law of robots and ais - lecture 1 - state of the art: technology

Introduction to the Law of Robots and Introduction to the Law of Robots and Introduction to the Law of Robots and Introduction to the Law of Robots and ArtificialArtificialArtificialArtificial IntelligencesIntelligencesIntelligencesIntelligences

Prof. Nicolas Petit ©Prof. Nicolas Petit ©Prof. Nicolas Petit ©Prof. Nicolas Petit ©

UniversityUniversityUniversityUniversity of of of of LiegeLiegeLiegeLiege, 2015, 2015, 2015, 2015----2016201620162016

Context

www.lcii.euwww.lcii.euwww.lcii.euwww.lcii.eu

Google’s Self-Driving-System “SDS”

� “Google seeks to produce a vehicle that contains L4 automated driving capabilities, and removes conventional driver controls and interfaces (like a steering wheel, throttle pedal, and brake pedal, among many other things)”.

� “Expresses concern that providing human occupants of the vehicle with mechanisms to control things like steering, acceleration, braking, or turn signals, or providing human occupants with information about vehicle operation controlled entirely by the SDS, could be detrimental to safety because the human occupants could attempt to override the SDS’s decisions”

� “Google’s design choices in its proposed approach to the SDV raise a number of novel issues in applying the FMVSSs. Those standards were drafted at a time when it was reasonable to assume that all motor vehicles would have a steering wheel, accelerator pedal, and brake pedal, almost always located at the front left seating position, and that all vehicles would be operated by a human driver. Accordingly, many of the FMVSSs require that a vehicle device or basic feature be located at or near the driver or the driver’s seating position. For vehicles with an AI driver that also preclude any occupant from assuming the driving task, these assumptions about a human driver and vehicle controls do not hold”.

� “Google has asked who or what is to be considered the driver and which seating position is considered to be the driver’s seating position in its SDV.”


NHTSA letter, 4 February 2016

� National Highway Traffic Safety Administration (NHTSA) is US Highway

Safety Agency in charge of enforcing the Federal Motor Vehicle Safety

Standards (FMVSSs)

� Provides certification for new vehicles by automotive producers

� Number of FMVSSs requirements

� All buit around the notion of “driver”, and “driver’s position” or “driver’s

seating position”

� “MVSS No. 101 contains requirements for location, identification, color, and illumination of motor vehicle controls, telltales, and indicators. S5.1.1 requires the controls listed in Tables 1 and 2 of the standard to be located so that they are operable by the [belted] driver”.

� “S5.3.1, which states that service brakes shall be activated by means of a foot control”

� 49 CFR 571.3 defines “driver” as the occupant of a motor vehicle seated

immediately behind the steering control system.


A Car has a Driver, a Driver need not be

human

OptionsOptionsOptionsOptions

� 1) “NHTSA could interpret the term “driver” as meaningless for purposes of Google’s SDV, since there is no human driver, and consider FMVSS provisions that refer to a driver as simply inapplicable to Google’s vehicle design”;

� 2) “NHTSA could interpret “driver” and “operator” as referring to the SDS”

NHTSANHTSANHTSANHTSA

� As a foundational starting point for the interpretations below, NHTSA will interpret driver in the context of Google’s described motor vehicle design as referring to the SDS, and not to any of the vehicle occupants.

� If no human occupant of the vehicle can actually drive the vehicle, it is more reasonable to identify the driver as whatever(as opposed to whoever) is doing the driving. In this instance, an item of motor vehicle equipment, the SDS, is actually driving the vehicle.


Consequences

� “The controls listed in Tables 1 and 2 may simply be operable by the SDS and need not be located so that they are available to any of the human occupants of the motor vehicle”.

� For more, see

� http://isearch.nhtsa.gov/files/Google%20--

%20compiled%20response%20to%2012%20Nov%20%201

5%20interp%20request%20--

%204%20Feb%2016%20final.htm

� http://spectrum.ieee.org/cars-that-

think/transportation/self-driving/an-ai-can-legally-be-

defined-as-a-cars-driver


TopicTopicTopicTopic DateDateDateDate

State of the Art: Technology 17 February 2016

Prospects for Society, and the Substitution Effect 24 February 2016

Should we regulate? 2 March 2016

How to regulate (1)? 16 March 2016

How to regulate (2)? 20 April 2016

How to regulate (3)? 27 April 2016

How to regulate (4)? 4 May 2016


Purpose of the course

TwoTwoTwoTwo questionsquestionsquestionsquestions

� ShouldShouldShouldShould wewewewe regulateregulateregulateregulate AIsAIsAIsAIs and and and and

robots?robots?robots?robots?

� If If If If yesyesyesyes, how , how , how , how shouldshouldshouldshould wewewewe regulateregulateregulateregulate

AIsAIsAIsAIs and robots?and robots?and robots?and robots?

MethodMethodMethodMethod

� ProvideProvideProvideProvide a a a a frameworkframeworkframeworkframework to to to to addressaddressaddressaddress

thosethosethosethose issuesissuesissuesissues

� MethodologyMethodologyMethodologyMethodology: Jan : Jan : Jan : Jan SmitsSmitsSmitsSmits, Law and , Law and , Law and , Law and

InterdisciplinaryInterdisciplinaryInterdisciplinaryInterdisciplinary StudiesStudiesStudiesStudies, 2014: , 2014: , 2014: , 2014:

«««« whatwhatwhatwhat the the the the lawlawlawlaw oughtoughtoughtought to to to to bebebebe ».».».».

� TransdisciplinaryTransdisciplinaryTransdisciplinaryTransdisciplinary

� Criminal law

� Liability law

� Product safety law

� Intellectual property

� Human rights

� European law

� …

Part I – State of the Art: Technology


2015, the year of the robot (Wired UK)

SeeSeeSeeSee http://www.wired.co.uk/magazine/archive/2015/06/wiredhttp://www.wired.co.uk/magazine/archive/2015/06/wiredhttp://www.wired.co.uk/magazine/archive/2015/06/wiredhttp://www.wired.co.uk/magazine/archive/2015/06/wired----worldworldworldworld----2015/the2015/the2015/the2015/the----yearyearyearyear----ofofofof----thethethethe----robotrobotrobotrobot


Examples

� RoboticRoboticRoboticRobotic carscarscarscars

� Drones Drones Drones Drones

� HiveHiveHiveHive and and and and swarmswarmswarmswarm robotsrobotsrobotsrobots


An old field, AI and robotics

� 1950s: «1950s: «1950s: «1950s: « Game AIGame AIGame AIGame AI », Arthur », Arthur », Arthur », Arthur Samuel’sSamuel’sSamuel’sSamuel’s checkercheckercheckerchecker----playingplayingplayingplaying programprogramprogramprogram

� 1954: Turing test 1954: Turing test 1954: Turing test 1954: Turing test

� 1955: 1955: 1955: 1955: NewellNewellNewellNewell and Simon, and Simon, and Simon, and Simon, «««« LogicLogicLogicLogic TheoristTheoristTheoristTheorist », », », », provesprovesprovesproves 38 out of 52 38 out of 52 38 out of 52 38 out of 52

mathematicalmathematicalmathematicalmathematical problemsproblemsproblemsproblems

� Dartmouth Summer Research Project of 1956Dartmouth Summer Research Project of 1956Dartmouth Summer Research Project of 1956Dartmouth Summer Research Project of 1956


Core ideas

� AnyAnyAnyAny physicalphysicalphysicalphysical processprocessprocessprocess includingincludingincludingincluding the the the the mindmindmindmind processprocessprocessprocess cancancancan bebebebemodelizedmodelizedmodelizedmodelized as a computable as a computable as a computable as a computable algorithmalgorithmalgorithmalgorithm (Church Turing (Church Turing (Church Turing (Church Turing thesisthesisthesisthesis))))

� A software A software A software A software isisisis a set of computable a set of computable a set of computable a set of computable algorithmsalgorithmsalgorithmsalgorithms. No . No . No . No reasonreasonreasonreason whywhywhywhy itititit couldcouldcouldcould not not not not reachreachreachreach outcomesoutcomesoutcomesoutcomes similarsimilarsimilarsimilar to to to to thosethosethosethose generatedgeneratedgeneratedgenerated by the by the by the by the mindmindmindmind (artefact)(artefact)(artefact)(artefact)

� Machines can learn: “Machines can learn: “Machines can learn: “Machines can learn: “Learning Learning Learning Learning is any process by which is any process by which is any process by which is any process by which a system improves performance from experiencea system improves performance from experiencea system improves performance from experiencea system improves performance from experience”, ”, ”, ”, Herbert Simon Herbert Simon Herbert Simon Herbert Simon

� UltimateUltimateUltimateUltimate ambition ambition ambition ambition isisisis to have computers do to have computers do to have computers do to have computers do whatwhatwhatwhathumanshumanshumanshumans do do do do wellwellwellwell ((((theytheytheythey alreadyalreadyalreadyalready know how to do know how to do know how to do know how to do thingsthingsthingsthingshumanshumanshumanshumans cannotcannotcannotcannot do): do): do): do): heuristicheuristicheuristicheuristic, , , , seeingseeingseeingseeing, , , , learninglearninglearninglearning


Milestones

� In 1997, DeepBlue beats Gary Kasparov on chess

� In 2005, Stanford robot wins DARPA Grand Challenge by driving autonomously for 131 miles along unrehearsed desert trail

� In February 2011, in a Jeopardy! quiz show exhibition match, IBM's question answering system, Watson, defeats the two greatest Jeopardy! champions, Brad Rutter and Ken Jennings

� In January 2016, Researchers from Google DeepMind have developed the first computer able to defeat a human champion at the board game Go


� 2020s, Personal computers will 2020s, Personal computers will 2020s, Personal computers will 2020s, Personal computers will have the same processing power have the same processing power have the same processing power have the same processing power as human brains.as human brains.as human brains.as human brains.

� 2030s, Mind uploading becomes 2030s, Mind uploading becomes 2030s, Mind uploading becomes 2030s, Mind uploading becomes possible.possible.possible.possible.

� 2040s, Human body 3.0 (as 2040s, Human body 3.0 (as 2040s, Human body 3.0 (as 2040s, Human body 3.0 (as Kurzweil calls it) comes into Kurzweil calls it) comes into Kurzweil calls it) comes into Kurzweil calls it) comes into existence; People spend most of existence; People spend most of existence; People spend most of existence; People spend most of their time in fulltheir time in fulltheir time in fulltheir time in full----immersion immersion immersion immersion virtual realityvirtual realityvirtual realityvirtual reality

� 2045s, The Singularity occurs as 2045s, The Singularity occurs as 2045s, The Singularity occurs as 2045s, The Singularity occurs as artificial intelligences surpass artificial intelligences surpass artificial intelligences surpass artificial intelligences surpass human beings as the smartest and human beings as the smartest and human beings as the smartest and human beings as the smartest and most capable life forms on the most capable life forms on the most capable life forms on the most capable life forms on the Earth; The extermination of Earth; The extermination of Earth; The extermination of Earth; The extermination of humanity by violent machines is humanity by violent machines is humanity by violent machines is humanity by violent machines is unlikely unlikely unlikely unlikely

Kurzweil, « The Singularity is Near », 2005

� Law of accelerating returns: Law of accelerating returns: Law of accelerating returns: Law of accelerating returns: technology progressing toward technology progressing toward technology progressing toward technology progressing toward Singularity at Singularity at Singularity at Singularity at exponentialexponentialexponentialexponential rate rate rate rate ((((eacheacheacheach transition transition transition transition occursoccursoccursoccurs more more more more rapidlyrapidlyrapidlyrapidly thanthanthanthan the last)the last)the last)the last)

� Functionality of the brain is Functionality of the brain is Functionality of the brain is Functionality of the brain is quantifiable in terms of quantifiable in terms of quantifiable in terms of quantifiable in terms of technology technology technology technology

� Baby boomers will live long Baby boomers will live long Baby boomers will live long Baby boomers will live long enough to see singularity. enough to see singularity. enough to see singularity. enough to see singularity. NanobotsNanobotsNanobotsNanobots will eventually be able will eventually be able will eventually be able will eventually be able to repair and replace any part of to repair and replace any part of to repair and replace any part of to repair and replace any part of the body that wears out,the body that wears out,the body that wears out,the body that wears out,

� Strong Artificial Intelligences and Strong Artificial Intelligences and Strong Artificial Intelligences and Strong Artificial Intelligences and cyberneticallycyberneticallycyberneticallycybernetically augmented humans augmented humans augmented humans augmented humans will become the dominant forms will become the dominant forms will become the dominant forms will become the dominant forms of sentient life on the Earthof sentient life on the Earthof sentient life on the Earthof sentient life on the Earth

Source: summary available on Wikipedia


Why now?

Moravec paradox solved?Moravec paradox solved?Moravec paradox solved?Moravec paradox solved?

� High High High High levellevellevellevel reasoningreasoningreasoningreasoning ((((playingplayingplayingplayingchesschesschesschess, , , , usingusingusingusing mathematicsmathematicsmathematicsmathematics, etc.) , etc.) , etc.) , etc.) easiereasiereasiereasier thanthanthanthan lowlowlowlow----level level level level sensorimotorsensorimotorsensorimotorsensorimotor skills (moving skills (moving skills (moving skills (moving across space, recognizing across space, recognizing across space, recognizing across space, recognizing speech, etc.)speech, etc.)speech, etc.)speech, etc.)

� This is because high level This is because high level This is because high level This is because high level reasoning demands less reasoning demands less reasoning demands less reasoning demands less computational powercomputational powercomputational powercomputational power

� SeeSeeSeeSee MoravecMoravecMoravecMoravec, H. (1998). When , H. (1998). When , H. (1998). When , H. (1998). When will computer hardware match will computer hardware match will computer hardware match will computer hardware match the human brain. Journal of the human brain. Journal of the human brain. Journal of the human brain. Journal of Evolution and Technology, 1. Evolution and Technology, 1. Evolution and Technology, 1. Evolution and Technology, 1.

Technological evolutionTechnological evolutionTechnological evolutionTechnological evolution

� Brute force computational Brute force computational Brute force computational Brute force computational

power now available (due to power now available (due to power now available (due to power now available (due to

Moore’s law)Moore’s law)Moore’s law)Moore’s law)

� Trillions of data now available, Trillions of data now available, Trillions of data now available, Trillions of data now available,

and networkedand networkedand networkedand networked


Philosophical debate

TuringTuringTuringTuring

� Dialogue Dialogue Dialogue Dialogue withwithwithwith a a a a humanhumanhumanhuman and a and a and a and a machine machine machine machine throughthroughthroughthrough teletypeteletypeteletypeteletype� If a machine could carry on a

conversation (over a teleprinter) that was indistinguishable from a conversation with a human being, then it was reasonable tosay that the machine was "thinking”

� Machine's ability to exhibitintelligent behavior equivalent to, or indistinguishable from, that of a human

� A. M. Turing (1950) Computing A. M. Turing (1950) Computing A. M. Turing (1950) Computing A. M. Turing (1950) Computing Machinery and Intelligence.Machinery and Intelligence.Machinery and Intelligence.Machinery and Intelligence. Mind Mind Mind Mind 49:49:49:49: 433433433433----460460460460

SearleSearleSearleSearle� «««« ChineseChineseChineseChinese roomroomroomroom » argument» argument» argument» argument

� You do not speak Chinese

� You’re in room with two slits, a book, and some scratch paper

� Someone slides Chinese charactersthrough first slit

� You follow the instructions in thebook, correlate characters as instructed by book, and slide theresulting sheet in the second slit.

� It appears you speak Chinese, yetyou do not understand a word of Chinese

� No need to understand Chinese totranslate it. Fact that computer is able to do is to execute certainprocesses does not create strong AI

� Weak AI that simulates thought

� httphttphttphttp://www.iep.utm.edu/chineser/://www.iep.utm.edu/chineser/://www.iep.utm.edu/chineser/://www.iep.utm.edu/chineser/


Debate amongst scientists

� Is Is Is Is thisthisthisthis a a a a computationalcomputationalcomputationalcomputational problemproblemproblemproblem onlyonlyonlyonly ((((KurzweilKurzweilKurzweilKurzweil)?)?)?)?

� Or Or Or Or isisisis theretheretherethere an an an an algorithmalgorithmalgorithmalgorithm thatthatthatthat wewewewe do not know?do not know?do not know?do not know?


Various subfields of AI, and examples

� DeepDeepDeepDeep learninglearninglearninglearning (or machine (or machine (or machine (or machine learninglearninglearninglearning))))

� Algorithms that enable robots to learn tasks through trial and error using a process that more closely approximates the way humans learn: spam filtering

� Neural networksNeural networksNeural networksNeural networks

� Emulate the ability of living organisms to integrate perceptual inputs smoothly with motor responses

� Speech recognitionSpeech recognitionSpeech recognitionSpeech recognition

� Uses sound metrics along with domain and context specific language to respond to voice commands

� Natural Natural Natural Natural languagelanguagelanguagelanguage processingprocessingprocessingprocessing

� Robots interacting and responding through interpretations of naturallanguage instructions

� ArtificialArtificialArtificialArtificial visionvisionvisionvision

� Object recognition, which allow robots to interact and measure their environment . Can include different features: visual object recognition and tracking, image stabilization, visual-based serving, human-to-machine interaction etc. => recognize x-rays, MRI scans, battlefield robots recognize kids, automated cars,

� KnowledgeKnowledgeKnowledgeKnowledge representationrepresentationrepresentationrepresentation


Challenges (1)

� SupervisedSupervisedSupervisedSupervised learninglearninglearninglearning v v v v unsupervisedunsupervisedunsupervisedunsupervised learninglearninglearninglearning

� Human feeds neural network with inputs (image) and output/label (face, dog, lamp, etc.), and the AI comes up with a statistical rule that correlatesinputs with the correct outputs => no causal explanation + error or reward signal

� AI does identify patterns

� Pornography example: Justice Potter Stewart, SCOTUS: « I know it when I see it »

� But all this is supervised learning, and is finite resource

� Natural Natural Natural Natural languagelanguagelanguagelanguage

� « Recognize speech » v « Wreck on the beach »

� Questions on Siri, Wolfram alpha, etc. generate different responses if different syntax is used

� Disambiguation: « I ate spaghetti with meatballs » v « I ate spaghetty withchopsticks » (see R. Mooney podcast)

� ArtificialArtificialArtificialArtificial vision and the vision and the vision and the vision and the toweltoweltoweltowel problemproblemproblemproblem: : : : https://www.youtube.com/watch?v=gy5g33S0Gzohttps://www.youtube.com/watch?v=gy5g33S0Gzohttps://www.youtube.com/watch?v=gy5g33S0Gzohttps://www.youtube.com/watch?v=gy5g33S0Gzo


Challenges (2)


Watson

� https://https://https://https://www.youtube.com/watch?v=pwh1INne97Qwww.youtube.com/watch?v=pwh1INne97Qwww.youtube.com/watch?v=pwh1INne97Qwww.youtube.com/watch?v=pwh1INne97Q


Possible advances

� Internet giants have a stockpile of information (input) Internet giants have a stockpile of information (input) Internet giants have a stockpile of information (input) Internet giants have a stockpile of information (input)

that is prethat is prethat is prethat is pre----labelled by users (face)labelled by users (face)labelled by users (face)labelled by users (face)


Robotics

� A robot A robot A robot A robot isisisis an «an «an «an « agencifiedagencifiedagencifiedagencified » AI» AI» AI» AI

� MechanicalMechanicalMechanicalMechanical engineering issues are not relevant, engineering issues are not relevant, engineering issues are not relevant, engineering issues are not relevant,

thoughthoughthoughthough theytheytheythey constituteconstituteconstituteconstitute significantsignificantsignificantsignificant limitslimitslimitslimits

� Power

� Material science

� Motor research


Survey of most relevant applications,

RoboLaw, 2014


Related technologies

� HumanHumanHumanHuman enhancementenhancementenhancementenhancement (and (and (and (and transhumantranshumantranshumantranshuman sciences)sciences)sciences)sciences)

� Bionics (see J. Fischman, National Geographic, 2010) and prosthetics

� Exosqueletons

� Mind uploading

� Care robots, social robots, etc.Care robots, social robots, etc.Care robots, social robots, etc.Care robots, social robots, etc.

� AugmentedAugmentedAugmentedAugmented realityrealityrealityreality


Definitional problem

1921, Karel Capek, R.U.R.

� Rossum’s Universal Robots:

Capek’s play makes first use of

the word “robot” to describe

an artificial person

� Capek invented the term,

basing it on the Czech word

for “forced labor” or

“servitude”:

http://www.wired.com/2011

/01/0125robot-cometh-

capek-rur-debut/

2014, Robolaw

� “In fact, the term “robot” can mean different things to different people, since there is no agreement on its meaning neither among professional users (i.e. roboticists) nor among laypeople”


Definitions

� ““““Actuated mechanism programmable in two or Actuated mechanism programmable in two or Actuated mechanism programmable in two or Actuated mechanism programmable in two or moremoremoremore axesaxesaxesaxes (4.3)(4.3)(4.3)(4.3) with a degree ofwith a degree ofwith a degree ofwith a degree of autonomyautonomyautonomyautonomy (2.2), moving within (2.2), moving within (2.2), moving within (2.2), moving within its environment, to perform intended tasksits environment, to perform intended tasksits environment, to perform intended tasksits environment, to perform intended tasks”, ”, ”, ”, ISOISOISOISO 8373:2012(en)8373:2012(en)8373:2012(en)8373:2012(en)

� ““““A robot A robot A robot A robot isisisis a a a a constructedconstructedconstructedconstructed system system system system thatthatthatthat displays displays displays displays bothbothbothboth physicialphysicialphysicialphysicial and and and and mental mental mental mental agencyagencyagencyagency, but , but , but , but isisisis not alive in the not alive in the not alive in the not alive in the biologicalbiologicalbiologicalbiological sensesensesensesense ”, , , , Neil M. Neil M. Neil M. Neil M.

Richards and William D. Smart, 2016Richards and William D. Smart, 2016Richards and William D. Smart, 2016Richards and William D. Smart, 2016

� ““““Robots are mechanical objects that take the world in, process Robots are mechanical objects that take the world in, process Robots are mechanical objects that take the world in, process Robots are mechanical objects that take the world in, process what they sense, and in turn act upon the worldwhat they sense, and in turn act upon the worldwhat they sense, and in turn act upon the worldwhat they sense, and in turn act upon the world”, Ryan ”, Ryan ”, Ryan ”, Ryan CaloCaloCaloCalo, , , ,

2015.2015.2015.2015.


ISO 8373:2012(en)

� “Moving “Moving “Moving “Moving within its within its within its within its environment”? environment”? environment”? environment”?

� Softbots do not move?

� Need “Hard”-bot seated behind a computer?

� Human being who makes online transactions does not move, yet may

create harm

� “to “to “to “to perform intended tasksperform intended tasksperform intended tasksperform intended tasks””””

� A robot has sufficient autonomy to refuse to engage into intended

harmful activity

� Drone will not launch bomb on hospital

� Google car will not crash in school

� Industrial bot refuses to operate if safety risk

� Localizing intention: initial intention or subsequent command?


« Constructed system that displays both physicaland mental agency », Richards and Smart� But Robots But Robots But Robots But Robots createdcreatedcreatedcreated by by by by

robots? Are robots? Are robots? Are robots? Are theytheytheytheyconstructedconstructedconstructedconstructed????

� How How How How muchmuchmuchmuch mental mental mental mental agencyagencyagencyagency? ? ? ? � Drones

� Robots w/o Robots w/o Robots w/o Robots w/o physicalphysicalphysicalphysical agencyagencyagencyagency: : : : softbotssoftbotssoftbotssoftbots ((((HartzogHartzogHartzogHartzog, 2015), 2015), 2015), 2015)� News generating bot

� Robot advertisers

� Computer composers: http://www.gizmag.com/creative-artificial-intelligence-computer-algorithmic-music/35764/


Sense – think – act, a spectrum?

Sense (acquire and

process information)

Think (decision

making)

Act (locomotion and

kinematics)

Low Industrial robots that

paint or weld car

parts

Exosqueleton,

DaVinci Robot

(teleoperated)

Augmented reality

devices (Hololens),

Medical diagnosis

robot

Medium Mars Rover, Drones

High Vacuum cleaner DriverlessCar, Social

Robots

Hoops Robotic

basketball-shooting

arm


Robolaw typology

� No No No No definitiondefinitiondefinitiondefinition, but 5 , but 5 , but 5 , but 5 categoriescategoriescategoriescategories of relevant items: of relevant items: of relevant items: of relevant items:

� Use or task: service or industrial

� Environment: physical (road, air, sea, etc.) v cyberspace

� Nature: embodied or disembodied (bionic systems)

� Human-Robot Interaction (HRI)

� Autonomy


Calo, 2015

� EmbodiementEmbodiementEmbodiementEmbodiement

� Robot as « machine » or « hardware »

� Softbots (eg, robot traders)?

� Mooney thinks this is irrelevant; true from scientists perspective, but not

necessary true form society perspective

� EmergenceEmergenceEmergenceEmergence

� New forms of conduct, including welfare enhancing behaviour =>

problem solving robots

� «««« Social valenceSocial valenceSocial valenceSocial valence »»»»

� Robots stimulate reactions from society: « social actors »

� Soldiers jeopardize themselves to preserve robots in military field

� People write love letters to Philae

� Often correlated to anthropomorphic embodiement (Honda Asimo)


Why is all this relevant to LAW?� Google’sGoogle’sGoogle’sGoogle’s car car car car runsrunsrunsruns intointointointo a a a a kid or an kid or an kid or an kid or an oldoldoldold womanwomanwomanwoman? A ? A ? A ? A kid kid kid kid withwithwithwith 5% high 5% high 5% high 5% high injuryinjuryinjuryinjury riskriskriskrisk v a v a v a v a

treetreetreetree withwithwithwith 99% high 99% high 99% high 99% high injuryinjuryinjuryinjury riskriskriskrisk for 4 for 4 for 4 for 4 passengerspassengerspassengerspassengers? A dog v ? A dog v ? A dog v ? A dog v anotheranotheranotheranother car?car?car?car?

� A robot A robot A robot A robot programmedprogrammedprogrammedprogrammed not to not to not to not to harmharmharmharm itsitsitsits ownerownerownerowner runsrunsrunsruns awayawayawayaway fromfromfromfrom the crime the crime the crime the crime itititit justjustjustjustcommittedcommittedcommittedcommitted

� Sophie Sophie Sophie Sophie misdiagnosesmisdiagnosesmisdiagnosesmisdiagnoses youryouryouryour illnessillnessillnessillness, , , , who’swho’swho’swho’s liable?liable?liable?liable?

� A robot A robot A robot A robot spiesspiesspiesspies on on on on youryouryouryour spousespousespousespouse whowhowhowho cheatscheatscheatscheats, , , , shallshallshallshall hehehehe report? Data protection issuereport? Data protection issuereport? Data protection issuereport? Data protection issue

� A robot A robot A robot A robot createscreatescreatescreates a new a new a new a new songsongsongsong: : : : whowhowhowho ownsownsownsowns itititit? ? ? ? WhatWhatWhatWhat if the if the if the if the songsongsongsong soundssoundssoundssounds similarsimilarsimilarsimilar to to to to thatthatthatthatof a of a of a of a copyrightedcopyrightedcopyrightedcopyrighted workworkworkwork? Who’s liable for the ? Who’s liable for the ? Who’s liable for the ? Who’s liable for the infringementinfringementinfringementinfringement????

� Bots: Bots: Bots: Bots: httphttphttphttp://://://://motherboard.vice.com/read/themotherboard.vice.com/read/themotherboard.vice.com/read/themotherboard.vice.com/read/the----bestbestbestbest----thingsthingsthingsthings----aaaa----randomrandomrandomrandom----botbotbotbot----boughtboughtboughtbought----onononon----thethethethe----darknetdarknetdarknetdarknet

� An An An An inventorinventorinventorinventor patents patents patents patents new robots: new robots: new robots: new robots: https://https://https://https://www.google.com/patents/US5952796www.google.com/patents/US5952796www.google.com/patents/US5952796www.google.com/patents/US5952796 ????

� You dont You dont You dont You dont wantwantwantwant to drive an to drive an to drive an to drive an autonomousautonomousautonomousautonomous car, but the car, but the car, but the car, but the insuranceinsuranceinsuranceinsurance companycompanycompanycompany refuses to refuses to refuses to refuses to provideprovideprovideprovide a a a a contractcontractcontractcontract

� A robot in A robot in A robot in A robot in humanhumanhumanhuman formformformform isisisis gettinggettinggettinggetting beat in the beat in the beat in the beat in the streetstreetstreetstreet by police by police by police by police officersofficersofficersofficers

� Right to dignity?; but the robot has killed someone: right to shoot him down?

� Death penalty for Bots?

� Right to procreate, to dignity, to decent funerals?


Regulatory needs and possible approaches?

� NeedsNeedsNeedsNeeds

� Updates in existing law ?

� Design new laws (emergence)?

� ApproachesApproachesApproachesApproaches::::

� Ex ante: embedding law in Robot code (> human)?

� Ex post: enforcing law to Robot conduct (< human)?


Asimov’s three laws of robotics (1950)

� Device Device Device Device that is wellthat is wellthat is wellthat is well----suited for work that is too dull, dirty or dangerous suited for work that is too dull, dirty or dangerous suited for work that is too dull, dirty or dangerous suited for work that is too dull, dirty or dangerous

for real for real for real for real humanshumanshumanshumans

� Safety feature introduced in all botsSafety feature introduced in all botsSafety feature introduced in all botsSafety feature introduced in all bots

� LAW LAW LAW LAW 1: 1: 1: 1: A robot may not injure a human being or, through inaction, allow

a human being to come to harm;

� LAW LAW LAW LAW 2: 2: 2: 2: A robot must obey the orders given it by human beings except

where such orders would conflict with the First Law;

� LAW LAW LAW LAW 3: 3: 3: 3: A robot must protect its own existence as long as such protection

does not conflict with the First or Second Laws

� In later fiction where robots had taken responsibility for government of

whole planets and human civilizations, Asimov also added a fourth, or

zeroth law, to precede the others:

� LAW 0:LAW 0:LAW 0:LAW 0: A robot may not harm humanity, or, by inaction, allow humanity

to come to harm