Transforming Legal Rules into Online Virtual World Rules: A Case Study in the VirtualLife Platform

Transcription

1 Transforming Legal Rules into Online Virtual World Rules: A Case Study in the VirtualLife Platform Vytautas ČYRAS Vilnius University, Lithuania vytautas.cyras@mif.vu.lt 1

2 Virtual Worlds Serious, e.g. Second Life, Active Worlds Educational Universe Not games e.g. World of Warcraft I am neither a proponent nor opponent of them Consider negative factors such as addiction Research & software development project FP7 ICT VirtualLife project, 3 years from Title Secure, Trusted and Legally Ruled Collaboration Environment in Virtual Life. Acronym VirtualLife Goal: software platform peer to peer architecture Learning support as a use scenario, e.g. University Virtual Campus 2

3 About FP7 VirtualLife project Objective to create a safe, democratic and legally ruled 3D collaboration environment Novelties issues of security and trust in world legal framework a Supreme Constitution, a Virtual Nation Constitution, a set of contracts peer to peer network communication architecture 3

4 Legal framework of VirtualLife Three tiers: 1. A Supreme Constitution Code of Conduct values that the user has to respect, e.g. avatars integrity, sanctity of property, reputation, etc. A part of EULA (End User License Agreement) 2. A Virtual Nation Constitution authentication procedure to become a member of Nation copyright law of Nation, e.g. CopyLeft or CopyRight 3. A set of different sample contracts sales contract teacher employment contract student contract 4

5 Learning needs of digital natives Pro and contra arguments for virtual worlds Students of today are active Web 2.0 participants easy create relationships in social networks like impressing peers with curious facts enjoy participating in online group activities function in multitasking mode a new phenomenon: they share the knowledge with unknown people do not like memorizing information for later use but they are effective in searching 5

6 Sample scenarios Web 2.0 information as a content asynchronous communication University Virtual Campus interaction as a content synchronous communication 6

7 Motivation of learning Pro virtual worlds Learning materials in Web 2.0 are static, searchable in 2D for learner s queries In 3D virtual worlds interactive objects Contra virtual worlds values? mono sensorial, perceived through computer s display multi sensorial learning in the real world human s brain and spinal brain function concurrently all senses: seeing, hearing, touching, etc. learning by doing when accomplishing real world tasks 7

8 Learning environment Constantly gratifying, encouraging social interaction 8

9 From legal rules to virtual world rules Keep off the grass to rules in software Translation Natural intelligence a team of (a) a legal expert, and (b) virtual world developer The subject avatar is forbidden the action walking on the grass Translation Natural intelligence a programmer A software program, i.e. a script. Implemented by trigers which control the avatar This translation complies with: Lawrence Lessig s conception Code is law Raph Koster s Declaration of the Rights of s 9 9

10 Examples of rules 1. An avatar is forbidden to touch objects not owned by him or a certain group. 2. An avatar not belonging to a given group is forbidden to a given area of the zone. 3. An avatar is forbidden to create more than a given number of objects during a given time interval. 4. An avatar is forbidden to use a given dictionary of words (slang) while chatting with other avatars. 5. An avatar of age is forbidden to chat with avatars under age. 6. An avatar is forbidden to execute authorized scripts in a certain area. 10

11 The editor of rules A law is composed of Norms, see (Vázquez Salceda et al. 2008). Norm is composed by: (1) NORM_CONDITION, (2) VIOLATION_CONDITION, (3) DETECTION_MECHANISM, (4) SANCTION (5) REPAIR. NORM_CONDITION is expressed by: TYPE {Obliged, Permitted, Forbidden} SUBJECT {, Zone, Nation} ACTION {ENTER, LEAVE, CREATE, MODIFY, MOVE, CREATE, TRADE, SELL, BUY, CHAT, etc.} COMPLEMENT {AREA, AVATAR, OBJECT, etc.} IF {logical_expresssion_using_subjects_properties} 11

12 Norm example (1) Norm condition: FORBIDDEN Student_ ENTER Library IF Student_.age < 18 (2) Violation condition: NOT over_age(student_) AND admit(student_, Library) (3) Detection mechanism: call over_age(student_) when Student_ enters Library (4) Sanction: decrease_reputation(student_); notify avatar (5) Repair: log and roll back if applicable 12

13 Facing the problems of translation Abstractness of norms. Legal rules are formulated abstractly. Open texture. Hart s example of Vehicles are forbidden in the park. Legal interpretation methods. The meaning of a legal text cannot be extracted from the sole text. grammatical interpretation systemic interpretation teleological interpretation Legal teleology. The purpose of a legal rule usually can be achieved by a variety of actions. Heuristics. The ability to translate abstract high level concepts and invent low level ones. Consciousness of the society. Law enforcement is a complex social phenomenon. 13

14 F. Lachmayer s spatialization Virtual space. Frame: constitutive. ~ Theatre Stage Actions 14

15 F. Lachmayer s spatialization Rules 1. Technical. Factual limitations, e.g. to fence the grass. Virtual space. Frame: constitutive. ~ Theatre Regimes, paradigms, ethics, professional morality Stage Actions 15

16 F. Lachmayer s spatialization Virtual space. Frame: constitutive. ~ Theatre Regimes, paradigms, ethics, professional morality Rules 1. Technical. Factual limitations, e.g. to fence the grass. Rules 2. Legal. Obligations, permissions, prohibitions, veto. Primary rules. Sanction is a secondary rule Stage Actions Office. Virtual procedures. E.g. online dispute resolution 16

17 F. Lachmayer s spatialization Virtual space. Frame: constitutive. ~ Theatre Regimes, paradigms, ethics, professional morality Rules 1. Technical. Factual limitations, e.g. to fence the grass. Rules 2. Legal. Obligations, permissions, prohibitions, veto. Primary rules. Sanction is a secondary rule Stage Rules 3. Reputation. Economic, social, civic. Rules n. Energy. Office. Virtual procedures. E.g. online dispute resolution Actions 17

18 Principles of construction (1) Core ontology Special ontology 1 Special ontology 2 Special ontology 3 Special ontology n Rules 1. Technical Rules 2. Legal Rules 3. Reputation Rules n. Energy 18

19 Principles of construction (2) Core ontology Special ontology 1 Special ontology 2 Special ontology 3 Special ontology n Rules 1. Technical Rules 2. Legal Rules 3. Reputation Rules n. Energy Different modes of effectiveness (Wirkung) or relevance Barrier. Strict Occasional. Probability p% Step by step. Entering without STOP is REFUSED Policeman fines for stepping the grass. This happens with p% probability if you do not succeed. Reputation/energy is decreased by 10 points 19

20 Example of a technical rule E law project, Austria if document.xml_format = OK then put_on_legislative_workflow ( document ) Running sushi transport belt Legislative workflow in Austria 20

21 Terminology: factual and technical rules? Factual rules Technical rules Natural rules Door is closed Room if door = closed then factual_hindrance if no XXXX_pin_code_to_cash_machine then no access_to_money Natural rules Natural law (Naturrecht) e.g. gravitation force Natural image or essence of man??? behavior 21

22 3 legal stages 1. Legislative stage Community Produce Rules 2. Stage of the game everyday life Negotiations, storytelling (see H. Prakken) 3. Judicial stage % Judgement 22

23 2 legislative substages 2. Stage of the game People think in roles, not rules Citizen, ticket Having meals Stage of access enter airport Passenger 23

24 2 legislative substages 1a. Legislative rules General rules e.g. 1b. Contract rules Individual rules Buyer Seller 2. Stage of the game inter partes People think in roles, not rules Citizen, ticket Having meals Stage of access enter airport Passenger 24

25 Technical rules Causation is formalized with the modus ponens rule. Example. no_code & (no_code no_money) no_money (1) Rule(P Q) (2) Fact(P) Conclusion. Fact(Q) Modus ponens rule in mathematical logic: If P, then Q. P. Therefore Q. Sequent notation: P Q, P Q P Q, P Lachmayer s notation: P Q & P Q Rule form: Q In some domains the following interpretation of the technical rule is aimed: (1) Rule(P Q) Obtained inference Fact( P) Fact( Q) and rule (2) Fact( P) (2) imply equivalence of P and Q, formally, P Q. Conclusion. Fact( Q) Denoted also P~Q. This is good for cash machine (ATM). But this may be unacceptable for other technical domains, see rule based knowledge representation. 25

26 Legal rules (1) Permission(P iff Q) Norm( P Q) Example. green if_and_only_if cross ( red do_not_cross ) (2) Fact( P) red is on (3) Fact(Q) you cross the street, nevertheless Interpretation. You are simply a bad guy. Nobody can stop you crossing. Notes: Here P denotes green, Q denotes cross, P denotes red. With probability p% a punishment procedure is exercised. This is done, for example, by a policeman. P iff Q is also denoted P Q 26

27 A n A Reputation/energy rules (1) Norm( A) (2) Fact(A) Conclusion. Energy reduction by 10% Formalization: Norm( A), A A := 0.9*A Energy is reduced to A 1, then A 2 and so on to A n. And at last A. A A 1 A 2 27

28 Thank you Acknowledgements: The whole VirtualLife consortium, 9 partner organisations virtuallife.eu 28