iVOD / 155402

Field Value
影片長度 671
委員名稱 羅智強
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/d4cdf32868ad364b682cf40cb9f85fe6768d2097a9b873f67579206f6b095827296ad41e3562adc05ea18f28b6918d91.mp4/playlist.m3u8
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 6.32534375
transcript.pyannote[0].end 12.09659375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 13.29471875
transcript.pyannote[1].end 13.31159375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 13.31159375
transcript.pyannote[2].end 13.41284375
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 13.41284375
transcript.pyannote[3].end 14.05409375
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 14.05409375
transcript.pyannote[4].end 14.18909375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 15.50534375
transcript.pyannote[5].end 25.07346875
transcript.pyannote[6].speaker SPEAKER_03
transcript.pyannote[6].start 25.20846875
transcript.pyannote[6].end 25.59659375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 25.91721875
transcript.pyannote[7].end 34.42221875
transcript.pyannote[8].speaker SPEAKER_03
transcript.pyannote[8].start 39.58596875
transcript.pyannote[8].end 40.61534375
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 40.91909375
transcript.pyannote[9].end 56.93346875
transcript.pyannote[10].speaker SPEAKER_03
transcript.pyannote[10].start 62.35034375
transcript.pyannote[10].end 62.90721875
transcript.pyannote[11].speaker SPEAKER_03
transcript.pyannote[11].start 62.97471875
transcript.pyannote[11].end 71.00721875
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 70.78784375
transcript.pyannote[12].end 72.67784375
transcript.pyannote[13].speaker SPEAKER_03
transcript.pyannote[13].start 71.04096875
transcript.pyannote[13].end 71.42909375
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 72.96471875
transcript.pyannote[14].end 92.55659375
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 93.28221875
transcript.pyannote[15].end 109.38096875
transcript.pyannote[16].speaker SPEAKER_03
transcript.pyannote[16].start 110.24159375
transcript.pyannote[16].end 117.17721875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 116.73846875
transcript.pyannote[17].end 122.44221875
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 123.35346875
transcript.pyannote[18].end 131.09909375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 131.87534375
transcript.pyannote[19].end 157.30596875
transcript.pyannote[20].speaker SPEAKER_03
transcript.pyannote[20].start 159.46596875
transcript.pyannote[20].end 168.74721875
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 166.19909375
transcript.pyannote[21].end 167.38034375
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 168.74721875
transcript.pyannote[22].end 170.75534375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 170.95784375
transcript.pyannote[23].end 178.16346875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 176.44221875
transcript.pyannote[24].end 179.64846875
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 179.49659375
transcript.pyannote[25].end 182.24721875
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 181.94346875
transcript.pyannote[26].end 183.47909375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 183.90096875
transcript.pyannote[27].end 186.07784375
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 186.39846875
transcript.pyannote[28].end 189.31784375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 189.52034375
transcript.pyannote[29].end 195.47721875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 195.12284375
transcript.pyannote[30].end 203.12159375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 203.35784375
transcript.pyannote[31].end 207.79596875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 206.88471875
transcript.pyannote[32].end 213.80346875
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 208.84221875
transcript.pyannote[33].end 209.11221875
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 214.15784375
transcript.pyannote[34].end 218.89971875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 214.20846875
transcript.pyannote[35].end 214.63034375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 219.50721875
transcript.pyannote[36].end 224.14784375
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 223.99596875
transcript.pyannote[37].end 231.03284375
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 231.60659375
transcript.pyannote[38].end 237.79971875
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 237.96846875
transcript.pyannote[39].end 239.48721875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 240.17909375
transcript.pyannote[40].end 241.61346875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 242.11971875
transcript.pyannote[41].end 245.24159375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 247.01346875
transcript.pyannote[42].end 252.09284375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 253.13909375
transcript.pyannote[43].end 254.16846875
transcript.pyannote[44].speaker SPEAKER_03
transcript.pyannote[44].start 255.33284375
transcript.pyannote[44].end 255.67034375
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 256.24409375
transcript.pyannote[45].end 257.03721875
transcript.pyannote[46].speaker SPEAKER_03
transcript.pyannote[46].start 258.42096875
transcript.pyannote[46].end 259.33221875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 259.28159375
transcript.pyannote[47].end 281.26971875
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 282.24846875
transcript.pyannote[48].end 282.90659375
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 283.17659375
transcript.pyannote[49].end 284.74596875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 285.26909375
transcript.pyannote[50].end 293.80784375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 295.25909375
transcript.pyannote[51].end 298.38096875
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 299.07284375
transcript.pyannote[52].end 312.13409375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 313.41659375
transcript.pyannote[53].end 321.60096875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 322.93409375
transcript.pyannote[54].end 325.26284375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 325.33034375
transcript.pyannote[55].end 333.10971875
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 334.29096875
transcript.pyannote[56].end 356.36346875
transcript.pyannote[57].speaker SPEAKER_03
transcript.pyannote[57].start 357.52784375
transcript.pyannote[57].end 357.66284375
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 357.84846875
transcript.pyannote[58].end 359.82284375
transcript.pyannote[59].speaker SPEAKER_03
transcript.pyannote[59].start 360.22784375
transcript.pyannote[59].end 365.84721875
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 366.20159375
transcript.pyannote[60].end 374.14971875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 374.14971875
transcript.pyannote[61].end 374.16659375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 374.16659375
transcript.pyannote[62].end 377.22096875
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 377.62596875
transcript.pyannote[63].end 382.09784375
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 383.29596875
transcript.pyannote[64].end 384.35909375
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 385.30409375
transcript.pyannote[65].end 385.59096875
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 385.86096875
transcript.pyannote[66].end 389.80971875
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 390.34971875
transcript.pyannote[67].end 399.32721875
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 400.47471875
transcript.pyannote[68].end 403.76534375
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 404.22096875
transcript.pyannote[69].end 411.40971875
transcript.pyannote[70].speaker SPEAKER_02
transcript.pyannote[70].start 411.86534375
transcript.pyannote[70].end 419.69534375
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 420.23534375
transcript.pyannote[71].end 422.81721875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 423.50909375
transcript.pyannote[72].end 428.62221875
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 429.29721875
transcript.pyannote[73].end 431.94659375
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 432.65534375
transcript.pyannote[74].end 433.27971875
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 433.95471875
transcript.pyannote[75].end 439.82721875
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 440.62034375
transcript.pyannote[76].end 441.49784375
transcript.pyannote[77].speaker SPEAKER_03
transcript.pyannote[77].start 442.51034375
transcript.pyannote[77].end 444.38346875
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 444.50159375
transcript.pyannote[78].end 446.03721875
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 446.47596875
transcript.pyannote[79].end 447.47159375
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 448.36596875
transcript.pyannote[80].end 449.32784375
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 451.03221875
transcript.pyannote[81].end 452.77034375
transcript.pyannote[82].speaker SPEAKER_03
transcript.pyannote[82].start 453.17534375
transcript.pyannote[82].end 454.69409375
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 454.71096875
transcript.pyannote[83].end 461.20784375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 461.83221875
transcript.pyannote[84].end 462.50721875
transcript.pyannote[85].speaker SPEAKER_03
transcript.pyannote[85].start 463.51971875
transcript.pyannote[85].end 464.61659375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 464.61659375
transcript.pyannote[86].end 469.54409375
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 469.56096875
transcript.pyannote[87].end 475.56846875
transcript.pyannote[88].speaker SPEAKER_03
transcript.pyannote[88].start 476.36159375
transcript.pyannote[88].end 478.28534375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 478.94346875
transcript.pyannote[89].end 480.15846875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 480.42846875
transcript.pyannote[90].end 485.44034375
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 486.13221875
transcript.pyannote[91].end 492.64596875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 493.75971875
transcript.pyannote[92].end 494.43471875
transcript.pyannote[93].speaker SPEAKER_03
transcript.pyannote[93].start 495.83534375
transcript.pyannote[93].end 496.22346875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 496.22346875
transcript.pyannote[94].end 504.54284375
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 504.88034375
transcript.pyannote[95].end 514.53284375
transcript.pyannote[96].speaker SPEAKER_02
transcript.pyannote[96].start 514.65096875
transcript.pyannote[96].end 520.87784375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 521.26596875
transcript.pyannote[97].end 523.89846875
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 524.13471875
transcript.pyannote[98].end 528.67409375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 530.15909375
transcript.pyannote[99].end 535.96409375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 535.96409375
transcript.pyannote[100].end 557.26034375
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 557.47971875
transcript.pyannote[101].end 561.44534375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 561.44534375
transcript.pyannote[102].end 561.61409375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 561.61409375
transcript.pyannote[103].end 561.98534375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 561.98534375
transcript.pyannote[104].end 562.89659375
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 562.00221875
transcript.pyannote[105].end 563.97659375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 563.97659375
transcript.pyannote[106].end 565.73159375
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 566.25471875
transcript.pyannote[107].end 585.79596875
transcript.pyannote[108].speaker SPEAKER_01
transcript.pyannote[108].start 585.79596875
transcript.pyannote[108].end 585.82971875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 586.89284375
transcript.pyannote[109].end 601.99596875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 591.71909375
transcript.pyannote[110].end 592.27596875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 592.54596875
transcript.pyannote[111].end 593.40659375
transcript.pyannote[112].speaker SPEAKER_02
transcript.pyannote[112].start 593.77784375
transcript.pyannote[112].end 593.98034375
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 596.03909375
transcript.pyannote[113].end 596.25846875
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 600.98346875
transcript.pyannote[114].end 602.35034375
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 602.35034375
transcript.pyannote[115].end 602.45159375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 602.45159375
transcript.pyannote[116].end 605.37096875
transcript.pyannote[117].speaker SPEAKER_01
transcript.pyannote[117].start 602.50221875
transcript.pyannote[117].end 602.56971875
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 605.77596875
transcript.pyannote[118].end 609.23534375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 609.96096875
transcript.pyannote[119].end 612.57659375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 613.58909375
transcript.pyannote[120].end 614.21346875
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 615.71534375
transcript.pyannote[121].end 619.10721875
transcript.pyannote[122].speaker SPEAKER_02
transcript.pyannote[122].start 619.10721875
transcript.pyannote[122].end 626.00909375
transcript.pyannote[123].speaker SPEAKER_03
transcript.pyannote[123].start 627.07221875
transcript.pyannote[123].end 631.72971875
transcript.pyannote[124].speaker SPEAKER_02
transcript.pyannote[124].start 627.54471875
transcript.pyannote[124].end 628.57409375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 631.20659375
transcript.pyannote[125].end 635.13846875
transcript.pyannote[126].speaker SPEAKER_03
transcript.pyannote[126].start 634.59846875
transcript.pyannote[126].end 637.41659375
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 637.56846875
transcript.pyannote[127].end 647.06909375
transcript.pyannote[128].speaker SPEAKER_03
transcript.pyannote[128].start 648.31784375
transcript.pyannote[128].end 649.07721875
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 649.07721875
transcript.pyannote[129].end 652.48596875
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 653.04284375
transcript.pyannote[130].end 657.21096875
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 657.68346875
transcript.pyannote[131].end 657.70034375
transcript.pyannote[132].speaker SPEAKER_01
transcript.pyannote[132].start 657.70034375
transcript.pyannote[132].end 662.45909375
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 662.45909375
transcript.pyannote[133].end 664.19721875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 665.56409375
transcript.pyannote[134].end 669.76596875
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 671.80784375
transcript.pyannote[135].end 672.11159375
transcript.whisperx[0].start 6.365
transcript.whisperx[0].end 26.802
transcript.whisperx[0].text 主席有請蘇人事長跟薛次長好請人事長跟薛次長委員早蘇發布的報告裡提到說將提出5年期的AI發展戰略計畫現在正在報請行政院核定對不對對那想請問這個是預計在115年啟動那我想請問次長5年的計畫預計編列多少的經費
transcript.whisperx[1].start 41.264
transcript.whisperx[1].end 53.858
transcript.whisperx[1].text 190億那我想請教一下因為AI發展牽涉到很多政府部門那速發部的角色當然也重要那我想請問次長那速發部明年編列多少預算來推動AI的發展
transcript.whisperx[2].start 64.798
transcript.whisperx[2].end 71.783
transcript.whisperx[2].text 我們明年是十幾億但是在速發部的預算那很多是跟其他部會一起提對好謝謝
transcript.whisperx[3].start 73.277
transcript.whisperx[3].end 92.164
transcript.whisperx[3].text 老實說啦跟那個次長說從速發部過去表現來看其實我對你們推動AI的能力是相當沒有信心的那比如說AI發展戰略計畫五大戰略裡面有一項叫做發展智慧化為民服務嘛對不對
transcript.whisperx[4].start 93.345
transcript.whisperx[4].end 122.202
transcript.whisperx[4].text 那是要利用AI客服來協助民眾查報查找政府服務那目前速發部推動的強化智慧政府數位發展計畫其實就是這個計畫有相當的重合度嘛對不對就是過去的計畫並不會特別強調AI的部分所以最大的差異是導入AI建網之來啦我就先看你過去到底做了什麼才能看你未來到底能做什麼
transcript.whisperx[5].start 123.39
transcript.whisperx[5].end 125.573
transcript.whisperx[5].text 那事實上在書發部剛送進來的114年預算書裡面顯示書發部過去的成果是用
transcript.whisperx[6].start 132.9
transcript.whisperx[6].end 157.111
transcript.whisperx[6].text 運用人工智慧新興科技來建置智能小幫手所以你剛剛講也不對你們就已經是要運用人工智慧新興科技了然後建置智能小幫手來協助民眾快速查找政府服務那我想請問次長你知道我們書發部這麼鄭重的推出這個智能小幫手成效如何這個
transcript.whisperx[7].start 161.657
transcript.whisperx[7].end 185.934
transcript.whisperx[7].text 這個我可不可以請這個蘇政司的司長回覆因為他牽涉到各部會的智能小幫手你說什麼跟誰請這個司長回覆好來沒關係來司長請說委員好因為這個我們115年開始那個計畫是五年期的計畫所以我們編一個我跟你講我現在是先看前面的表現啦所以我們114年我們就先有個銜接的好啦沒關係我來問齁這個智能小幫手什麼時候上線的啊
transcript.whisperx[8].start 186.448
transcript.whisperx[8].end 202.905
transcript.whisperx[8].text 而智能小幫手我們是預計今年底是在我們如果是講的是我們速發布自己的話我們是在今年底在我們的整個路口網站上線我想之前的你們之前就有了111年11月上線連自己上線過的東西都不知道不會吧
transcript.whisperx[9].start 203.587
transcript.whisperx[9].end 230.598
transcript.whisperx[9].text 我們那個智能小幫桶應該是純粹智能小幫桶他應該沒有到112年底齁你們這一套的系統你知道累積使用人數是多少嗎111年11月到112年底大概一年時間左右啦我們的入口網大概每年大概是十幾萬人左右我講的是這一個系統不是講你的入口網站好不好你不要把拿你的整個速發部入口網站來蒙混
transcript.whisperx[10].start 231.65
transcript.whisperx[10].end 253.729
transcript.whisperx[10].text 你速發入口網站一年十幾萬的瀏覽人數你也不要驕傲你覺得驕傲嗎?次長你也不覺得驕傲吧?次長你上來好了啦我看他也答不出來所以我跟你說啦使用人次累計是4096人次啦次長你滿意嗎?你滿意嗎?
transcript.whisperx[11].start 258.619
transcript.whisperx[11].end 262.062
transcript.whisperx[11].text 111年11月到12月底使用的是1239次算起來112年全年使用是2587次平均每個月238次每天不到8次點擊率啊 點閱啊
transcript.whisperx[12].start 282.344
transcript.whisperx[12].end 293.511
transcript.whisperx[12].text 所以部長 次長為什麼要拿這個問題問你總知道了吧你知道這個112年度所謂的強化智慧政府數位發展計畫編列多少錢嗎我告訴你啦4149萬啦
transcript.whisperx[13].start 299.144
transcript.whisperx[13].end 321.101
transcript.whisperx[13].text 然後可是你現在照你過去的這個績效用全國規模的預算推出的這個智能小幫手服務人士連一個里我們大概去隨便一個里的人數都比你多那這樣子的話我覺得你的智能小幫手先提升一下我們書發部本身的智能一下好嗎4000多萬先去改善書發部的智能
transcript.whisperx[14].start 323.124
transcript.whisperx[14].end 332.553
transcript.whisperx[14].text 這是為什麼今天我要跟你講說我們當然支持政府來去打造台灣但現在總統說的阿要把台灣打造成AI智慧之島阿
transcript.whisperx[15].start 334.349
transcript.whisperx[15].end 355.712
transcript.whisperx[15].text 可是如果說你過去蘇發布的績效是這個樣子的話那說真的我怎麼對你未來的績效有信心呢打造AI之島當然啦國科會有責任啦對不對我看我們人事總處也在努力要把政府的那個系統怎麼樣去AI化可是蘇發布是重中之重沒錯吧
transcript.whisperx[16].start 357.96
transcript.whisperx[16].end 361.844
transcript.whisperx[16].text 社長我跟你講你講的都要藉口啦4000多個點擊次兩年齁真的是有夠難看的我直接講啦
transcript.whisperx[17].start 383.339
transcript.whisperx[17].end 411.097
transcript.whisperx[17].text 那你等於是一個你花了四千多萬欸一個點擊次是一萬元的成本欸服務一個民眾上去點一次一萬塊欸不是這個意思那你跟我講那個現在也不實用因為現在有新的技術出來打掉了要重練了那我問你過去你就你一個點擊次要一萬塊啊我說真的我未來怎麼對你有信心呢我想書發部的揮霍預算早就惡名昭彰了也不是這件事啦
transcript.whisperx[18].start 412.843
transcript.whisperx[18].end 439.112
transcript.whisperx[18].text 2022年成立嘛大家都希望書發部能夠讓台灣更智慧化數位化推動AI打擊詐騙齁期待很高啦對不對當年嘛對不對可是立法院給了很多的預算事實上你也知道書發部大概是民眾齁最不滿意的部會之一啦為什麼你光像打詐慘不能賭然後很多的東西你知道王世堅委員怎麼形容你們嗎還記得嗎市長還記得嗎
transcript.whisperx[19].start 442.957
transcript.whisperx[19].end 462.068
transcript.whisperx[19].text 我最近記憶力不太好不太好我幫你提醒一下飯桶啊你們是飯桶嗎王世堅委員說你們是飯桶啊我們尊重委員的意見我告訴你不是尊重你們拿出點績效跟行動力證明速發部不是飯桶嘛可以嗎
transcript.whisperx[20].start 463.547
transcript.whisperx[20].end 492.342
transcript.whisperx[20].text 我們會努力 謝謝努力啦 證明不是飯桶 是非常低階的努力啦那我再舉個例子 講你揮霍蘇發部今年出國預算幾個 編列多少預算今年應該是 32個啦預算是3133萬啦 所以有人常講蘇發部叫出國部啦國際交流重要 但是我要跟市長說我就先不講別的部門 最重要的國際交流部門應該是哪個部門
transcript.whisperx[21].start 493.803
transcript.whisperx[21].end 520.774
transcript.whisperx[21].text 政府裡面?外交部當然是外交部啊外交部今年編了也只有14個出國計畫然後編列2908萬書發部不是不能出國考察交流啦可是你們的計畫是外交部的兩倍然後你們的AI服務人士像我剛剛講的Lililala本業都沒做好一天到晚想出國這難怪人家覺得不服難怪王世堅要罵你們是飯桶嘛
transcript.whisperx[22].start 521.394
transcript.whisperx[22].end 528.43
transcript.whisperx[22].text 所以這是你們自己本務要先做好那我要問一下人事長請問國人薪資中位數是多少
transcript.whisperx[23].start 530.402
transcript.whisperx[23].end 556.809
transcript.whisperx[23].text 國人的薪資中位數大概六七十萬之間我看到數字是111年是薪資中位數是51.8萬平均月薪4.3萬那是我的看當然你的數字也許有更不一樣的數字你再告訴我我再提供給委員那我想請問一下人事長你知道蘇發布全體職員平均的月薪是多少嗎比4.3萬高還是低高多少你知道嗎
transcript.whisperx[24].start 557.549
transcript.whisperx[24].end 585.53
transcript.whisperx[24].text 我肯定知道他一定會比較高啊不然他找不到人對對對好比較高我也認同比較高一點我告訴你啊速發部114年編列預算250百位法定編制員和23位約聘僱編列薪水獎金加給加班費加起來月薪是10.2萬一年是122萬那是國人薪資中位數的2.4倍那你知道比起其他部會高還是低
transcript.whisperx[25].start 587.063
transcript.whisperx[25].end 587.083
transcript.whisperx[25].text 請問次長
transcript.whisperx[26].start 619.162
transcript.whisperx[26].end 625.467
transcript.whisperx[26].text 我要告訴你的是基本上你如果拿到的比較好的薪水績效就要怎麼樣
transcript.whisperx[27].start 627.188
transcript.whisperx[27].end 633.112
transcript.whisperx[27].text 中位數有中位數 平均值有平均值的意義啊我要講的是 你拿的薪水比一般的民眾高沒錯吧 你總不能跟他講不是吧
transcript.whisperx[28].start 649.083
transcript.whisperx[28].end 669.197
transcript.whisperx[28].text 平均值你也比較高啦 你還在跟我扯 沈仁市長 速發部現在拿月薪10萬平均值我比一般民眾高有沒有 你跟我講按照我最近看的資料是比一般外面的高對啊 那你還在跟我扯什麼不要在那邊凹來凹去找藉口 人事長都已經打臉你了 以上 謝謝
會議時間 2024-10-14T09:00:00+08:00
委員發言時間 09:39:42 - 09:50:53
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 155402
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/155402
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 2024-10-14T09:39:42+08:00
結束時間 2024-10-14T09:50:53+08:00
支援功能[0] ai-transcript