1
Plan
• Present*and*future*challenges
• The*technological*growth
• Impact*on*business*and*job*market
• Managers*role*?*
• Ethical*and*Philosophical*issues
2
Why*now?**
ExponenAal*growth*in*compuAng*power
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
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.
5
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.
6
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
7
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
8
More%and%more%people%connected%every%day%
9
More%and%more%people%connected%every%day%
10
Not%just%people,%but%also%things%
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.
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
13
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
14
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.
15
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*.
16
On*the*other*hand*…
1. InnovaAon*is*important*for*the*growth 2. AI*is*important*for*innovaAon*
17
AI*and*management
18
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.
19
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
20
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)
21
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.”
*
22
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)
23
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
24
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*vanish
A*more*general*Mind*Body*problem
25
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.
26
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”
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*!
Machine*ethics*
Moreover,*human*behaviours*and*machine*behaviours*are*
ruled*by*different*laws*!!
*An*example*with*the*(famous)*trolley*problem
29
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 swerve and 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 follows in making such choices: should the same mandatory ethics setting (MES) be implemented in all cars or should every driver have the choice to select his or her own personal ethics setting (PES).
Gogoll and M¨uller (2016) submit that despite the advantages of a PES, a mandatory 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 unwanted outcomes; (2) a MES that minimizes the risk of people being harmed in traffic is 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 of lives.
Millar (2015) observes that technologies may act as moral proxies, imple- menting moral choices. He argues that user/owners, rather than designers should maintain responsibility for such choices. In particular “designers [...]
should reasonably strive to build options into self driving cars allowing the choice to be left to the user.”
According to a study by Bonnefon et al (2016), through three on-line surveys conducted in June 2015, people are comfortable with the idea that AVs should
2
30
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*
31
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* selfU preservaAon* (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*
32
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
33
…*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
34
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
*
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.*
