Can AI fight fake news?
The phenomenon of “fake news” may have captured the imagination of Americans during the 2016 presidential campaign and subsequent investigation of Russia’s attempts to change the election to Donald Trump using fake news on Facebook, among other schemes.
The truth is that fake or fake news has existed as a tool for a while and for many to spread propaganda and conspiracy theories for many years before the 2016 election. Websites like InfoWars and Brietbart, among others, have been spreading fake news that supports their agendas.
However, it has become a political and social problem since the elections and poor Facebook has become the example of websites that fell for the scheme.
Recently, the social media company has admitted its mistakes and tried to patch things up with its subscribers. You are now flagging fake news articles that go to Facebook members via your news feed. You are using AI to achieve this.
The company is using artificial intelligence to identify words or phrases that could mean that an article is actually fake. The data for this task is based on articles that Facebook members have individually flagged as fake stories.
Currently, the technology uses four methods to detect fake news. They include:
- Web page scoring. The first to use this technique was Google. Use facts to create a score for websites. Obviously rating websites is an act in progress. However, as Google has been doing, the technology has grown significantly.
- Weigh the facts. This method uses natural language processing engines to review the subject of stories. AI using other models discovers if other sites are reporting the same facts.
- Predict reputation. This technique is based on artificial intelligence that uses predictive analytics and machine learning to forecast website reputation by considering a number of characteristics including domain name and Alexa web rank.
- Discover great words. Advocates of fake news have used sensational headlines to capture the interest of a potential audience. This technique uncovers and flags fake news headlines using keyword analysis.
The actual detection of these types of items by AI is a difficult task. Of course, big data analytics is involved, but it also concerns the veracity of the data. Identifying it is really involved with determining the accuracy of the data. This can be done using the weighting of facts method. What happens if a fake news article appears on hundreds of websites at the same time? In this circumstance, using the technique of weighing the facts may cause AI to determine that the story is legitimate. Perhaps using the method of predicting reputation in conjunction with weighting of facts can help, but there could still be problems. For example, trusted news source websites that don’t take the time to verify a story might pick it up on the assumption that it is true.
It is obvious that the use of AI to identify these items needs further development. Various organizations are involved in improving AI capabilities. One of those establishments that is involved is West Virginia University.
The Reed College of Media in cooperation with the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University has created a course that focuses on using artificial intelligence to identify fake news articles.
Seniors taking a computer science elective course are working in teams to develop and implement their own AI programs and are also involved in the project.
Another group known as the Fake News Challenge is also looking for a way for AI to successfully combat fake news. It is a grassroots organization of more than 100 volunteers and 71 teams from academia and industry to tackle the problem of fake news. You are developing tools to help people verify and identify fake news.
As organizations work to improve artificial intelligence to find these stories, there are a variety of tools available to strike them down. These include:
Spike, who identifies and predicts breakouts and viral stories and uses big data to predict what will lead to engagement.
Hoaxy, which is a tool that helps users identify fake news websites.
Snoopey, which is a website that helps identify fake news articles.
CrowdTangle, which is a tool that helps monitor social content.
Meedan, which is a tool that helps to check the breaking news online.
Google Trends, which monitors searches.
La Decodes From Le Monde, which is a database of fake news and real news websites.
Pheme, which is a tool that verifies the veracity of user-generated and online content.