Artificial Intelligence and the Law:
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge ; Antwerp ; Chicago
Intersentia
[2021]
|
| Schriftenreihe: | Centrum voor Verbintenissen- en Goederenrecht
4 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXXI, 520 Seiten |
| ISBN: | 9781839701030 |
Internformat
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV047222823 | ||
| 003 | DE-604 | ||
| 005 | 20210804 | ||
| 007 | t | ||
| 008 | 210401s2021 xxk |||| 00||| eng d | ||
| 020 | |a 9781839701030 |9 978-1-83970-103-0 | ||
| 035 | |a (OCoLC)1242403658 | ||
| 035 | |a (DE-599)BVBBV047222823 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 044 | |a xxk |c XA-GB |a ne |c XA-NL |a xxu |c XD-US | ||
| 049 | |a DE-M382 |a DE-19 | ||
| 084 | |a INTRECHT |q DE-1a |2 fid | ||
| 084 | |a 86.59 |2 bkl | ||
| 245 | 1 | 0 | |a Artificial Intelligence and the Law |
| 264 | 1 | |a Cambridge ; Antwerp ; Chicago |b Intersentia |c [2021] | |
| 300 | |a XXXI, 520 Seiten | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Centrum voor Verbintenissen- en Goederenrecht |v 4 | |
| 650 | 0 | 7 | |a Recht |0 (DE-588)4048737-4 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4143413-4 |a Aufsatzsammlung |2 gnd-content | |
| 689 | 0 | 0 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |D s |
| 689 | 0 | 1 | |a Recht |0 (DE-588)4048737-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Bruyne, Jan de |0 (DE-588)1082770566 |4 edt | |
| 700 | 1 | |a Vanleenhove, Cedric |0 (DE-588)1119477980 |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-83970-104-7 |
| 856 | 4 | 2 | |m SWB Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032627411&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
Datensatz im Suchindex
| _version_ | 1805079632355000320 |
|---|---|
| adam_text |
CONTENTS
FOREWORD XIX
CONTRIBUTING AUTHORS XXV
CHAPTER 1.
BASIC CONCEPTS OF AI FOR LEGAL SCHOLARS
REMBRANDT
DEVILLE,
NICO
SERGEYSSELS
AND CATHERINE
MIDDAG
1
1. INTRODUCTION 1
2. DEFINING AND MEASURING AI 2
2.1. DEFINITION: WHAT IS AI? 2
2.2. THE TURING TEST AND THE LOEBNER PRIZE 3
3. BASIC PRINCIPLES OF AI 4
3.1. KNOWLEDGE-BASED VERSUS DATA-BASED LEARNING 4
3.2. INTERNET OF THINGS AND BIG DATA 5
3.3. MACHINE LEARNING 6
3.4. ARTIFICIAL NEURAL NETWORKS AND DEEP LEARNING 7
3.5. DATA BIAS AND MODEL BIAS 10
4. AI SUB-DISCIPLINES 11
4.1. SEARCH ALGORITHMS 12
4.2. COMPUTER VISION 12
4.3. NATURAL LANGUAGE 12
4.4. SPEECH 13
4.5. AGENTS 14
5. THE CURRENT AND FUTURE USE OF AI APPLICATIONS 14
5.1. AN OVERVIEW OF SOME AI APPLICATIONS IN THE PRESENT AND NEAR
FUTURE 14
5.1.1. TRANSPORTATION 15
5.1.2. ROBOTS 16
5.1.3. HEALTHCARE 17
5.1.4. EDUCATION 18
5.1.5. PUBLIC SAFETY AND SECURITY 18
5.1.6. ARTS AND ENTERTAINMENT 19
5.1.7. LAW 20
5.2. AI IN THE MORE DISTANT FUTURE 20
6. CONCLUSION 21
INTERSENTIA
CONTENTS
CHAPTER 2.
DIFFERENT MODELS OF INNOVATION AND THEIR RELATION TO LAW
CHARLES
DELMOTTE
23
1. INTRODUCTION 23
2. STANDARD ECONOMIC MODEL ON INNOVATION 26
2.1. THE NEOCLASSICAL MODEL 26
2.2. TAX INCENTIVES FOR INNOVATION 28
2.3. DUBIOUS EMPIRICAL TRACK RECORD OF TAX INCENTIVES 31
3. INSTITUTIONAL ECONOMICS 32
3.1. THE MARKET AS A DYNAMIC PROCESS 33
3.2. INNOVATION: AN ENDOGENOUS AND UNPREDICTABLE PHENOMENON 37
3.3. TAX INCENTIVES FOR INNOVATION: A CRITIQUE 40
3.3.1. IDENTIFYING INNOVATORS 40
3.3.2. THE AMOUNT OF THE TAX BENEFIT 41
3.4. INNOVATION POLICY: THE PROPERTARIAN APPROACH 42
4. CONCLUSION 48
CHAPTER 3.
SETTING THE SCENE: ON AI ETHICS AND REGULATION
MICHIEL
FIERENS,
STEPHANIE
ROSSELLO
AND ELLEN
WAUTERS
49
1. INTRODUCTION 49
2. ETHICS OF AI 50
3. REGULATION OF AI 55
4. CURRENT TRENDS IN AI GOVERNANCE 62
5. CONCLUSION 71
CHAPTER 4.
QUANTITATIVE LEGAL PREDICTION: THE FUTURE OF DISPUTE RESOLUTION?
MATTHIAS VAN DER HAEGEN 73
1. INTRODUCTION 73
2. LEGAL ANALYTICS 74
3. EXISTING APPLICATIONS 77
3.1. COMPAS 78
3.2. HART 78
3.3. CASE LAW ANALYTICS 78
3.4. PROMETEA 79
4. POTENTIAL USE CASES AND THEIR ADVANTAGES 80
4.1. POTENTIAL USE CASES 80
4.2. ADVANTAGES OF QLP 82
5. CHALLENGES 82
5.1. LIMITS OF PREDICTIVE MODELS WITHIN THE LEGAL DOMAIN 83
VLU
INTERSENTIA
CONTENTS
5.1.1. THE APPLICATION OF LAW DOES NOT ADHERE TO
PREDETERMINED RULES 83
5.1.2. CHANGEABLE NATURE OF LAW 84
5.1.3. RISK OF A NORMATIVE PREDICTION 85
5.2. CHALLENGES INHERENT TO PREDICTIVE MODELS 86
5.2.1. BIAS WITHIN PREDICTIVE MODELS 86
A. BIASED TRAINING DATA 87
B. BIASED DATA 87
C. BIASED ALGORITHMS 89
5.2.2. TRANSPARENCY 90
5.2.3. TRUST 93
6. THE CASE FOR BELGIUM 94
6.1. PUBLICATION OF CASE LAW BY THE JUDICIARY 96
6.2. PUBLICATION OF CASE LAW BY PUBLISHERS 97
6.3. GENERAL PUBLICATION OF CASE LAW IN THE NEAR FUTURE? 97
7. CONCLUSION 98
CHAPTER 5.
AI ARBITRATORS . 'DOES NOT COMPUTE'
KEVIN
ONGENAE
101
1. INTRODUCTION 101
2. THERE ARE CONSIDERABLE DATA-RELATED HURDLES TO AI-BASED ARBITRATORS
. 104
2.1. THE AMOUNT OF DATA NEEDED FOR PERFORMANT AI IS NOT
AVAILABLE IN ARBITRATION 104
2.2. ARBITRATION DATA IS NOT SUITABLE FOR AI DEVELOPMENT 106
2.3. AN AI ARBITRATOR MOST LIKELY COULD NOT COPE WITH NOVEL OR
UNIQUE ISSUES 108
2.4. AI ARBITRATOR WOULD COPY MISTAKES IN PREVIOUS DATA 109
2.5. CONCLUSION CONCERNING DATA-BASED FLAWS ILL
3. THE CURRENT LEGAL FRAMEWORK IS INHOSPITABLE TO AI ARBITRATORS ILL
3.1. ARBITRATION LAW IS BUILT AROUND THE ASSUMPTION OF A HUMAN
ARBITRATOR 113
3.2. INDEPENDENCE AND IMPARTIALITY OF AN AI ARBITRATOR? 115
3.3. FORMAL REQUIREMENTS FOR RENDERING AN ARBITRAL AWARD
CURRENTLY EXCLUDE AN AI ARBITRATOR 116
3.4. DUTY TO PROVIDE REASONS 118
3.5. CONCLUSION CONCERNING THE LEGAL FRAMEWORK 119
4. CONCLUSION AND LOOK AHEAD 120
INTERSENTIA
CONTENTS
CHAPTER 6.
AI THROUGH A HUMAN RIGHTS LENS. HIE ROLE OF HUMAN RIGHTS IN
FULFILLING AFS POTENTIAL
CHARLINE DAELMAN 123
1. INTRODUCTION 123
2. THE IMPACT OF AI ON HUMAN RIGHTS: RISKS AND OPPORTUNITIES 124
2.1. RIGHT TO LIFE, LIBERTY, SECURITY AND A FAIR TRIAL 125
2.2. RIGHT TO PRIVACY 126
2.3. RIGHT TO FREEDOM OF THOUGHT, CONSCIENCE AND RELIGION,
EXPRESSION AND ASSEMBLY/ASSOCIATION 127
2.4. PROHIBITION OF DISCRIMINATION 129
2.5. RIGHT TO POLITICAL PARTICIPATION AND PROHIBITION ON PROPAGANDA.
130
2.6. RIGHT TO WORK AND TO AN ADEQUATE STANDARD OF LIVING 131
2.7. RIGHTTO HEALTH 133
2.8. RIGHT TO EDUCATION 135
2.9. THE PROTECTION OF INTELLECTUAL PROPERTY 136
3. THE RECURRING ISSUE: DISCRIMINATION AND BIAS 137
3.1. DISCRIMINATION CAUSED BY AI SYSTEMS 137
3.1.1. DISCRIMINATION AT THE PROCESS LEVEL 138
3.1.2. DISCRIMINATION AT THE CLASSIFICATION LEVEL 140
3.2. DISCRIMINATION GROUNDS 141
3.2.1. DISCRIMINATION BASED ON ETHNICITY: UYGHUR MUSLIM
IN CHINA 141
3.2.2. DISCRIMINATION BASED ON GENDER: ONLINE JOB
ADVERTISEMENTS 142
3.2.3. DISCRIMINATION BASED ON RELIGION, BELIEF AND POLITICAL
OPINION: FACEBOOK 143
3.2.4. DISCRIMINATION BASED ON RACE: GERRYMANDERING 143
3.3. SILVER LININGS 144
4. BENDING THREATS INTO OPPORTUNITIES: HUMAN RIGHTS AS THE ETHICAL
FRAMEWORK TO ENSURE AI'S POTENTIAL 145
5. CONCLUSION 148
CHAPTER 7.
KILLER ROBOTS: LETHAL AUTONOMOUS WEAPONS AND INTERNATIONAL LAW
SEBASTIAAN
VAN SEVEREN
AND CARL
VANDER MAELEN
151
1. INTRODUCTION 151
2. INTERNATIONAL HUMANITARIAN LAW 152
3. APPLYING THE CURRENT LEGAL FRAMEWORK TO LAWS 156
4. CURRENT APPLICATIONS AND FORESEEABLE DEVELOPMENTS 164
5. NECESSITY OF LEGAL FRAMEWORK 169
6. CONCLUSION 172
X
INTERSENTIA
CONTENTS
CHAPTER 8.
AI AND DATA PROTECTION: THE CASE OF SMART HOME ASSISTANTS
CARL
VANDER MAELEN,
EVA
LIEVENS,
JUDITH
VERMEULEN
AND
INGRIDA
MILKAITE
173
1. INTRODUCTION 173
2. SHAS AND THE GENERAL DATA PROTECTION REGULATION 179
2.1. SHAS AND THE LAWFUL PROCESSING OF DATA: 'IT'S COMPLICATED' 184
2.2. CHILDREN AND SHAS: PRESENT BUT 'INVISIBLE' DATA SUBJECTS 188
2.3. SPECIAL CATEGORIES OF PERSONAL DATA: DOMESTIC SETTING REVEALS
VERY PRIVATE INFORMATION 191
2.4. TRANSPARENCY: INNOVATIVE AND EFFECTIVE INFORMATION FORMATS
NEEDED 193
2.5. DATA SUBJECT RIGHTS: RECTIFICATION, ERASURE, RESTRICTION,
PORTABILITY AND OBJECTION 194
2.6. AUTOMATED DECISION-MAKING: CAUSE FOR CONCERN 196
2.7. MAIN DATA CONTROLLER AND PROCESSOR OBLIGATIONS: THE
IMPORTANCE OF DATA PROTECTION IMPACT ASSESSMENTS AND
CODES OF CONDUCT 199
2.8. ENFORCEMENT: SLOWLY BUT SURELY DPAS TAKE ACTION 202
3. CONCLUSION: TOWARDS DATA PROTECTION COMPLIANT SHAS 204
CHAPTER 9.
AI AND IP: A TALE OF TWO ACRONYMS
JOZEFIEN VANHERPE 207
1. INTRODUCTION 207
2. IP PROTECTION FOR AI TECHNOLOGY 214
2.1. OVERVIEW 214
2.2. PROTECTION UNDER PATENT LAW 214
2.3. PROTECTION UNDER COPYRIGHT LAW 217
3. IP PROTECTION FOR AI-GENERATED OUTPUT 218
3.1. AI AUTHORSHIP OF AI-GENERATED WORKS 219
3.2. AI INVENTORSHIP OF AI-GENERATED INVENTIONS 227
3.3. OWNERSHIP OF AI-GENERATED OUTPUT 232
4. CONCLUSIONS 239
CHAPTER 10.
TAX AND ROBOTS
DINA
SCORNOS
241
1. INTRODUCTION 241
2. RELEVANT BELGIAN TAX RULES FOR CORPORATIONS USING SMART ROBOTS
AND/OR AI 243
INTERSENTIA
XI
CONTENTS
2.1. THE INVESTMENT DEDUCTION 244
2.2. THE INNOVATION INCOME DEDUCTION 246
2.3. THE EXEMPTION OF THE REGIONAL REAL ESTATE TAX ON EQUIPMENT,
MACHINES AND OTHER INSTALLATIONS 249
3. TO TAX OR NOT TO TAX ROBOTS? 250
3.1. DISCUSSIONS TO INTRODUCE A ROBOT TAX IN BELGIUM 250
3.2. TAX POLICY CONSIDERATIONS 251
3.2.1. IS THERE A NEED FOR A ROBOT TAX? 251
3.2.2. HYPOTHESIS: IT IS ESTABLISHED THAT THERE IS A NEED FOR A
ROBOT TAX 254
3.3. CHALLENGES IN THE DESIGN AND IMPLEMENTATION OF A ROBOT TAX . 255
3.3.1. HOW TO DEFINE ROBOTS FOR TAX PURPOSES 255
3.3.2. A TAX ON THE USE OF ROBOTS? 257
3.3.3. A TAX ON ROBOTS THEMSELVES? 258
3.4. ALTERNATIVES TO A ROBOT TAX 260
3.5. CONCLUSION 262
4. SMART ROBOTS AND INTERNATIONAL TAX RULES 262
4.1. OVERVIEW OF CURRENT INTERNATIONAL TAX RULES AND THEIR
(NON?) APPLICABILITY TO SMART ROBOTS/AI 263
4.1.1. FIXED PLACE OF BUSINESS PE 265
A. EXISTENCE OF A PE 265
B. PROFIT ALLOCATION TO THE PE 267
4.1.2. AGENCY PE 268
4.2. NECESSITY TO ADAPT THE INTERNATIONAL TAX RULES FROM A POLICY
PERSPECTIVE 269
4.3. THE PILLAR ONE BLUEPRINT 271
4.3.1. ACTIVITIES AND BUSINESSES TARGETED BY THE PROPOSAL 271
A. AUTOMATED DIGITAL SERVICES 271
B. CONSUMER-FACING BUSINESSES (CFB) 273
4.3.2. QUANTITATIVE THRESHOLDS 274
4.3.3. DETERMINATION OF TAXING RIGHTS OF THE MARKET
JURISDICTION 274
4.3.4. PROFIT ALLOCATION TO THE NON-RESIDENT COUNTRY 276
4.3.5. THE ISSUE OF DOUBLE COUNTING 277
4.3.6. CONCLUSION 278
4.4. IMPLICATIONS OF ALLOCATING LEGAL PERSONALITY TO ROBOTS ON THE
APPLICABILITY OF INTERNATIONAL TAX RULES 278
5. OPPORTUNITIES CREATED BY AI AND ROBOTS 280
5.1. OPPORTUNITIES FOR TAX AUTHORITIES 280
5.2. OPPORTUNITIES FOR TAX PRACTITIONERS 281
5.3. OPPORTUNITIES FOR CORPORATIONS 282
6. CONCLUSION 282
XN
CONTENTS
CHAPTER 11.
ROBOTISATION AND LABOUR LAW. THE DARK FACTORY: THE DARK SIDE OF WORK?
SIMON TAES 285
1. INTRODUCTION 285
2. THE APPEARANCE OF ROBOTISATION 287
2.1. TOWARDS A FOURTH INDUSTRIAL REVOLUTION 287
2.2. ROBOTISATION: THE NEXT STAGE IN THE DIVISION OF LABOUR 287
3. SOCIAL IMPLICATIONS OF ROBOTISATION 291
3.1. THE 'ROBOTISED' LABOUR MARKET 291
3.1.1. THREE HYPOTHESES FROM LABOUR-ECONOMIC PERSPECTIVE . 291
3.1.2. CONSEQUENCES FOR LABOUR MARKET POLICY 294
3.1.3. RECOMMENDATIONS FOR BELGIAN LABOUR MARKET POLICY 295
A. MATCHING SKILLS ON THE'ROBOTISED'LABOUR MARKET. 295
B. CLOSING THE SOCIAL INEQUALITY GAP 299
4. LABOUR LAW IN THE 'ROBOTISED' WORK ENVIRONMENT 300
4.1. THE EVOLVING HUMAN-ROBOT RELATIONSHIP 301
4.1.1. GUARANTEEING PHYSICAL SAFETY AND MENTAL HEALTH 301
4.1.2. WORKERS' RESPONSIBILITY FOR ROBOT COLLEAGUES 305
4.1.3. RECOMMENDATIONS FOR THE EVOLVING HUMAN-ROBOT
RELATIONSHIP 306
4.2. IMPACT OF ROBOTS ON THE EMPLOYMENT RELATIONSHIP 306
4.2.1. ROBOTIC DECISION-MAKING AND PRIVACY 307
4.2.2. ROBOTIC DECISION-MAKING AND DISCRIMINATION 310
4.2.3. SHARING RESPONSIBILITY IN THE 'ROBOTISED' EMPLOYMENT
RELATIONSHIP 311
5. HUMANISATION IN CONTEXT OF ROBOTISATION 314
CHAPTER 12.
THE HYPOTHESIS OF TECHNOLOGICAL UNEMPLOYMENT CAUSED BY AI-DRIVEN
AUTOMATION AND ITS IMPACT ON SOCIAL SECURITY LAW
JAKOB MARKUS
WERBROUCK
317
1. INTRODUCTION 317
2. THE TECHNOLOGICAL UNEMPLOYMENT HYPOTHESIS 318
3. THE POTENTIAL IMPACT OF TECHNOLOGICAL UNEMPLOYMENT ON SOCIAL
SECURITY 322
3.1. EMPLOYMENT AS AN ESSENTIAL VARIABLE IN SOCIAL SECURITY
LEGISLATION 322
3.1.1. HISTORICAL SIGNIFICANCE OF EMPLOYMENT IN THE DESIGN OF
THE BELGIAN WELFARE STATE 323
3.1.2. RESULTING IMPACT OF THIS GENESIS ON SOCIAL SECURITY
LEGISLATION 325
INTERSENTIA X1U
CONTENTS
3.2. EMPLOYMENT AS A LEGITIMATION FOR THE RIGHTS-BASED CHARACTER
OF SOCIAL SECURITY ENTITLEMENTS 329
4. CONCLUSION: A DUTY TO RETHINK THE STATUS QUO? 333
CHAPTER 13.
AI IN BELGIAN CONTRACT LAW: DISRUPTIVE CHALLENGE OR BUSINESS AS USUAL?
ALEXANDER
APPELMANS,
MAARTEN
HERBOSCH
AND BENJAMIN
VERHEYE 335
1. INTRODUCTION 335
2. AI AS A COMMUNICATION TOOL 337
2.1. INTRODUCTION 337
2.2. CONFLICT BETWEEN THE EXPRESSED WILL AND THE ACTUAL WILL 338
2.3. DEFECT OF CONSENT 339
2.4. EVALUATION 342
3. AI SYSTEMS AS LEGAL PERSONS 344
3.1. THE SIGNIFICANCE OF LEGAL CAPACITY 344
3.2. CONTRACTUAL CONSEQUENCE 1: ATTRIBUTION OF ACTS TO THE AI
SYSTEM 347
3.3. CONTRACTUAL CONSEQUENCE 2: AI SYSTEM AS A REPRESENTATIVE 348
3.3.1. MANDATE 348
3.3.2. APPARENT MANDATE 351
3.4. EVALUATION 353
4. BUILDING BRIDGES 354
4.1. INTRODUCTION 354
4.2. ROMAN LAW PECULIUM 354
5. CONCLUSION 357
CHAPTER 14.
TORT LAW AND DAMAGE CAUSED BY AI SYSTEMS
JAN
DE BRUYNE,
ELIAS
VAN GOOL
AND THOMAS
GILS
359
1. INTRODUCTION 359
2. FAULT-BASED LIABILITY 361
2.1. GENERAL CONSIDERATIONS ON THE BURDEN OF PROOF FOR FAULT-
BASED LIABILITY 364
2.2. VIOLATION OF A LEGAL RULE REQUIRING SPECIFIC CONDUCT 366
2.3. VIOLATION OF THE GENERAL DUTY OF CARE 370
3. PRODUCT LIABILITY 376
3.1. THE NOTION OF'PRODUCT' 377
3.2. THE NOTION OF'DEFECT' 380
3.3. THE NOTION OF'PRODUCER' 384
3.4. THE DEFENCES FOR THE PRODUCER 385
XIV
CONTENTS
4. LIABILITY FOR DEFECTIVE THINGS 388
4.1. THE NOTION OF'DEFECTIVE THING' 388
4.2. THE CUSTODIAN 393
5. OTHER COMMON AND RELEVANT ELEMENTS IN TORT LIABILITY CLAIMS 395
5.1. DAMAGE IN AN AL-CONTEXT 395
5.2. CAUSATION IN AN AL-CONTEXT 397
6. LEGAL PERSONALITY FOR AI SYSTEMS 400
7. CONCLUDING REMARKS 402
CHAPTER 15.
INSURANCE UNDERWRITING ON THE BASIS OF TELEMATICS: SEGMENTATION
AND PROFILING
JEFFREY
AMANKWAH
405
1. INTRODUCTION 405
2. POLICY UNDERWRITING IN VEHICLE INSURANCE 406
2.1. THE BASICS OF INSURANCE UNDERWRITING 406
2.2. VEHICLE INSURANCE UNDERWRITING 408
3. USAGE-BASED INSURANCE: PARADIGM SHIFT 410
3.1. DIFFERENT TYPES OF TELEMATICS/UBI SCHEMES 412
3.2. POTENTIAL BENEFITS OF TELEMATICS/UBI BASED INSURANCE 414
4. LEGAL CHALLENGES 416
4.1. REFINED CLASSIFICATION: LEGAL AND ECONOMIC CONSIDERATIONS 416
4.1.1. PRINCIPLE OF MUTUALISATION AND SOLIDARITY 416
4.1.2. REFINED CLASSIFICATION AND REDUCING SUBSIDISING
SOLIDARITY: IDENTIFYING THE ISSUES AND LIMITS 418
A. LEGAL SAFEGUARDS REGARDING SEGMENTATION IN
BELGIUM 418
B. PRICING COMPETITION 420
C. UNINSURABILITY 420
D. LACK OF TRANSPARENCY AND (INDIRECT) DISCRIMINATION . 421
4.2. PROTECTION OF PRIVACY AND PERSONAL DATA: LEGAL CONSIDERATIONS 422
4.2.1. GENERAL PRINCIPLES OF DATA PROTECTION 423
4.2.2. ESTABLISHING AN INDIVIDUALISED RISK PROFILE 424
4.2.3. LEGITIMISING UBI 425
5. CONCLUSION 428
CHAPTER 16.
AI AND CREDITWORTHINESS ASSESSMENTS: THE TALE OF CREDIT SCORING AND
CONSUMER PROTECTION. A STORY WITH A HAPPY ENDING?
JULIE
GOETGHEBUER
429
1. INTRODUCTION 429
2. THE CREDITWORTHINESS ASSESSMENT 431
INTERSENTIA
XV
CONTENTS
2.1. CREDIT-WORTHINESS ASSESSMENT AND THE CONSUMER CREDIT
DIRECTIVE 431
2.2. CREDITWORTHINESS ASSESSMENT AND INFORMATION 432
2.3. CREDITWORTHINESS ASSESSMENT AND RESPONSIBLE LENDING 436
3. THE AUTOMATION OF CREDITWORTHINESS ASSESSMENT THROUGH CREDIT
SCORING 440
3.1. MEANING AND FUNCTION 440
3.2. NEW CREDIT SCORING TECHNIQUES 444
4. THE IMPACT OF CREDIT SCORING ON CONSUMERS 447
4.1. THE POTENTIAL EFFECTS ON CONSUMERS-BORROWERS 447
4.1.1. BENEFITS 447
4.1.2. CHALLENGES 449
4.2. THE CONFINES OF THE CONSUMER CREDIT DIRECTIVE 452
4.2.1. CAN THE USE OF CREDIT SCORING TECHNIQUES BE
CONSIDERED A RESPONSIBLE LENDING PRACTICE? 452
4.2.2. ARE THE PROVISIONS OF THE CONSUMER CREDIT DIRECTIVE
SUFFICIENT TO FULLY PROTECT CONSUMERS? 453
5. CONCLUSION 458
CHAPTER 17.
AI AND THE CONSUMER
SKANDER BENNIS 461
1. INTRODUCTION 461
2. BENEFITS AND RISKS OF AI AS A MARKET TOOL 462
3. BUILDING BLOCKS FOR A CONSUMER POLICY IN THE AGE OF AI 465
4. CONSUMER AUTONOMY VERSUS AUTONOMOUS MACHINES 473
4.1. AI-BASED MARKETING 473
4.1.1. AI AND PERSONALISED MARKETING (TARGETING) 473
4.1.2. AI AND PERSONALISED PRICING 479
4.2. AI-AIDED CONTRACTING 481
4.3. AI-AUTOMATED ENFORCEMENT 484
5. CONCLUSION: A TALE ABOUT OPEN-MINDEDNESS AND VIGILANCE 485
CHAPTER 18.
ROBOTS AND AI IN THE HEALTHCARE SECTOR: POTENTIAL EXISTING LEGAL
SAFEGUARDS AGAINST A(N) (UN)JUSTIFIED FEAR FOR 'DEHUMANISATION' OF THE
PHYSICIAN-PATIENT RELATIONSHIP
WANNES
BUELENS
487
1. INTRODUCTION 487
2. THE RISE OF ROBOTICS AND AI TO DEAL WITH INCREASING DEMANDS IN
THE HEALTHCARE SECTOR 487
XVI
CONTENTS
3. ONLY QUALIFIED PERSONS ARE ALLOWED TO PROVIDE HEALTHCARE 493
4. LIABILITY RULES 494
5. THE RIGHT OF THE PATIENT TO RECEIVE INFORMATION ABOUT HIS/HER
HEALTH CONDITION AND TO GIVE INFORMED CONSENT UNDER THE BELGIAN
LAW ON PATIENT RIGHTS 499
5.1. PURPOSE AND NATURE OF THE TREATMENT 501
5.2. RELEVANT RISKS OF THE USE OF AI 502
5.3. DISCLOSURE OF THE ALTERNATIVE TREATMENTS 503
5.3.1. DISCLOSURE OF ALTERNATIVES TO AI SYSTEMS AND ROBOTS 503
5.3.2. DISCLOSURE OF AI AS AN ALTERNATIVE 505
5.3.3. DISCLOSURE OF AI TREATMENTS IN OTHER HOSPITALS 506
5.4. RIGHT OF THE PATIENT TO RECEIVE INFORMATION ABOUT HIS/HER
HEALTH CONDITION 507
5.5. INFORMATION ABOUT THE USE OF AI/ROBOTS AND THE UNDERLYING
TECHNOLOGY? 508
6. TRANSPARENCY AND INFORMED CONSENT UNDER THE GDPR 511
6.1. TRANSPARENCY IS KEY UNDER THE GDPR 511
6.1.1. GENERAL 511
6.1.2. DECISIONS SOLELY BASED ON AUTOMATED PROCESSING OF
PERSONAL (HEALTH) DATA 512
6.1.3. INFORMED CONSENT UNDER THE GDPR 516
7. CONCLUSION 518
INTERSENTIA
XVN |
| adam_txt |
CONTENTS
FOREWORD XIX
CONTRIBUTING AUTHORS XXV
CHAPTER 1.
BASIC CONCEPTS OF AI FOR LEGAL SCHOLARS
REMBRANDT
DEVILLE,
NICO
SERGEYSSELS
AND CATHERINE
MIDDAG
1
1. INTRODUCTION 1
2. DEFINING AND MEASURING AI 2
2.1. DEFINITION: WHAT IS AI? 2
2.2. THE TURING TEST AND THE LOEBNER PRIZE 3
3. BASIC PRINCIPLES OF AI 4
3.1. KNOWLEDGE-BASED VERSUS DATA-BASED LEARNING 4
3.2. INTERNET OF THINGS AND BIG DATA 5
3.3. MACHINE LEARNING 6
3.4. ARTIFICIAL NEURAL NETWORKS AND DEEP LEARNING 7
3.5. DATA BIAS AND MODEL BIAS 10
4. AI SUB-DISCIPLINES 11
4.1. SEARCH ALGORITHMS 12
4.2. COMPUTER VISION 12
4.3. NATURAL LANGUAGE 12
4.4. SPEECH 13
4.5. AGENTS 14
5. THE CURRENT AND FUTURE USE OF AI APPLICATIONS 14
5.1. AN OVERVIEW OF SOME AI APPLICATIONS IN THE PRESENT AND NEAR
FUTURE 14
5.1.1. TRANSPORTATION 15
5.1.2. ROBOTS 16
5.1.3. HEALTHCARE 17
5.1.4. EDUCATION 18
5.1.5. PUBLIC SAFETY AND SECURITY 18
5.1.6. ARTS AND ENTERTAINMENT 19
5.1.7. LAW 20
5.2. AI IN THE MORE DISTANT FUTURE 20
6. CONCLUSION 21
INTERSENTIA
CONTENTS
CHAPTER 2.
DIFFERENT MODELS OF INNOVATION AND THEIR RELATION TO LAW
CHARLES
DELMOTTE
23
1. INTRODUCTION 23
2. STANDARD ECONOMIC MODEL ON INNOVATION 26
2.1. THE NEOCLASSICAL MODEL 26
2.2. TAX INCENTIVES FOR INNOVATION 28
2.3. DUBIOUS EMPIRICAL TRACK RECORD OF TAX INCENTIVES 31
3. INSTITUTIONAL ECONOMICS 32
3.1. THE MARKET AS A DYNAMIC PROCESS 33
3.2. INNOVATION: AN ENDOGENOUS AND UNPREDICTABLE PHENOMENON 37
3.3. TAX INCENTIVES FOR INNOVATION: A CRITIQUE 40
3.3.1. IDENTIFYING INNOVATORS 40
3.3.2. THE AMOUNT OF THE TAX BENEFIT 41
3.4. INNOVATION POLICY: THE PROPERTARIAN APPROACH 42
4. CONCLUSION 48
CHAPTER 3.
SETTING THE SCENE: ON AI ETHICS AND REGULATION
MICHIEL
FIERENS,
STEPHANIE
ROSSELLO
AND ELLEN
WAUTERS
49
1. INTRODUCTION 49
2. ETHICS OF AI 50
3. REGULATION OF AI 55
4. CURRENT TRENDS IN AI GOVERNANCE 62
5. CONCLUSION 71
CHAPTER 4.
QUANTITATIVE LEGAL PREDICTION: THE FUTURE OF DISPUTE RESOLUTION?
MATTHIAS VAN DER HAEGEN 73
1. INTRODUCTION 73
2. LEGAL ANALYTICS 74
3. EXISTING APPLICATIONS 77
3.1. COMPAS 78
3.2. HART 78
3.3. CASE LAW ANALYTICS 78
3.4. PROMETEA 79
4. POTENTIAL USE CASES AND THEIR ADVANTAGES 80
4.1. POTENTIAL USE CASES 80
4.2. ADVANTAGES OF QLP 82
5. CHALLENGES 82
5.1. LIMITS OF PREDICTIVE MODELS WITHIN THE LEGAL DOMAIN 83
VLU
INTERSENTIA
CONTENTS
5.1.1. THE APPLICATION OF LAW DOES NOT ADHERE TO
PREDETERMINED RULES 83
5.1.2. CHANGEABLE NATURE OF LAW 84
5.1.3. RISK OF A NORMATIVE PREDICTION 85
5.2. CHALLENGES INHERENT TO PREDICTIVE MODELS 86
5.2.1. BIAS WITHIN PREDICTIVE MODELS 86
A. BIASED TRAINING DATA 87
B. BIASED DATA 87
C. BIASED ALGORITHMS 89
5.2.2. TRANSPARENCY 90
5.2.3. TRUST 93
6. THE CASE FOR BELGIUM 94
6.1. PUBLICATION OF CASE LAW BY THE JUDICIARY 96
6.2. PUBLICATION OF CASE LAW BY PUBLISHERS 97
6.3. GENERAL PUBLICATION OF CASE LAW IN THE NEAR FUTURE? 97
7. CONCLUSION 98
CHAPTER 5.
AI ARBITRATORS . 'DOES NOT COMPUTE'
KEVIN
ONGENAE
101
1. INTRODUCTION 101
2. THERE ARE CONSIDERABLE DATA-RELATED HURDLES TO AI-BASED ARBITRATORS
. 104
2.1. THE AMOUNT OF DATA NEEDED FOR PERFORMANT AI IS NOT
AVAILABLE IN ARBITRATION 104
2.2. ARBITRATION DATA IS NOT SUITABLE FOR AI DEVELOPMENT 106
2.3. AN AI ARBITRATOR MOST LIKELY COULD NOT COPE WITH NOVEL OR
UNIQUE ISSUES 108
2.4. AI ARBITRATOR WOULD COPY MISTAKES IN PREVIOUS DATA 109
2.5. CONCLUSION CONCERNING DATA-BASED FLAWS ILL
3. THE CURRENT LEGAL FRAMEWORK IS INHOSPITABLE TO AI ARBITRATORS ILL
3.1. ARBITRATION LAW IS BUILT AROUND THE ASSUMPTION OF A HUMAN
ARBITRATOR 113
3.2. INDEPENDENCE AND IMPARTIALITY OF AN AI ARBITRATOR? 115
3.3. FORMAL REQUIREMENTS FOR RENDERING AN ARBITRAL AWARD
CURRENTLY EXCLUDE AN AI ARBITRATOR 116
3.4. DUTY TO PROVIDE REASONS 118
3.5. CONCLUSION CONCERNING THE LEGAL FRAMEWORK 119
4. CONCLUSION AND LOOK AHEAD 120
INTERSENTIA
CONTENTS
CHAPTER 6.
AI THROUGH A HUMAN RIGHTS LENS. HIE ROLE OF HUMAN RIGHTS IN
FULFILLING AFS POTENTIAL
CHARLINE DAELMAN 123
1. INTRODUCTION 123
2. THE IMPACT OF AI ON HUMAN RIGHTS: RISKS AND OPPORTUNITIES 124
2.1. RIGHT TO LIFE, LIBERTY, SECURITY AND A FAIR TRIAL 125
2.2. RIGHT TO PRIVACY 126
2.3. RIGHT TO FREEDOM OF THOUGHT, CONSCIENCE AND RELIGION,
EXPRESSION AND ASSEMBLY/ASSOCIATION 127
2.4. PROHIBITION OF DISCRIMINATION 129
2.5. RIGHT TO POLITICAL PARTICIPATION AND PROHIBITION ON PROPAGANDA.
130
2.6. RIGHT TO WORK AND TO AN ADEQUATE STANDARD OF LIVING 131
2.7. RIGHTTO HEALTH 133
2.8. RIGHT TO EDUCATION 135
2.9. THE PROTECTION OF INTELLECTUAL PROPERTY 136
3. THE RECURRING ISSUE: DISCRIMINATION AND BIAS 137
3.1. DISCRIMINATION CAUSED BY AI SYSTEMS 137
3.1.1. DISCRIMINATION AT THE PROCESS LEVEL 138
3.1.2. DISCRIMINATION AT THE CLASSIFICATION LEVEL 140
3.2. DISCRIMINATION GROUNDS 141
3.2.1. DISCRIMINATION BASED ON ETHNICITY: UYGHUR MUSLIM
IN CHINA 141
3.2.2. DISCRIMINATION BASED ON GENDER: ONLINE JOB
ADVERTISEMENTS 142
3.2.3. DISCRIMINATION BASED ON RELIGION, BELIEF AND POLITICAL
OPINION: FACEBOOK 143
3.2.4. DISCRIMINATION BASED ON RACE: GERRYMANDERING 143
3.3. SILVER LININGS 144
4. BENDING THREATS INTO OPPORTUNITIES: HUMAN RIGHTS AS THE ETHICAL
FRAMEWORK TO ENSURE AI'S POTENTIAL 145
5. CONCLUSION 148
CHAPTER 7.
KILLER ROBOTS: LETHAL AUTONOMOUS WEAPONS AND INTERNATIONAL LAW
SEBASTIAAN
VAN SEVEREN
AND CARL
VANDER MAELEN
151
1. INTRODUCTION 151
2. INTERNATIONAL HUMANITARIAN LAW 152
3. APPLYING THE CURRENT LEGAL FRAMEWORK TO LAWS 156
4. CURRENT APPLICATIONS AND FORESEEABLE DEVELOPMENTS 164
5. NECESSITY OF LEGAL FRAMEWORK 169
6. CONCLUSION 172
X
INTERSENTIA
CONTENTS
CHAPTER 8.
AI AND DATA PROTECTION: THE CASE OF SMART HOME ASSISTANTS
CARL
VANDER MAELEN,
EVA
LIEVENS,
JUDITH
VERMEULEN
AND
INGRIDA
MILKAITE
173
1. INTRODUCTION 173
2. SHAS AND THE GENERAL DATA PROTECTION REGULATION 179
2.1. SHAS AND THE LAWFUL PROCESSING OF DATA: 'IT'S COMPLICATED' 184
2.2. CHILDREN AND SHAS: PRESENT BUT 'INVISIBLE' DATA SUBJECTS 188
2.3. SPECIAL CATEGORIES OF PERSONAL DATA: DOMESTIC SETTING REVEALS
VERY PRIVATE INFORMATION 191
2.4. TRANSPARENCY: INNOVATIVE AND EFFECTIVE INFORMATION FORMATS
NEEDED 193
2.5. DATA SUBJECT RIGHTS: RECTIFICATION, ERASURE, RESTRICTION,
PORTABILITY AND OBJECTION 194
2.6. AUTOMATED DECISION-MAKING: CAUSE FOR CONCERN 196
2.7. MAIN DATA CONTROLLER AND PROCESSOR OBLIGATIONS: THE
IMPORTANCE OF DATA PROTECTION IMPACT ASSESSMENTS AND
CODES OF CONDUCT 199
2.8. ENFORCEMENT: SLOWLY BUT SURELY DPAS TAKE ACTION 202
3. CONCLUSION: TOWARDS DATA PROTECTION COMPLIANT SHAS 204
CHAPTER 9.
AI AND IP: A TALE OF TWO ACRONYMS
JOZEFIEN VANHERPE 207
1. INTRODUCTION 207
2. IP PROTECTION FOR AI TECHNOLOGY 214
2.1. OVERVIEW 214
2.2. PROTECTION UNDER PATENT LAW 214
2.3. PROTECTION UNDER COPYRIGHT LAW 217
3. IP PROTECTION FOR AI-GENERATED OUTPUT 218
3.1. AI AUTHORSHIP OF AI-GENERATED WORKS 219
3.2. AI INVENTORSHIP OF AI-GENERATED INVENTIONS 227
3.3. OWNERSHIP OF AI-GENERATED OUTPUT 232
4. CONCLUSIONS 239
CHAPTER 10.
TAX AND ROBOTS
DINA
SCORNOS
241
1. INTRODUCTION 241
2. RELEVANT BELGIAN TAX RULES FOR CORPORATIONS USING SMART ROBOTS
AND/OR AI 243
INTERSENTIA
XI
CONTENTS
2.1. THE INVESTMENT DEDUCTION 244
2.2. THE INNOVATION INCOME DEDUCTION 246
2.3. THE EXEMPTION OF THE REGIONAL REAL ESTATE TAX ON EQUIPMENT,
MACHINES AND OTHER INSTALLATIONS 249
3. TO TAX OR NOT TO TAX ROBOTS? 250
3.1. DISCUSSIONS TO INTRODUCE A ROBOT TAX IN BELGIUM 250
3.2. TAX POLICY CONSIDERATIONS 251
3.2.1. IS THERE A NEED FOR A ROBOT TAX? 251
3.2.2. HYPOTHESIS: IT IS ESTABLISHED THAT THERE IS A NEED FOR A
ROBOT TAX 254
3.3. CHALLENGES IN THE DESIGN AND IMPLEMENTATION OF A ROBOT TAX . 255
3.3.1. HOW TO DEFINE ROBOTS FOR TAX PURPOSES 255
3.3.2. A TAX ON THE USE OF ROBOTS? 257
3.3.3. A TAX ON ROBOTS THEMSELVES? 258
3.4. ALTERNATIVES TO A ROBOT TAX 260
3.5. CONCLUSION 262
4. SMART ROBOTS AND INTERNATIONAL TAX RULES 262
4.1. OVERVIEW OF CURRENT INTERNATIONAL TAX RULES AND THEIR
(NON?) APPLICABILITY TO SMART ROBOTS/AI 263
4.1.1. FIXED PLACE OF BUSINESS PE 265
A. EXISTENCE OF A PE 265
B. PROFIT ALLOCATION TO THE PE 267
4.1.2. AGENCY PE 268
4.2. NECESSITY TO ADAPT THE INTERNATIONAL TAX RULES FROM A POLICY
PERSPECTIVE 269
4.3. THE PILLAR ONE BLUEPRINT 271
4.3.1. ACTIVITIES AND BUSINESSES TARGETED BY THE PROPOSAL 271
A. AUTOMATED DIGITAL SERVICES 271
B. CONSUMER-FACING BUSINESSES (CFB) 273
4.3.2. QUANTITATIVE THRESHOLDS 274
4.3.3. DETERMINATION OF TAXING RIGHTS OF THE MARKET
JURISDICTION 274
4.3.4. PROFIT ALLOCATION TO THE NON-RESIDENT COUNTRY 276
4.3.5. THE ISSUE OF DOUBLE COUNTING 277
4.3.6. CONCLUSION 278
4.4. IMPLICATIONS OF ALLOCATING LEGAL PERSONALITY TO ROBOTS ON THE
APPLICABILITY OF INTERNATIONAL TAX RULES 278
5. OPPORTUNITIES CREATED BY AI AND ROBOTS 280
5.1. OPPORTUNITIES FOR TAX AUTHORITIES 280
5.2. OPPORTUNITIES FOR TAX PRACTITIONERS 281
5.3. OPPORTUNITIES FOR CORPORATIONS 282
6. CONCLUSION 282
XN
CONTENTS
CHAPTER 11.
ROBOTISATION AND LABOUR LAW. THE DARK FACTORY: THE DARK SIDE OF WORK?
SIMON TAES 285
1. INTRODUCTION 285
2. THE APPEARANCE OF ROBOTISATION 287
2.1. TOWARDS A FOURTH INDUSTRIAL REVOLUTION 287
2.2. ROBOTISATION: THE NEXT STAGE IN THE DIVISION OF LABOUR 287
3. SOCIAL IMPLICATIONS OF ROBOTISATION 291
3.1. THE 'ROBOTISED' LABOUR MARKET 291
3.1.1. THREE HYPOTHESES FROM LABOUR-ECONOMIC PERSPECTIVE . 291
3.1.2. CONSEQUENCES FOR LABOUR MARKET POLICY 294
3.1.3. RECOMMENDATIONS FOR BELGIAN LABOUR MARKET POLICY 295
A. MATCHING SKILLS ON THE'ROBOTISED'LABOUR MARKET. 295
B. CLOSING THE SOCIAL INEQUALITY GAP 299
4. LABOUR LAW IN THE 'ROBOTISED' WORK ENVIRONMENT 300
4.1. THE EVOLVING HUMAN-ROBOT RELATIONSHIP 301
4.1.1. GUARANTEEING PHYSICAL SAFETY AND MENTAL HEALTH 301
4.1.2. WORKERS' RESPONSIBILITY FOR ROBOT COLLEAGUES 305
4.1.3. RECOMMENDATIONS FOR THE EVOLVING HUMAN-ROBOT
RELATIONSHIP 306
4.2. IMPACT OF ROBOTS ON THE EMPLOYMENT RELATIONSHIP 306
4.2.1. ROBOTIC DECISION-MAKING AND PRIVACY 307
4.2.2. ROBOTIC DECISION-MAKING AND DISCRIMINATION 310
4.2.3. SHARING RESPONSIBILITY IN THE 'ROBOTISED' EMPLOYMENT
RELATIONSHIP 311
5. HUMANISATION IN CONTEXT OF ROBOTISATION 314
CHAPTER 12.
THE HYPOTHESIS OF TECHNOLOGICAL UNEMPLOYMENT CAUSED BY AI-DRIVEN
AUTOMATION AND ITS IMPACT ON SOCIAL SECURITY LAW
JAKOB MARKUS
WERBROUCK
317
1. INTRODUCTION 317
2. THE TECHNOLOGICAL UNEMPLOYMENT HYPOTHESIS 318
3. THE POTENTIAL IMPACT OF TECHNOLOGICAL UNEMPLOYMENT ON SOCIAL
SECURITY 322
3.1. EMPLOYMENT AS AN ESSENTIAL VARIABLE IN SOCIAL SECURITY
LEGISLATION 322
3.1.1. HISTORICAL SIGNIFICANCE OF EMPLOYMENT IN THE DESIGN OF
THE BELGIAN WELFARE STATE 323
3.1.2. RESULTING IMPACT OF THIS GENESIS ON SOCIAL SECURITY
LEGISLATION 325
INTERSENTIA X1U
CONTENTS
3.2. EMPLOYMENT AS A LEGITIMATION FOR THE RIGHTS-BASED CHARACTER
OF SOCIAL SECURITY ENTITLEMENTS 329
4. CONCLUSION: A DUTY TO RETHINK THE STATUS QUO? 333
CHAPTER 13.
AI IN BELGIAN CONTRACT LAW: DISRUPTIVE CHALLENGE OR BUSINESS AS USUAL?
ALEXANDER
APPELMANS,
MAARTEN
HERBOSCH
AND BENJAMIN
VERHEYE 335
1. INTRODUCTION 335
2. AI AS A COMMUNICATION TOOL 337
2.1. INTRODUCTION 337
2.2. CONFLICT BETWEEN THE EXPRESSED WILL AND THE ACTUAL WILL 338
2.3. DEFECT OF CONSENT 339
2.4. EVALUATION 342
3. AI SYSTEMS AS LEGAL PERSONS 344
3.1. THE SIGNIFICANCE OF LEGAL CAPACITY 344
3.2. CONTRACTUAL CONSEQUENCE 1: ATTRIBUTION OF ACTS TO THE AI
SYSTEM 347
3.3. CONTRACTUAL CONSEQUENCE 2: AI SYSTEM AS A REPRESENTATIVE 348
3.3.1. MANDATE 348
3.3.2. APPARENT MANDATE 351
3.4. EVALUATION 353
4. BUILDING BRIDGES 354
4.1. INTRODUCTION 354
4.2. ROMAN LAW PECULIUM 354
5. CONCLUSION 357
CHAPTER 14.
TORT LAW AND DAMAGE CAUSED BY AI SYSTEMS
JAN
DE BRUYNE,
ELIAS
VAN GOOL
AND THOMAS
GILS
359
1. INTRODUCTION 359
2. FAULT-BASED LIABILITY 361
2.1. GENERAL CONSIDERATIONS ON THE BURDEN OF PROOF FOR FAULT-
BASED LIABILITY 364
2.2. VIOLATION OF A LEGAL RULE REQUIRING SPECIFIC CONDUCT 366
2.3. VIOLATION OF THE GENERAL DUTY OF CARE 370
3. PRODUCT LIABILITY 376
3.1. THE NOTION OF'PRODUCT' 377
3.2. THE NOTION OF'DEFECT' 380
3.3. THE NOTION OF'PRODUCER' 384
3.4. THE DEFENCES FOR THE PRODUCER 385
XIV
CONTENTS
4. LIABILITY FOR DEFECTIVE THINGS 388
4.1. THE NOTION OF'DEFECTIVE THING' 388
4.2. THE CUSTODIAN 393
5. OTHER COMMON AND RELEVANT ELEMENTS IN TORT LIABILITY CLAIMS 395
5.1. DAMAGE IN AN AL-CONTEXT 395
5.2. CAUSATION IN AN AL-CONTEXT 397
6. LEGAL PERSONALITY FOR AI SYSTEMS 400
7. CONCLUDING REMARKS 402
CHAPTER 15.
INSURANCE UNDERWRITING ON THE BASIS OF TELEMATICS: SEGMENTATION
AND PROFILING
JEFFREY
AMANKWAH
405
1. INTRODUCTION 405
2. POLICY UNDERWRITING IN VEHICLE INSURANCE 406
2.1. THE BASICS OF INSURANCE UNDERWRITING 406
2.2. VEHICLE INSURANCE UNDERWRITING 408
3. USAGE-BASED INSURANCE: PARADIGM SHIFT 410
3.1. DIFFERENT TYPES OF TELEMATICS/UBI SCHEMES 412
3.2. POTENTIAL BENEFITS OF TELEMATICS/UBI BASED INSURANCE 414
4. LEGAL CHALLENGES 416
4.1. REFINED CLASSIFICATION: LEGAL AND ECONOMIC CONSIDERATIONS 416
4.1.1. PRINCIPLE OF MUTUALISATION AND SOLIDARITY 416
4.1.2. REFINED CLASSIFICATION AND REDUCING SUBSIDISING
SOLIDARITY: IDENTIFYING THE ISSUES AND LIMITS 418
A. LEGAL SAFEGUARDS REGARDING SEGMENTATION IN
BELGIUM 418
B. PRICING COMPETITION 420
C. UNINSURABILITY 420
D. LACK OF TRANSPARENCY AND (INDIRECT) DISCRIMINATION . 421
4.2. PROTECTION OF PRIVACY AND PERSONAL DATA: LEGAL CONSIDERATIONS 422
4.2.1. GENERAL PRINCIPLES OF DATA PROTECTION 423
4.2.2. ESTABLISHING AN INDIVIDUALISED RISK PROFILE 424
4.2.3. LEGITIMISING UBI 425
5. CONCLUSION 428
CHAPTER 16.
AI AND CREDITWORTHINESS ASSESSMENTS: THE TALE OF CREDIT SCORING AND
CONSUMER PROTECTION. A STORY WITH A HAPPY ENDING?
JULIE
GOETGHEBUER
429
1. INTRODUCTION 429
2. THE CREDITWORTHINESS ASSESSMENT 431
INTERSENTIA
XV
CONTENTS
2.1. CREDIT-WORTHINESS ASSESSMENT AND THE CONSUMER CREDIT
DIRECTIVE 431
2.2. CREDITWORTHINESS ASSESSMENT AND INFORMATION 432
2.3. CREDITWORTHINESS ASSESSMENT AND RESPONSIBLE LENDING 436
3. THE AUTOMATION OF CREDITWORTHINESS ASSESSMENT THROUGH CREDIT
SCORING 440
3.1. MEANING AND FUNCTION 440
3.2. NEW CREDIT SCORING TECHNIQUES 444
4. THE IMPACT OF CREDIT SCORING ON CONSUMERS 447
4.1. THE POTENTIAL EFFECTS ON CONSUMERS-BORROWERS 447
4.1.1. BENEFITS 447
4.1.2. CHALLENGES 449
4.2. THE CONFINES OF THE CONSUMER CREDIT DIRECTIVE 452
4.2.1. CAN THE USE OF CREDIT SCORING TECHNIQUES BE
CONSIDERED A RESPONSIBLE LENDING PRACTICE? 452
4.2.2. ARE THE PROVISIONS OF THE CONSUMER CREDIT DIRECTIVE
SUFFICIENT TO FULLY PROTECT CONSUMERS? 453
5. CONCLUSION 458
CHAPTER 17.
AI AND THE CONSUMER
SKANDER BENNIS 461
1. INTRODUCTION 461
2. BENEFITS AND RISKS OF AI AS A MARKET TOOL 462
3. BUILDING BLOCKS FOR A CONSUMER POLICY IN THE AGE OF AI 465
4. CONSUMER AUTONOMY VERSUS AUTONOMOUS MACHINES 473
4.1. AI-BASED MARKETING 473
4.1.1. AI AND PERSONALISED MARKETING (TARGETING) 473
4.1.2. AI AND PERSONALISED PRICING 479
4.2. AI-AIDED CONTRACTING 481
4.3. AI-AUTOMATED ENFORCEMENT 484
5. CONCLUSION: A TALE ABOUT OPEN-MINDEDNESS AND VIGILANCE 485
CHAPTER 18.
ROBOTS AND AI IN THE HEALTHCARE SECTOR: POTENTIAL EXISTING LEGAL
SAFEGUARDS AGAINST A(N) (UN)JUSTIFIED FEAR FOR 'DEHUMANISATION' OF THE
PHYSICIAN-PATIENT RELATIONSHIP
WANNES
BUELENS
487
1. INTRODUCTION 487
2. THE RISE OF ROBOTICS AND AI TO DEAL WITH INCREASING DEMANDS IN
THE HEALTHCARE SECTOR 487
XVI
CONTENTS
3. ONLY QUALIFIED PERSONS ARE ALLOWED TO PROVIDE HEALTHCARE 493
4. LIABILITY RULES 494
5. THE RIGHT OF THE PATIENT TO RECEIVE INFORMATION ABOUT HIS/HER
HEALTH CONDITION AND TO GIVE INFORMED CONSENT UNDER THE BELGIAN
LAW ON PATIENT RIGHTS 499
5.1. PURPOSE AND NATURE OF THE TREATMENT 501
5.2. RELEVANT RISKS OF THE USE OF AI 502
5.3. DISCLOSURE OF THE ALTERNATIVE TREATMENTS 503
5.3.1. DISCLOSURE OF ALTERNATIVES TO AI SYSTEMS AND ROBOTS 503
5.3.2. DISCLOSURE OF AI AS AN ALTERNATIVE 505
5.3.3. DISCLOSURE OF AI TREATMENTS IN OTHER HOSPITALS 506
5.4. RIGHT OF THE PATIENT TO RECEIVE INFORMATION ABOUT HIS/HER
HEALTH CONDITION 507
5.5. INFORMATION ABOUT THE USE OF AI/ROBOTS AND THE UNDERLYING
TECHNOLOGY? 508
6. TRANSPARENCY AND INFORMED CONSENT UNDER THE GDPR 511
6.1. TRANSPARENCY IS KEY UNDER THE GDPR 511
6.1.1. GENERAL 511
6.1.2. DECISIONS SOLELY BASED ON AUTOMATED PROCESSING OF
PERSONAL (HEALTH) DATA 512
6.1.3. INFORMED CONSENT UNDER THE GDPR 516
7. CONCLUSION 518
INTERSENTIA
XVN |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author2 | Bruyne, Jan de Vanleenhove, Cedric |
| author2_role | edt edt |
| author2_variant | j d b jd jdb c v cv |
| author_GND | (DE-588)1082770566 (DE-588)1119477980 |
| author_facet | Bruyne, Jan de Vanleenhove, Cedric |
| building | Verbundindex |
| bvnumber | BV047222823 |
| ctrlnum | (OCoLC)1242403658 (DE-599)BVBBV047222823 |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 cb4500</leader><controlfield tag="001">BV047222823</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20210804</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">210401s2021 xxk |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781839701030</subfield><subfield code="9">978-1-83970-103-0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1242403658</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047222823</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">xxk</subfield><subfield code="c">XA-GB</subfield><subfield code="a">ne</subfield><subfield code="c">XA-NL</subfield><subfield code="a">xxu</subfield><subfield code="c">XD-US</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-M382</subfield><subfield code="a">DE-19</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">INTRECHT</subfield><subfield code="q">DE-1a</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">86.59</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Artificial Intelligence and the Law</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge ; Antwerp ; Chicago</subfield><subfield code="b">Intersentia</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XXXI, 520 Seiten</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Centrum voor Verbintenissen- en Goederenrecht</subfield><subfield code="v">4</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Recht</subfield><subfield code="0">(DE-588)4048737-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4143413-4</subfield><subfield code="a">Aufsatzsammlung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Recht</subfield><subfield code="0">(DE-588)4048737-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bruyne, Jan de</subfield><subfield code="0">(DE-588)1082770566</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Vanleenhove, Cedric</subfield><subfield code="0">(DE-588)1119477980</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-1-83970-104-7</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">SWB Datenaustausch</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032627411&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield></record></collection> |
| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV047222823 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:58:04Z |
| indexdate | 2024-07-20T06:48:04Z |
| institution | BVB |
| isbn | 9781839701030 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032627411 |
| oclc_num | 1242403658 |
| open_access_boolean | |
| owner | DE-M382 DE-19 DE-BY-UBM |
| owner_facet | DE-M382 DE-19 DE-BY-UBM |
| physical | XXXI, 520 Seiten |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | Intersentia |
| record_format | marc |
| series2 | Centrum voor Verbintenissen- en Goederenrecht |
| spelling | Artificial Intelligence and the Law Cambridge ; Antwerp ; Chicago Intersentia [2021] XXXI, 520 Seiten txt rdacontent n rdamedia nc rdacarrier Centrum voor Verbintenissen- en Goederenrecht 4 Recht (DE-588)4048737-4 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Künstliche Intelligenz (DE-588)4033447-8 s Recht (DE-588)4048737-4 s DE-604 Bruyne, Jan de (DE-588)1082770566 edt Vanleenhove, Cedric (DE-588)1119477980 edt Erscheint auch als Online-Ausgabe 978-1-83970-104-7 SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032627411&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Artificial Intelligence and the Law Recht (DE-588)4048737-4 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4048737-4 (DE-588)4033447-8 (DE-588)4143413-4 |
| title | Artificial Intelligence and the Law |
| title_auth | Artificial Intelligence and the Law |
| title_exact_search | Artificial Intelligence and the Law |
| title_exact_search_txtP | Artificial Intelligence and the Law |
| title_full | Artificial Intelligence and the Law |
| title_fullStr | Artificial Intelligence and the Law |
| title_full_unstemmed | Artificial Intelligence and the Law |
| title_short | Artificial Intelligence and the Law |
| title_sort | artificial intelligence and the law |
| topic | Recht (DE-588)4048737-4 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Recht Künstliche Intelligenz Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032627411&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT bruynejande artificialintelligenceandthelaw AT vanleenhovecedric artificialintelligenceandthelaw |