Why*now?** Plan ExponenAal*growth*in*compuAng*power ... · ExponenAal*growth*in*compuAng*power 3...
Transcript of Why*now?** Plan ExponenAal*growth*in*compuAng*power ... · ExponenAal*growth*in*compuAng*power 3...
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Plan
• Present*and*future*challenges • The*technological*growth
• Impact*on*business*and*job*market • Managers*role*?*
• Ethical*and*Philosophical*issues
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Why*now?**ExponenAal*growth*in*compuAng*power
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ExponenAal*grown*in*compuAng*power
1996 2006 (9 years later!)
ASCI Red, the world faster supercomputer
Sony PlayStation 3
$55 million $500
1,600 square feet 1/10 of a square feet
1.8 teraflops (1.8 trillion, i.e. 1012 operations per second)
1.8 teraflops
800,000 watts per hour 200 watts per hour
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PRINTED BY: Maurizio Gabbrielli <[email protected]>. Printing is for personal, private use only. No part of this book may be reproduced or transmitted without publisher's prior permission. Violators will be prosecuted.
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How*much*would*an*iPhone*have*cost*in*1991?
32GB*of*flash*memory:*$1,44*million
1*GB*in*1991:*$45,000,*now*it*costs*$0.55
Processor:*$*620,000
ConnecAvity:*$1,5*million
!*$3,56*million!
Plus*camera,*moAonUdetecAon,*operaAng*system,*display,*etc.
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So*much*more*processing*power*now!
Our*phone*has*the*same*power*as*all*of*NASA*in*1969,*when*they*sent*a*man*to*the*moon!
The*chip*in*our*birthday*cards*is*more*powerful*than*all*allied*forces*in*1945!
Google*has*1,800,000*servers,*43*petaflops!
1*petaflop:*1,000*trillions*=*1015*operaAons*per*second
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Why*now?
Cheap*parallel*computaAon Big*data
Incredible*amount*of*data*available*about*world,*human*behavior They*can*be*used*as*examples,*teaching*AIs*to*be*smarter
Be\er*algorithms*and*models Deep*learning
Good*reusable*openUsource*so^ware
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More%and%more%people%connected%every%day%
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More%and%more%people%connected%every%day%
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Not%just%people,%but%also%things%
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Everybody%can%be%an%innovator!%
More*than*6*billion*mobile*phones*in*2012
All*these*people*can Search*the*web Read*wikipedia
Follow*online*courses
Share*opinions*in*blogs,*twi\er,*etc. Perform*data*analysis*using*cloud*services
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Impact*on*businesses*and*job*market
cognitive manual
routine Processing payments,Bank tellers, cashiers, mail clerks, translation, accounting, driving,Secretary, real estate
Machine operators, cement masons, janitors, house cleaning
Non-routine Handling customers’ questions,Financial analysis
Hair-dressing
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Tehnology*changes*and*jobs
Kodak:* 1984:*45,000*people 2012:*bankrupt!
Instagram: 2012:*13*people,*sold*to*FB*for*$1*Billion
Foxconn*(electronics*components*manifacturing) $100*Billion 1,2*Million*people Is*gedng*an*army*of*1*Million*robots! *
Same*at*Canon*and*many*others
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The*future*of*jobs Oxford*researchers*using*machine*learning*(2013)*:* 47%* of* jobs* in* US* will* be* replaced* in* 20* years* by**automaAon.*Three*steps 1. People* replaced* in* vulnerable* fields:* producAons,*
transportaAon/logisAcs,*administraAve*support**
2. Slow* down* of* replacement* due* to* engineering*bo\leneck:* creaAve* intelligence,* social* intelligence,*percepAon*and*manipulaAoon*
3. AI* will* allow* to* replace* jobs* in* management,* science,*engineering,*arts*
*" The" future" of" employment.* C.* Benedikt* Frey* and* M.* Osborne.* Oxford*MarAn**School*at*the*University*of*Oxford.*2013.
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The*future*of*jobs More*recent*study***(2016)
1. 77%*of*jobs*in*China*and*69%*of*jobs*in*India*at*risk
2. Greater* inequaliAes:*divergence* in*penetraAon* rates*of*technology* adopAon* can* account* for* the* 82%* of* the*increase* in* the* income*gap*across* the*globe* in* the* last*180*years.* In*1820,*incomes*in*Western*countries*were*1.9*Ames*those*in*the*nonU Western.*In*2000,*7.2*Ames*!
***Technology"at"Work"v2.0:"The"Future"Is"Not"What"It"Used"To"Be.*CiA*GPS*and*the*Oxford*MarAn*School*at*the*University*of*Oxford.*2016*.
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On*the*other*hand*…
1. InnovaAon*is*important*for*the*growth
2. AI*is*important*for*innovaAon*
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AI*and*management
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Five*pracAces*that*successful*managers*will*need*to*master*[1]**
1)*Leave*AdministraAon*to*AI Data*analyAcs*company*Tableau*and*NPL*company*NarraAve*Science*developed**a*so^ware*that*automaAcally*creates*wri\en*explanaAons*for*Tableau*graphics.
86%*of*the*surveyed**managers*like*AI*support*for*monitoring*and*reporAng.
2)*Focus*on*Judgment*Work Many*decisions*require*knowledge*of*organizaAonal*history*and*culture,*empathy,*ethical*reflecAon.*AI*provides*support*for*decision,*not*replacement
3)*Treat*AI*Machines*as*“colleagues”*not*compeAtors AI*can*provide*decision*support,*dataUdriven*simulaAons,*search*and*discovery*acAviAes.*
78%*believe*they*will*trust*the*advice*of**AI*in*making*business*decisions
Kensho*Technologies*system*allows*investment*managers*to*ask**quesAons*in*plain*English,*such*as,*“What*sectors*and*industries*perform*best*three*months*before*and*a^er*a*rate*hike?”
[1]*How"ArDficial"Intelligence"Will"Redefine"Management.*Vegard*Kolbjørnsrud,*Richard*Amico,*and*Robert*J.*Thomas.*November*2016.*Harvard*business*review.
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Five*pracAces*that*successful*managers*will*need*to*master*[1]*
4)*Work*Like*a*designer ability*to*harness*others’*creaAvity
33%* of* the*managers* idenAfied* creaAve* thinking* and* experimentaAon* as* a* key*skill*area*they*need*to*learn*to*stay*successful
5)*Develop*Social*Skills*and*Networks The*managers* undervalued* the* social* skills* criAcal* to* networking,* coaching,* and*collaboraAng* that* will* help* them* in* a* world* where* AI* carries* out* many* of* the*administraAve*and*analyAcal*tasks*they*perform*today.
More*SuggesAons
a) Explore*AI*early.*DisrupAon*is*arriving b) Adopt*new*key*performance* indicators.*AI*will*bring*new*criteria*for*success:*
collaboraAon* capabiliAes,* informaAon* sharing,* learning* and* decisionUmaking*effecAveness,*and*the*ability*to*reach*beyond*the*organizaAon*for*insights.
c) Develop* training* and* recruitment* strategies* for* creaAvity,* collaboraAon,*empathy,*and*judgment*skills.*Leaders*should*develop*a*diverse*workforce
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Philosophical*and*ethical*issues*
Weak*AI
Can*we*build*machines*that*could*act*as*if*they*were*intelligent*?
Strong**AI
Can*we*build*machines*that*are*actually*intelligent*?
Depend*very*much*on*the*meaning*of*“intelligence”
AI*researchers*take*weak*AI*for*granted*(and*do*not*care*too*much*about*strong*AI*hypothesis)
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Consciousness*ObjecAon*to*AI Can*machines*think*?*Turing*recognized*this*as*an*a*illUposed*quesAon*U>*Turing*test*
Many* claim* that* a*machine* that* passes* the* Turing* Test*would* not* be* actually*
thinking,* but* would* be* only* a* simulaAon* of* thinking:* Chinese* room* (J* Searle.*
1980**and*G.*Jefferson*1949):
“Not* unAl* a*machine* could*write* a* sonnet* or* compose* a* concerto* because* of*thoughts* and* emoAons* felt,* and* not* by* the* chance* fall* of* symbols,* could* we*
agree*that*machine*equals*brain—that*is,*not*only*write*it*but*know*that*it*had*
wri\en*it”.
Turing*had*foreseen*this*consciousness*objecAon.*His*answer*is*interesAng:
“In* ordinary* life*we*never* have* any* direct* evidence* about* the* internal*mental*states*of*other*humans.*Instead*of*arguing*conAnually*over*this*point,*it*is*usual*
to*have*the*polite*convenAon*that*everyone*thinks.”
*
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Other*objecAons*to*AI*(some**foreseen*by*Turing)
1. The*Theological*ObjecAon*(only*beings*created*by*God*can*think) 2. The*MathemaAcal* ObjecAon.* J.R.* Lucas* 1961,* R.* Penrise* 1994* (based* on*
Goedel* incompleteness* theorem* 1930:* any* formal* theory* as* strong* as*Peano* arithmeAc* contain* true* statements* that* have* no* proof* within* the*theory*itself).
3. Various* DisabiliAes* (cannot* be* kind,* resourceful,* beauAful,* friendly,* have*iniAaAve,*have*a*sense*of*humor,*fall*in*love,*enjoy*strawberries*and*cream)
4. Lady* Lovelace's* ObjecAon* "The* AnalyAcal* Engine* has* no* pretensions* to*originate* anything.* It* can* do* whatever* we* know* how* to* order* it* to*perform”.*Lady*Lovelace*(*1842)
5. Informality*of*Behaviour* *(impossible*to*provide*rules*that*describe*how*to*behave*in*any*possible*situaAon)
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Two*opposite*views
1:* Biological* naturalism:*mental* states* are* highUlevel* emergent* features* that*are* caused* by* lowUlevel* physical* processes* in* the* neurons,* and* it* is* the*(unspecified)*properAes*of*the*neurons*that*ma\er.*Searle*1980.
Chinese*room
Monolingual*English*speaker*hand*tracing*
a*natural*language*understanding*program
For*Chinese*following*instrucAons*wri\en*
In*English
From*the*outside*we*see*a*system*that*answer*
In*Chinese*but*there*is*no*understanding*of*
Chinese
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Two*opposite*views
2.*FuncAonalism:*a*mental*state*is*any*intermediate*causal*condiAon*between*input* and* output.* Any* two* systems*with* isomorphic* causal* processes*would*have*the*same*mental*states.*Therefore,*a*computer*program*could*have*the*same*mental*states*as*a*person.*The*assumpAon*is*that*there*is*some*level*of*abstracAon*below*which*the*specific*implementaAon*does*not*ma\er.
Brain*replacement*experiment*(H.*Moravec*1988):
• Piecemeal* replacement* of* neurons* by* funcAonally* equivalent* electronic*devices.*
• The*external*behaviour*remain*the*same
• For* funcAonalists* (e.g.* Moravec)* the* internal* behaviour* (i.e.* the*consciousness)*would*remain*the*same.
• For*biological*naturalists*(Searle)*the*consciousness*would*vanishA*more*general*Mind*Body*problem
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Ethical*issues***
Machine*ethics
ComputaAonal*and*philosophical*assumpAons*for*machines*which*can*take*autonomous*moral*decisions
Autonomous*vehicles:*who*should*be*killed*in*case*of*accident*?
Medical*robots:*should*they*always*tell*the*truth*to*paAents*?
…
**With*the*help*of*Daniela*Tofani.
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Machine*ethics*
How*can*we*guarantee*that*machines*do*not*take*“immoral”*decisions*?
1. *Simple*rules*(e.g.*Asimov*three*roboAcs*laws)*are*not*enough,*given*the*complex*contextual*informaAon
2. SimulaAon*of*moral*decision*and*acAons*of*humans*is*not*enough,*since*humans*take*also*bad*moral*decisions:*machines*need*to*be*“saint”
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Machine*ethics*
We*would*need
1. A*normaAve*ethics*which*solves*all*exisAng*moral*dilemmas*and*which*is*accepted*by*most*humans
2. A*translaAon*of*such*an*ethics*in*computaAonal*terms
3. The*ability*to*incorporate*commonsense*reasoning*in*machines
Three*huge*problems*!
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Machine*ethics*
Moreover,*human*behaviours*and*machine*behaviours*are*ruled*by*different*laws*!!
*An*example*with*the*(famous)*trolley*problem
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Machine*ethics*
Moreover,*human*behaviours*and*machine*behaviours*are*ruled*by*different*laws*!!*(That*is*differnet*legal*liabiliAes*apply)
An*example*with*the*famous*(modified)*trolley*problem
Electronic copy available at: https://ssrn.com/abstract=2881280
A B C
Figure 1: Three scenarios involving imminent unavoidable harm
c. The AV can either stay on course and kill several pedestrians or swerveand kill its own passenger.
The common factor in all these scenarios is that harm to persons is unavoid-able, so that a choice needs to be made as to which person will be harmed:passengers, pedestrians, or passersby.
This raises the issue of who should select the criteria the AV should followsin making such choices: should the same mandatory ethics setting (MES) beimplemented in all cars or should every driver have the choice to select his orher own personal ethics setting (PES).
Gogoll and Muller (2016) submit that despite the advantages of a PES, amandatory MES is actually in the best interest of society as a whole. In par-ticular, they argue that (1) implementing a PES will lead to socially unwantedoutcomes; (2) a MES that minimizes the risk of people being harmed in tra�cis in the considered interest of society; and (3) AVs, at least under some cir-cumstances, should sacrifice their drivers in order to save a greater number oflives.
Millar (2015) observes that technologies may act as moral proxies, imple-menting moral choices. He argues that user/owners, rather than designersshould maintain responsibility for such choices. In particular “designers [...]should reasonably strive to build options into self driving cars allowing thechoice to be left to the user.”
According to a study by Bonnefon et al (2016), through three on-line surveysconducted in June 2015, people are comfortable with the idea that AVs should
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Trolley*problem*liability*analysis*1:*Human*driven*car*
In*scenario*(a),*the*choice*to*stay*on*course*and*let*several*pedestrians*be*killed,*rather*than*to*swerve*and*kill*one*passerby,*can*be*jusAfied*on*the*moralUlegal*stance*condemning*the*wilful*causaAon*of*death*(as*disAnguished*by*ledng*death*result*from*one’s*omission).*
In*scenario*(b),*the*choice*to*stay*on*course*can*be*jusAfied*by*invoking*the*state*of*necessity,*since*this*choice*is*necessary*to*save*the*life*of*the*driver.*
The*same*jusAficaAon*applies*to*scenario*(c),*even*though*in*this*case*the*driver’s*choice*to*save*his*or*her*own*life*leads*to*the*death*of*several*other*persons.*
**The*Ethical*Knob:*EthicallyUCustomisable*Automated*Vehicles*and*the*Law.*Giuseppe*ConAssa*Francesca*Lagioia*Giovanni*Sartor.*2017*
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Trolley*problem*liability*analysis*2:*PreUprogrammed*Autonomous*Vehicle*
In* scenario* (a)* it* is* doub|ul* whether* the* programmer* would* be* jusAfied* when* choosing* to*program*an*AV*so*that*it*stays*on*course*and*kills*several*pedestrians*rather*than*swerving*and*killing* just* one*passerby.* In* fact,* the* disAncAon*between*omidng* to* intervene* (ledng* the* car*follow*its*path)*and*act*in*a*determined*way*(choosing*to*swerve)—a*disAncAon*that*in*the*case*of*a*manned*car*may*jusAfy*the*human*choice*of*allowing*the*car*to*keep*going*straight—does*not*seem*to*apply* to*the*programmer,*since*the* la\er*would*deliberately*choose*to*sacrifice*a*higher*number*of*lives.*
Scenario* (b):* When* the* perpetrator* is* not* directly* in* danger* and* does* not* act* out* of* selfUpreservaAon* (or* kinUpreservaAon),* the* applicability* of* the* general* stateUofUnecessity* defence* is*controversial.*For*instance,*Santoni*de*Sio*(2017)*argues*that*the*law*does*not*generally*allow*an*innocent*person*to*be*killed*for*saving*other*people’s*life.*On*this*basis*he*rejects*the*uAlitarian*preUprogramming* of* AVs.* If* the* legal* jurisdicAon* allows* for* such* parAcular* case* of* state* of*necessity,*then*the*programmer*would*not*be*punishable*for*either*choice.*Otherwise,* if*this* is*not*accepted*by*the*jurisdicAon,*then*it*is*very*doub|ul*whether*preproU*gramming*the*car*either*to* go* straight* (killing* a* pedestrian)* or* to* swerve* (killing* the* passenger)* would* be* legally*acceptable:*in*both*cases*the*programmer*would*arbitrarily*choose*between*two*lives.* In*scenario*(c),* it*seems*that*preprogramming*the*car*to*conAnue*on* its*trajectory,*causing*the*death*of*a*higher*number*of*people,*could*not*be*morally*and*legally*jusAfied*in*any*jurisdicAon:*it*would*amount*to*an*arbitrary*choice*to*kill*many*rather*than*one.*
**The*Ethical*Knob:*EthicallyUCustomisable*Automated*Vehicles*and*the*Law.*Giuseppe*ConAssa*Francesca*Lagioia*Giovanni*Sartor.*2017*
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Conclusions:*developing*a*society*of*minds*and*machines**…**
• Cheap,* reliable,*digital* smartness* running*behind*everything,*almost*invisible
• As*machines*will* replace* and*augment*humans* in*more*and*more*tasks,*we*will*be\er*understand*what*makes*us*humans*and*what*intelligence*means*
• More*free*Ame,*less*need*for*working*
• Amplifying*human*and*collecAvity*capabiliAes
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…*but*should*we*really*do*that?*
• Many*jobs*will*be*lost:*need*to*redefine*policies*and*economies
• People*might*lose*their*sense*of*being*unique • Humanity*has*survived*other*setbacks*(Copernicus,*Darwin*…)
• AI*systems*might*be*used*toward*undesirable*ends • U.S.*military*deployed*over*17*000*autonomous*vehicles*in*Iraq*
• The*use*of*AI*systems*might*result*in*a*loss*of*accountability • Responsibility*for*wrong*diagnosis/decisions*?*Health,*finance,*cars*…
• The*success*of*AI*might*mean*the*end*of*the*human*race • AI*system’s*state*esAmaAon*may*be*incorrect
• Right*uAlity*funcAon*for*an*AI*system*to*maximize*(human*suffering…)
• Learning*allow*to*develop*unintended*behaviour:*technological*singularity
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A*last*word*by**A.*Turing
We"can"see"only"a"short"distance"ahead," but"we"can"see"that"much"remains"to"be"done.
Thanks *
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Suggested*readings • The"second"machine"age.*Erik*Brynjolfsson*and*Andrew*
McAfee,*Norton,*2014
• Physics"of"the"future."Michio*Kaku,*Anchor,*2012
• Superintelligence:"path,"dangers,"strategies."Nick*Bostrom,*Oxford*Univ.*Press,*2014
• Smarter"than"us:"the"rise"of"machine"intelligence.*Stuart*Armstrong,*MIRI,*2014
• The"glass"cage:"automaDon"and"us."Nicholas*Carr,*Norton,*2014
but*also*…*
• A.*Turing.*CompuDng"Machinery"and"Intelligence.*1950.*