transcript.whisperx[20].end 489.006
transcript.whisperx[20].text 人工智慧長就是這個Chief AI Officer這是CAIO他們現在也已經開始美國的這個包括他們的國防部包括他們的網路安全局都已經開始都已經設置了這個AI長而且他們是要求未來每一個機關都必須設置AI長
transcript.whisperx[21].start 491.076
transcript.whisperx[21].end 516.639
transcript.whisperx[21].text 這個部分我們有沒有考慮是不是國科會先講我們在基本法架構裡面有沒有這個部分報告委員基本法應該沒有規範到這個沒有規範到這個部分所以要請人事總長這個要考量如果要考量這個我再看到這個我們國科會的基本法裡面這個列在如果要設這個AI長列在哪裡
transcript.whisperx[22].start 517.762
transcript.whisperx[22].end 524.148
transcript.whisperx[22].text 第一個這是我們現在基本法草案第12條政府應建立AI應用負責機制阿這個主管機關應該就是人種啦報告委員那是速發部啦應用的負責機制是速發部嗎
transcript.whisperx[23].start 536.649
transcript.whisperx[23].end 549.259
transcript.whisperx[23].text 應用整個應用在政府機關的應用政策的規劃推動是在沈發部那人總扮演的角色是公務人員人工智慧的培訓在公務人員這一個區塊我剛提的這個美國所設置的這個人工智慧長AI長
transcript.whisperx[24].start 558.152
transcript.whisperx[24].end 573.251
transcript.whisperx[24].text 我們有沒有考慮因為現在事實上我們資安我們在各個政府機關現在都有設置資安長這個是已經各個政府機關都有設置我想AI長的部分是因為那個人工智慧基本法裡面現在沒有規定現在沒有規定對但是
transcript.whisperx[25].start 573.772
transcript.whisperx[25].end 597.918
transcript.whisperx[25].text 但是按照剛剛這樣大家討論的結果有關政府建立AI應用負責機制應該是訴發部來規劃就是說我們在修法的過程中不斷的在討論是要分級還是分類那因為歐盟是分級美國是分類那分類的基礎就是說不同的政府機關這個我理解啦我是請我們訴發部
transcript.whisperx[26].start 601.024
transcript.whisperx[26].end 621.349
transcript.whisperx[26].text 能夠在考慮這個未來這個AI的這個使用上面在評估確認AI應用於哪些用途他對影響這個國民的安全跟權利這個部分設置在各機關設置AI長我個人認為是有必要的他不一定是常設的但是他可以像資安長一樣他是一個專責負責的人好不好我們請蘇發部來研議那蘇發部既然上來我就順便問蘇發部一個問題
transcript.whisperx[27].start 629.531
transcript.whisperx[27].end 645.183
transcript.whisperx[27].text 我看到你們在今年9月30號這個我們人事長跟我們這個國科會請回了最後就是再請問蘇法部我在9月30號看到你們表示齁你們預計在12月釋出政府機關AI應用指引對不對對
transcript.whisperx[28].start 646.804
transcript.whisperx[28].end 661.84
transcript.whisperx[28].text 那我要請問就是說你們要釋出將來12月預計要釋出的這個政府機關AI使用指引應用指引跟現行的行政院及所屬機關使用生成式AI參考指引有什麼不一樣
transcript.whisperx[29].start 662.774
transcript.whisperx[29].end 681.711
transcript.whisperx[29].text 跟委員報告他是一個上位跟上位的指導概念還是一個補充的概念還是一個取而代之的概念用這個新的公佈的指引來取代舊的指引是什麼樣的就AI這件事情當初內閣是決定說指引先行
transcript.whisperx[30].start 682.392
transcript.whisperx[30].end 704.509
transcript.whisperx[30].text 那指引先行後面再立法那指引先行就是說國科會他先訂了一個指引但是因為這個指引沒辦法包含各部會不同的使用情境比如說也就是說我這樣理解你的意思是說現在現行的已經公佈在實施的行政院及所屬機關使用生成式AI參考指引
transcript.whisperx[31].start 705.917
transcript.whisperx[31].end 732.209
transcript.whisperx[31].text 這個部分還不夠所以你們速發部要所要在12月要提出的政府機關AI應用指引是補充性的嗎行政院提的這個指引是管制類的然後我們提的是應用類那這個應用類必須有各部會的應用指引先出來以後我們再去取也就是並行的就對了對那目前事實上我看到相當多的部會都已經都已經有訂定指引了但還沒有全部了
transcript.whisperx[32].start 732.649
transcript.whisperx[32].end 749.758
transcript.whisperx[32].text 對,因為這個是一個有button up的過程,就是各部會根據自己的應用情境去定出應用之意,然後抒發部這邊會再做彙整所以說所屬機關現行的這個是,你們說你們所做的是應用類的,那現行的是什麼類的?管制類的
transcript.whisperx[33].start 752.335
transcript.whisperx[33].end 767.026
transcript.whisperx[33].text 好 這個部分我會看你們到時候所提出來這個政府機關AI應用指引我看這個內容跟現行的指引之間的有沒有相關的競合或者是這個抵觸的地方我再來觀察好 謝謝謝謝委員好 謝謝沈委員
會議時間 2024-10-14T09:00:00+08:00
委員發言時間 09:26:46 - 09:39:37
會議名稱 立法院第11屆第2會期司法及法制委員會第4次全體委員會議(事由:邀請行政院人事行政總處人事長暨相關部會列席就「政府機關導入AI提升效能」進行專題報告,並備質詢。)
IVOD_ID 155400
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/155400
日期 2024-10-14
會議資料.會議代碼 委員會-11-2-36-4
會議資料.屆 11
會議資料.會期 2
會議資料.會次 4
會議資料.種類 委員會
會議資料.委員會代碼[0] 36
會議資料.標題 第11屆第2會期司法及法制委員會第4次全體委員會議
影片種類 Clip
開始時間 2024-10-14T09:26:46+08:00
結束時間 2024-10-14T09:39:37+08:00
支援功能[0] ai-transcript