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IkhlaqSidhu,contentauthor
Ikhlaq SidhuFounding Faculty Director Sutardja Center for Entrepreneurship & TechnologyDepartment of Industrial Engineering & Operations Research IEOR Emerging Area Professor Award
ArtificialIntelligenceApplications,ResearchandEconomics
IkhlaqSidhu,contentauthor
MyTopicsforToday:
1. TechnicalevolutionofAI/ML
2. Berkeleyresearchperspective
3. JobLoss,Economics,andSingularityvsMultiplicity
IkhlaqSidhu,contentauthor
MyPerspective:Sutardja CenterforEntrepreneurship&Technology
CollegeofEngineering,UCBerkeley
ApproachBerkeleyMethod:Ø EntrepreneurshipØ InnovationLeadership
IkhlaqSidhu,contentauthor
Lots of Students Our Model Brings Bay Area Executives and Entrepreneurs into the Classroom
1600 Undergraduates100 Ph.D / Graduate Students100 Executives10 Global Partners
Michael Marks, KKR, former CEO, FlextronicsShomt Ghose, Venture Partner, Onset VenturesUdi Manber, VP Engineering, GoogleMarc Andreesen, Founder, NetscapeLarry Baer, COO, San Francisco GiantsAmine Haoui, CEO, Sensys NetworksStacey Lawson, Founder In Part, Executive SeibelJim Davidson, Managing Director, Silverlake PartnersDonna Dubinsky, Former CEO, PalmMatt Caspari, co-founder, Aurora BiofuelsRichard Gorman, SVP, Siebel SystemsMike Olson, founder and CEO, ClouderaBrodie Keast, EVP, TiVoDavid Ladd, Managing Director, MayfieldJeff Miller, CEO, DocumentumEva Miranda, SVP, Sony CorporationRavi Mohan, Managing Director, Shasta VenturesTed Hoff, Inventor,of the MicroprocessorNat Goldhaber, Managing Director, Claremont Creek VenturesPeter Thiel, co-founder and CEO, PayPalVictoria Hale, founder and CEO, Medicines 360Steve Newcomb, founder , Powerset (part of Microsoft’s BING)Pehong Cheng, CEO, Broadvision
We focus on the Mindsets & Behaviors needed for Innovation and Entrepreneurship(in context of technology change)
IkhlaqSidhu,contentauthor
• Detectionoffakenews
• Predictionoflong-termenergypricesto
solveWallStreetproblem
• Predictionapplicationsstockmarket,
sportsbetting,andmore
• AIforcrimedetection,trafficguidance,
medicaldiagnostics,etc.
• AversionofZillowthatisrecalculated
withtheeffectsofAirBnBincome
andmanymore…
My newest course: IEOR 135 Applied Data Science with Venture ApplicationsSample Data-X Projects
IkhlaqSidhu,contentauthor
Data and AI Technology:Where is it going?
IkhlaqSidhu,contentauthor
Traditionally2Tasks:Classification&PredictiveScoring
Themostfamousapplicationhasbeenrecommendation:“whichotheruserismostlikeyou”
ExtractedDataofteninTableFormat
Classification:CatsandDogs,SpeechRecognitionMovieRecommendation
Scoring:CreditScore,MovieRatingHeathScore, AnyIsoquant…
IkhlaqSidhu,contentauthor
X Y
X Y
X YMLAlgorithmsGuessthisfunctionF(x)
WehavenowswitchedtoNeuralNetworksasFunctionApproximators
IkhlaqSidhu,contentauthor
Neuralnetresultsareclosethumanresults
IkhlaqSidhu,contentauthor
PeterAbbeel – DeepReinforcementLearning
PeterAbbeelProfessoratUCBerkeley
IkhlaqSidhu,contentauthor
IkhlaqSidhu,contentauthor
MostRecentAINews
IkhlaqSidhu,contentauthor
Does this mean AI Can Do Everything Better than Humans
IkhlaqSidhu,contentauthor
Perfect Information vs. Real World
fully observed uncertaindiscrete multi-agentsingle agent
infinite time horizoncontinuous
finite
KenGoldbergUCBerkeley
Eventhen,AICannotSolveSolveRealLifeProblemsBetterThanHumansAndinfact,AICannotevenWorkwithoutHumans
KenGoldbergLeadingAIResearcheratBerkeley
ProfessorandDepartmentChair,IEOR
WilliamS.FloydJr.DistinguishedChair
IkhlaqSidhu,contentauthor
AcknowledgementtoKenGoldbergUCBerkeley
AISystemsOnlyWorkbecauseofHumanarePartoftheSystem
GoogleOperations
People WriteWebPages People atGoogleTunetheResults
People ClickonWhatTheyWant
Result
FeedbackByclicks
MassiveData
Thereisno“intelligence”,“Desire”,or“Existence”inAIwithoutPeopleThereareonlypeoplewho“investin,designandoperatethemachines”
IkhlaqSidhu,contentauthor
37 faculty
AtBerkeley,wehavealotofresearchon“HowMachinesWillWorkasPartofLargerSystems
thatWorkwithPeople”
IkhlaqSidhu,contentauthor
MyDriveHomeFrom
Berkeley
IkhlaqSidhu,contentauthor
Autonomous Driving and Driver-Assist
•Communicating intent •Driver-in-the-loop modeling •Two-way learning: knowledge transfer between vehicle and driver •Safety in autonomous and assisted driving
Principal investigators:
Ken Goldberg UC Berkeley
Anca Dragan UC Berkeley
Trevor Darrell UC Berkeley
Francesco Borrelli UC Berkeley
Ruzena Bajcsy UC Berkeley
Source:KenGoldberg,CPAR,PeopleandRoboticsInitiative
IkhlaqSidhu,contentauthorSource:KenGoldberg,CPAR,PeopleandRoboticsInitiative
Safety in Human-Robot Interaction: Guarantees and Verification
Safety-constrained motion planning for efficiency in factory human-robot interaction
Learning and prediction for safety in HRI
Provably safe human-centric autonomy
Masayoshi Tomizuka UC Berkeley
Principal investigators:
Claire Tomlin UC Berkeley
Francesco Borrelli UC Berkeley
IkhlaqSidhu,contentauthor
LongerTermFutureNarratives:Multiplicy vsSingularityApocalypse
Multiplicity:diversecombinationsofpeopleandmachinesworktogethertosolveproblemsandinnovate.Multiplicityisnotsciencefiction.Extendingonthecombinationofmachinelearning,thewisdomofcrowds,andcloudcomputingalreadyunderliesmanycomplextasksperformedeveryday
KenGoldberg,UCBerkeley
MultiplicitySingularity
Singularity:Google’sdirectorofEngineering,RayKurzweil,haspredicted singularitytotakeplacearound2045Singularityisatippingpointwhentherobotspoweredbyartificialintelligence willbecomemoreintelligentthanhumanbeings.Singularityisthetime whenartificialintelligencewon’trequire humaninterventiontobecomemoreintelligent.Computerswillbeself-sufficient,theywillmaketheirowndecisions
http://techbakbak.com/singularity-will-happen/
https://www.wsj.com/articles/the-robot-human-alliance-1497213576
IkhlaqSidhu,contentauthor
AI and Job Loss
IkhlaqSidhu,contentauthor
AUTOMATION HAS BEEN CHANGING THE JOB LANDSCAPE FOR MANY YEARS
Over many decades:
– Routinejobs(manualorcognitive)havedeclined.
– Onlynon-routinejobshavecontinuedtogrow.(Source:Economist)
Now: The most famous study on Job Lossand AI, by Carl Frey and Michael Osbourne,predicts that 47% of the workforce is indanger.
9/6/2017 Automation and anxiety
https://www.economist.com/news/special-report/21700758-will-smarter-machines-cause-mass-unemployment-automation-and-anxiety 5/11
Economist
IkhlaqSidhu,contentauthorIkhlaqSidhu,UniversityofCalifornia,Berkeley
TextilevsHandweaving:Duringthe19thcentury,amountofclothasingleweaverinAmericacouldproduce=50Xgain.Laborrequiredfellby98%.Result:clothbecamecheaper,demandgreater,4Xmorejobswerecreatedinthesamesector.
Economists and historians claim that job disruption actually helped the economies that participated.
AutovsHorse-basedtransportation:Thisledtoadeclineinhorse-relatedjobs.However,theautomobileindustryitselfgrewfast.Jobswerealsocreatedindifferentsectors,e.g.motelandfast-foodindustriesthatarosetoservemotoristsandtruckdrivers.
ATMMachinesatBanks:Automatedtellermachines(ATMs)reducethenumberofbankclerks(20/bankin1988to13/bankin2004)bytakingoversomeoftheirroutinetasks.However,bankbranchesgrewinnumbersby43%andtotalemployeesgrew.
Reference:Doweunderstandtheimpactofartificialintelligenceonemployment?|Bruegel
OneCaveat:TheMcKinseyGlobalInstituteestimatesthat,comparedwiththeIndustrialRevolutionofthelate18thandearly19thcenturies,AI’sdisruptionofsocietyishappeningtentimesfasterandat300timesthescale.
IkhlaqSidhu,contentauthor
PWC:DefiningAI
- EconomytoGrow$15.7TUSDby2030
- earlyvaluefromproductivity(2017-2024)– $6.6T
- latervaluefromincreasedconsumption (2024+)$9.1T
We therefore consider four elements of artificial intelligence:
• Automated intelligence: Automation of manual, routine tasks
• Assisted intelligence: Helping to perform tasks faster and better
• Augmented intelligence: Helping people to make better decisions
• Autonomous intelligence: Automating decision-making processes without human intervention
Figure 1: The scope of artificial intelligence
Hardwired/specific systems
Adaptive systems
PwC Data & Analytics
Human-in-the-loop No Human-in-the-loop
Assisted intelligence
AI systems that assist humans in making decisions or taking actions. Hard-wired systems that do not learn from their interactions.
Automation
Automation of manual and cognitive tasks that are routine. This does not involve new ways of doing things – automates existing tasks.
Augmented intelligence
AI systems that augment human decision making continuously learn from their interactions with humans and the environment.
Automation intelligence
AI systems that can adapt to different situations and can act autonomously without human assistance.
6 The economic impact of artificial intelligence on the UK economy
Figure 3: Where will the value gains come from with AI?
During the first phase of the impact (2017-2024), productivity growth could account for a relatively larger share of the gains than the period that follows, when the consumption-side impacts are likely to dominate. This is due to the fact that it takes time for firms to enter the marketplace and supply new varieties of AI-enhanced products to consumers following the stimulation in consumer spending from higher real wages and initial product improvements. As this takes place, competition within AI goods-producing markets increases dramatically, leading to further increases in the value of goods to consumers and therefore greater expenditure on these products as their affordability and attractiveness rises. Overall, the impact on UK GDP will likely be more heavily-weighted towards the consumption-side impacts than other countries4. This is partially because employment in the UK is not highly concentrated in sectors that are automatable, but is also related to the particularly large impact of new goods varieties on the affordability of products in the UK due to the competitive market structure.
Notably, although the labour productivity channel is a ‘production side’ effect, the GDP gain is not only restricted to increased efficiency of production. As real wages rise with productivity, consumer spending increases since goods become more affordable, regardless of the downwards price pressure from increased production efficiency.
The potential for artificial intelligence to impact the UK economy is slightly higher compared to the potential in Northern Europe more generally. Our recent report5 assesses the global potential for AI and the likely impact for regional economies. The analysis concludes that GDP in Northern Europe could be up to 9.9% higher in 2030. The UK could see larger gains as a result of having stronger foundations in technology already – many technology companies have their EMEA headquarters located in the UK – and greater access to the talent and skills required to develop AI technologies.
On the topic of jobs, the adoption of ‘no-human-in-loop’ technologies will mean that some posts will inevitably become redundant, but others will be created by the shifts in productivity and consumer demand emanating from AI, and through the value chain of AI itself. Along with jobs in the development and application of AI, the technologies will need to be built, maintained, operated and regulated. For example, we will need the equivalent of air traffic controllers to control the autonomous vehicles on the road. Same day delivery and robotic packaging and warehousing are also resulting in more jobs for robots and for humans. Furthermore, the extra demand generated in the economy, as a result of artificial intelligence increasing output and incomes, will lead to the creation of jobs not directly related to AI in non-AI intensive sectors. All of this will facilitate the creation of jobs that would not have existed in a world without AI.
4 PwC (2017), “Sizing the prize: What’s the real value of AI for your business and how can you capitalise?”5 Ibid.
Phase 1: Productivity-driven impact Phase 2: Consumption-side impacts dominate
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2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Labour productivity Personalisation Time saved Utility
12 The economic impact of artificial intelligence on the UK economy
Thetransitiontimingisstillabigfactor
Thistime,itwillbe10Xfasterandscaleof300Xthanthelastindustrialrevolution.Wehavenotseenthislevelofdisplacementbefore.SourceMcKinsey
IkhlaqSidhu,contentauthor
ArgumentNarrative
• Couldyouhavestoppedthefirstindustrialrevolution?No,ifyouchosetonotparticipate,youwouldbecomeirrelevant:– Whobenefited:i)people/governmentswhocreatedthetools.ii)peoplewholearnedto“operatethemachine”,iii)thosethatinventordesigntheuse-caseorprocess.
– Whosuffered:displacedworkersanddisplacedeconomies.
• Massdisplacementalsomeanstherewillbealackofspending,butsofarnoeconomistshavevalidatedthisconcern.
• Innovativepeoplewithentrepreneurialbehaviorsarebestsuitedtosurvivetransition.Retraining willbeessential.Psychologyisthebiggestfactor.Weshouldconsiderhowtobestre-trainforthischange.
IkhlaqSidhu,contentauthor
Contact:
IkhlaqSidhuFoundingFacultyDirector,CenterforEntrepreneurship&TechnologyIEOREmergingAreaProfessor,UCBerkeleysidhu @berkeley.edu,scet.berkeley.edu
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