䚡ḩ㟤㨰㢌䚍䟀㫴G 㥐Y`ỀG 㥐Y䝬 ý 종 설 ý {G rqhltG }UY`OYPSG hSG YWX`
항공분야의 ੋҕמ
현 우 ศ 㽅⬚⬅ᳩ㽂 㻭㲡パ⾝㽂ᛥ
$UWLILFLDO ,QWHOOLJHQFH LQ $YLDWLRQ
:RR6HRN +\XQ 3K''HSDUWPHQW RI &RPSXWHU 6RIWZDUH .RUHDQ %LEOH 8QLYHUVLW\ 6HRXO .RUHD
빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲 G hG pG OhpPG G G X`\]G G G G G G G G G G G G G G
GGGGGUGhpGGGGGGGGG
G G G SG G G G G G G G UG pG G
SG pG G G G G hpG G G G G G G G
GGUGpGGGGGGGGGGGG
G G UG ~G G G G G G G G G hpG SG G G
GGGGGGGGGGGGGGGGG
G G G G G G G hpUG
빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲빲 r GaG hG pSG hSG hSG t
접수: 2019년 8월 4일, 심사완료일: 2019년 8월 11일 교신저자: 현우석
우 01757 서울시 노원구 동일로 214길 32 한국성서대학교 컴퓨터소프트웨어학과 Tel: 02-950-5504, Fax: 070-4275-0164 E-mail: [email protected]
I. 서
᠙ᚭ⾹㎩ㄭ❩⿕㽁⿕ㅡᗭᳩⳉ ⾝∍ゝ┡㈅ọㄭ㽝ᚙ㽑 ㄥ≅ⵑㅡᗭ⫆䁅ㄭ 㿪ⳉㄥ≅ᘅ⬉㽁ᛉㅹ㽁ᱽᙬㄩㅡ⍁ㅁ
」ↁḅスㅁ㽁᪁ㅝ. ១᷂⼱ㅁᛥ㽂★ㅁᚙᛥ┥ㅡㅡᛞ
㎩(artificial intelligence, AI)ᛥ ㅹ᷂䀽(automation)ᱽ ㅝ⇕㽅
スㄭ㽝ᚙ㽝㋭Ⰱㅱᱽ᠙Ⰹ≅⬅ 㝅៥⾹ℑᙙゝᛩⳕㄭ ☄ᛉ
ㅱ.
㎩ㅁ⪕ㅁ◡ᱽ⛡⾹Ἑ⍝㎩⼳ᛉㅝ㽝㽁ᛉ⪕ᛉ㽁
⿕ ⾝ᾍ ㅥㄭ 㽁ᱽ ᙬㄭ ㅁ◡㽅. 㝅㛱ㅁ ⳍを䀽 㣝㻑㬙ㅡ
ENIACㅝ 㚁ㄵ ᘅ★ḁᵁ1940ᬭᳩ ㅝ䂭≅ ㎩Ⳇ ㅹ⊵⾹ 㣝㻑
㬙⍥ㅝを㽅⪙ᛥㇾㄭㄞ㽒㽁⿕ㅡᗭㅁ ㎩ㄭ⛡ᾉ⛝∍ᱽ
ⳅᶭọㅝ ㅱ⾱. ㍲ ᳢ⳅ⾹ ㅝ◡ Ⰱ㽂 ᚭ⪙ Ớ⾹⬅ ㅡᗭㅁ
䃑⼕ᗩ㽁ᱽ㣝㻑㬙ㅁ ∎ㄭ⛝ᛉㅝ⍥ ★ⳅ㪍㣝㻑㬙 ᶭ㎩ㄭᗩ㎱ ⰁㅱㄭᙬㅝⅥᱽ ㋥ㆎ⾹ᛩⳕㄭᗿᙵḁ⾱.
⿕᠙⾹ 㛱㘦᠙ 㛱⬆ㄭ ⎵ỉ ㅝᱽ ㅁ ⽑⇙ 㲅⎪(Alan
Turing)ㅝ. 㲅⎪ㄩ゙⬉㎩⾹ᳩ㽅㠊ㇾᗩ㽅ㇾㅁ⍥⎵
ọ⾱ㄥ ㅝ⍥㲅⎪㬵ⲍ㲡Ⅵᛉ 㽁⿕ㅡᗭᛥ㣝㻑㬙⍥ ❭㽁 ᱽᵙ ㅝを㽁[1]. ㅝᱽ ᗭ᳑䅱 ⬍⑮㽁 ㎩ ⿕❩⍥ 㳹⚭
㽁ᱽᙩ⪕ㅹᗩ㣝㻑㬙〩⪕ⅵㄭ❭㽉 Ⰱ ⾯ᱽ⪪㫅⾹⬅⒑ḹ
⾹ᙵ ┝ㅺロ≅㎱┡ㄭᵁ㎩ᛉ⽺㒦⾹⬅ᳩ᳞ㄭ☄⼭⬅ 㣝㻑㬙
〩 ⪕ⅵㄭ❭㽉Ⰱ⾯ᱽㇾᶭᗩḁ ᳩ᳞⾹㘡⿕㽅㣝㻑㬙 ᶭ㎩ㄭᗩ㎩ᛉㅱᛉ㳹᳑㽁ᱽᙬㅝ. AIᱽ㎩ㄭᗩ㎭
ㅡᗭㅁ 㽲᷂ㄭ ⒑☒㽉 Ⰱ ㅱᱽ ᠙ᚭⅥᛉ ㇾㅁ㽉 Ⰱ ㅱᱽᵙ
1956ᬭ⾹ ◡ 㲡␡ⲍ ᳩ㽂⒑ㅭ⾹⬅ ㅡᛞ㎩ㅝⅥᱽ を⾝
⍥ ⪕を㽁⬅ ㅝ ⳅㇹㄭ ㅡᛞ㎩ ㅁ ⳅㅺㇹㄥ≅ ⛡.
ㅡᛞ㎩ᱽStrong AI〩Weak AI≅᪁ᯭ⾝⛥Ⰱㅱ.
Strong AIᱽ ⪕ⅵᛥ ᘂㄩ ㇾᶭㅁ ㅡ㎩∎ㄭ ⛝ㅝᱽ ⪪㫅≅⬅
㝽≉, ┡㈅㽝ᚙ, ᚭ䁶 Ớㅁ ∎ㅝち⾹ ㅹ⼭ㅁⳆ, ᗹㇾ, ⽺ⳕ
Ớㅁ ㅡᗭぽọᠵ㎩ᗩ㎩ ᚦ㿁᠙☁㽂Ⲟ∎ㅝ 㪪ソ㽁
. ㍲ⳍ㈅⪕ᛉ⍥㮞㽁⿕┡㈅⍥㽝ᚙ㽉Ⰱㅱᱽ♽をAIㅡ
ᙬㅝ. ☁Weak AIᱽ㲢ㇾ┡㈅⾹ 㽅ḅ㽝ᚙ∎ㄭᗿᱽ
ㇾᶭ⍥ ㅁ◡㽅(artificial narrow intelligence). ⼵㳵ᛉ〩 ᘂㅝ
◽Ḻ⾹⎵ 㲢䀽ḅAIᗩWeak AIㅁᳩ㹅ㅡ⿱ㅝᛉ ⲍ㪩サ㍱
Ớㅁ ᛞ⪪ᛥ㽂䀽⾹Ớㆎ㽁ᱽ⎵≅⛰ㄩStrong AI⾹ᗩᡆ
ᛉ㽉Ⰱㅱ. Strong AI ❭⽥ᱽ ⼭㎪ㄩᗱᠡㅝ␥❭⽥ㅝ
㎂ẛ
ͷΚΘ͑͑͟͢͟΄ΥΒΘΖΤ͑ΠΗ͑ͲΣΥΚΗΚΔΚΒΝ͑ͺΟΥΖΝΝΚΘΖΟΔΖ͟
ᛉ 㿭㆕ㅁAIᱽ 㲢ㇾ ┡㈅⍥ 㽝ᚙ㽁᠙ ロ㽁⿕ ㅡᗭㅁ ㅡ
㎩∎ㄭㅥ❩ 䄲ᱽⰁ㋩ㅁweak AIᗩᳩ❩❭ㅝ. ㅝち
⾹㛱ㅡᛞ㎩(artificial super intelligence)ㄩ ᛥ㽂᠙Ⰹ⦹⼭Ჱ
Ⅵ, ⪕䁵 ∎ ᠵ㎩ ㅡᗭㅁ ∎ㄭ ⒑ỉ ⾹⬅ 㛱ソ㽁ᱽ
ㅡᗭ⛝ ⏍゙ ゙ソ㽅 ㅡᛞ㎩ㅝ(Fig. 1) [2]. 」ᲁ᪉AI᠙ Ⰹㄩⲍ⎱㲡㷙ㅝ᪁ᘅㅡを㣝㻑㬙Ớㄭ㮞㽁⿕ ㅝ◡ⳍ⫆䁅⾹
⎷ㅝ 䁅をḁᛉ ㅱ. Siri, Alexa, Google Assistant Ớㅝ ゙⎕
㋥⚩⾹⬅ 䄽䅱 ⛥ Ⰱ ㅱᱽ ⿱ọㅝ. Ό㽅 ㅹㄑ㋥㽲㘑 Ớᛥ
ᘂㄩ ゝ⮊Ⰱ᳑, 㽖ᛞ❩┡, ᙵㅭ ⪙⾮ Ớ⾹⬅ ⳍを䀽ḁᛉ ㅱㄥ
㝅៥⾹ᱽ ㅁ⊵❩┡⾹ᠵ㎩ ⳉ⭶䅱 䀾ᳩḁᛉ ㅱ.
㝅៥⾹ ᛩḅ ᠙☁ ᛥ㽂 ᠙Ⰹㅁ ★⾹ ἙⅥ ㅡᛞ㎩⾹
ᳩ㽅ᛩⳕㅝℑᙙサ㎩ᛉ ㅱㄥ, ⳍ⾹⎵␡┝⍝㎩⼳ᛉⳍ
⫆䁅⾹䀾⪙ḁ⾝ᴽ ㅝ⪪᪗⬉を⾝ᗩ⼭Ჱ. ⛡᭥┡⾹⬅ᱽ
ㅡᛞ㎩ㅁ⪕◸ ᠙⛡᠙Ⰹọㄭ⪝㶝⛝ᛉ㽖ᛞ◸ㅁ㽂 ❭
⽥⍥ ㋺ⳕㄥ≅ 㝅៥ㅁ 䁅を ⿱ọㄭ ⪝㶝⛝ᛉㅹ 㽅.
II. 본 ՇՄԶ⒄ਁ⛌ྱ⑤Զ⋹ᶸ
1950ᬭᳩAIㅁᘅᬹㅝ⫆ㅝↁ≅ ᛩḅ᠙Ⰹọᛥ ㄞ㽒㽁
⬅⽺㽁ᙵ★㽁᠙ ⳅㅺ㽱. 㛱᠙⾹㣝㻑㬙ᗩ⛞ㆊ㽅Ⰱ 㽂ᚭ⪙⎵ㄭᬹ㽁ᗩ ⍡をᶭ≅ᶭ⪕をㅝ ᗩ㽁ᱽᘅ
ᬹㅝ⫆᠙⬅ㅝᙬㄭ㿭㽁᠙ロ㽅㣝㻑㬙⾡⾝≅⬅LISPㅝ
1958ᬭ⾹★㹅ḁ⾱ᛉ 」ↅ᠙ᗭㅡᛞ㎩⾡⾝≅ㅹ⎕⏍ᠩ㽝
〽[3]. ⠭Ⲡ㽅ⳅ᠙⾹Ⰱㅁㅹ⊵ㅮ∎ㄥ≅❩㬙㽁᪁ㅁᚙᛥ
⍥ ⛝ᱽ ⼵ᛉ⎕㎁ㄭ ⪕を㽁ᱽPerceptronㅝ ᘅ★ḁ⾱.
ㅝᙬㄩ ⪙⾹ ⳍ㈅ ᮵⍥ ⬚㽁ᱽ ⳉᚦ ⬡㷕 ᱝ⇙ㅁ ᷂ㅺᛥ
ㄉ⪕㽁ᙵ ᛉ⼱ḁ⾱ᱽᵙ 㽂Ⲟ∎ㄭ ᗩ㎭ ᠙᠙≅ ㋥⒒☄⼭⬅
ㅝ䂭 ⳉᚦ⏆⾹⎷ㅝㄺをḁ⾱[4]. 1961ᬭ⾹ᱽNewellᛥ
Simon⾹ ㅁ㽁⿕ Ⰱ᳑-⒒㹅❭⬆(means-ends analysis, MEA)ㄭ
ㅝを㽅┡㈅㽝ᚙ☒♾ㅝㅡᛞ㎩⾹ ㈅⼱ḁ⾱[5].
ㅝ☒♾ㄩㅡᗭㅁ᠙⛡ㅡ┡㈅㽝ᚙ☒♾ㄭ⛡ℕᙬㅡᵙ ㋥⾝
㎭ ┡㈅⾹⬅ 㿭㆕ ⪪㫅〩 ⒒㹅 ⪪㫅 ⪕ㅝㅁ 㘑ㅝ⍥ ᚭ⪙㽁ᛉ
⿕᠙⾹ᘅㅮ㽉Ⰱㅱᱽ ㉙ㅺㅹ⍥ḹ⾝⬅ㅝ⍥ 㮞㽁⿕Ⰵ㘑ㄥ
≅ ㅝ ḹ ⪪㫅ㅁ 㘑ㅝ⍥ 㝅䀽㽉 Ⰱ ㅱᙵ ⪙ㄭ ☁⛞㽁ᱽ
ᙬㅝ. ㅝ ☒♾ㄩ ┡㈅ 㽝ᚙ ☒⼱⾹ ⎷ㄩ ᶭォㄭ ㋥⾱ㄥ᪁
㽝ᚙ㽝⽥㽁ᱽ ┡㈅ᗩ⎷⼭㎩⬅ 㼭ぽ㽅⒑⎕ᗩ᠙㽁៲Ⰱ
ㄥ≅ 㣍㎩ᙵḁ⾝を㽁᠙ᗩ⾝∍サ㈵. ㅝ⾹ἙⅥ ⿕⇕┡
㈅⍥㽅♱⾹ㅥ☁ㄥ≅㽝ᚙ㽁ᱽᙬ⛝ᱽ㲢ㇾ┡㈅⾹㎺㋺
㽁⿕ 㽝ᚙ㽁ᱽ☒♾ㅝ⒑⪲ḁ⾱ᛉ1970ᬭᳩ㛱☁⾹ ᪁】┡
ᗩⳅⲍ㭅(expert system)ㅝᳩ㹅ㄥ≅ㅡᛞ㎩ ᠙Ⰹㅁㄺを
❭⽥ ㋺⾹⬅ ᗩㆎ 䁅★㽁ᙵ ㄺをḁᛉ ㅱᱽ ❭⽥ㅝ[6].
1980ᬭᳩ⾹ᱽ䀾⍉ㅝ≉ᛥᱽ ⍝ᙵ⽉⏍㽅ㇾ⛝⍥ ㇾ↲䀽 㽁⿕ 㹅㿭㽁ᱽ 㵥㎩ㅝ≉(fuzzy theory)ㅝ ★ḁ⾱. ㅝ⍥ ㄺ を㽁⿕ ㅡᗭㅁ ⪕ᛉ ∎⾹ ᗩᠵゝ ᠙ㄭ 㿭㽁ᱽ ᗩ
䁅★㽁ᙵ ㎭㽲ḁᛉㅱㄥ, ᗩ㈅㹱, ㅹ᷂㈅⾝❭⽥⾹ㄺを㽅
㈅㹱ọㅝ㞅㿭㽁[7]. ⫆┥㽂㎭䀽⒑ᵡ⾹⬅ 㘒⼱㽅㎭䀽
⪙᠙♾ᶭ ᘅ★ḁ⾝ ㄺを Ⰱ㽂❭⽥⾹⬅ ⪕を㽁ᱽ ㉙㽒 㝅
䀽┡㈅⍥ ㋥≅ ⋕. 1990ᬭᳩ 䀾⍉≉ㄭ ᶭㅮ㽅 䀾⍉ ១ↁ 㻭⒑ᵡㅝᘅ★ḁ⬅ᳩを↲⚩Ⰱọㅁ⛞ㆊ㽅⪪䀡ᛩᚭᶭ ㉙
◩㽁ᙵ 㹅㿭㽉Ⰱㅱᙵḁ⾱ᱽᵙ≅⛰ᛞ㽂, ㅁ⊵㎭᳑❭⽥ Ớ⾹
⬅㋺ぽ㽅᠙Ⰹㅝḁ⾱[8]. 2000ᬭᳩọ⾝⬅ᱽ㿭㆕ㅁㅡ㬙 ᬠᛥ ᘂㄩ❭⪙䁁ᚦ⾹⬅モ┡⬅, 㳵ㅥ, ⬅⠭ⲍỚㅁ⎕ⲍ⍥
㪩 ᵙㅝ㬙≅ᯭⳅ㪍ㇾ⛝〩ㅹス⪕ㅝㅁᛩᚭ-ㅁ◡ㇾ⛝
⍥ 㣝㻑㬙ᗩ㚁⎕㽉Ⰱㅱᱽ】㮑≅㎩㿾㫅≅ 㹅㿭㽁ᛉ, 㣝㻑 㬙ᗩ ㅝ⇙ㅹスㄭㅝ㽝㽁⿕ 㼭ぽ㽅⬅⠭ⲍ⍥㎩ㄥ≅ㅝを 㽉 Ⰱ ㅱᱽ ⳅ⑁㳚 モ(semantic web)᠙Ⰹᶭ ᘅḁ⾱[9].
ᳩ↲ㅁᵙㅝ㬙≅❩㬙⪱≖ᛉㅁ◡ㅱᱽ ㇾ⛝⍥㝽㞅㽁ᱽᵙ ㅝ㬙 ⎱ㅝ᳆(data mining) ᶭọᶭ ㅝ ⳅᳩ⾹ ⭶⭶ ᘅ★ḁ⾱
. ⼭ァ⇕⠮ᵙㅝ㬙⍥㚁⎕㽉 ⰁㅱᱽAIᶭ᷂ⳅ⾹⎷ㄩ
★ㅝ ㅱ⾱.
ՈՄԶ⒄ਁ⛌ྱԶḽ଼ἬԶ
ㅡᛞ㎩ㅝⅩ ㅡᗭㅝᗩ㎭㎩ᗪ, 㽂Ⲟ, 㝽≉, ㅹ⾡⾝ 㚁⎕
Ớㅁ ∎ㄭ㣝㻑㬙ᗩⳍ㽲㽉Ⰱㅱᶭ≆⎵ỉ 㻭≅១↑ㅝⅥᛉ
㽉Ⰱㅱ. ㅡᛞ㎩ㄭ⬚㽁ᱽ᠙Ⰹぽọ≅ᱽ㪹⪲(search),
㎩Ⳇ㹅㿭(knowledge representation), 㝽≉(inference) 㽂Ⲟ(learning), ᚭ䁶Ⰱ⎦(planning) Ớㅝ ㅱㄥ ᠙ᚭ㽂Ⲟ(machine learning), Ἆ⇕᳆(deep learning), ㅹ⾝㚁⎕(natural language processing), ㄵ⬚ㅡⳆ(speech recognition), ⳅᗪㅡⳆ Ớ 㚑᳑᠙Ⰹㄭ ᘅ★㽁 ᱽ ☒㾎ㄥ≅ ★ḁᛉ ㅱ(Fig. 2).
ㅡᛞ㎩ㄭ㽞ⳕ᠙Ⰹ≅ ⪕を㽁ᱽ㋥ぽ㽅 ❭⽥ọ≅ᱽ┡
ᗩⳅⲍ㭅, ᵙㅝ㬙 ⎱ㅝ᳆, 㴑㬝ㅡⳆ(pattern recognition), ㅹ
⾝ 㚁⎕, 㣝㻑㬙 ⠭, ㄵ⬚ㅡⳆ, ≅⛰ᛞ㽂(robotics), ⾹ㅝ㲡 (agent), ㅡᛞⳉᚦ⏆(artificial neural network), ᠙ᚭ㽂Ⲟ ◸Ἆ⇕
᳆ Ớㅝ ㅱᱽᵙ ᗪ ᠙Ⰹọㄭ ᗭ᳑䅱 ⪝㶝⛝ ㄵᛥ ᘂ.
┡ᗩⳅⲍ㭅ㄩ㲢ㇾ┡㈅⾹ᳩ㽁⿕ ┡ᗩⰁ㋩ㅁ㽝ᚙ☒⼱
㋫ੳᬂ⋺ⓖ֨⓶ੳ✾ဣ
ͷΚΘ͑ͣ͑͟͟汾击滆垫͑匶爎͑匶朦刂͑昢捊枪 笊筯͟
ㄭ㈅ᛞ㽁ᶭ≆㽁ᱽ ᙬㄭ⒒㹅≅㽁ᱽᵙ, ㎩Ⳇ㹅㿭❩❭ᛥៅ
㡂᠙☁ⳅⲍ㭅ㅡ㝽≉ ❩❭ㄥ≅⬚ḅ. ㍲ㅡᗭㅝ㲢ㇾ❭
⽥⾹ᳩ㽁⿕ᗩ㎩ᛉ ㅱᱽ┡ㅡ㎩Ⳇㄭ 㣝㻑㬙⾹ㅮ∎ⳅ㤅
⪪䀡ᳩ䀽⍥㮞㽁⿕ ᚙᛥ⍥⾤ᱽㅹ┡㿾ⳅⲍ㭅ㅝ. ㅁ⊵❭
⽥⾹⬅㚁ㄵㄥ≅ᘅ★ḅ ┡ᗩⳅⲍ㭅ㅡMYCINㄩㅝ❭⽥ㅁ
䂑ⳅ≅⬅ 䁁ㅹㅁ ᗹ⚺ㄭ ㎭᳑㽁ᛉ 㽖៉㈅⍥ 㚁☒㽁⬅ 㽝
᳢ḅᚙᛥ⾹ ᳩ㽅㝽≉ㄭ㹅㿭㽉Ⰱㅱᱽ ᳩ䀽㿾㻭≅១↑ㄥ≅
ㅡ⪪ㅡ ㎭᳑ㇾ䀾ᶭ⍥⛝⿕㋥⾝⬅ㅝ䂭ㄉ⪕㽅ㅁ㽂㻭≅១
↑ ᘅ★ㅁ㛱⬆ㅝḁ⾱[10]. ㅝ ┡ᗩⳅⲍ㭅ㄩ⪪⾮ㄥ≅
ᶭ ⿕⇕ ❭⽥⾹ 䁅★㽁ᙵ をḁ⾝ ㅁ⊵㎭᳑ ⳅⲍ㭅 ㅝち⾹
ㄉ᠙䀽㽒┥㉙❭⬆, ┥㪹⪕ ⳅⲍ㭅Ớㅝᘅ★ḁ⾱. ┡
ᗩⳅⲍ㭅 ᘅ★ᶭㅡPrologᶭ ㅝ ⳅ᠙⾹ ᘅ★ḁ⾱.
ᵙㅝ㬙⎱ㅝ᳆ㄩᳩ↲ㅁᵙㅝ㬙⾹⬅ㄉㅁ◡㽅 㴑㬝ㅝ᪁❭
⬆ᚙᛥ⍥ 㘧ᱽ ᙬㄥ≅ ᠙ᚭ㽂Ⲟㅝ᪁ 㮞ᚭ㽂 ᠙Ⰹㄭ ★ⳅ㤅
ㇺ⒒㽅⼵ᛉ⎕㎁ㄭ⪕を㽅. ⠮ᵙㅝ㬙⾹ᳩ㽅⎱ㅝ᳆ ᠙Ⰹㅝ
㋥⒒☄ᛉ ㅱㄥ ⫆┥㽂⾹⬅ ㄉ㚝 ⠮ᵙㅝ㬙⾹⬅ ㅁ◡ ㅱᱽ
ㄉ㚝 㴑㬝ㄭ ⼵⼭ᱽᵙ ⪪᳢㽅 ⬚ᛥ⍥ 〕⎕ᛉ ㅱ.
㴑㬝ㅡⳆㄩ┡ㅹ᪁ㄵ⬚ ⪪, 㬶ⲍ㲡Ớㅁᵙㅝ㬙⾹⬅㴑㬝 ㅝ᪁ៅ㡂⬚ㄭ㘧ᱽ ᙬㄭ⎹㽅. ᗭ᳑㽁ᙵᱽ ⲍ⎱㲡㷙⾹⬅ㅁ
㼭᠙㚝ㅡⳆ⾹⪕をḁᛉ ㆉⰁ㽑⾹⬅᪁⍥ㅝを㽅 㽑ㇾ
Ⳇ⚭◸㝽 Ớ⾹ᶭㅮḁ⾝ⳅ㿁ḁᛉㅱ. ㅝ᪁㋺⾹
⬅ᱽCCTV⪪ㄭ 㴑㬝ㅡⳆ ᠙Ⰹㄭ ㅝを㽁⿕ ❭⬆㽁⿕ ᛞᛞ
ㆎ⾹⬅ㅁ㬵⇕ロ㿺ㄭ ㉙᠙㪹㎩㽁ᱽᵙ䁅を㽁ᛉㅱ. 㴑㬝 ㅡⳆ᠙Ⰹㅁ ᠙Ⰹぽọ≅ᱽ Ἆ⇕᳆, ᠙ᚭ㽂Ⲟ, 㣝㻑㬙 ⠭, 䀾⍉⒑ᵡㅁ ᠙Ⰹọㅝ 䁅をḅ.
ㅹ⾝ 㚁⎕ᱽㅡᗭㅝㅝを㽁ᱽㅥ☁⾝⍥ ㅝ㽝㽁⿕⬅⠭ⲍ 㽁ᱽ ᠙Ⰹㅝ. 䁵⪕⾹⬅⫆⪙ḁᱽ ┡⬅⍥ㅝ㽝㽁ᛉㅡᗭ⾹ᙵ
ぽ⽦㽁⿕⛝ᛉ㽉Ⰱㅱᱽᘅㅡ⠭⬅ㅁ㽉ᶭ㽉Ⰱㅱㄭᙬㅝ.
㣝㻑㬙 ⠭ㄩ㣝㻑㬙⍥ ㅝを㽁⿕ㅝ◡㎩ ㅹ⊵⍥㚁⎕㽁⿕
㽝⬆ㅝ ᗩ㽅 ⳅᗪ᠙ㄭ ᗩ㎩ᱽ ᠙ᚭㆎ㡁⍥ ⎵ọ∍ᱽ ❭⽥
≅⬅⪪᳢䅱ⳍを䀽ḅ⼵ᛉ⎕㎁ọㅝᘅ★ḁ⾝⪪を䀽ḁᛉㅱ.
ㄵ⬚ㅡⳆㄩ 㣝㻑㬙ᗩ ㄵ⬚ㄭ ㅮ∎☄⼭ ㅡⳆ㽁ᛉ ┡ㆎㄥ≅
⚩䁁㽁ᱽ ᠙Ⰹㅝ. ㅝ ᠙Ⰹㄩ ⍅ㅝ 」ↁḅ ❭⽥≅⬅
ㅝ◡1990ᬭᳩ⾹⪙䄝ᳩ䀽⾹ᶭ᠙Ⰹㅝ 㪺㆕ḁ⾱⾱ᛉ㝅
៥⾹ᱽ Ⰹ㽅 ᘅㅡ ⠭⬅ 㻭≅១↑⾹⬅ ㋺ぽ㽅 㽉ㄭ 㽁ᛉ
ㅱㄥ ᗩ㈅㹱⾹ᶭ 㪺㆕ḁ⾝ ⳍを䀽ḁᛉ ㅱ.
≅⛰ᛞ㽂ㄩ᠙ᚭᛞ㽂, ㅹᛞ㽂, ㇾ⛝ᛞ㽂, 㣝㻑㬙ᛥ㽂Ớㅝ
㉮㽒ㄥ≅ ⾝゙⇕㎭ ᛥ㽂᠙Ⰹ ❭⽥≅⬅ ㅡᗭㄭ ⛡ᾉ⬅ ㅡᗭ ㅝ 㽉 Ⰱ ㅱᱽ ㅥㄭ ᳩⳉ㽝 ㋭ Ⰱ ㅱᱽ ᠙ᚭ⍥ ⎵ễᱽ ᙬㅝ
⒒㹅ㅝ. ⿕᠙⾹ᱽㅹ᠙ᚭ ᠙Ⰹ(mechatronics), 㣝㻑㬙᠙Ⰹ, ᪁᭡ᛞ㽂, ⫆┥ᛞ㽂Ớㅝ⪕をḁ⿕᠙⾹⽺㽅AI ᠙Ⰹọᶭ
ㄞ㽒ḁ⾝ ㅱ.
⾹ㅝ㲡(Agent)ᱽ ㅡᗭㄥ≅❩㬙 ⑮∢ㄭ ☄⼭ ㅭ┝⍥ ㅹㄑ
ㄥ≅㚁⎕㽝㋥ᱽⳅⲍ㭅ㄭ⎹㽅. 㛱᠙⾹ᱽ᳑Ⰵ䅱ㅮ∎⾹
ᳩ㽁⿕ㇾ㽝㎭☁ㄺ⎵ㄭ㽁ᱽ᳑ᚭ⾹⬅⬥⬅⍥㮞㽁⿕ 䁁ᚦㄭ
ㅡ㎩㽁ᛉ ㅹⳉㅁ ㎩Ⳇᛥ ㇾ⛝⍥ ⪕を㽁⿕ 㽂Ⲟ㽁ᛉ ⒒㹅᳕⬚
ㄭ ロ㽅ᚭ䁶ᠵ㎩⬡サ⬅ⳍ㽲㽁ᱽ᳑ᚭ≅★㽁ᛉ ㅱ. ㅡ ᛞⳉᚦ⏆ㄩ⠭⬉㿾ㅹ⊵㚁⎕⾹⬅ㅹ⊵ㅮ㞅∎⾹⬅ ⬅≅⛞㽒
ㅡ ᛩᚭᗩ⫆ᠡἵㅡ㚝᮵ㅁⳉᚦ⏆ᛥ ⠭Ⲡ㽅⼵ᛉ⎕㎁ㄭㅝ を㽅. ㅥ㘑⪙ḅᚙᛥᗩ㞒❭㽁㎩⼳ㄩᚦ゙ᱽ ⍡⼵ᛉ
㎂ẛ
ͷΚΘ͑ͤ͑͟͟ͽΖΒΣΟΚΟΘ͑ΖΧΠΝΦΥΚΠΟ͑ΚΟ͑ΒΣΥΚΗΚΔΚΒΝ ΚΟΥΖΝΝΚΘΖΟΔΖ͟
⎕㎁ㄭ ㅝを㽁⿕ ⳅ ⪙ㄭ ☁⛞㽁⿕ 㝅㉮ᚙ≉⾹ ᶭ᳕㽁ᙵ
ḅ. ᠙ᚭ㽂Ⲟㄩㅡᗭㅁ ᮵〩ㄉ⪕㽁ᙵᚦ㿁ㄭ㝾㽁⿕㽂Ⲟ ㄭ㽁ᙵḁᱽᵙ, ⪱≅ゝ㎩Ⳇㅝ⳼ㅝ⪱≅ゝᚙㇾ⼵ᛉ⎕㎁
ㄭ ⫆⬚㽁⿕ ᚙ≉⾹ ᶭ᳕㽁ᙵ ḅ.
Ἆ⇕᳆(ⳕ㠞㽂Ⲟ, deep learning, hierarchical learning)᠙Ⰹㄩ
⿕⇕⠭⬉㿾⚩䁁᠙♾ㅁ ㉙㽒ㄭ㮞㽝↲ㅁᵙㅝ㬙⾹⬅㽞ⳕ
ㅡをΌᱽ ᠙ㄭぽ⽦㽁ᱽㅺ⾮ㄭ㽉Ⰱㅱᱽ᭻ㄩⰁ㋩
ㅁ᠙ᚭ㽂Ⲟ⼵ᛉ⎕㎁ㅁ ㎺㽒ㅡᵙ, ⪕ⅵㅁ⪕ᛉ☒Ⳇㄭ 㣝㻑㬙
⾹ᙵ ᗩ⍝㡁ᱽ ᠙ᚭ㽂Ⲟㅁ 㽅 ❭⽥≅⬅ 㝅៥⾹ ᗩㆎ ᗪㄭ
☄ᛉㅱᱽ᠙Ⰹㅝ(Fig. 3). ㅝᱽ Ⰹ㽅ㅡᛞⳉᚦ⏆⾹⬅
㞅★㽅 ᠙♾ㅡᵙ 㝅៥⾹ ⠭⽦ㅡ ★ㄭ ㅝ⋑⾝⬅ ㅹ
⾝㚁⎕, 㣝㻑㬙⠭, ㅹ᷂ㄵ⬚ㅡⳆ, ⽦┥★ᚕ Ớ⪙⾮ᚭ⾹⬅
⎷ㄩ⬚ᛥ⍥ᛉㅱ[11]. 㚝ㄥ≅ 㝅៥⾹ⳍを䀽ḅ᠙Ⰹ
⬚ᛥ┥ọㄩIBM 〼ⲑ, ⪕をⰁ⮊≅⛰Big Dog, ㅹ᷂♱᠙,
㎩㿾ᗩ㈅㹱Ớㅝ⪪を䀽ḁᛉㅱᛉㅡᗭᛥㅁ☒㾎㮞 ㄭᗾ䀽㽅ChatBot (chatter bot) Ớㅝㅱ[12]. ゙㩕Ⅵㅝ᪁⾹
⬅ᘅ★ḅEugene GoostmanㅝⅥᱽChatBotㄩⰉ㽅 㲅⎪㬵 ⲍ㲡⍥㝅㛱≅㮞ᛥ㽁⿕ ᭥Ⅹㄩㅱ⾱ㄥ᪁㎩ㄭᗩ㎭ㅡᛞ㎩
ChatBot ㄥ≅ ㅡㇾ☄⽁[13]. ㅝ䂭 ⎱ㅝ㩕≅㻭㲡⾹⬅
2016ᬭ⾹ᳩ䀽⪪ᳩ☒ㅁ⬚㾎ㄭ㽂Ⲟ㽁⿕ᳩ䀽㽁ᶭ≆⎵ọ⾝
㎭TayⅥᱽㅡᛞ㎩ChatBotㄭ᭼⽁ᱽᵙㅝᱽ⼮ㅁㅡᳩ
䀽 㽂Ⲟ ἵ┡⾹ ᛐ ㋺᳑ḁ⾱[14]. ㅝ ⪕ᙝㄩ ㅡᛞ㎩ ❭⽥
⾹⬅ㅁㅡᗭᳩAI ᠙Ⰹ ⪕ㅝ⾹⬅ㅁㄍ⎕ㅡ┡㈅ ★⫆ㅁᗩ
⬚ㄭ ㅥᡑサ㋥ᛉ ㅱ.
ՉՄԶ⒄ਁ⛌ྱ⑤Զ⩨ଈქ㊱
㝅៥ ゙⎕㋥⚩ㅁㅡᛞ㎩⬅⠭ⲍᱽ㲢ㇾㅭ┝⎵Ⰱ㽲㽁ᱽ
ᗭ᳑㽅 ᙬ❩㬙 ♽を ㈅㹱⾹ ㅝ⍝᠙ᠵ㎩ ⽺㽝㎩ᛉ ㅱ.
ⲍ⎱㲡㷙ㅝ ㅡᛞ ㎩ㅁ 㾎ㄭ ᗩㆎ ␥ ☄ㄩ ᠙᠙ㅁ 㽁 ᪁ㅝ. ᳩ㹅ㄥ≅ㄵ⬚ㅡⳆ◸ᘅㅡ⠭⬅⬅⠭ⲍ 㻭≅១↑ㄥ
≅ 〭⬚ᶭᱽ ⍝㎩⎵ ♽ロ㽁ᙵ ⪕をḁᛉ ㅱ. ⿱⍥ ọ
ㄵ⬚⾹ ㅁ㽁⿕ ㇾ⛝ ᙩ⪲ㄭ 㽁 䀽ᶭ ᙡ Ⰱ ㅱᱽ ᙬㅝ.
ㅝᙬㄭ ロ㽁⿕ ㄵ⬚ㅡⳆ, ㅹ⾝ 㚁⎕, ㇾ⛝ᙩ⪲, 㝽≉ Ớㅁ
⽺㽅 ㅡᛞ㎩ㅁ᠙⛡᠙Ⰹọㅝ䁅をḁᛉㅱ. 㝅៥ ᛞ㽖⾹
⎷ㅝᶭㅮḅ ᛞ㽖⼱ᶭ゙◡⍥ 㽁ᱽ ᳩ䀽㿾ChatBot⾹ᱽロ ㅁ⿕⇕᠙Ⰹ⾹Ἆ⇕᳆᠙Ⰹᠵ㎩ ⾝゙⇕㈡ㅱ. IBM⾹⬅ᘅ
★㽅 〼ⲑㄩㅹ⾝≅㋥⾝㎭㎱┡⾹᳞⚩㽁ᱽㅡᛞ㎩ⳅⲍ 㭅ㄥ≅ ㅹ⾝ 㚁⎕, ㇾ⛝ᙩ⪲, ㎩Ⳇ 㹅㿭 ◸ 㝽≉, ᠙ᚭ㽂Ⲟ
Ớㅁ ㅡᛞ㎩᠙Ⰹọㄭㅝを㽁ᛉㅱ. 〼ⲑㅁ䁅を ❩┡㋺
ㅁ⊵❩┡⾹ㅁ 䁅⽦ㄩ ᯱ❩⬽⬅ 㽂Ⲟ∎ㅝ 㝅ᛉ៲ ┡ ㅁ⪕
㽅⪕ⅵㅝ2ᬭᗭ ᛞ❩㽁ᱽ ⽺ㄭ ⽦ ☁᪁ㇱᶭ ⼱ ḁᱽ ⳅᗭ⾹
㽂Ⲟ㽁⿕┡ᗩọㄭ᭩Ⅵᙵ㽁[15]. 㽁㎩⎵ⳍ㈅⚺ス⾹
⬅ㅁ 䁅を⬚ㄩ⼭㎪◡◡㽁⿕⾭㚖᪅᠙ᚭ㽂Ⲟ∎⾹ᶭ❱
㽁ᛉ ⼭㎪ㄩㄉㅁ㽅㘑ㅝᱽ⛝ㅝ㎩⼳ᛉㅱ. 㽁㎩⎵ㄉㅹ
❭⬆ ㅹ⊵ ❭⬆, ៱ㄞ⬅⠭ⲍ, 㮞ⳉ, ⪕䁵 㿭⪪ ❭⬆ Ớ⾹⬅ᱽ
ㅝ◡ ⎷ㄩ 䁅を ᗩ⬚ㄭ ⛝ㅝᛉ ㅱ.
៩ᛥ 㬵ⲕⅥ⾹⬅ᱽ ㅹㄑ㋥㽲 ㅹ᷂㘑⾹ ㅡᛞ㎩ ᠙Ⰹㄭ
ㇺ⒒㽁⿕ ⬚ᛞㅡⳅ♽⬅⠭ⲍ⍥⛝ㅝᛉㅱ. ⳍ㈅≅ ᳩ❩❭
ㅁㅹ᷂㘑䁵⪕⾹⬅ᱽゝㅹㅁ ⪪㫅⍥⪝㶝⬅ᚦᛉ⍥ 㽁ᙙ᪁
ゝ ㋺㘑⬉ㅝ㪱ㄭᚦᛉ㽁ᛉ㋥㘑ⳅ⾹ ㅹ᷂㘑ㅁ㝅ㅹ⬡
⍥⼱㽁ᱽ ỚWeak AIⰁ㋩⾹⬅ᱽㅝ◡ⳍ⫆䁅⾹ọ⾝〩ㅱ ㄥ ᝪ២ㄥ≅ᱽ 〭 ㅹㄑ ゝ㽲ㅝ ᗩ㽉 ᙬㄥ≅ ⛝ㅡ.
≅⛰❭⽥ㅁ ᛭⒒㽉⎵㽅 ★ㄩ ☒ ❭⽥⍥ ㋺ⳕㄥ≅ᶭ ㅝ⋑
⾝㎩ᛉㅱ. ◡⛝ⲍ㬝 ㅝ᪁◢ⲍ⪕⾹⬅ᱽをㄥ≅⽥
⾹⬅ 䀽┥ㄭ ᪁⍝ᱽ をᶭ≅BigDogㅝⅥᱽ4㉚ ⛝㽲 ≅⛰ㄭ
ᘅ★㽁ᱽᵙ ⪙⼮㎩㿾⾹⬅ ㅡọᛥ ᘂㅝ ⬚ᛞㄥ≅ ㅝ᷂
ㅭ┝⍥ 〭Ⰱ㽁(Fig. 4). ㅝ䁵⪕⾹⬅ᱽ ㅡᗭᛥㄉ⪕㽅2㉚
⛝㽲 ≅⛰ᶭ⬚ᛞㄥ≅ᘅ★㽁ᛉㅱ. ㅝ⇕㽅≅⛰ ᘅ★⾹ᱽ
Ⰹ㽅 ⒑ỉ ᠙Ⰹọㅝ ᭢⼭ọ⾝ ㄞ㽒ḁ⾝ㅱ[16].
ㅥ⪪⾹⬅ 䄽䅱 ⪕をḁᱽ ⬅⠭ⲍ ㋺⾹ ♱⬅⠭ⲍ(machine
translation)ᶭ ㅱ. ៩⾹⬅ ゝ㽁ᱽ㳵㳵ᛉ ♱᠙ᱽ⬡
㋫ੳᬂ⋺ⓖ֨⓶ੳ✾ဣ
ͷΚΘ͑ͥ͑͟͟ͳΚΘ͑͵ΠΘ͑ΓΪ͑ͳΠΤΥΠΟ͑͵ΪΟΒΞΚΔΤ͑͟ͳΚΘ͑͵ΠΘ͑ΦΒΕΣΦΡΖΕ͑ΣΠΓΠΥΚΔΤ ΓΖΚΟΘ͑ΕΖΧΖΝΠΡΖΕ͑ΒΤ͑Β͑ΞΦΝΖ͑ΥΙΒΥ͑ΔΒΟ͑ΥΣΒΧΖΣΤΖ͑ΕΚΗΗΚΔΦΝΥ͑ΥΖΣΣΒΚΟ͟
ΙΥΥΡΤͫ͠͠ΨΨΨ͟ΪΠΦΥΦΓΖ͟ΔΠΞ͠ΨΒΥΔΙͰΧͮΔͿΤΣΨΦΞ͙͑ΒΔΔΖΤΤΖΕ͑ͲΦΘΦΤΥ͝
͚ͥ͑ͣͪ͢͟͝͡
΅ΒΓΝΖ͑͢͟ 沂愞汾͑堆旇求嵢͑汾击滆垫櫖͑堆穢͑抎橎͑柲庲͑浶斲͑冶刂
抎橎͑柲庲͑氦笛 愷把氮
͑Ͳͺ儆͑滇櫋汊͑掂橝橊͑儎͑冉 ͖ͤ͟͢͡
͑儢汾͑稊岂決憊柢͑獮空 ͖ͤͤ͢͟
͑Ͳͺ儆͑汾儊昷汊͑掂橝橊儎͑冉 ͖ͣͧ͢͟
͑Ͳͺ儆͑汾儊櫖͑堆穳穞垚͑冉 ͖͑ͩͩ͟
͑Ͳͺ儆͑憚淊櫖͑決殯埿穞垚͑冉 ͖͑ͩͨ͟
͑Ͳͺ儆͑柪朞庂͑洆滆幺垚͑冉 ͖͑ͩͥ͟
΄ΊΊΊ͑͵ΚΘΚΥΒΝ͑ͺΟΤΚΘΙΥ͑ΖΡΠΣΥ͑ͣͨ͢͟͡
ᚭㅁⰁⳖᘅ⾡⾝⍥ⳍⳅᗭㄥ≅♱㽝㋥ᱽ⬅⠭ⲍ⍥㈅ᛞ㽁 ᛉㅱᱽᵙ㮞ᚭ㽂 ᠙♾ㅝをḅ᠙ᚭ㽂Ⲟ♾ᛥἎ⇕᳆᠙Ⰹ ㅝ をḁ⾝ ㅱ[16]. ᠙ᚭ 㽂Ⲟㅁ ㇾⰁ⍥ ⛝ㅡ ⿱ᱽ ◽Ḻ㻭
≅១↑ㅡ⼵㳵ᛉ≅⬅ᚦㅝ≅ゝ◽Ḻᳩ㽂Ⲟ ∎ㄭ㮞㽁⿕
⬡ᚭ⾹ ⼵∍㎩ᙵ ḁ⾱[17].
ՊՄԶ⒄ਁ⛌ྱ⑤Զ⌍㊱
ㅡᛞ㎩ ᠙Ⰹㅝᗪ㉮⪙⾮⾹ ⛡ᚒㄥ≅をḁ᠙ⳅ ㅺ㽁⬅⫆⪙⬚◸ 䂑ㄑ⬚㎆ᳩ, 㶡⎕⬚ 㾎⪪Ớᗪ㉮ ៶ㇾ
㳵៲䂑ᛥ⍥ ㅥㄥ㪍ᛉ ㅱ.
ㅡᛞ㎩ㄭ 㷕㽑㽅᠙Ⰹㄩ᠙㉝ㅁㅥㅹ⎕⍥⾯⽉᠙ᶭ㽁ᛉ
⪱≅ ⎵ọ᠙ᶭ 㽉 ᙬㄥ≅ ⛝ㅡ. ㅝ⾹ᱽ ⪙⾮䀽⾹ ㅁ㽁⿕
᭡᷂∎ㅝ⎷ㅝ⒑ḁᱽ ㎪⾮ㅝ᠙ᚭ≅ᳩ㚝ḁ⬅⎷ㅝ⪕
Ⅵ㈵ㄥ᪁◡ↁ⾹ᱽㅡᛞ㎩ㅁ⛝㶡䀽⾹ἙⅥ⬅៱ㄞㅡ, ♾⍉
ᗩ, ㅁ⪕ Ớㅁ 䀽ㅝ㲡㡥Ⅵ ┡㎪ᶭ ⚩䀽ᗩ ❱ᗩ㼥 㽝㈵.
ㅥ☁ㄥ≅ᱽAIㅁᶭㅮㅝ㎩Ⳇ㎺⽦ ㎪⾮⾹ᱽ᪁⩅㾎ㄭ
㋥ᛉ, ᭡᷂㎺⽦ ㎪⾮⾹ᱽ ⚭⍡ 㾎ㄭ ㋥㎩ ⼳ㄭ ᙬㄥ≅
⿱⪪㽁㎩⎵ 㾎䂭⾹ᱽ ⾝ᾍ ☒㾎ㅝỉ ⪙⾮ᚭㅁ ㎪⾮ㅁ 㳹ᶭ
⾹㩙⚩䀽ᗩ ⿱⪪ḅ. ㄍ⎕ㅡ┡㈅ᶭ★⫆㽉ᙬㄥ≅⿱⪪
ḁᱽᵙㅡᗭᳩⳉAIᗩ㋥ᶭㄥ≅㳹᳑㽁⿕ ┡㈅ᗩ⫆᠙ᱽᚦ
゙ᱽ㘮ㅭ㆕⾹ ᳩ㽅᭥ㆪㅝ⿱⪪ḅ. 䄽䅱ᙙ≉ḁᱽ⿱≅
⬅ㅹㄑ㋥㽲ㅹ᷂㘑ㅁ ⪕ᛉ⿱≅⬅㼥㽉Ⰱ⾯ᱽ⪕ᛉ ⪪䁒⾹
⬅⛝㽲ㅹ1⑮ㄭ䅕⫆㽁⿕Ⰱㅁ ⍡⛝㽲ㅹ⍥⛝䀡㽁ᱽ⿱
≅⬅᠙ᚭㅁ㳹᳑ㅝ ㄍ⎕ㄥ≅Ⰱを㽉⎵㽅ᙬㅡ㎩⾹ᳩ㽅᭥
ㆪㅝ១ᙬㅝ. ㅝ◡ ᛞ⪪ᛥ㽂䀽Ớ⾹⬅⋑⾝㎩ᱽをọ
≅㝅㉮ㅡ㳹᳑ㅁ ㋥㚝ᗩㅡᗭㅝ⼭ᲱᛉAI Ớㅁ ᠙ᚭㅡᚦ
゙ ㅡᗭㅁ ㉝⾭⬚ㅝ ᶭ☄ㄭ ᗩ⬚ᶭ 㞒❭䅱 ㅱ. ⳍ㈅≅
AI᠙Ⰹㄩ⪕❭⽥⾹⬅〾⬚㽁ᙵ䁅をḁᛉ ㅱᱽᵙ⪝⪪をㅹ ㄑ┝᠙ 㚝ᚭᗩ ᳩ㹅ㅡ ⿱≅⬅ 㬙◡ᬍㅝ㬙 䀽⾹⬅㚁⇥ ᠙ ᚭ〩 ㅡᗭᛥㅁ 㽅㳹 Ⲣ❩ㅁ ⠭២ㅝ ⫆ᠡ Ⰱᶭ ㅱ. ㄉ⪕㽅
ⳍ㈅⿱≅⬅, 60~70ᬭᳩ⾹ ᷂ᶮ⾹⬅⬅ᶮㄥ≅ㅁ⏆⑮ㄭ⎲᠙
ロ㽝 ᷂ᶮㅝᚦ⾹⬍㡁㽅┝ㅡㅹ᷂ ᠙ᛩ㜆⾹ㅁ㽅ㅹ᷂
⪕ᚒ⾹ ㅹㄉ⍥ 㘧⼭ ᚦㄭ ᬁᵁ ⎷ㄩ ᷂ᶮㅡọㅝ 䅕⫆ḅ◽
ㅱ. 㿭㆕ㅁAI ᠙♾ㄭ ㅝを㽁⿕ ㄉ⪕㽅 ㆎ㡁⍥ ⬍㡁㽅
᳢䅱䃑⼕ ⎷ㄩ㼥㽝⍥⛥ᙬㅝ. ᗩ᪁ ᳑㚝ᗩAI⍥ ㆎ⼮
㽁⿕ᘅㅡㅁ⪕⫆䁅ㄩ┥≉⒑ỉᙬㄭ㮞㈅㽁ᛉㅹ㽅䀽
⾹ ᪁」ᱽ⠮⟵Ⅵᴽㅁ㞅㿭ᶭ㞒❭䅱ᗩ㽅ⳅ᪁⎕」ㅝ. ㅝ
⇕㽅 ⿕⇕ᗩ㎩゙∍ἵ┡⾹ㅡᗭㅁ㉝⾭⬚ㄭ ᳝⛝㽉Ⰱㅱᱽ
ᛩ⎕◸㮞㈅ⳅⲍ㭅ㅝ 㞒❭䅱Ạ☄㡑ḁ⾝⽥㽁ᱽᵙㅝ❩❭ㄩ
᠙Ⰹ ❭⽥〩ᴽ❱⾝㾎䂭AI ⾹㋺ぽ㽅㽅❭⽥ᗩ ḉᙬㅝ
.
┡ᗩ ㎺᳑ㄭᾉ᪁ㅥ☁ᳩ㋺⪕ㅝ⾹⬅ᱽ ㅡᛞ㎩᠙Ⰹㅝ
ⲍ⎱㲡㷙, ᗩ㈅㹱, ㅹ᷂㘑Ớ⫆䁅ㅁ⿕⇕❩┡⾹⬅ㅝ◡䁅 をḁᛉㅱ㎩⎵ᳩ❩❭㲢ㇾ᠙ㅁ㽝ᚙㄭロ㽅ᶭ≅⎵⿕᠙ ᛉ ⪙⾮◸⪕䁵☁⾹◡㡁ᱽ㾎∎⾹ ᳩ㽝⬅ᱽㆁㅝ㽝㽁
㎩ ⒤㽁ᛉㅱᱽᙬㄥ≅⛝ㅡ. 㽅㉙⪕⾹⬅ᱽ ㅥ☁ㅡᳩ
⪪ㄥ≅ ㅡᛞ㎩⾹ ᳩ㽅 ❱⼱ ⳕ⎕⍥ ㉙⪕㽁ᱽᵙ ㄺ᳞ㅹㅁ
30%ᗩAIᗩ 㾎䂭 ゙⎕ㅁ ㎪⾮ㄭ ⡥⽀⼭ ᗱ ᙬㅝⅥᛉ ㄺ᳞㽁
ᱽ ᚙᛥ⍥⛝⿕⬅⎷ㄩ⪕ⅵọㅝAI᠙Ⰹㅝ゙䀡ㅡ☁∍ㅹ≅
⬅ᛞ㉝㽁ᱽᵙ⾹ᱽ ⼭㎪ㅁⳕㄭᗩ㎩ᛉ ㅱᱽᙬㄥ≅⛝ㅡ
(Table 1) [18].
ՋՄԶ㉹ਁ᪐⊈⋜Ḩ⑤Զ⒄ਁ⛌ྱ
㽖ᛞ❭⽥ᱽᳩ㹅ㅡ㎩Ⳇ㎺⽦ ⪙⾮ㄥ≅AI ᠙Ⰹㅝᗩ ㆎ ␥ᶭㅮḅ❭⽥ㅝ. ⼱ㅝᗩㆎ㋺ⳅḁᱽ ❭⽥᳞ᙵ㉙
㉮⪕⍥ᶭ〩⬅⠭㽲⼱ㄭᗾ䀽㽁ᱽ ☒⼱ㄥ≅⬅AI ᠙Ⰹọㅝ
ᶭㅮḁ⾱. 㚁ㄵ⾹ᱽㅹ᷂㉙㉮ㆎ㡁⍥㋺ⳕㄥ≅㉙㉮⪕ㅁ ⠭ 㽲⾮┝❩᳝ㄭ㋭ㅝᛉㆎᙙ⎕⠭㽲ⳅ㽖≅⍥ ㅬ⾝♭⎕㎩⼳ᶭ
≆ᶭ〩㋥ᱽ㽉ㇾᶭ≅ⳅㅺ㽁. ㅝ䂭⠭㽲᠙ᗩᳩ㿾䀽ḁ
⬅᠙⪪⾹ ⪪ᛩ⾯ㅝ㉩ᴽㆎᙙ⎕⍥⠭㽲㽁ᱽ☁᠙ᛩ⪕, 㮞ⳉ⪕, 㽖♾⪕ Ớㅁ ㉙㉮ⳍ 㪺Ⲣㅡスㅝ ᗹḁᛉ, ᛞ㽖ᛥ ㋥
⚩ㇺ៥㎩ㄩ㷕䀽ḁ⾝ゝ㽖Ⲣ┝スㅁ ⾮┝❩᳝ㅝ㩕ᙵᲁᛉ
ㅝ⾹ἙⅥ⪕ᛉ★⫆ㅝᲁᙵ ḁ⾱. ㅝ⾹ἙⅥAI ᠙Ⰹㄭㇺ⒒ 㽁⿕ ゝ㽖Ⲣ┝スọㅁ⾮┝❩᳝ㄭ㋭⿕㋥ᛉゝ㽖 ⳅ⾮┝㳹
᳑ㄭ ⡉⍝ᛉ ㇾ䀾㽁ᙵ ㅝ⋑⾝㎩ᶭ≆ ⎷ㄩ ᠙⿕⍥ 㽁ᛉ ㅱ.
㎂ẛ
㍲ ㅝ◡ ⪪を䀽ḁ⾝ ⪕をḁᛉ ㅱᱽ ㅹ᷂㉙㉮ㆎ㡁(autopilot)᪁
ㅹ᷂⛞㽲㎩スㆎ㡁(TOGA) Ớ⠭㽲㋺ㅁ㋺ぽ㽅ᚙㇾㅁⰅᗭ⾹
ᱽ ㅝ◡ ⎷ㄩAI ᠙Ⰹㅝ をḁᛉ ㅱ.
ㅝ⇰ᙵ ㅝ◡ 㲢⚭㽅 ㅭ┝㋺ⳕㄥ≅Weak Ⰱ㋩ㅁ ㅡᛞ㎩
᠙Ⰹㅝ 䁅をḁᛉ ㅱㄥ᪁ ᝪ២ㄥ≅ᱽ ㅡᗭ ㉙㉮⪕⍥ 〭䅱
ᳩ㚝㽉 Ⰱ ㅱᱽ ᛉᶭㅁ ㅡᛞ㎩ㅝ 㞅㿭㽉 ᙬㄥ≅ ⿱⪪ḅ.
◡ᛞ⾹⬅ᱽAIᗩᛞ㋺៲ㄉ, Ⰱ⮊ ◸㰕ㅭ┝⾹⬅ ㄉㅡ㽖 ᛞ᠙ㅁ㽉ㄭᳩ㚝㽉ᙬㄥ≅⿱⪪㽁ᛉㅱᛉㄉ⇦ᛥ◡ 㽝
Ớ⾹⬅ᱽWeak AI⛝㉩ᴽ 㷖ㄩAI ᠙Ⰹㄭを㽅┝ㅡ
ㇾ㘙/ᛞᚒ᠙⒑ᵡㄭᘅ★㽁⿕ⳅ㈅᠙⍥㈅ㅺ㽁ᛉⳅ㿁㽁ᛉㅱ
[19].
㽖ᛞ⪕ゝ❩❭⾹ᶭAI᠙Ⰹㄭᶭㅮ㽁 ⪪᳢㽅⚩䀽⍥⫆
ᠡᙬㅝ. ᛉᘆᛩ⎕ 㘑ス⾹⬅᠙㉝Ⲣᘆㅁ㪺Ⲣᚦ㾎ㄭ㳵⼮
㽁⿕ 㪺Ⲣ ❩㬙 㽖ᛞ ⏍ ㄉᶭ ◸ ᛞ㽖ㇺ, ㉵⬆ ☙ㇾ, Ⰱ䀽┥ᛩ⎕ Ớ ㅥ☁㎪スọㅝ㽝」ᵁ⬅⠭ⲍ⍥㉩ᴽㄉ㽁ᙵ
䂑ㄑㄥ≅ 㽉 Ⰱ ㅱㄭ ᙬㅡᵙ 㚝ㅡ を❭⽥ᱽ ㄵᛥ
ᘂㄩ⿱ọㅝḉ ᙬㅝ. 㚔㏡, 㽖ᛞᗩᚒᚙㇾ⾹ㄉ⬚ ㅱᙵ
᷂ㄥ≅ᚙㇾ㽉Ⰱ ㅱㄭᙬㅝ(dynamic pricing). ṁ㏡, ⳅ ㆎ◸䁵⪕⪪䁒⾹ 㝅䀽ḅᗩᚒㄭ⬍ㇾ㽁⿕㪺Ⲣ⍉ㄭ㝅ᳩ䀽 㽉 Ⰱ ㅱㄭ ᙬㅝ(price optimization). ⬴㏡, ⠭㽲ⲍ㣩㋭ ㎩
ㄩ᠙⪪, ⠭㽲᠙ ᛉㆎỚⰁ⎷ㄩㅡㅹọㅝᛩ⿕㽁⿕★⫆㽁ᱽ ᵙAI ᠙Ⰹㄭ ㅝを㽁⿕ ㎩ ⿱⪪ ㇾᶭ ◸ ᳩ㚝 ⲍ㣩㋭ Ớㄭ
ⳅ⾹㈅ⳅ㽝㋭Ⰱ ㅱㄭᙬㅝ(flight delay prediction). 㽖ᛞ
⪕ㅮㆎ⾹⬅ᱽ⠭㽲ᛩ⎕ᶭ㋺ぽ㽅❭⽥ㅝ. ゙⬉, AI ᠙Ⰹㄭ
ㅝを㽅㝅ㅁ㽖≅ ★◸ㄉ㎩ᱽㄉ⍁⠭, 㽖ᛞ᠙ゝをⳅᗭ
᳑㝾Ớㄭ㮞㽁⿕⎷ㄩゝをᚦ⠭⍥ ㇱᗹ㽉Ⰱㅱ(flight route optimization). ㄵㄥ≅, Ⲣᘆọㅁ⿕㽲ⲍ㣩㋭ ◸Ⲣ┝ス ៥┝
ⲍ㣩㋭ᶭ㝅䀽ⳅ㤅㈅ⳅ㽉Ⰱㅱ(avoiding travel disruption, crew scheduling).
㪺Ⲣᘆ ⛝⼱⾹ᶭ ㄉを㽁ᙵ を㽉 Ⰱ ㅱᱽᵙ ᳩ 㬵⇕ ᳢
ㄥ≅❩㬙 ⳍⳅᗭㄥ≅ ⾮ᵙㅝ㲡ḅ ㅹ⊵⍥ ◽㪾ㄥ≅ 㽂Ⲟ㽁⿕
㬵⇕ ロ㿁ㄭ ◡⎕ ᗹ㎩㽁⿕ ᚦ⛝⍥ ㋥ᙙ᪁ 㼭ぽ㽅 ㉙㡁⍥ 㽉
Ⰱㅱㄭᙬㅝ. 㽖ᛞ⪕ᚦ⾮┝⾹⬅ᶭAI᠙Ⰹㇺ⒒⾹ㅁ㽁⿕
⎷ㄩ ᶭォㄭ ☄ㄭ Ⰱ ㅱㄭ ᙬㅝ. 㽖ᛞ᠙ ゝ㽖 ㋺ ★⫆㽁ᱽ
ㄉ⍁⠭Ớㅁ 㼭Ⰱぽᚦ⠭ㅁᯭḅ ᵙㅝ㬙⍥㽂Ⲟ㽁ᛉ ᚦ
ㅹㅡ ㉙ㅺㅹㅁ ぽ⾹ ⏇ᙵ 㝽≉ ❭⬆㽁⿕ ⳍⳅᗭㄥ≅ ⠭㽲
⪪䁒ㄭ⒑Ჱ㬙⎪㽁⿕ᗩㆎᚦ㈅ㅡ⠭㽲㽖≅⍥㘧ᛉㆎ᠙
ㄥ≅ᱽ ᯭḅ ᵙㅝ㬙⍥ ◽㪾ㄥ≅ ⪱≅ゝ ⠭㽲᠙ ᠙㉮ ⏍
Ớ ᚦ 㳹᳑⾹ ᶭォㅝ ḉ Ⰱ ㅱ. ㅥ☁㽖ᛞ ❭⽥⾹⬅ᶭAI ᠙Ⰹọㅝ㿾⠭㽲᠙⾹ᶭ をḁ᠙ⳅㅺ㽁. ᗩㆎ␥ᶭ ㅮᙬㄩ⾽㎭ ㇾ⠭❩❭ㅝ. ⠭㽲᠙⬚㹱㋺⾹⬅ᗩㆎ⛞ㆊ 㽁⿕ ㇾ⠭ ぽᗩ ⎷ㄩ ⾽㎭❩⾹AI᠙Ⰹㅝ をḁ⾝ ㋥⾝㎭
⠭㽲㉙ᙝ⾹⬅㝅ㅁ⾽㎭䂑ㄑㄭ★䄁㽁ᙵ㽁ᛉㆎ⠱ᶭ⍥
㋭ㅝᛉㇾ⠭ぽ⍥䁶᠙ㄥ≅ᗹⳅ㪍ᛉㅱ(Full Authority Digital Engine Control; FADEC) [20]. FADECㅝㆎ㘒ḅ⠭㽲 ᠙ᱽ⾽㎭⾹⽺㽅 ⬥⬅⍥❩㘒㽁⿕⠭㽲㋺⠭㽲ㅹ⊵⍥ 㝾
㽁ᛉᬍ㲡サ㩕⍥㮞㽁⿕䁵⪕ ⬅♭᪁⾽㎭㈅ㅺ⪕㩝Ⅵ゙ễ
〩 㮞㽁 ⲍⲍ≅ 㽂Ⲟ㽁⿕ ㇾ⠭ ⳅ᠙, ᛉㆎ ロ㿁ᶭ, ᛉㆎ
⿱⪪❩ロ◸ⳍ㈅ᛉㆎ★⫆❩ロỚㄭ⼵∍㋥ᙵḁ⾝ᗪ⾽㎭⾹
⏇ᱽ ⿱☒ㇾ⠭ᶭ ᗩ㽝㈡⬅ ゝ㽖 ㋺ ⾽㎭ ᛉㆎ⍉ㄭ 㿭䅱
ᗹⳅ㪍ᛉ ㅱ.
ᛩ㈅ ❭⽥⾹⬅ᶭAI ᠙Ⰹᶭㅮ⾹ἙⅥ⎷ㄩ⾮┝䂑ㄑ⬚ ㎆ ᳩᗩ ⿱⪪ḅ. 㿭㆕ᱽ⠭㽲㋺ㅡ㽖⾹⬅㞒ᶵロ㿁ᶭ⿱⪪ ◸
ロ㿁㶲ᗩ⾹ Ἑ⍡ᚦ⛝⾮┝Ớㅝⳅ㿁ḁᛉㅱ. ᛩ㈅ⳅ⬍䀢 ㄩ⠭㽲᠙ㅝ⪪⾹Ἑ⍡ ⠭ㇾ⪪⪪䁒⾹⬅ㅁ៲ᛩ㈅Ớ⾹ᶭ ᯭ
ḅ ᛩ㈅ ᵙㅝ㬙⍥ 㽂Ⲟ㽁⿕ ៲ᳩ㚁 ☒⼱ㄭ ㈅ⳅ㽝 ㋭ Ⰱ
ㅱᛉ ㅹ⊵⍥ᯭ㽁⿕ᛩ㈅ 㻭≅㮉㥅ㄭᘅ⬉㽁ᛉ㽖ᛞ⪕ᵙㅝ 㬙〩 ᷂㽁⿕ 㽖≅⍥ 㝅䀽㽁ᱽᵙ ᶭォㄭ ㋭ Ⰱ ㅱ.
ㅝ⇕㽅᠙Ⰹ★⾹ᶭ❱㽁ᛉ⼱㽅 㽖ᛞゝ㽖ㄭロ㽅ㅡ
ぽㅡᛥ ㅡᛞ㎩ㅁ㉙䀽☒㾎⾹ᳩ㽅᭥ㅁᗩ㼭ぽ㽁. ☁
ㅡ⪙⾮㲡⇵ễ⍥ ᛉ∍㽉ἵㅡᗭ㉙㉮⪕〩AI (≅⛰ ㉙㉮⪕) ᗩ ᛞ㉝㽉ᙬㄥ≅⏆ḑ⾹ἙⅥḹᘅ㚝ㅁ ㉙䀽⾹ᳩ㽅㋩⠭
〩 ᛉ◥ㅝ㼭ぽ㽅ⳅㇹㅝ」ᛉㅱ. 㽖ᛞ᠙ ⪕ᛉᱽ★⫆⍉ㄩ
᪗㎩⎵⍡㮞Ⰱ᳑ᛥ᳕⎕⪕ᛉㅁ㡁⑮⬚ㅝ᭻⼭⼱⬚⾹
ᳩ㽅ぽᗩ ⏍゙᭻. 2018⾹⬅2019ᬭ⪕ㅝ⾹ㅝ⾝ ★⫆
㽅B737 MAX ⪕ᛉᱽ ᠙ᚭ〩ㅡᗭㅁ⾮┝㉙䀽⾹ᛉ◥ㅝ㼭
ぽ㽑ㄭ ⛝⿕㋥⾱[21]. ⛡ ⪕ᛉᱽ ⒑ḹ ㅝ⍂㽅 ㎪䂭 㝽Ⅶ㽝
㪺Ⲣㅹスㅝ⪕⏆㽅ᙬㅡᵙ㉙㉮⪕ᗩⰁ᷂ㄥ≅㉙㉮㽁ᱽ ⪪ 䁒⾹⬅ ㅹ᷂㉙ㇾ㣝㻑㬙⑮∢(AI ⼵ᛉ⎕㎁)ㅝ゙⬉㽁⿕ ㅺ᷂㽁 ᶭ≆⬍ᚭḁ⾝㉙㉮⪕ᗩ㽖ᛞ᠙⍥㮞㈅㽉Ⰱ⾯ᱽ⪪䁒ㅝ★⫆
㽁⿕ ⫆ᙬㅝ. ㅝ⍂㎪䂭㻵→ㄭㇺㄩ䂭⾹ㅁᶭ㽁㎩⼳ᙵ
☄ㄵᗪㅝ 㣍㈡⬅ⳍ⭶⾹ㅁ㽅㝽Ⅶㅝ㉮㉮ㅥ⾝᪁ᱽᵙ ᳩ❩❭
㉙㉮⪕ ⳍⰁ⾹ㅁ㽅ᙬㅝ. ㅝ♱⪕ᛉㅁ㋥ḅ スㅡㄥ≅㎩⒒ ḁᱽMCAS (Maneuvering Characteristics Augmentation System) ㆎ㡁ᱽㅝ⇰ᙵ☄ㄵᗪㅝ㣍㈡⬅ⳍ⭶ロ㿁 ⪪㫅ᗩḁ㉙㉮⪕
⍥ ☙㈅㽁ᛉ ㉙㉮㣝㻑㬙ᗩ ㅹ᷂ㄥ≅ ᤕ⎕᪉ᘅ⍥ ォ㎪⿕⬅ ☄ ㄵᗪㄭ ᪗㝽⾝ⳍ⭶ㄭ☒㎩㽝㋥ᱽ㽉ㄭ㽁ᱽᙬㅝ. ㅝㆎ 㡁ᱽ ᳢ⳅ ១ ㅹ㚝≅ᱽ ┡㈅ᗩ ⾯⾱ㄥ᪁ 㣝㻑㬙⾹ ☄ㄵᗪ⾹
ᳩ㽅 ㇾ⛝⍥㋥ᱽ⬥⬅ᗩᛉㆎ᪁ㅱᱽ ⪪㫅ᗩḁ⬅⠭㽲㣝 㻑㬙ᱽㆁ⒤ḅㇾ⛝⍥◽㪾ㄥ≅ ㉙㉮⪕⍥☙㈅㽁ᛉㅭㅁ≅ ⠭ 㽲᠙⍥ ៲ᗾ㽁ⳅ㤅 㝽Ⅶ㽁ᙵ ḅ ᙬㅝ. ┡㈅ᱽ 㻵→ㄭ ㇺㄩ
ㅝ䂭⾹ᱽ 㣝㻑㬙ᗩ㉙㉮⪕ᶭ⒑⍝ᙵ ㉙㉮ㄭ㽁ᛉㅱㄵ⾹ᶭ ❱
㽁ᛉ ㉙㉮⪕ᱽ ㇾㅺ ┝ⲑ ㅥㅝ ♵⾝㎩ᱽ㎩ ⼵ Ⰱᗩ ⾯ᶭ≆
⼵ᛉ⎕㎁ ⬍ᚭᗩḁ⾝ㅱᱽㇹㅝ. ᚙㄩㅝ⇕㽅 ⪕ᛉᛞ 㷕≅ ㅡ㽝 ㅡᛞ㎩ㅁ 䀾ᳩ をㄩ ㅥㇾ᠙ᗭ ⠭ㅹ 㽖⾹
❩ἓ㿩㎩ḉᙬㄥ≅⛝ㅡ. B737 MAX⪕ᙝㄭ䂱ㄥ≅⛝
⠭ㇾ⪪⪪䁒⾹⬅㉙㉮⪕ㅁ⪪䁒ㅡⳆ(situation awareness) ◸
ㇱ㘑 Ⰱ㽲⾹ㅡᛞ㎩᠙Ⰹㄩᶭォㄭ㋭Ⰱᱽ ㅱㄥ᪁㝅㉮㉙
㉮ㄩ ㅡᗭㅝ㮞㈅㽁ᱽ☒㾎ㄥ≅ ⬍ᚭ⍥☁㽁ᱽᙬㅝ 㿭㆕ㅁ
᠙㋩⾹⬅ᱽ 㽒⎕ㅥ ᙬㅝ.
ⲍロⲍ⾹⬅2017ᬭ⾹8㚅⑮ㄭ ᳩ⪪ㄥ≅ 㝅ⳉ ㅡᛞ㎩ ᠙ Ⰹㄭ を㽁⿕, ㉙㉮⪕ᗩ⾯ᱽ㽖ᛞ᠙⾹㪺Ⲣ⿕❩⍥ ┤ᱽ㉙
㋫ੳᬂ⋺ⓖ֨⓶ੳ✾ဣ
⪕⍥㽁ᱽᵙ, 㿭㆕ 㪺Ⲣㅁ50% ᗩᚒㄭ㈅ⳅ㽅ᱽ ㉙ᙝ⾹
⬅ᶭ, ⪕ⅵọㄩ⿕䅱 ┝ㅡ㽖ᛞ᠙⾹㪺Ⲣ㽁ᱽᙬㄭᢥ⎕ᱽᙬ ㄥ≅᪁㪩᪕[22]. ㄺ᳞ㅹㅁ63%ᗩ┝ㅡ⿕ᘆ᠙⾹ᳩ㽝☁ᳩ 㽁ᛉ, 㲢䅱54%ᱽ㽅⑮ㅝ㉙㉮㽁ᱽ⿕ᘆ᠙⾹ᶭ㪺Ⲣ㽁ᱽ ᙬ ㄭ ᙙ❩㽁ᛉ, ᳑㎩17%⎵ㅝ 㪱 ㅁ㾎ㅝ ㅱㄵㄭ 㹅⑮㽁.
ㅝᚙᛥᱽ㿭㆕ㅁㅡᛞ㎩᠙Ⰹㅝ ⼱ㄭ᳝⛝㽁᠙⾹ᱽ❩
㉚㽁ᛉᱹᩥᛉㅱㄵㄭ ㅁ◡㽅. ㅡᗭㄩ㎪ᛩᛥ㮞㘙∎ㄭ㮞 㽝⪪䁒ㄭ⿱⪪㽁ᱽ ∎ㅝㅱᱽ☁, 㣝㻑㬙ᱽⰁ㽂⪙
ㄭ㮞㽅〭ᚙ⬚ㄭᗩ㎭⾮┝⾹㮞㽁▩≅ㅝ⇕㽅㘑ㅝ⍥ ᠙☁
ㄥ≅ㅡᗭㅁㅁ⪕ᚙㇾ 」⍁⍥㝅䀽㽁ᱽ☒㾎ㄥ≅AI〩ㅁ㿺
⾮ㄭ ⒑⪲㽁ᱽ ᙬㅝ 㾎䂭 ☒㾎ㄥ≅ ⛝ㅡ.
ՌՄԶ⑤㉥Զ᪐⊈⋜Ḩ⑤Զ⒄ਁ⛌ྱ
ㅁ⊵ ❭⽥⾹⬅ ⬚ᛞㅡ 䁁ㅹ ㎭⊵ㅁ ᗩㆎ ㋺ぽ㽅 ㅡㅹᱽ
㎩Ⳇᛥᚦ㿁ㅝ. ㅁ⊵㎭ㅝ ㎩⭶ㄥ≅㽂Ⲟㄭ⎷ㅝ㽁⿕㎩Ⳇ ㅝ ⎷⼭㎩ᛉ 䁁ㅹ⍥ ⎷ㅝ ⋑⾝⬅ ㄉ⪕㽅 ᚦ㿁ㅝ 㝾ḁ
䁁ㅹ㎭⊵ㅁ⬚ᛞ⍉ㅝ㎆ᗩ㽉 ᙬㅝ. ㅁ⊵❭⽥⾹⬅AIㅁ㽉 ㄩㅝḹᗩ㎩㝾ㄭ㋺ⳕㄥ≅ ㅝ㽝㽁⿕⽥㽅. ㍲ᳩ↲ㅁᵙㅝ 㬙⍥ⳉ⭶䅱㞒㽁ᛉㅝ⍥㚁⎕㽁ᱽ⼵ᛉ⎕㎁ㄭㄞ㽒㽁⿕㎩
Ⳇㄭ ᚦ㿁⾹ ᭢⿕ᱽ ᙬㅝ. ㅁ⊵ ❭⽥⾹⬅AI᠙Ⰹㅝ ᗩㆎ
⎷ㅝ䁅をḁᱽ❭⽥ᱽ ⪪ㅁ㽂❭⽥Ⅵᛉ㽉Ⰱㅱ. ㅝᙬㄩ
ㅝ◡㎩ ㅡⳆ᠙Ⰹ⾹ ↲ㅁ ỽ㎩㬡 ㅹ⊵㎺ᛥ 㣝㻑㬙 ⪙
∎ㅁ ᛭⒒㽉⎵㽅 㾎⪪ㅝ ᴽ㽝㈡⬅ ㅝ⋑⾝㈵. 㲢䅱 㝅៥⾹
CT scanㄭ⠭≘㽅 ᙙㅁ ⒑ỉ ⪪ㅹ⊵ᗩỽ㎩㬡 ㅹ⊵≅⫆⬚
ḁ⬅AI ᠙Ⰹㅁ をㅝ ᗩ㽁ᙵ ḅ ㇹᶭ ㋥ぽスㅡㄥ≅ ᤦ 䅵. ⼭ァ⇕ㅁ⊵ᙩ⪕⾹⬅ ⪪ᙩ⪕ᗩ㉩ᴽ㋺ぽ㽝㎩⬅⿱
⛝⎷ㅝⳅ㽲ḁᛉᲁ⾝᪅⾮┝↲⾹⠭㽁⿕ Ⰲ∑ḅ⪪ㅁ 㽂 ㅁ⪕ᗩ ⪪ᳩㄥ≅ ❩㉚㽝㎭ ᙬㅝAI ᠙Ⰹ ᶭㅮㄭ 㛲㎭ⳅ 㪑ㇹㅝḁᛉ ㅱ. 㝅៥⾹ᱽㅝ◡㎩㻭≅⬡ⲍ◸㣝㻑㬙⠭
⼵ᛉ⎕㎁ㄭ ᗾ䀽㽁⿕ ⚺⚩ㄭ ㇾ䀾䅱 㳹᳑㽁⿕ ⳉ⭶㽁ᙵ ㎭᳑
⾹ㅝ⍝ᙵ㽁⬅᳢᳝ㅁ⊵㎭⾹ᙵ ㄺ៲⪪䁒ㅝ᪁᠙㪩ロ㿁ᶭ
⍥㶲ᗩ㽁⿕ᚙㇾㅡ 㡁⊵♾ᠵ㎩㈅ⳅ㽁ᛉㅱ. ⎵⼭㎪ᠵ
㎩ᱽ ⪪ㅁ㽂ᛥ ㅁ⊵㎭ㄭ ᳩ㡁㽁ᱽ ㇾᶭᱽ ⼭Ჱ ㅁ⊵㎭ㅁ
㳹᳑ㅝ◡㡁㎩⒤㽁ᱽ ❩❭ㄭ⛝〭㽁ᱽⰁ㋩⾹ㅱ[23]. 㚝
ㅡ⿱≅ᗺㅺⲍ⇕ゝ᮵㞅㿱≅ㄺ៲㚁㡁ᗩ㼭ぽ㽅 䁁ㅹᗩ★
⫆㽁ㄭἵ3㘑ス ᮵CT⍥ 㜕㽁⬅㞅㿱 䀢ㄩㅁⳕ❩ロ⍥
AI ᠙Ⰹ≅㘧⼭⬅ᗾ㉙㽁⿕ㅁ⊵㎭⾹ᙵ ⛝⿕㋥⡉⍡㳹᳑ㄭ
ᗩ㽁ᙵ㽁ᛉ㾎䂭 ᳩ㘮ᠵ㎩㈅ⳅ㽝㋥⾝㡁⊵ㅁ䄹⍭ㄭⳉ⭶
㽁ᙵ 㽉 Ⰱ ㅱᱽ ᙬㅝ. ㅝ⍥ 㚁⎕㽁ᱽ ⼵ᛉ⎕㎁ㄩ ᠙㉝ㅁ
PACS (picture achieving and communication system)〩᷂ḁ ᙵ⬍ᚭḅ[24]. ㉩ᴽ★ḅ⼵ᛉ⎕㎁ㄩㅹ᷂⚺⚩ㅡⳆⳅⲍ 㭅ㄥ≅★㽁᠙ᶭ㽁ᱽᵙᗭ, 㚂㝽, 㶹, ⳕ㿱ᛩᚭỚ⾹⬅ ⫆
⚺⚩ㄭ㜕ḅᵙㅝ㬙⍥ ⪙㽁⿕ㅁᶭ㽁㎩⼳ㄩ㎱䁁ㄭ★ᚕ 㽁᠙ᶭ㽁ᱽᙬㅝ. ⿱⍥ ọ㶹㎱䁁ㄭㅁⳕ㽁⿕䄲❩CT⍥
㜕㽁ᱽᵙㇾㅺ㶹⾹ᱽ⚺⚩ㅝ⾯ᛉᘂㅝ⾤ㄩỽ㎩㬡 ㅝ◡
㎩ ᵙㅝ㬙⾹⬅゙䅱ⳕ㿱ᛩ㎱䁁ㄭ★ᚕ㽝ᱽᙬㅝ. ⼽ 䁁 ㅹ㎭⊵⾹⬅ᱽ⪪ㅹ⊵⾹៥ᙙ㽅⚺᠙㳹ᶮㅝ㡁⊵☒㾎⬍ㇾ
⾹㋺ぽ㽅ᵙ, ⎥㻭ㇱ ㅝ㳹ᶮỚㄩㅡᗭㅁⳅ∎ᛥᚦ㿁Ớㄥ
≅ㅝㄉ┝⍥㳹᳑㽁ᱽᵙ⼭㎪ᶭㇾ䀾ᶭᗩ᭻㎩⼳ㄩᵙἎ⇕
᳆ㅁ ᠙ᚭ㽂Ⲟㄭ㮞㽅AI 㳹ᶮ∎ㄭㅝを㽅ᚙᛥ᠙㉝ㅁ⊵
㎭⛝ 㳹ᶮ∎ㅝ ᭻⽁ᛉ 㽁ᱽ ⛝ᛉᶭ ㅱ[25].
㉮⽺㽂 ❭⽥⾹⬅ᱽ㶹⼽ㅁ㉙㎪㽂㎭᳑⾹ᳩ㽅⾹⬅
⚺⎕㹅⛡ⲕⅥㅝễᙩ⪕⾹⬅⚺⎕ㅁ⪕ọ⛝᪁ㄩᙩ⪕∎ㄭ
⛝ᱽᗩㅱ[26]. ⳕㆎ㽂❭⽥⾹⬅ᶭᗩㅱᱽᵙ
ⳕㆎSPECT᪁㛱ㄵ㳵ᙩ⪕, ⳕᶭᙩ⪕ Ớ ㅭ⪪ㅁ⪕ọ⾹ᙵ
ᶭᠵ≅ゝᙩ⪕ᚙᛥ㽝⬆ㄭ㽁ᛉㅝ⇕㽅ᙩ⪕ᚙᛥọㄭ◽㪾 ㄥ≅ ᠙㉝ㅁᚙᛥọᛥ⠭㽅㴑㬝❭⬆ㄭ㽁⿕ⳕ❩ 䁁ㅹọ
⾹⬅ᱽ ⪕⏆⍉ᠵ㎩⿱㠊㽉Ⰱㅱᱽⳅᶭᶭㅱᛉ 㽅. ᳢ᯑ
⬚ ⏆⎲㎱䁁ㄩㅥ☁ㅡⳍ⑮ㅁᗩㆎ㩙㎱䁁ㅡᵙ, 㽅⾹⬅
ᱽ9,900⿕⑮ㅁ 䁁ㅹ ㅹ⊵⍥ Ἆ⇕᳆ㄭ ㅝを㽁⿕ 㽂Ⲟⳅ㤅⬅
AI᠙♾ㄭㅝを㽁⿕㎱䁁ㅁ ㉙᠙㎭᳑ㄭ㳹᳑㽁ᱽⳅ㿁⾹⬅⼱
ᛥㅁ⪕ọ⛝᭻ㄩ ⬚ᛞ⍉ㄭ⛝ㅭㄭ⛝ᛉ㽅◽ᶭㅱᛉ㽅
[27].
III. 결 론
㝅៥⾹゙⎕㋥⚩⾹⬅ㅡᛞ㎩ ⬅⠭ⲍᗩ⎷⼭㎩ᛉㅱ. 㲢 ㇾㅭ┝⎵ Ⰱ㽲㽁ᱽ ᗭ᳑㽅 ᙬ❩㬙 ♽を ㈅㹱⾹ ㅝ⍝᠙ ᠵ㎩
⽺㽁. ㅹㄑ㋥㽲㘑, ៩ㅁ ⼵㳵ᛉᱽㅥ☁ㅡọ⾹ᙵㅡᛞ㎩
ⳅᳩᗩᶭↁ㽑ㄭ ⼵∡ᛉIBM 〼ⲑㄩㅁ⊵❭⽥ Ớᗪ ❭⽥
┡ᗩọ⾹ᙵ ⏍゙ㅡ⪪ㅡ䁅⽦⪪ㄭ⛝⿕㋥⾝⬅AIㅁᳩ㋺
䀽 ⳅᳩ⍥ ㅝᨭᱽᵙ ⬉ᶭㅡ 㽉ㄭ 㽁. ⎵ ㅡᛞ㎩
᠙Ⰹㄩ⼭㎪┝⍝ㅞ㎩⼳⽁ᛉ᠙Ⰹᛥᚙḅ⪕ᛉọㅝ ᗭᗭㅝ
★⫆㽁⿕ ᳩ❩❭ㅁ ⪕ⅵọㅝ ⼭㎪ㄩ ゙䀡ㅡ ☁∍ㅹ≅⬅ ᛞ
㉝㽁ᱽ ᵙᱽㅁⳕㄭᗩ㎩ᛉㅱᱽᙬㄥ≅⛝ㅡ. ㅝ⇙㝽⬡
≅⬅ᱽㅡᛞ㎩ㅁ䀾ᳩをㄩ ⠭ㅹ㽖⾹❩ἓ㿩 ㅥㇾ᠙ ᗭ㎩ḉᙬㄥ≅⛝⿕⬅ㅡᗭᛥㅡᛞ㎩ㄭᳩ㹅≅㽁ᱽ᠙ᚭ
〩ㅁ ᛞ㉝⾹ᳩ㽅⿕⇕ ᗩ㎩ᛉ◥ㄭ㽝⽥ 㽉ᙬㅝ. 㿭㆕ᠵ㎩
ㅁ 㝽⬡≅ᱽㅡᛞ㎩᠙Ⰹㄩㅡᗭ⫆䁅⾹⎷ㄩ ᶭォㄭ㋭Ⰱ ᱽ ㅱㄥ᪁ 㝅㉮ ᚙㇾㄩ ㅡᗭㅝ 㮞㈅㽁ᱽ ☒㾎ㄥ≅ 㽁ᱽ ᙬㅝ
㿭㆕ㅁ ᠙㋩⾹⬅ᱽ 㽒⎕ㅥ ᙬㅝ.
REFERENCES
1. Abramson, D. “Turing’s Responses to Two Objections.” Minds and Machines 2008;18:147-67.
2. McCarthy J. From here to human-levle AI. Artificial intelligence.
2007;171:1174-1182.
3. McCarthy J. History of LISP. History of Program-ming Languages, ACM Monograph Series, chapter IV, New York: Academic Press,
㎂ẛ
1981:173.
4. Rosenblatt F. The Perceptron: a probabilistic model for information storage and organization in the brain, Cornell Aeronautical Laboratory.
Psychological Review 1958;65:386(6)-408.
5. Kaciak E, Cullen CW. Analysis of means-end chain data in marketing research. J Targeting, Measurement and Analysis for Marketing 2006; 15:12-20.
6. Giarratano JC. Expert system: Priciples and Programming. Boston:
PWS-Kent, 1989:1-23.
7. Arabacioglu BC. Using fuzzy inference system for architectural space analysis. Applied Soft Computing 2010;10(3):926-937.
8. King G. Probabilistic graphical models: introduction and overview. AI Magazine 2009;30:69-70.
9. Loraine Lawson. Myths About Semantic Technology Retrived July 2019 fron http://www.itbusinessedge.com/cm/blogs/lawson/myths-about-semantic-technology.
10. Yu VL,Fagan LM, Wraith SM. Antimicrobial Selection by a Computer: a blinded evaluation by infectious diseases Experts. JAMA 1979;242(12):1279-1282.
11. Bengio Y, Courville A, Vincent P. Representation Learning: A Review and New Perspectives,IEEE Trans PAMI special issue Learning Deep Architectures. 2013;12-13.
12. https://www.cadengineering.org/ai/newera/.
13. https://www.chatbots.org/chatterbot/eugene_goostman/.
14. https://chatbotslife.com/the-accountability-of-ai-case-study-micros ofts-tay.
15. https://www.ibm.com/watson.
16. https://www.bostondynamics.com/.
17. https://en.wikipedia.org/wiki/AlphaGo.
18. How People Feel About AI: What Marketers Need to Know.
SYZYGY Digital Insight Report 2017.
19. https://www.navyrecognition.com/...navy-naval.../4187-neuron-g.
20. Federal Aviation Administration. Aircraft Systems. Pilot’s Handbook of Aeronautical Knowledge. Washington DC, 2008;6-19.
21. https://en.wikipedia.org/wiki/Boeing_737_MAX_groundings.
22. https://www.efc.be/member-post/ubs-switzerland-ag/.
23. Mintz Y, Brodie R. Introduction to artificial intelligence in medicine.
Minim Invasive Ther Allied Technol 2019;28(2):73-81.
24. Li YH, Zhang L, Hu QM. Automatic subarachnoid space segmentation and hemorrhage detection in c linical head CT scans. Int J CARS 2012;7:305-312.
25. Bejnordi BE, Veta M, van Diest PJ. Disagnostic assessment of deep learning algorithmss for detection of lymph node metastasis in women with breast cancer. JAMA 2017;318:2199-2210.
26. Yu KH, Zhang C, Berry GI. Predicting nonsmall cell lung cancer prognosis by fully automated microscopic pathology image features. Nat Commun 2016;7:12474.
27. Gulshan v, Peng L, Voram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photography. JAMA 2016; 316:2402-2410.