[{"command":"settings","settings":{"ajaxPageState":{"theme":"hm_theme","theme_token":"V0w3wyziX8NYqWBhXDwV0ugHDAUZsH2ge93gYyrFEZI","libraries":"eJwDAAAAAAE"},"ajaxTrustedUrl":{"form_action_p_pvdeGsVG5zNF_XLGPTvYSKCf43t8qZYSwcfZl2uzM":true},"pluralDelimiter":"\u0003","user":{"uid":0,"permissionsHash":"2af85631393b514cbde3779a1f71d92618d53b94b54ea1960d28b2e2d121ff12"}},"merge":true},{"command":"openDialog","selector":"#drupal-modal","settings":null,"data":"\u003Cdiv id=\u0022republish_modal_form\u0022\u003E\u003Cform class=\u0022modal-form-example-modal-form ecl-form\u0022 data-drupal-selector=\u0022modal-form-example-modal-form\u0022 action=\u0022\/en\/article\/modal\/7049\u0022 method=\u0022post\u0022 id=\u0022modal-form-example-modal-form\u0022 accept-charset=\u0022UTF-8\u0022\u003E\u003Cp\u003EHorizon articles can be republished for free under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.\u003C\/p\u003E\n \u003Cp\u003EYou must give appropriate credit. We ask you to do this by:\u003Cbr \/\u003E\n 1) Using the original journalist\u0027s byline\u003Cbr \/\u003E\n 2) Linking back to our original story\u003Cbr \/\u003E\n 3) Using the following text in the footer: This article was originally published in \u003Ca href=\u0027#\u0027\u003EHorizon, the EU Research and Innovation magazine\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003ESee our full republication guidelines \u003Ca href=\u0027\/horizon-magazine\/republish-our-stories\u0027\u003Ehere\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003EHTML for this article, including the attribution and page view counter, is below:\u003C\/p\u003E\u003Cdiv class=\u0022js-form-item form-item js-form-type-textarea form-item-body-content js-form-item-body-content ecl-form-group ecl-form-group--text-area form-no-label ecl-u-mv-m\u0022\u003E\n \n\u003Cdiv\u003E\n \u003Ctextarea data-drupal-selector=\u0022edit-body-content\u0022 aria-describedby=\u0022edit-body-content--description\u0022 id=\u0022edit-body-content\u0022 name=\u0022body_content\u0022 rows=\u00225\u0022 cols=\u002260\u0022 class=\u0022form-textarea ecl-text-area\u0022\u003E\u003Ch2\u003ECan artificial intelligence help end fake news? \u003C\/h2\u003E\u003Cp\u003EWant to make yourself sound like Obama? In the past, that might have required physically imitating his voice, party-trick style. And even if you were very good at it, it almost certainly wouldn\u2019t present a danger to our democracy. But technology has changed that. You can now easily and accurately make anyone say anything through AI. Just use the service of an online program to\u0026nbsp;record a sentence and listen to what you said in a famous person\u0027s voice.\u003C\/p\u003E\u003Cp\u003EPrograms like this are often called deep fakes - AI systems that adapt audio, pictures and videos to make people say and do things they never did.\u003C\/p\u003E\u003Cp\u003EThese technologies could launch a new era of fake news and online misinformation. In 2017, \u003Ca href=\u0022https:\/\/www.nature.com\/news\/the-scientist-who-spots-fake-videos-1.22784\u0022 target=\u0022_blank\u0022 rel=\u0022noopener noreferrer\u0022\u003EHany Farid\u003C\/a\u003E, a computer scientist at Dartmouth College,US, who detects fake videos said the rapid proliferation of new manipulation techniques has led to an \u2018arms race\u2019. Just imagine what elections will be like when we\u2019re no longer able to trust video and audio. But some researchers are now fighting back and showing that AI can also be used for good.\u003C\/p\u003E\u003Cp\u003E\u2018AI has many ethical problems,\u2019 said Francesco Nucci, applications research director at the Engineering Group, based in Italy. \u2018But sometimes it can also be the solution. You can use AI in unethical ways to for example make and spread fake news, but you can also use it to do good, for example, to combat misinformation.\u2019\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EFact-checkers\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EHe is the principal researcher\u0026nbsp;on the \u003Ca href=\u0022https:\/\/cordis.europa.eu\/project\/rcn\/213549\/factsheet\/en\u0022 target=\u0022_blank\u0022 rel=\u0022noopener noreferrer\u0022\u003EFandango\u003C\/a\u003E project, which aims to do just that. The team is building software tools to help journalists and fact-checkers detect and fight fake news, says Nucci. They hope to serve journalists in three ways.\u003C\/p\u003E\u003Cp\u003EThe first component is what Nucci calls content-independent detection by using tools which target the form of the content.\u003C\/p\u003E\u003Cp\u003ENucci explains that today, images and video can easily be manipulated, whether through simple Photoshop or more complex techniques like deep fakes. Fandango\u2019s systems can reverse-engineer those changes, and use algorithms to help journalists spot manipulated content.\u003C\/p\u003E\u003Cp\u003E\u003Cblockquote class=\u0022tw-text-center tw-text-blue tw-font-bold tw-text-2xl lg:tw-w-1\/2 tw-border-2 tw-border-blue tw-p-12 tw-my-8 lg:tw-m-12 lg:tw--ml-16 tw-float-left\u0022\u003E\n \u003Cspan class=\u0022tw-text-5xl tw-rotate-180\u0022\u003E\u201c\u003C\/span\u003E\n \u003Cp class=\u0022tw-font-serif tw-italic\u0022\u003E\u2018Fake news is not a mathematical question of algorithms and data, but a very philosophical question of how we deal with the truth.\u2019\u003C\/p\u003E\n \u003Cfooter\u003E\n \u003Ccite class=\u0022tw-not-italic tw-font-normal tw-text-sm tw-text-black\u0022\u003EFrancesco Nucci, Engineering Group, Italy\u003C\/cite\u003E\n \u003C\/footer\u003E\n\u003C\/blockquote\u003E\n\u003C\/p\u003E\u003Cp\u003EAs these tools look at form, they don\u2019t check whether the content itself makes false claims, which is what Fandango\u2019s second line of research does. Here they link stories that have been proven false by human fact-checkers, and look for online pages or social media posts with similar words and claims.\u003C\/p\u003E\u003Cp\u003E\u2018The tools can spot which fake news stories share the same root and allow journalists to investigate them,\u2019 said Nucci.\u003C\/p\u003E\u003Cp\u003EBoth of these components strongly rely on various AI algorithms, like the processing of natural language. The third component allows journalists to respond to fake news.\u003C\/p\u003E\u003Cp\u003EA fake story might, for example, make the claim that a very high percentage of crimes in a European country are committed by foreign immigrants. In theory that might be an easy claim to disprove because of large troves of available open data, yet journalists waste valuable time in finding that data. So Fandango\u2019s tool links all kinds of European open data sources together, and bundles and visualises it. Journalists can use, for example, pooled together national data to address claims about crimes or apply data from the European Copernicus satellites to climate change debates.\u003C\/p\u003E\u003Cp\u003E\u2018This way journalists can quickly respond to fake stories and not waste any time,\u2019 said Nucci.\u003C\/p\u003E\u003Cp\u003ETheir tools are currently being tested by Belgian public broadcaster VRT, ANSA, the main Italian news agency, and CIVIO, a Spanish non-profit organisation.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EFake news detection\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EYet spotting fake news might not only be a question of finding untrue claims, but also of analysing massive amounts of social media sharing patterns, says Michael Bronstein, professor at the University of Lugano in Switzerland and at Imperial College London, the UK.\u003C\/p\u003E\u003Cp\u003EHe leads a project called \u003Ca href=\u0022https:\/\/cordis.europa.eu\/project\/rcn\/218443\/factsheet\/en\u0022 target=\u0022_blank\u0022 rel=\u0022noopener noreferrer\u0022\u003EGoodNews\u003C\/a\u003E, which uses AI to take an atypical approach to fake news detection.\u003C\/p\u003E\u003Cp\u003E\u2018Most existing approaches look at the content,\u2019 said Prof. Bronstein. \u2018They analyse semantic features that are characteristic of fake news. Which works to a certain degree, but runs into all kinds of problems.\u003C\/p\u003E\u003Cp\u003E\u2018There are, for example, language barriers, platforms like WhatsApp don\u2019t give you access to the content because it\u2019s encrypted and in many cases fake news might be an image, which is harder to analyse using techniques like natural language processing.\u2019\u003C\/p\u003E\u003Cp\u003ESo Prof. Bronstein and his team turned this model on its head, looking instead at how fake news spreads.\u003C\/p\u003E\u003Cp\u003EEssentially, previous studies show that fake news stories are shared online in different ways from real news stories, says Prof. Bronstein. Fake news might have far more shares than likes on Facebook, while regular posts tend to have more likes than they have shares. By spotting patterns like these, GoodNews attaches a credibility score to a news item.\u003C\/p\u003E\u003Cp\u003EThe\u0026nbsp;team has\u0026nbsp;built their first prototype, which uses graph-based machine-learning, an AI-technique in which Prof. Bronstein is an expert. The prototype is trained on data from Twitter where the researchers trace stories fact-checked by journalists and shown to be false. Journalists in this way train the AI-algorithm by showing it which stories are fake, and which are not.\u003C\/p\u003E\u003Cp\u003EThe GoodNews team hopes to monetise this service through a start-up called \u003Ca href=\u0022https:\/\/fabula.ai\/\u0022 target=\u0022_blank\u0022 rel=\u0022noopener noreferrer\u0022\u003EFabula AI\u003C\/a\u003E, based in London. While they hope to roll out the product at the end of the year, they envisage having customers such as large media companies like Facebook and Twitter, but also individual users.\u003C\/p\u003E\u003Cp\u003E\u2018Our bigger vision is that we want to become a credibility rating house for news, in the same way that certain companies rate a person\u0027s consumer credit score,\u2019 said Prof. Bronstein.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESolve\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOf course that leaves a bigger question - can technology really solve fake news? Both researchers are sceptical, but convinced technology can help. Nucci emphasises that the concept of fake news is contested, and that stories are often not entirely true, but also not entirely false.\u003C\/p\u003E\u003Cp\u003E\u2018Fake news is not a mathematical question of algorithms and data,\u2019 he said. \u2018But a very philosophical question of how we deal with the truth. Nevertheless our technology can help improve transparency around fake claims and misinformation.\u2019\u003C\/p\u003E\u003Cp\u003EProf. Bronstein says it would be naive to expect technology to solve the problem of fake news.\u003C\/p\u003E\u003Cp\u003E\u2018It\u0027s not just about detecting fake news. It\u2019s also a problem of trust and a lack of critical thinking. People are losing trust in traditional media and institutions, and that\u0027s not something that can be mitigated only through technology,\u2019 he said.\u003C\/p\u003E\u003Cp\u003E\u2018It requires efforts from all stakeholders, and hopefully our project can play a part in this larger effort.\u2019\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EThe research in this article was funded by the EU. 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