In: Computer Science
“So much Fake News. Never been more voluminous or more inaccurate,” tweeted President Trump. A database of Trump remarks contains 320 references to fake news, named as term of the year in 2017. Leading news channels are not immune, for example in 2016 a story claiming HH Shaikh Mohammad Bin Zayed Al Nayhan had chanted a Hindu prayer went viral in India and was tweeted by main news channels. Fake news has been blamed for causing tension between countries, for example the Deputy Chairman of Dubai Police blamed Al Jazeera for deepening the crisis between Qatar and the UAE. Fake news has also resulted in tighter regulation of social media, and is now seen as a threat to democracy and free debate.
Historically, political interests have always misrepresented facts, but the identification, categorization and concept of fake news has become more complex and challenging. One team of students from Berkeley identified four classifications; clickbait, propaganda, commentary and humour and built a tool www.classify.news which scores the truth of information based on its URL. Their site claims 84% accuracy but the sample is based on only 5000 articles. IBM tested a prototype Question Answering Machine (QAM) called Watson to separate fact from fiction, and Google funded a fact checking operation called Full Fact to develop an automated fact-checking system. However, the successful implementation of fact checking models requires a constantly updated corpus of knowledge which is verified.
There are different data science architectures to check facts. The traditional NLP method of fake news detection is used by Thomson Reuters, a trusted global news source. Tracer News is a sensitive algorithmically driven system which filters news stories and social feeds for truth, and assigns a veracity score. It’s claimed to be 84% accurate, and with a sample of 5 tweets the system achieves 78% accuracy on distinguishing rumour and fact.
Research has shown that tweets containing false news spread faster and wider on Twitter than those with valid news. One estimate claims that in the month before the 2016 US election people read up to 3 articles of fake news. How this may possibly effect our attitudes is unknown, and psychologists have taken an interest in fake news. The Cognitive Reflection Test (CRT) was used to measure the ability to think analytically and consequently to predict people who can distinguish fake news from real news. Research has shown that if people agree with a message then they are more likely to believe it.
Social platforms such as Facebook are attempting to crack down on fake news in response to pressure. Facebook was accused of publishing fake posts using the name Lewis, who is a financial expert. Many people were thereby scammed to trust a financial product. Lewis pursued legal action to force social media to change their policy on advertising and be liable for hosting scams. Facebook are now playing an editorial role by changing the way News Feed functions. CEO Zuckerberg commented that sensationalism, misinformation and polarization are too common.
Countries such as Malaysia are making fake news punishable with up to 10 years in prison in an effort to protect national security. The law penalizes those who create, offer, circulate, print or publish fake news, which is defined as “any news, information, data and reports which is, or are, wholly or partly false whether in the form of features, visuals or audio recordings or in any other form capable of suggesting words or ideas”. Opponents call this an attack on freedom of speech and fear the new law could be used to penalize critical attacks on the government.
Human fact checkers are a rigorous and expensive way to combat fake news. A simple claim could take hours to verify and the manpower required could be considerable. If the responsibility lies with algorithms, false positives and negatives could lead to the suppression of a news story. In the UAE, the Youth Media Council is playing a role in the UAE’s strategy of developing the media sector and verifying credible from fake news. In a Dubai competition the winners research had explored a fake news incident whereby students’ names were spread on social media as soldiers who had died. Workshops to educate and teach young people skills to identify fake news were suggested.
Technology has enabled anyone to create news and for that news to go viral. The success of the message is not reliant on the truth of the contents, and there is too much information to validate. Many questions are raised about the effects of tagging news as fake, susceptibility to fake news, is fake news more real if its viral, and how to identify fake news. How can we create and sustain a global culture which promotes and values truth? What indeed is the truth of an event when multiple perspectives of the same event can hold truth.
Ques 1: What is/are the problem/problems here? Is there an underlying fundamental problem?
Answer: Fake news is the problem.False news spread faster and wider on Twitter and social platforms.Misinterpretation of facts leads to fake news.It takes lot of knowledge to check facts and algorithms to clarify difference between fake and real news.
Ques 2: Who are the major stakeholders and what are their
perspectives?
Ans: All the countries,people,social media platforms are major
stakeholders.Everyone is putting their effort to reduce fake news
as much as possible.
Ques 3: What are the major ethical, legal, and security aspects associated with the problem.
Ans: Fake news is a threat to democracy and free debate.
Fake news has been blamed for causing tension between countries,
for example the Deputy Chairman of Dubai Police blamed Al Jazeera
for deepening the crisis between Qatar and the UAE.
The law should penalize those who create, offer, circulate, print
or publish fake news, which is defined as “any news, information,
data and reports which is, or are, wholly or partly false whether
in the form of features, visuals or audio recordings or in any
other form capable of suggesting words or ideas.We should follow
Malasia law for dealing with fake news.
Ques: What are the intended and unintended consequences of existing
computing solutions? Consider the consequences on individuals,
organizations and society within local and global contexts
Ans: Intended Consequence implies no/less fake news being
created and spread.
Unintended consequences is it is a threat to democracy and free
debate.
Individuals can share their opionion based on information as it may
lead to misinterpretation of facts.
Organisations,social media platforms needs to make sure they do not
participate in creating,distribution of fake news.
Ques: What recommendations would you propose that will lead to potential solutions.
Ans: 1.We should create organisation that verifies crediblity
from fake news.
2. We should create strict laws so that people ensures
and circulates only validated information.
3.We can take help of technology.Artificial
Intelligence should be used for fact checking.