Fake news is down to YOU: Study reveals we tend to twist facts and statistics on controversial issues to fit our own beliefs

  • Study found that we twist numerical statics of topics to fit our own beliefs 
  • Study had one person remember the number of Mexican immigrants in the US
  • They twisted the information to show that it increased, when it really declined
  • That person then shared the information with someone else and so on
  •  Found numbers get father from the truth the more they are shared 

From news outlets to social media sites, there are numerous places that spread fake news, but a study has uncovered a new source – you.

Researchers found that people will misremember numerical statistics on a controversial topic in a way that fits their own commonly held beliefs.

For example, when people were shown that the number of Mexican immigrants in the United States declined recently during the study—which is true but goes against many people's beliefs—they tended to remember the opposite.

And the team also found that as people pass along this misinformation, the numbers can become further and further from the truth.

The study was conducted by a team at Ohio State University, who carried out two studies to investigate how people perceive and spread fake news.

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From news outlets to social media sites, there are numerous places that spread misinformation, but a study has uncovered a new source – you. Researchers found that people will misremember numerical statistics on a controversial topic in a way that fits their own commonly held beliefs

From news outlets to social media sites, there are numerous places that spread misinformation, but a study has uncovered a new source – you. Researchers found that people will misremember numerical statistics on a controversial topic in a way that fits their own commonly held beliefs

Jason Coronel, lead author of the study and assistant professor of communication at The Ohio State University, said: 'People can self-generate their own misinformation. It doesn't all come from external sources.'

'They may not be doing it purposely, but their own biases can lead them astray.'

'And the problem becomes larger when they share their self-generated misinformation with others.'

In the first part of the study, 110 participants were presented with short written descriptions of four societal issues that involved numerical information.

The team conducted pre-tests for two of the issues, which they found that the factually accurate numerical relationship fit with many people's understanding of the issue.

For example, many people generally expect more Americans to support same-sex marriage than oppose it, which coincides with public opinion polls.

For example, when people were shown that the number of Mexican immigrants in the United States declined recently during the study—which is true but goes against many people's beliefs—they tended to remember the opposite

For example, when people were shown that the number of Mexican immigrants in the United States declined recently during the study—which is true but goes against many people's beliefs—they tended to remember the opposite

But the researchers also presented participants with two issues for which the numbers didn't fit with how most people viewed the topics.

This includes the number of Mexican immigrants in the US.

Most people believe that the number of immigrants grew between 2007 and 2014 – but it was just the opposite.

The factual information revealed the number declined from 12.8 million in 2007 to 11.7 million in 2014.

Participants were then asked to write down the numbers that that were in the descriptions of the four issues.

And they were not told in advance they would have to memorize the numbers.

The researchers found that people usually got the numerical relationship right on the issues for which the stats were consistent with how many people viewed the world.

For example, participants typically wrote down a larger number for the percentage of people who supported same-sex marriage than for those who opposed it—which is the true relationship.

But when it came to the issues where the numbers went against many people's beliefs—such as whether the number of Mexican immigrants had gone up or down—participants were much more likely to remember the numbers in a way that agreed with their probable biases rather than the truth.

'We had instances where participants got the numbers exactly correct—11.7 and 12.8—but they would flip them around,' Coronel said.

'They weren't guessing—they got the numbers right. But their biases were leading them to misremember the direction they were going.'

By using eye-tracking technology on participants while they read the descriptions of the issues, the researchers had additional evidence that people really were paying attention when they viewed the statistics.

'We could tell when participants got to numbers that didn't fit their expectations,' Coronel said.

'Their eyes went back and forth between the numbers, as if they were asking 'what's going on.'

'They generally didn't do that when the numbers confirmed their expectations.'

'You would think that if they were paying more attention to the numbers that went against their expectations, they would have a better memory for them. But that's not what we found.'

In the second study, researchers investigated how these memory distortions could spread and grow more distorted in everyday life.

The childhood game of 'telephone' was constructed to investigate this issue.

The first person in the chain was give the correct statistics about the Mexican immigrants living in the US.

FAKE NEWS WRITING AI IS RELEASED TO THE PUBLIC 

An  artificial intelligence project capable of writing fake news that was deemed 'too dangerous' to release to the public has been recreated by two university students in August 2019.

Open AI, a project founded with the support of Elon Musk, is able to generate news stories from a headline or first line of text.

In February, the firm released a limited version of its software for other developers to use, to explore its potential.

The firm, which Musk is no longer involved in, has since launched an updated version of the software with half of the power of the full AI.

Now, computer science master's students Aaron Gokaslan and Vanya Cohen from Brown University have shared code for what they say is the full version.

The pair say they aren't hoping to cause chaos by releasing the code, but want to show that creating this kind of software is achievable without the resources of someone like Elon Musk.

They used free cloud computing time provided by Google to academic institutions to complete the project.

Speaking to Wired, Mr Cohen said: 'This allows everyone to have an important conversation about security, and researchers to help secure against future potential abuses.

'I’ve gotten scores of messages, and most of them have been like, "Way to go".'

The software, called GPT-2, was trained using eight million web pages, and adapts the style and content of what it produces in line with your input.

 

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They were then instructed to write it down that it went down from 12.8 million to 11.7 million from memory and then pass it along to the second person in the telephone chain, who had to remember them and write them down. The second person's estimates were then sent to a third participant and so on and so forth.

Results showed that, on average, the first person flipped the numbers, saying that the number of Mexican immigrants increased by 900,000 from 2007 to 2014 instead of the truth, which was that it decreased by about 1.1 million.

By the end of the chain, the average participant had said the number of Mexican immigrants had increased in those 7 years by about 4.6 million.

'These memory errors tended to get bigger and bigger as they were transmitted between people,' Sweitzer said.

Coronel said the study did have limitations. For example, it is possible that the participants would have been less likely to misremember if they were given explanations as to why the numbers didn't fit expectations.

And the researchers didn't measure each person's biases going in—they used the biases that had been identified by pre-tests they conducted.

Finally, the telephone game study did not capture important features of real-life conversations that may have limited the spread of misinformation.

But the results did suggest that we shouldn't worry only about the misinformation that we run into in the outside world, Poulsen said.

'We need to realize that internal sources of misinformation can possibly be as significant as or more significant than external sources,' she said.

'We live with our biases all day, but we only come into contact with false informationoccasionally.'

 

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