Winners of the AI and the News Open ChallengeWe’ve been absolutely blown away by the interest and excitement around our AI and the News Open Challenge. After several months and the efforts of a small army of amazing reviewers to sift through the 500+ applications we received, we’re excited to finally announce the winners of the challenge today. Since we launched the challenge back in September, the tricky questions at the intersection of machine learning and the news have only become more complex. Debates about the role of the news in shaping public understanding of machine learning and its societal implications continue to intensify. Questions loom over the role automation should play in augmenting the work of journalists. Whether machine learning-generated fakes will play a role in the future of efforts to manipulate the news and public discourse continues to be a widely discussed possibility. The seven winners of our $750,000 challenge represent a portfolio of incredible organizations seeking to attack these problems from a number of different angles:John S. and James L. Knight FoundationKF_a1198cd6-ebbf-11df-ae5d-52537a64ea2aMIT Media LabWe’d also like to thank our partners at the MIT Media Lab and Harvard’s Berkman Klein Center for Internet & Society, in addition to our funders, the John S. and James L. Knight Foundation, Luminate Group, William and Flora Hewlett Foundation, and Reid Hoffman.Harvard’s Berkman Klein Center for Internet & SocietyLuminate GroupWilliam and Flora Hewlett FoundationReid HoffmanAI & the News Open Challenge ReviewersWe’d also like to thank the following people who took the time to join us in reviewing the applications. The pool of reviewers represents a diverse group of experts from the fields of journalism, technology, research and other disciplines:Amanda LevendowskiNYU LawAmar AsharBerkman-Klein CenterAnthony OrtizMILAAron PilhoferTemple UniversityCameron HickeyHarvard Kennedy SchoolClarence WardellResults for AmericaClement WolfGoogleDevin GaffneyCrayonErik ReynaThe Washington PostGeraldine MoribaJSK Fellow at Stanford UniversityHong QuHarvard Kennedy SchoolJeremy GilbertThe Washington PostJessica FordeProject JupyterJoy BonaguroCorelightJustin MyersAssociated PressKat LoUniversity of California, IrvineKatyanna QuachThe RegisterKim FoxThe Philadelphia InquirerLillian RuizCivil MediaMeredith BroussardNYUMi-Ai ParrishMAP Strategies GroupNatalie NzeyimanaNuancedNathan Olivarez-GilesAppleNicholas HagarNorthwestern UniversityNick DiakopoulosNorthwestern University & Tow CenterOrlando WatsonHoneycombRetha HillArizona State UniversitySam GreenspanBellwetherTaylor NakagawaTechCrunchTing CaiMicrosoft/BingTricia WangData & Society, Berkman Klein Center for Internet & Society at Harvard UniversityEli PariserUpworthyEugene YiCorticoHilary RossAssembly Program at the Berkman Klein Center and MIT Media LabJohn BrackenDigital Public Library of AmericaJohn KeefeQuartzJulia AngwinThe MarkupLatoya PetersonMarie-Therese PngDeepMindMarina Walker GuevaraICIJNatalie SaltielMIT Media LabRenata BarretoBerkeley Law / GeorgetownSamuel WoolleyDigital Intelligence LabSharon ChanSeattle TimesStephanie DinkinsStony Brook UniversityStephanie PereiraNew IncTom SimoniteWiredVeronica AvilaRestaurant Opportunities Centers United_20409440-5021-11e9-b006-4fd8861d81c0To address questions at the intersection of machine learning and the news_2040965c-5021-11e9-b006-4fd8861d81c0Ethics & Decision MakingInvestigate the ethics of algorithms and the implications of automated decision making._20409742-5021-11e9-b006-4fd8861d81c01ChequeadoChequeado, a veteran fact-checking organization based in Argentina, will be launching a new investigative series on the ethics of algorithms and the implications of automated decision making for Latin America. ArgentinaLatin America_2040980a-5021-11e9-b006-4fd8861d81c0Community MediaTrain community media journalists to uncover and analyze machine learning systems._204098e6-5021-11e9-b006-4fd8861d81c02Craig Newmark Graduate School of JournalismSandeep Junnarkar and his team at CUNY will be launching a program that trains community media journalists to uncover and analyze machine learning systems, with an eye towards producing a series of news pieces looking at the impact of these technologies on immigrants and low-income communities.CUNYSandeep JunnarkarCommunity Media JournalistsImmigrantsLow-Income Communities_204099a4-5021-11e9-b006-4fd8861d81c0Work & LaborReport on the implications of machine learning and automation on work and labor._20409a6c-5021-11e9-b006-4fd8861d81c03Seattle TimesThe Seattle Times will run a year-long reporting project focused on the implications of machine learning and automation on work and labor.The project will aim to connect broader technological trends with the near-term, practical questions of who gets the gains from these technologies and how they are distributed._20409b5c-5021-11e9-b006-4fd8861d81c0Government DocumentsSift through massive government document dumps._20409c2e-5021-11e9-b006-4fd8861d81c04MuckRock FoundationThe MuckRock Foundation will be building on its long-standing public records requests platform to launch Sidekick, a toolkit of machine learning classifiers that will support newsrooms and researchers in meeting the challenge posed by sifting through massive government document dumps.NewsroomsResearchers_20409cf6-5021-11e9-b006-4fd8861d81c0Government ContractsExtract structured data from government contracts._20409ddc-5021-11e9-b006-4fd8861d81c05Legal RobotLegal Robot will develop a tool that will apply machine learning to quickly extract structured data from government contracts.CitiesThis engineering effort will be paired with a campaign to request millions of city, county and state-level contracts from around the United States.CountiesStates_20409eae-5021-11e9-b006-4fd8861d81c0Fact CheckingBuild a tool to support the efforts of fact-checkers working in India._20409f8a-5021-11e9-b006-4fd8861d81c06Tattle Civic TechnologiesTarunima Prabhakar and Denny George at Tattle will build a tool to support the efforts of fact-checkers working in India, specifically targeting the challenge of addressing misinformation on the WhatsApp platform.Tarunima PrabhakarDenny GeorgeFact-Checkers in IndiaWhatsAppThe tool will experiment with using machine learning for tasks like language detection and image matching, which are frequently needed in the fact-checking process._2040a084-5021-11e9-b006-4fd8861d81c0Video & AudioIdentify evidence that a given piece of video or audio is a fake generated via machine learning._2040a16a-5021-11e9-b006-4fd8861d81c07Rochester Institute of TechnologyMatt Wright and his team at RIT will experiment with techniques to assist researchers and the public in identifying evidence that a given piece of video or audio is a fake generated via machine learning.Matt WrightJournalistsThese techniques will then be field tested with journalists and media forensics experts who are on the frontlines of identifying and evaluating media “in the wild.” Media Forensics Experts_2040a246-5021-11e9-b006-4fd8861d81c02019-03-122019-03-26https://aiethicsinitiative.org/news/2019/3/12/announcing-the-winners-of-the-ai-and-the-news-open-challengeOwenAmburOwen.Ambur@verizon.net