tempo ai - designing ai interfaces

DesigningAIInterfaces

RajSinghCEOTempoAI,Inc.

510-282-4229(M)raj@tempo.ai@mobileraj

“Itisthescienceandengineeringofmakingintelligentmachines,especiallyintelligentcomputerprograms. Itisrelatedtothesimilartaskofusingcomputerstounderstandhumanintelligence,butAIdoesnothavetoconfineitselftomethodsthatarebiologicallyobservable.”

“Itpasses theTuringtest.”

“Thestudyanddevelopmentofintelligentagents.”

“Softwarethatlearnsandcompletestasksforyou.”

WhatIsAI?

3

Raj:“WhatisAI?”Nephew:“It’srobotsandshit…”

AndthenthereisHollywood’sdefinition:

4RecommendationEngines- ImplicitandExplicitLearning

AIHasBeenOmnipresent

5ButthepuristssayWatsonisdumb!

ManyhavesaidWatsonwasthefirstmainstreamdemonstrationofAI

Anticipatory:“Predictyournextwantoraction”

Smart:“GivemeonlytheinformationIneed”

Assistant:“Completetasksforme”

Ihaveasmartphonebutit’snotsmart!

ButWhatIsMobileAI

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DesigninganAI-AssistedUXIsNotEasy

Designing95%UIYoudon’tknowifyourrecommendations arerightorwrong

Whatifthesuggestionwaswrong?Certainappsarealotmoreforgiving

Howdoestheusertrainthesystem?Mostsurveythattheywilltrainbutfewactuallydo.

Howdoyougetthedata?AIsuffersfromfalsestarts.

Allthataside,anticipatoryUIdesignisthenextfrontier!

SomeExamples(RecommendationEngines)

Pandora FourSquare LinkedIn

Doesthisbotheryou?

AnotherExample(RecommendationEngine)

Itdoesbecausetheserecommendationshaverightandwronganswers.

Flipboard vs Zite

ExtensiveML

LittletoNoML

• “Suggestions”– indicatesintelligence• “Recommendations”– slightlylowerbarthan“suggestions”• “Searched/Results”– lessintelligent

RecommendationLanguageMatters

TempoSearchedMeetingLocations

• Howdoyoudeterminethebalance?‒ Usertestingdoesn’talwayswork

• Constrainthedomain‒ Segment theusersviacohortanalysis‒ Whatistherightnumber ofsegments?

• The“More”buttoncanbeyourbestfriend‒ Infinitescroll

• Trainthesystem‒ Tempousertestingindicatedlessthan3%wouldtrain

‒ Thumbsup/down, ratingsvs implicitlearning?

BalanceofNoisevs Precision

PrismaticNewsTraining

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Siriisentertainingbutbeingunconstrainedkilledtheirengagement

• Itwouldannoyyouless• Youknowwhatyoucanaskanddo• You“settheexpectations”

ExamplesAutomatedsupportsystemsTellMe /Free411SalesforceVoiceAccess

ConstrainingCanSetExpectations

Lexee AppVoiceCommandsforSalesforce

• Animationsworkmosteffectively‒ Butifittakestoolong, ithinders theUX

• Speedofapplicationdirectlycorrelatedtoretentionrate‒ 15searchresultsvs 10searchresults(Google SearchResults)

• InTempo,wenumberedtheresults• Searchenginesusedtonumbertheirresultsaswell

IndicatingIntelligence

NumberedResultstoIndicateSmarts

• Falsestartsareverycommon‒ Introducerecommendations andanticipatoryactionsthrough use

• Keepon-boardingaslight-weightaspossible‒ Toomuchtimebetweenon-boardingandfirst-usewillcauseproblems

‒ Canyoucollectdataasyougoalong

• First3-Dayusagewillbeheavyexperimentationtoseewhatthesystemdoes‒ SiriusersexperimentbyaskingalotofQs

‒ Tempouserscreate10sofmtgs inthefirstfewdays

AINeedsData

Sosh Setup

BeingAnticipatory

• Anticipatewithoutthenoise‒ Pushnotificationsdriverepeatusagebutifnoisyresultinbounced users

• NotifyingyouwhentoleaveinTempo‒ Wewantedtobeveryanticipatorybutwe’renot95%yet

‒ Falsenotifications resultinangstandalostuser

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It’sJustBeginning!

FourSquare GoogleNow Prisimatic

Bigdatatosuggestplacestoexplore

Searchhistorytobecomemoreanticipatory

Machinelearningtosuggestrelevantnews

• Recommendationsworkbestwhentheusercan’ttellwhat’srightorwrong.

• Bespecificwithyourlanguagebecauseithelpssetexpectations• Bettertoundersellandover-deliver• Userswillwanttotrainthesystembutfewwilldoit.Beconsciousthattrainingmaycreateanaversereaction

• Cold-startsarecommon;needtohaveacompellingcaseandintegratetheuserdataover-time

• Useclustering/segmentationtoimprovethecold-start(egchooseyourinterests)

• Besensitiveaboutnotificationsandtrackengagementtomachinelearnonyournotifications

• UnderstandthatwhatyoumaythinkofasAI,theuserthinksisdumb(andvice-versa);incorporateanimationsorothertoindicateAI

Summarizing

Whatdoessmartmeanineverycoreapp?

RajSinghCEOTempoAI,Inc.

510-282-4229(M)raj@tempo.ai@mobileraj