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저자 : 김진한
금오공과대학교 경영학과에 재직 중인 김진한은 서강대학교에서 경영과학 전공으로 박사학위를 받았다. 저자는 한국외환은행 경제연구소, 현대경제연구원, 포스코경영연구소, 피츠버그대학교에서 과학적 의사결정, 신사업, 기술혁신과 네트워크 등에 대한 컨설팅과 프로젝트를 수행하였으며, 서강대, 이화여자대학교, 건국대, 인천대, 세종대 등에서 강의를 한 바 있다. 현재 대학에서는 서비스운영관리, 기술경영, 공급사슬관리, 빅데이터분석 관련 과목의 강의를 주로 하고 있다.
저자 : 김주한
한국과학기술원 부설 고등과학원에 재직 중인 김주한은 서울대학교에서 천문학 전공으로 박사학위를 받은 후 한국천문연구원, 고등과학원에서 박사 후 연구원으로 재직하였다. 그 이후에 캐나다 이론천체물리연구소에서 국비 방문연구원으로 1년 간 재직하고 경희대 응용과학대학에서 학술 연구교수로 재직 후에 고등과학원으로 옮겨 지금까지 재직 중이다. 주된 연구분야는 수치우주론으로, 계산우주론 시뮬레이션을 통해 우주의 생성과 진화 그리고 은하 등을 연구하였고 지금가지 다수의 세계적인 우주론 다체 시뮬레이션을 수행한 경험을 갖고 있다.
목차
1장 서비스 운영과 AI의 등장 3
1. 서비스 운영의 개념과 역사 ···············································································3
1.1. 서비스 운영의 기본 개념 3
1.2. 서비스 운영의 역사 6
2. 쉽게 경험하는 AI ·····························································································11
2.1. AI를 이용한 흥미로운 경험 11
2.2. 일상에서 AI 13
3. 서비스에서 AI의 등장 배경 ············································································16
3.1. 현상 16
3.2. AI의 일반적 등장 배경 17
3.3. 서비스 부문에서 AI의 등장 배경 18
4. 서비스의 미래에서 기술의 역할 ·····································································25
4.1. 기술이 포함된 서비스의 미래에 대한 학자들의 견해 25
4.2. 인간？기술 결합 26
2장 머신러닝과 AI의 원리 31
1. 머신러닝 ············································································································33
1.1. 유형 33
1.2. 선형모델 33
1.3. 역전파(backward propagation) 알고리듬 44
2. 인공신경망(ANN: Artificial Neural Network) ·······································46
2.1. 뇌 신경망의 구조 46
2.2. 퍼셉트론 47
2.3. 활성함수(Activation Function) 50
2.4. 합성곱 인공신경망(CNN: Convolutional Neural Networks) 53
2.5. 재귀 인공신경망(RNN: Recurrent Neural Networks) 54
3. 의사결정 트리(Decision Tree) ·····································································54
3.1. 의사결정 트리를 이용한 분류 예시1 54
3.2. 결정트리를 이용한 분류 예시2 57
4. 랜덤 포레스트(Random Forest) ·································································58
3장 AI의 정의와 구성요소 63
1. AI의 역사 ··········································································································63
1.1. AI의 시작 63
1.2. 튜링테스트 63
1.3. AI 연구의 겨울(1974？1980) 64
1.4. AI 연구의 성장기 64
1.5. AI 연구의 폭발기 64
2. AI의 정의 ··········································································································65
2.1. 포괄성에 기초한 정의 66
2.2. 인간 및 AI의 역량과 관련한 정의 68
2.3. 시스템의 초점에 따른 정의 70
2.4. 비즈니스에서 정의 70
2.5. 서비스에서 정의 72
3. 서비스 부문에서 AI의 수준별 유형분류 ························································73
3.1. 서비스 AI의 유형 73
4. AI 시스템의 구성요소 ······················································································83
4.1. AI의 기본 기법 83
4.2. AI 프레임워크 84
4.3. AI 시스템의 구성요소 85
4장 서비스 부문 AI의 적용기법과 분야 93
1. AI의 연구 분야와 적용 기법 ··········································································93
1.1. 연구 분야 93
1.2. 일반적 AI 기법 94
2. 서비스 부문에서 AI 기법의 적용 ·································································102
2.1. 비즈니스에서 AI 적용 102
2.2. 서비스 부문에서 AI의 활용과 에이전트 103
3. 서비스 산업에서 AI의 활용 사례 ·································································110
3.1. AI의 적용 예시 110
3.2. 서비스 부문별 적용 112
4. COVID？19로 인한 관련 기술의 적용 확대 ··············································115
4.1. 팬데믹 이후 AI의 적용 115
4.2. 로봇/코봇의 적용 116
4.3. 자동화의 적용 116
4.4. 챗봇의 적용 117
4.5. 가상 어시스턴트의 적용 117
4.6. 감시시스템과 스캔의 적용 117
4.7. 컴퓨터비전 기술의 적용 118
4.8. 클라우드시스템의 적용 118
4.9. 스마트2 음성자동응답 118
5장 서비스 부문 AI의 적용 전략과 결정요인 121
1. AI의 적용 목적 ·······························································································121
2. AI 적용의 이론적 설명 ··················································································123
2.1. 전통적 기술수용이론의 적용과 차이 123
2.2. AI 적용의 이론적 프레임워크 사례 125
3. AI 적용의 가능요인 ·······················································································126
3.1. 기술적 127
3.2. 조직적 128
3.3. 환경적 130
4. 서비스 로봇의 적용 요인 ··············································································132
4.1. 협력적 서비스 로봇 132
4.2. 고객 재방문에 기초한 서비스 로봇 수용 요인 137
4.3. 기타 연구 140
5. 도입전략의 도전사항 ······················································································141
6장 AI에 기반한 서비스 접점 관리 147
1. 기술을 포함한 서비스 삼각형 ·······································································147
2. AI 유형별 고객 관여 및 접점 ······································································152
2.1. 서비스 업무의 특성 153
2.2. 서비스 오퍼링의 특성 154
2.3. 서비스 제공자의 전략적 강조 156
2.4. 서비스 프로세스 단계 157
3. 서비스 직원의 기술 대체에 초점을 둔 서비스 유형 ··································162
3.1. 인간 상호 간(고객 대 현장직원) 서비스 접점 162
3.2. 이종 간 서비스 접점: AI？고객 165
3.3. 이종 간 서비스 접점: AI？현장직원 168
3.4. 모조 서비스 접점 169
3.5. AI 상호간 서비스 접점 169
4. 기술기반 서비스 접점의 공공보건 사례 ······················································171
4.1. 공공보건에서 기술기반 서비스 접점 171
4.2. AI 기술기반 서비스 접점의 선행요인과 성과 172
7장 현장서비스에서 AI 유형 179
1. 현장 서비스에서 기술 침투 ···········································································179
1.1. 기존의 현장서비스 기술 투입 유형 179
1.2. AI기반 서비스 181
1.3. 새로운 현장서비스 기술투입 유형 187
2. 현장서비스 기술 유형 ····················································································192
2.1. 대화형 에이전트 192
2.2. 확장현실 기술 194
2.3. 블록체인 195
8장 서비스 부문에서 AI의 가치와 공동창출 199
1. AI가 제공하는 가치 ·······················································································199
1.1. 사례: 소매분야에서 AI에 기반한 솔루션의 네 가지 가치 199
1.2. 사례: AI 기반의 사회적 로봇의 잠재가치 202
2. 서비스 로봇에 대한 고객의 경험 ·································································206
2.1. 서비스 로봇의 장단점 206
2.2. 고객 경험에 영향을 미치는 요소 207
2.3. 상호작용을 통해 고객이 하는 경험 208
3. AI에 의한 가치 공동창출 ··············································································214
3.1. 가치 공동창출의 개념 214
3.2. AI와 가치 공동창출 사례 215
3.3. AI에 의한 가치 공동창출 접근법 216
4. 기술중심의 서비스 접점에서 가치의 손실 ···················································217
4.1. 가치 공동파괴의 개념 217
4.2. 자원 손실 유형 218
4.3. 선행요인 219
4.4. 손실에 대한 고객의 대응전략 222
9장 서비스 부문 AI 역량과 품질 227
1. 성공적 실행을 위한 AI 역량 ········································································227
1.1. AI 역량의 개념 227
1.2. AI 역량 프레임워크 228
2. AI와 관련한 서비스 품질 ··············································································234
2.1. AI 챗봇의 서비스 품질 234
2.2. AI 서비스에이전트의 품질 236
2.3. 스마트레스토랑 품질 238
2.4. AI 서비스의 품질평가 차원 239
10장 서비스 부문 AI의 가치창출과 시사점 243
1. AI의 세 가지 효과 ·························································································243
2. 가치사슬별 성과 ·····························································································244
3. AI의 기업가치에 대한 영향 ··········································································246
3.1. 직접적 영향 247
3.2. 간접적 영향 250
3.3. 이해관계자별 가치창출 255
4. 서비스 부문 AI의 시사점 ··············································································259
4.1. 비즈니스에 대한 시사점 259
4.2. 인간에 대한 시사점 260
4.3. 산업에 대한 시사점 260
4.4. 사회에 대한 시사점 261
5. 서비스 부문 AI의 그늘 ··················································································261
5.1. B2C 상황 262
5.2. B2B 상황 262
11장 AI와 비즈니스 기능 1 ？ 운영, 물류, 공급사슬관리, 마케팅 267
1. 비즈니스에서 AI 활용 ····················································································267
1.1. 추세 267
1.2. 한계 268
2. AI와 운영, 물류 및 공급사슬관리 ································································269
2.1. 특징 269
2.2. 주요 AI 역할 270
2.3. 주요 AI 기법 279
3. AI와 마케팅 ····································································································281
3.1. 특징 281
3.2. 주요 AI 역할 282
3.3. 주요 AI 기법 291
3.4. AI와 마케팅의 미래 추세 295
12장 AI와 비즈니스 기능 2 ？ 인적자원, 재무, 회계, 지식 및 혁신 305
1. AI와 인적자원관리 ·························································································305
1.1. 특징 305
1.2. 주요 AI 역할 306
1.3. 주요 AI 기법 315
2. AI와 회계 및 감사 ·······················································································317
2.1. 특징 317
2.2. 주요 AI 역할 318
2.3. 주요 AI 기법？설명가능한 AI 318
3. AI와 재무 ········································································································320
3.1. 특징 320
3.2. 주요 AI 역할 321
3.3. 주요 AI 기법 324
4. AI와 혁신과 지식경영 ····················································································327
4.1. 특징 327
4.2. AI가 가능하게 하는 혁신 유형 328
4.3. AI가 가능하게 하는 지식경영 330
4.4. 주요 AI 역할 334
4.5. 주요 AI 기법 340
13장 서비스 산업별 AI 적용 347
1. AI의 서비스 부문에 적용 ··············································································347
1.1. 서비스 AI의 주요 특징 347
1.2. 데이터와 솔루션 관점에서 AI의 적용 348
1.3. 산업별 AI의 영향 349
2. 소매산업 ··········································································································350
2.1. 특징 350
2.2. 주요 AI 역할 351
3. 보건의료산업 ···································································································355
3.1. 특징 355
3.2. 주요 AI 역할 356
4. 머신러닝 ··········································································································360
4.1. 특징 360
4.2. 주요 AI 역할 361
5. 미디어와 엔터테인먼트산업 ···········································································368
5.1. 특징 368
5.2. 주요 AI 역할 368
6. 금융과 보험산업 ·····························································································374
6.1. 특징 374
6.2. 주요 AI 역할 375
7. 교육부문 ··········································································································377
7.1. 특징 377
7.2. 주요 AI 역할 378
8. 운송서비스산업 ·······························································································385
8.1. 특징 385
8.2. 주요 AI 역할 386
9. 통신과 기타 네트워크 서비스 ·······································································389
9.1. 특징 389
9.2. 네트워크 운영에서 AI 적용 389
10. 공공서비스 ····································································································392
10.1. 특징 392
10.2. 주요 역할 394
10.3. 도전사항 398
11. 전문서비스산업 ·····························································································399
11.1. 특징 399
11.2. 주요 AI 역할 401
14장 AI의 잠재적 위험과 미래 407
1. AI의 잠재적 위험 ···························································································407
1.1. 인식된 정체성 위협 407
1.2. 네트워크 보안과 정보 프라이버시 408
1.3. 변화에 대한 저항 409
1.4. 고용 혼란 410
1.5. 불평등한 접근, 편익, 영향 411
1.6. 충격, 공격, 실패의 확산 411
1.7. 효율성과 회복성 412
2. AI의 단점과 위험 ···························································································412
2.1. 상식의 결여 412
2.2. 목적함수의 문제 414
2.3. 안전하고 현실적인 학습 환경 415
2.4. 편향된 AI 416
2.5. 설명가능한 AI 417
2.6. 통제가능한 AI 418
3. AI의 미래 ········································································································418
3.1. AI의 미래에 대한 견해 418
3.2. 이해관계자별 미래에 대한 견해 422
4. 서비스산업에서 AI와 고용 ············································································426
4.1. AI와 고용 규모 426
4.2. AI와 고용구조 427
4.3. AI와 고용 소득 427
4.4. AI와 노동 이동성 428
5. AI와 윤리 ········································································································428
5.1. 배경 428
5.2. 핵심 AI 윤리 이슈 429
5.3. AI 및 로봇 활용에 대한 흥미로운 윤리적 이슈 429
1. 서비스 운영의 개념과 역사 ···············································································3
1.1. 서비스 운영의 기본 개념 3
1.2. 서비스 운영의 역사 6
2. 쉽게 경험하는 AI ·····························································································11
2.1. AI를 이용한 흥미로운 경험 11
2.2. 일상에서 AI 13
3. 서비스에서 AI의 등장 배경 ············································································16
3.1. 현상 16
3.2. AI의 일반적 등장 배경 17
3.3. 서비스 부문에서 AI의 등장 배경 18
4. 서비스의 미래에서 기술의 역할 ·····································································25
4.1. 기술이 포함된 서비스의 미래에 대한 학자들의 견해 25
4.2. 인간？기술 결합 26
2장 머신러닝과 AI의 원리 31
1. 머신러닝 ············································································································33
1.1. 유형 33
1.2. 선형모델 33
1.3. 역전파(backward propagation) 알고리듬 44
2. 인공신경망(ANN: Artificial Neural Network) ·······································46
2.1. 뇌 신경망의 구조 46
2.2. 퍼셉트론 47
2.3. 활성함수(Activation Function) 50
2.4. 합성곱 인공신경망(CNN: Convolutional Neural Networks) 53
2.5. 재귀 인공신경망(RNN: Recurrent Neural Networks) 54
3. 의사결정 트리(Decision Tree) ·····································································54
3.1. 의사결정 트리를 이용한 분류 예시1 54
3.2. 결정트리를 이용한 분류 예시2 57
4. 랜덤 포레스트(Random Forest) ·································································58
3장 AI의 정의와 구성요소 63
1. AI의 역사 ··········································································································63
1.1. AI의 시작 63
1.2. 튜링테스트 63
1.3. AI 연구의 겨울(1974？1980) 64
1.4. AI 연구의 성장기 64
1.5. AI 연구의 폭발기 64
2. AI의 정의 ··········································································································65
2.1. 포괄성에 기초한 정의 66
2.2. 인간 및 AI의 역량과 관련한 정의 68
2.3. 시스템의 초점에 따른 정의 70
2.4. 비즈니스에서 정의 70
2.5. 서비스에서 정의 72
3. 서비스 부문에서 AI의 수준별 유형분류 ························································73
3.1. 서비스 AI의 유형 73
4. AI 시스템의 구성요소 ······················································································83
4.1. AI의 기본 기법 83
4.2. AI 프레임워크 84
4.3. AI 시스템의 구성요소 85
4장 서비스 부문 AI의 적용기법과 분야 93
1. AI의 연구 분야와 적용 기법 ··········································································93
1.1. 연구 분야 93
1.2. 일반적 AI 기법 94
2. 서비스 부문에서 AI 기법의 적용 ·································································102
2.1. 비즈니스에서 AI 적용 102
2.2. 서비스 부문에서 AI의 활용과 에이전트 103
3. 서비스 산업에서 AI의 활용 사례 ·································································110
3.1. AI의 적용 예시 110
3.2. 서비스 부문별 적용 112
4. COVID？19로 인한 관련 기술의 적용 확대 ··············································115
4.1. 팬데믹 이후 AI의 적용 115
4.2. 로봇/코봇의 적용 116
4.3. 자동화의 적용 116
4.4. 챗봇의 적용 117
4.5. 가상 어시스턴트의 적용 117
4.6. 감시시스템과 스캔의 적용 117
4.7. 컴퓨터비전 기술의 적용 118
4.8. 클라우드시스템의 적용 118
4.9. 스마트2 음성자동응답 118
5장 서비스 부문 AI의 적용 전략과 결정요인 121
1. AI의 적용 목적 ·······························································································121
2. AI 적용의 이론적 설명 ··················································································123
2.1. 전통적 기술수용이론의 적용과 차이 123
2.2. AI 적용의 이론적 프레임워크 사례 125
3. AI 적용의 가능요인 ·······················································································126
3.1. 기술적 127
3.2. 조직적 128
3.3. 환경적 130
4. 서비스 로봇의 적용 요인 ··············································································132
4.1. 협력적 서비스 로봇 132
4.2. 고객 재방문에 기초한 서비스 로봇 수용 요인 137
4.3. 기타 연구 140
5. 도입전략의 도전사항 ······················································································141
6장 AI에 기반한 서비스 접점 관리 147
1. 기술을 포함한 서비스 삼각형 ·······································································147
2. AI 유형별 고객 관여 및 접점 ······································································152
2.1. 서비스 업무의 특성 153
2.2. 서비스 오퍼링의 특성 154
2.3. 서비스 제공자의 전략적 강조 156
2.4. 서비스 프로세스 단계 157
3. 서비스 직원의 기술 대체에 초점을 둔 서비스 유형 ··································162
3.1. 인간 상호 간(고객 대 현장직원) 서비스 접점 162
3.2. 이종 간 서비스 접점: AI？고객 165
3.3. 이종 간 서비스 접점: AI？현장직원 168
3.4. 모조 서비스 접점 169
3.5. AI 상호간 서비스 접점 169
4. 기술기반 서비스 접점의 공공보건 사례 ······················································171
4.1. 공공보건에서 기술기반 서비스 접점 171
4.2. AI 기술기반 서비스 접점의 선행요인과 성과 172
7장 현장서비스에서 AI 유형 179
1. 현장 서비스에서 기술 침투 ···········································································179
1.1. 기존의 현장서비스 기술 투입 유형 179
1.2. AI기반 서비스 181
1.3. 새로운 현장서비스 기술투입 유형 187
2. 현장서비스 기술 유형 ····················································································192
2.1. 대화형 에이전트 192
2.2. 확장현실 기술 194
2.3. 블록체인 195
8장 서비스 부문에서 AI의 가치와 공동창출 199
1. AI가 제공하는 가치 ·······················································································199
1.1. 사례: 소매분야에서 AI에 기반한 솔루션의 네 가지 가치 199
1.2. 사례: AI 기반의 사회적 로봇의 잠재가치 202
2. 서비스 로봇에 대한 고객의 경험 ·································································206
2.1. 서비스 로봇의 장단점 206
2.2. 고객 경험에 영향을 미치는 요소 207
2.3. 상호작용을 통해 고객이 하는 경험 208
3. AI에 의한 가치 공동창출 ··············································································214
3.1. 가치 공동창출의 개념 214
3.2. AI와 가치 공동창출 사례 215
3.3. AI에 의한 가치 공동창출 접근법 216
4. 기술중심의 서비스 접점에서 가치의 손실 ···················································217
4.1. 가치 공동파괴의 개념 217
4.2. 자원 손실 유형 218
4.3. 선행요인 219
4.4. 손실에 대한 고객의 대응전략 222
9장 서비스 부문 AI 역량과 품질 227
1. 성공적 실행을 위한 AI 역량 ········································································227
1.1. AI 역량의 개념 227
1.2. AI 역량 프레임워크 228
2. AI와 관련한 서비스 품질 ··············································································234
2.1. AI 챗봇의 서비스 품질 234
2.2. AI 서비스에이전트의 품질 236
2.3. 스마트레스토랑 품질 238
2.4. AI 서비스의 품질평가 차원 239
10장 서비스 부문 AI의 가치창출과 시사점 243
1. AI의 세 가지 효과 ·························································································243
2. 가치사슬별 성과 ·····························································································244
3. AI의 기업가치에 대한 영향 ··········································································246
3.1. 직접적 영향 247
3.2. 간접적 영향 250
3.3. 이해관계자별 가치창출 255
4. 서비스 부문 AI의 시사점 ··············································································259
4.1. 비즈니스에 대한 시사점 259
4.2. 인간에 대한 시사점 260
4.3. 산업에 대한 시사점 260
4.4. 사회에 대한 시사점 261
5. 서비스 부문 AI의 그늘 ··················································································261
5.1. B2C 상황 262
5.2. B2B 상황 262
11장 AI와 비즈니스 기능 1 ？ 운영, 물류, 공급사슬관리, 마케팅 267
1. 비즈니스에서 AI 활용 ····················································································267
1.1. 추세 267
1.2. 한계 268
2. AI와 운영, 물류 및 공급사슬관리 ································································269
2.1. 특징 269
2.2. 주요 AI 역할 270
2.3. 주요 AI 기법 279
3. AI와 마케팅 ····································································································281
3.1. 특징 281
3.2. 주요 AI 역할 282
3.3. 주요 AI 기법 291
3.4. AI와 마케팅의 미래 추세 295
12장 AI와 비즈니스 기능 2 ？ 인적자원, 재무, 회계, 지식 및 혁신 305
1. AI와 인적자원관리 ·························································································305
1.1. 특징 305
1.2. 주요 AI 역할 306
1.3. 주요 AI 기법 315
2. AI와 회계 및 감사 ·······················································································317
2.1. 특징 317
2.2. 주요 AI 역할 318
2.3. 주요 AI 기법？설명가능한 AI 318
3. AI와 재무 ········································································································320
3.1. 특징 320
3.2. 주요 AI 역할 321
3.3. 주요 AI 기법 324
4. AI와 혁신과 지식경영 ····················································································327
4.1. 특징 327
4.2. AI가 가능하게 하는 혁신 유형 328
4.3. AI가 가능하게 하는 지식경영 330
4.4. 주요 AI 역할 334
4.5. 주요 AI 기법 340
13장 서비스 산업별 AI 적용 347
1. AI의 서비스 부문에 적용 ··············································································347
1.1. 서비스 AI의 주요 특징 347
1.2. 데이터와 솔루션 관점에서 AI의 적용 348
1.3. 산업별 AI의 영향 349
2. 소매산업 ··········································································································350
2.1. 특징 350
2.2. 주요 AI 역할 351
3. 보건의료산업 ···································································································355
3.1. 특징 355
3.2. 주요 AI 역할 356
4. 머신러닝 ··········································································································360
4.1. 특징 360
4.2. 주요 AI 역할 361
5. 미디어와 엔터테인먼트산업 ···········································································368
5.1. 특징 368
5.2. 주요 AI 역할 368
6. 금융과 보험산업 ·····························································································374
6.1. 특징 374
6.2. 주요 AI 역할 375
7. 교육부문 ··········································································································377
7.1. 특징 377
7.2. 주요 AI 역할 378
8. 운송서비스산업 ·······························································································385
8.1. 특징 385
8.2. 주요 AI 역할 386
9. 통신과 기타 네트워크 서비스 ·······································································389
9.1. 특징 389
9.2. 네트워크 운영에서 AI 적용 389
10. 공공서비스 ····································································································392
10.1. 특징 392
10.2. 주요 역할 394
10.3. 도전사항 398
11. 전문서비스산업 ·····························································································399
11.1. 특징 399
11.2. 주요 AI 역할 401
14장 AI의 잠재적 위험과 미래 407
1. AI의 잠재적 위험 ···························································································407
1.1. 인식된 정체성 위협 407
1.2. 네트워크 보안과 정보 프라이버시 408
1.3. 변화에 대한 저항 409
1.4. 고용 혼란 410
1.5. 불평등한 접근, 편익, 영향 411
1.6. 충격, 공격, 실패의 확산 411
1.7. 효율성과 회복성 412
2. AI의 단점과 위험 ···························································································412
2.1. 상식의 결여 412
2.2. 목적함수의 문제 414
2.3. 안전하고 현실적인 학습 환경 415
2.4. 편향된 AI 416
2.5. 설명가능한 AI 417
2.6. 통제가능한 AI 418
3. AI의 미래 ········································································································418
3.1. AI의 미래에 대한 견해 418
3.2. 이해관계자별 미래에 대한 견해 422
4. 서비스산업에서 AI와 고용 ············································································426
4.1. AI와 고용 규모 426
4.2. AI와 고용구조 427
4.3. AI와 고용 소득 427
4.4. AI와 노동 이동성 428
5. AI와 윤리 ········································································································428
5.1. 배경 428
5.2. 핵심 AI 윤리 이슈 429
5.3. AI 및 로봇 활용에 대한 흥미로운 윤리적 이슈 429
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반품/교환
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환불지연에 따른 배상- 상품의 불량에 의한 반품, 교환, A/S, 환불, 품질보증 및 피해보상 등에 관한 사항은
소비자 분쟁해결 기준(공정거래위원회고시)에 준하여 처리됨 - 대금 환불 및 환불지연에 따른 배상금 지급 조건, 절차 등은 전자상거래 등에서의
소비자 보호에 관한 법률에 따라 처리함
반품/교환 주소 경기도 파주시 문발로 77, 웅진북센(반디앤루니스)
