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Why crowdsourcing is the solution to data annotation

The process of annotating data to prepare high-quality training data is a major hurdle in any AI development project. For small teams of data scientists, having to manually label enough data points to create good training data consumes a lot of valuable time. visit https://www.tictag.io/ for more

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Why crowdsourcing is the solution to data annotation

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  1. Whycrowdsourcing isthesolution to data annotation It iseasytogetconfusedwhenthere aresomanydifferent areasofAI, butsimply put,AIisthe ability foracomputertodoworknormallydonebyhumansbyimitating human intelligence. Artificial intelligence Artificialintelligenceis aversatiletechnology thatseesuseinadiverserangeof industries. Itwouldseemthere’snothingAIisn'tcapableofaswecontinuetopush the boundariesofautomation.Many processesandjobs cannow becompletedwith much greaterefficiency thanksto theaid ofAImodels.However,despiterapid advancementinAIoverthelastfew years,mostMachineLearning modelsstillrely oneducation fromhumansin theformofdataannotation. Theprocessofannotatingdatatopreparehigh-qualitytrainingdataisamajorhurdle inany AIdevelopmentproject.Forsmallteamsofdatascientists,havingtomanually labelenoughdatapointstocreategoodtrainingdataconsumesalotofvaluable time.This time isbetterused making insights andworkingonotherareasof development,somanycompanieschoose to outsourcetheirannotationworkto specialised dataannotationcompanies.

  2. Whatiscrowdsourcing? Theact ofcrowdsourcinginvolvesobtainingthehelpofa largeandusually open groupofpeopletocompleteacertaintask.In thescopeofdataannotationthiscan beespeciallyeffectiveatgettinglargeamountsofdatalabelled.Togiveanexample, for adata setcontaining1,000 datapoints,a groupof200peoplewouldonly need to label 5pointseachcomparedtoa teamof20peoplelabelling50pointseach. Dividing thisworkamongalargergroupofpeoplealsomeansitislesstaxingon eachindividual,whichincreases thelikelihoodofconsistentlyaccuratelabellingfor eachdatapoint.Crowdsourcingallowshugenumbers ofdatapointstobelabelledin a fractionofthetimeitwouldtakeatraditional annotation team. Howdoes Tictag use the power ofcrowdsourcing? AtTictagwehavetakena uniqueapproachtotappingon the powerof crowdsourcing.Oneofthe maingoalswehaveisto makedata annotation accessibletoeveryonewhilealsomakingit fun,easy,andrewarding. Toachievethis,weuseagamified platform,specially designedfor mobilityandinclusivity,to introducegame elementstostandarddataannotation. Withthis,theprocessofdataannotationistransformedfromatraditionallyslowand tiringprocess forasmallgroupofpeopletosomethingthatcanbedonequicklyand easily by anyonewithasmartphone.Beingableto performthesetasksatany time and placeintheworldisalsoagreatadvantageofbeingamobileapplication. Buildingacommunity ofskilledandenthusiasticdatalabellersor“Taggers”isnotan easypursuit. Alargeincentive forpeopleto becomea part ofthe Taggercommunity is thecoin-basedrewardssystemweuse. As Taggerscompletedifferenttypes of annotationtaskstheyearncoinsbasedontheaccuracy andnumberofdatapoints theylabel.These coins areexchanged for arangeofprizeslikeGrab/Amazon vouchers,householdappliances,electronicsand more. Additionally,specialbig ticketitems alsocomeandgoas part oftheselectionof redeemablerewards.Badgescanalsobeearnedby taggingfrequentlyand consistently toshow aTagger’sskillanddedicationtotagging,andtorewardand recognisethemfor familiaritywithaparticulartask.A largecrowdalsomeansthat

  3. youmightfindexpertiseinspecificnicheareasthatmightnot otherwisebeeasy to comeby! Amainconcern forcrowdsourcingdataannotationworkistheaccuracy ofthe labels. Fortunately,ourannotationplatformcomesinthe formofaneasy-to-usephone basedappwithanintuitiveUIwhichgivesusersahighlevelofcontroltotag accurately. Tasks arebrokenupwhendistributedto the crowd,andarebrought togetheragaintoensurethehighestlevelofaccuracypossible.Severalquality control measuresarealsointegratedintoourannotationprocessthatensuresthe production ofhigh-quality labelleddata. Sourcedfrom:https://www.tictag.io/post/crowdsourcing-solution-data-annotation

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