Algorithmic regulation and personalized law: a handbook
Gespeichert in:
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| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
München
C.H. Beck
2021
Oxford Hart Baden-Baden Nomos |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031326699&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Auch angekündigt unter dem Titel: "Data economy and algorithmic regulation." |
| Umfang: | XIII, 292 Seiten 24 cm x 16 cm |
| ISBN: | 9783406743917 3406743919 9783848769209 9781509931750 |
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| adam_text |
ALGORITHMIC REGULATION
AND PERSONALIZED LAW
A HANDBOOK
EDITED BY
CHRISTOPH BUSCH
ALBERTO DE FRANCESCHI
2021
TABLE OF CONTENTS
LIST OF AUTHORS XI
INTRODUCTION
PERSONALIZATION AND GRANULARITY OF LEGAL NORMS IN THE DATA ECONOMY:
A TRANSATLANTIC DEBATE (BUSCH/DC FRANCESCLII) '
PART 1
THE CONCEPT OF PERSONALIZED LAW
A. PERSONALIZING DEFAULT RULES AND DISCLOSURE WITH BIG DATA
(POMT/SLRAHILCVITZ) 5
I. INTRODUCTION 5
II. THEORIES OF PERSONALIZED DEFAULT RULES
9
1. CONTRACT LAW DEFAULT RULES
1()
2. MAJORITARIAN DEFAULT RULES ''
A) IN GENERAL 11
B) PERSONALIZED MAJORITARIAN DEFAULT RULES
L2
3. MINORITARIAN (OR PENALTY) DEFAULT RULES
L3
A) IN GENERAL 13
B) MINORITARIAN DEFAULT RULES AS FACILITATORS OF PERSONALIZED DEFAULT
RULES IS
4. THIRD-PARTY EFFECTS
1(
I
III. THE FEASIBILITY OF PERSONALIZED DEFAULT RULES
17
1. BIG DATA AND BIG FIVE "ZZZZZ'Z
18
2. BIG DATA IN THE LAW 23
A) CONSUMER CONTRACTS 23
B) ORGAN DONATION 24
C) MEDICAL MALPRACTICE 26
D) LANDLORD-TENANT LAW 28
E) LABOR LAW ZZZZZZZ'Z'Z
2Y
3. BIG DATA GUINEA PIGS 30
IV. POSSIBLE OBJECTIONS AND LIMITATIONS
32
1. CROSS SUBSIDIES 33
2. STRATEGIC BEHAVIOR 34
3. ABUSE BY MERCHANTS 35
4. UNCERTAINTY 36
5. CASE LAW FRAGMENTATION 38
6. STATISTICS, STEREOTYPING, AND VALUABLE DEFAULT RULES
39
7. SUBORDINATION, ADAPTIVE PREFERENCES, AND PERSONALIZATION '"
8. PRIVACY 44
9. "BUT 1 CAN CHANGE!" AND OPTING IN
4(T
V. PERSONALIZED DISCLOSURE "J7
VI. CONCLUSION 51
I!. PERSONALIZING NEGLIGENCE LAW (IKN-SHAHAR/PORAT)
5T
I. INTRODUCTION 54
II. PERSONALIZED NEGLIGENCE UNDER EXISTING LAW 60
1. DIMINISHED CAPACITY 61
A) PHYSICALLY DISABLED 61
B) CHILDREN 61
C) MENTALLY DISABLED 62
2. KLEVATED CAPACITY 63
3. RESOURCE-BASED PERSONALIZATION 64
TABLE OF CONTENTS
4. PERSONALIZATION THROUGH INSURANCE? 65
5. SUMMARY 66
III. THE EFFICIENCY OF PERSONALIZED STANDARDS 67
1. LEVELS OF CARE 67
A) SKILL-BASED PERSONALIZATION 67
B) RISK-BASED PERSONALIZATION 69
C) SELF-PERSONALIZATION 71
D) SUMMARY 73
2. LEVELS OF ACTIVITY 74
A) IMPROVING OR DISTORTING LEVELS OF ACTIVITY 74
B) ACTIVITY LEVELS WITH SELF-PERSONALIZATION 75
C) A HYBRID REGIME 76
3. VICTIM CARE 76
A) SKILL-BASED PERSONALIZATION 77
B) RISK-BASED PERSONALIZATION 78
4. EX ANTE INVESTMENT IN IMPROVING PRIVATE CHARACTERISTICS 78
A) SKILL-BASED PERSONALIZATION 79
AA) PERSONALIZED STANDARDS 79
BB) UNIFORM STANDARDS WITH FULL COMPLIANCE 79
B) RISK-BASED PERSONALIZATION 80
AA) PERSONALIZED STANDARDS 80
BB) UNIFORM STANDARDS WITH FULL COMPLIANCE 81
5. SUMMARY 82
IV. JUSTICE CONSIDERATIONS 83
1. CORRECTIVE JUSTICE 83
2. DISTRIBUTIVE JUSTICE 84
A) AMONG INJURERS 85
B) VICTIMS VERSUS INJURERS 86
V. BROADENING PERSONALIZATION 87
1. PROCEDURES FOR IMPLEMENTING PERSONALIZED STANDARDS 88
A) GRADUAL PERSONALIZATION 89
B) PRESUMPTIONS 89
2. WHICH PERSONAL INFORMATION? 90
A) PHYSICAL CHARACTERISTICS 91
B) COGNITIVE AND EMOTIONAL CHARACTERISTICS 91
C) PAST BEHAVIORS 94
D) RESOURCES 95
VI. CONCLUSION 95
C. THE DEATH OF RULES AND STANDARDS (CNSCY/NIBKTT) 98
I. INTRODUCTION 98
II. THE EMERGENCE OF MICRODIRECTIVES AND THE DECLINE OF RULES AND
STANDARDS 102
1. BACKGROUND: RULES AND STANDARDS 102
2. TECHNOLOGY WILL FACILITATE THE EMERGENCE OF MICRODIRECTIVES AS A NEW
FORM OF LAW 103
A) PREDICTIVE TECHNOLOGY 103
B) COMMUNICATION TECHNOLOGY 104
C) SUMMARY 104
3. EXAMPLES 105
A) PREDICTIVE TECHNOLOGY IN MEDICAL DIAGNOSIS 105
B) COMMUNICATION TECHNOLOGY IN TRAFFIC LAWS 108
4. THE DIFFERENT CHANNELS LEADING TO THE DEATH OF RULES AND STANDARDS
109
A) THE PRODUCTION OF MICRODIRECTIVES BY NONLCGISLATIVE LAWMAKERS 109
AA) REGULATORY MICRODIRECTIVES 109
BB) JUDICIAL MICRODIRECTIVES 110
B) AN ALTERNATIVE PATH: PRIVATE USE OF TECHNOLOGY BY REGULATED ACTORS
111
III. CONCLUSION 112
VI
TABLE OF CONTENTS
PART 2
CRITIQUE AND THEORETICAL PERSPECTIVES
I). THE LAW BETWEEN GENERALITY AND PARTICULARITY. CHANCES AND LIMITS OF
PERSONALIZED LAW
(GRIGOLEIT/BEMKR) 115
I. INTRODUCTION 115
II. DISTINCTIONS AND NOTIONAL SPECIFICATIONS 116
1. TECHNOLOGY-RELATED SPECIFICATIONS 116
A) TECHNOLOGICAL VS. CONVENTIONAL 117
B) RULE-ELABORATION (BIG DATA) VS. RULE-COMMUNICATION (BIG LINK) 118
2. LAW-RELATED SPECIFICATIONS 118
A) FACTUAL-PRIVATE VS. LEGAL-PUBLIC 119
B) RULES VS. STANDARDS 120
C) EVOLUTION (CHANGES WITHIN THE SYSTEM) VS. REVOLUTION (CHANGES OF THE
SYSTEM) 121
III. EVOLUTIONARY PERSPECTIVES 121
1. TORTS: THE REASONABLE STANDARD OF CARE '22
A) LIMITS OF PERSONALIZATION OF STANDARDS 122
B) EX POST-RULE-PERSONALIZALION 122
C) EX ANLE-RULE-PERSONALIZATION 124
2. CONTRACTS 125
A) DEFAULT RULES ZZ"I'ZZZIZZZZZZZZZZIZZZZ"ZZ'. 125
AA) THEORETICAL OBJECTIONS TO THE PURELY EMPIRICAL APPROACH TO DEFAULT
RULES 126
BB) CONSTITUTIONAL LIMITS: EQUALITY AND FREEDOM 127
B) DISCLOSURE RULES 130
IV. REVOLUTIONARY PERSPECTIVES 131
1. THE DIGITAL REVOLUTION AS A FACTUAL PHENOMENON 131
A) GENERALIZING THE FIELD-SPECIFIC APPROACH 131
B) ESPECIALLY: DEALING WITH PROBABILITIES 131
2. LIMITATIONS TO CHANGES OF THE VERY STRUCTURE OF THE LEGAL SYSTEM 132
A) LEGITIMACY-RELATED CONCERNS WITH REGARD TO ALGORITHMIZATION 132
B) CONSTITUTIONAL CONCERNS WITH REGARD TO PERSONALIZATION 133
AA) SEPARATION OF POWERS: POSSIBLE POWER SHIFTS AWAY FROM THE PARLIAMENT
AND THE JUDICIARY 133
BB) DEMOCRACY: DISSOLUTION OF PUBLICITY 1M
CC) EQUALITY: DISCRIMINATION AND DISSOLUTION 135
V. CONCLUSIONS 136
E. GRANULAR NORMS AND THE CONCEPT OF LAW: A CRITIQUE (AUCR) 137
I. THE INEVITABILITY OF LEGAL TYPIFICATION 138
II. THE PROBLEM OF ALGORITHMIC DISCRIMINATION I
42
III. THE SCOPE OF GRANULAR LAW AND THE RISE OF CONSUMERISM 145
IV. REGULATION AND THE RULE OF LAW 149
V. GRANULARIZATION AND THE PROBLEM OF RULE-FOLLOWING I
51
F. LOGOPOEIA: NORMATIVE TYPIFICATION AND GRANULAR NORM'S INFORMATIONAL
DIFFERENTIATION
(FEMIA) 155
I. MORE ACTS OR MORE WORDS: NEGOTIA, PRAGMATA, ACTIVITIES I
55
II. TWO WAYS OF GRASPING REALITY: TAMING THE CHAOS WITH EMILIO BETTI AND
TULLIO ASCARELLI. 157
III. END OF THE JOURNEY AMONG THE CONCEPTS' PENUMBRA. FROM TYPE TO
TYPIFICATION,
AND FROM TYPIFICATION TO DISSEMINATION
160
IV. BIG DATA: QUANTITIES MAKE A QUALITATIVE SHIFT IN NOMOGENESIS 161
V. NOMOGENESIS AT THE INTERSECTION POINT BETWEEN NORMATIVE TECHNIQUE AND
INFORMATIONAL
LIMIT 163
VI. THE LOSS OF INFORMATIONAL INNOCENCE '64
VII. NORMS ON THE MOVE 165
VIII. LES COMMUNICATIONS & LES COMMERCES 166
IX. POLITICS OR ALGORITHMICS 170
VII
TABLE OF CONTENTS
! ERAL AND SOCIALIST PERSPECTIVES
172
G. "GRANULARIZATION" AND CROSS-SUBSIDIES-I IHPNL IW 11 *
(DCNOZZC/MAUGERI) NCOHBERAL AND SOCIALIST PERSPECTIVES
I. GRANULARIZATION: A CONSISTENT OUTCOME'OF A NEOHBERAL 'TREND \N
M * _ *
IZED" RULES 177
,
SLLBSIDY
-
JIT
Y
IN
NEOHBERAL IHOU^TZIIIZ 179
VI. WHAT'S WRONG, IF ANYTHING, WITH CR
(
,SS'-SUBSIDY?;II;I;;;;;;;; [J?
I. **
PART 3
I ERSONALUATION IN CONTRACT, CONSUMER AND TORT LAW
H
-
G
*
NLLLA
Y LEGAL NORMS' IN THE FINANCIAL I
"' ^
18
;
OF FINANCIAL SERVICES
1. THE KNOW-YOUR-CUSTOMER RULE IN INVESTMCNT"S"E^IC \L\
2. THE KNOW-YOUR-CUSTOMER RULE IN INSURANCE SERVICES \LL
3. THE KNOW-YOUR-CUSTOMCR RULE IN CREDIT BANKING O
V. SOME DUAL REMARKS
H
198
I. DE- OR RC-TYPIFLCATION THROUGLI BI
K
DATA ANILVTIRC? TI ^
(MICKLITZ)
FC ANA
'YT'CS? THE CASE OF CONSUMER LAW
I. CLARIFICATION AND ARGUMENT
203
II. FROM TYPIFICATION TO GRANULARIZATION PRIOR TO "N'IA'N ", A""V
203
1. CONSUMER IMAGES
P 8 DATA
ANALYTICS 206
2. CONSUMER LAW 2.0 206
3. CONTRACTUAL UNDERWORLD
20(
'
4. CONSUMERIZATION OF CONSUMER LAW
207
2. BIG DATA ANALYTICS 209
IV. BIG DATA ANALYTICS IN LAW MAKMG^D UWLNFOREEMCNT
EVL BD LI H
Y AKMG^D UWLNFOREEMCNT 2P
. EVULENCE BASED POLICY THROUGH BIG DATA ANALYTICS ILL
2. SHORTCOMINGS OF STATISTICS
213
V. PROSPECTS FOR BIG DATA ANALYTICS IN'CONSUMER LAW LIT
1. INFORMATION RIGHTS AND OBLIGATIONS
2. REDUCING THE COMPLEXITY OF INFORMATION'LHROU^B^D^'^IC'; 2,7
3. COMPLEXITIES OF CONSUMER LAW ENFORCEMENT ANALYTICS 217
Z
II. THE SETTING WITHIN THE EUROPEAN CONTEXT"!"!"
221
1. THE THEORETICAL FRAMEWORK
222
2. THE EUROPEAN METHODOLOGY
222
A) THE SCOPE OF APPLICATION OF THE JUDICIAL CONTROL ILL
B) THE UNFAIRNESS TEST
C) THE CONSEQUENCES OF UNFAIRNESS
VIII
TABLE OF CONTENTS
K. PERSONALIZATION OF TORT LAW? (VON BAR) 236
PART 4
TECHNOLOGICAL AND BEHAVIORAL PERSPECTIVES
L. PERSONALIZED LAW AND THE BEHAVIORAL SCIENCES (HACKER) 241
I. A VERY SHORT INTRODUCTION TO BEHAVIORAL LAW AND ECONOMICS 242
1. BEHAVIORAL ECONOMICS 242
2. LEGAL APPLICATIONS 243
II. THE KNOWLEDGE PROBLEM IN BEHAVIORAL LAW AND ECONOMICS 244
1. UNCERTAINTY ABOUT THE TRUE RATIONALITY OF MARKET ACTORS 244
2. PSYCHOMETRICS AND THE QUANTIFICATION OF BIAS
245
3. PERSONALIZED LAW AS A SOLUTION TO THE KNOWLEDGE PROBLEM 2-16
III. EXAMPLES OF PERSONALIZED BEHAVIORAL LAW
247
1. DISCLOSURES 247
A) GENERAL IDEA 247
B) CONCRETE EXAMPLES 248
A) CONSUMER DISCLOSURES: PERSONALIZING THE CONSUMER RIGHTS DIRECTIVE 248
B) FINANCIAL DISCLOSURES: PERSONALIZING MIL'ID II ~
49
2. DEFAULT RULES 250
A) GENERAL IDEA ZZZZZZZZ"ZZZ!ZZZZZZZ"!!
2S()
B) CONCRETE EXAMPLES 251
3. MANDATORY LAW 252
A) GENERAL IDEA 252
B) CONCRETE EXAMPLES 252
AA) PERSONALIZING UNFAIR COMMERCIAL PRACTICES UNDER THE UCI'D 253
BB) THE BENEFITS OF PERSONALIZATION 257
IV. THE LIMITS OF PERSONALIZED BEHAVIORAL LAW 258
1. THE STRENGTH OF EMPIRICAL CORRELATIONS 258
2. ALGORITHMIC BIAS AND DISCRIMINATION 259
V. GOOD GOVERNANCE OF PERSONALIZED BEHAVIORAL LAW 261
1. PRIVACY RESPECTING METRICS 261
2. OVERSIGHT AND ALGORITHMIC AUDITING 262
VI. CONCLUSION 263
M. "SMART CONTRACT", "GRANULAR NORMS" AND
NON-LYISCRIMMATION(ZCNO-ZCNCOVICLT) 264
I. ONLY WORDS 264
II. HOW "SMART" CAN CONTRACTS BE? 268
III. CREDITWORTHINESS 271
IV. "GRANULAR NORMS" 275
V. NON-DISCRIMINATION IN THE AGE OF BIG DATA 278
N. ALGORITHMIC REGULATION AND (IM)PCRFECT ENFORCEMENT IN THE
PERSONALIZED ECONOMY
(LIUSCH) 279
I. INTRODUCTION 279
II. BIG DATA AND THE CRISIS OF GENERALITIES
28()
III. MAKING LAWS FOR THE PERSONALIZED ECONOMY
281
1. GRANULAR LEGAL NORMS: THE DEMISE OF TYPIFICATIONS?
2T!1
2. USE CASES OF PERSONALIZED LAW 282
A) PERSONALIZED DISCLOSURES ON DIGITAL MARKETPLACES
283
B) DE-BIASING CUSTOMER RATINGS IN THE SHARING ECONOMY
283
C) PERSONALIZED TRAFFIC RULES IN THE SMART CITY
285
3. FIGHTING FIRE WITH FIRE: ADVERSE TARGETING MEETS PERSONALIZED LAW 286
IV. GOVERNANCE OF ALGORITHMS FOR PERSONALIZED LAW
2S8
1. PERSONALIZED LAW AS ALGORITHMIC REGULATION
288
2. PRIVACY AND CHOICE 289
3. QUALITY OF DATA AND MODELS 290
4. COMPLIANCE MONITORING AND ALGORITHMIC AUDITING
29()
V. CONCLUSION 291
IX |
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Beck</subfield><subfield code="c">2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Oxford</subfield><subfield code="b">Hart</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Baden-Baden</subfield><subfield code="b">Nomos</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XIII, 292 Seiten</subfield><subfield code="c">24 cm x 16 cm</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="500" ind1=" " ind2=" "><subfield code="a">Auch angekündigt unter dem Titel: "Data economy and algorithmic regulation."</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Personalisierung</subfield><subfield code="0">(DE-588)4384600-2</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="650" ind1="0" ind2="7"><subfield code="a">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Regulierung</subfield><subfield code="0">(DE-588)4201190-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Algorithmische Programmiersprache</subfield><subfield code="0">(DE-588)4141876-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Legal Tech</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Datenschutzrecht</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Artificial Intelligence</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">Big Data</subfield><subfield code="0">(DE-588)4802620-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><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="2"><subfield code="a">Algorithmische Programmiersprache</subfield><subfield code="0">(DE-588)4141876-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Regulierung</subfield><subfield code="0">(DE-588)4201190-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="4"><subfield code="a">Personalisierung</subfield><subfield code="0">(DE-588)4384600-2</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">Busch, Christoph</subfield><subfield code="d">1975-</subfield><subfield code="0">(DE-588)135876656</subfield><subfield code="4">edt</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">De Franceschi, Alberto</subfield><subfield code="d">1978-</subfield><subfield code="0">(DE-588)1114427403</subfield><subfield code="4">edt</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">Verlag C.H. 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| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV045944507 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-11T15:09:19Z |
| institution | BVB |
| institution_GND | (DE-588)1023902869 |
| isbn | 9783406743917 3406743919 9783848769209 9781509931750 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031326699 |
| oclc_num | 1226705893 |
| open_access_boolean | |
| owner | DE-M382 DE-703 DE-29 DE-739 DE-355 DE-BY-UBR DE-1051 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-12 DE-188 DE-11 DE-384 |
| owner_facet | DE-M382 DE-703 DE-29 DE-739 DE-355 DE-BY-UBR DE-1051 DE-19 DE-BY-UBM DE-91 DE-BY-TUM DE-12 DE-188 DE-11 DE-384 |
| physical | XIII, 292 Seiten 24 cm x 16 cm |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | C.H. Beck Hart Nomos |
| record_format | marc |
| spellingShingle | Busch, Christoph 1975- Algorithmic regulation and personalized law a handbook Personalisierung (DE-588)4384600-2 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Big Data (DE-588)4802620-7 gnd Regulierung (DE-588)4201190-5 gnd Algorithmische Programmiersprache (DE-588)4141876-1 gnd |
| subject_GND | (DE-588)4384600-2 (DE-588)4033447-8 (DE-588)4802620-7 (DE-588)4201190-5 (DE-588)4141876-1 (DE-588)4143413-4 |
| title | Algorithmic regulation and personalized law a handbook |
| title_auth | Algorithmic regulation and personalized law a handbook |
| title_exact_search | Algorithmic regulation and personalized law a handbook |
| title_full | Algorithmic regulation and personalized law a handbook edited by Christoph Busch, Alberto De Franceschi |
| title_fullStr | Algorithmic regulation and personalized law a handbook edited by Christoph Busch, Alberto De Franceschi |
| title_full_unstemmed | Algorithmic regulation and personalized law a handbook edited by Christoph Busch, Alberto De Franceschi |
| title_short | Algorithmic regulation and personalized law |
| title_sort | algorithmic regulation and personalized law a handbook |
| title_sub | a handbook |
| topic | Personalisierung (DE-588)4384600-2 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Big Data (DE-588)4802620-7 gnd Regulierung (DE-588)4201190-5 gnd Algorithmische Programmiersprache (DE-588)4141876-1 gnd |
| topic_facet | Personalisierung Künstliche Intelligenz Big Data Regulierung Algorithmische Programmiersprache Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031326699&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT buschchristoph algorithmicregulationandpersonalizedlawahandbook AT defranceschialberto algorithmicregulationandpersonalizedlawahandbook AT verlagchbeck algorithmicregulationandpersonalizedlawahandbook |
Inhaltsverzeichnis
Paper/Kapitel scannen lassen
Paper/Kapitel scannen lassen
Handapparate (nicht verfügbar)
| Signatur: |
0041 JUR 037 2021 A 908
Lageplan |
|---|---|
| Exemplar 1 | Dauerhaft ausgeliehen Ausgeliehen – Rückgabe bis: 31.12.9999 |