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Fact Checking

Critical Thinking Approach: Data-Driven Fact-Checking Skills

Discover the importance of data-driven fact-checking in today's information-rich world. Learn how to distinguish reliable information from misinformation while cultivating critical thinking skills for a well-informed perspective.

With so much information at our fingertips, the need for accurate and reliable data has never been greater. Relying on data-driven fact-checking can help us better understand what’s real and reputable over what’s false and misleading, but in addition to a technology-based approach, we also need to develop our own critical thinking approaches. 

But as the case with any kind of skill development, where do you even begin? In this article, we’ll take a closer look at what data-driven fact-checking actually means, how it’s implemented and how you can develop your own critical thinking skills alongside the developments in technology to accurately judge and inform yourself as the digital landscape continues to grow and shift. 

Why Is Critical Thinking So Important? 

With the rise of fake news, misinformation and information overload, it’s easy to turn passive and just accept whatever comes your way as fact. It’s also a very risky strategy that if left unchecked, can have real-world consequences. By developing data-driven fact-checking skills, you empower yourself to understand truth from fiction and make more informed decisions by pulling from the most accurate information around you. 

What Skills Should You Develop for Better Data-Driven Fact-Checking? 

Developing your data-driven fact-checking skills isn’t something that can happen overnight, but the more you familiarize yourself with the process and use it when evaluating the credibility of an article, a picture or a video, the more your critical thinking skills will improve. That means: 

Verifying the Source

Not all sources are created equal. You often can’t tell how credible a specific source is just by looking at the title or the author. Take a deeper look at the author’s credentials and any affiliations that they’re part of which might reveal human biases within the article. 

It also helps to cross-reference the claim. If multiple sources are making the same claim across a variety of types of content (for example, an eyewitness video, a news article and a podcast discussion all cover the same claim consistently), it’s more likely to be true. 

Beyond this, trustworthy sources aren’t afraid to cite where they got their data from. The highest quality of these citations come from peer-reviewed journals, academic research, clinical studies and other detailed and heavily-scrutinized sources of content. If you’re concerned, look at those sources as well 

Understanding the Data

With a critical thinking approach to fact-checking, you need to go beyond just “checking your sources” and also understand the data behind them. That means reading beyond just the numbers in isolation. For example, if a supplement is said to be “100% effective” but the sample size was super low, you’d understand the conditions the product was tested under and could draw conclusions accordingly.

Beyond just casting a critical eye at the numbers themselves, understanding the different types of data is also a fundamental critical thinking skill worth developing. For example, being aware of the differences between qualitative and quantitative data and when you’d use each one. 

Having a basic mathematical and statistical understanding is also important to be able to interpret data effectively, calculate percentages correctly and spot any obvious errors or exaggerations in the conclusions that others draw from the research. 

Statistical Analysis

This is the point at which many people get into the weeds, however, developing statistical analysis skills when combined with data-driven fact-checking can help you see disinformation and misinformation much more easily and draw attention to misleading facts and figures as they occur.

This can mean everything from having an understanding of variances and when they matter to being able to spot data patterns including normal and skewed distributions. One of the most common pitfalls in interpreting the data is confusing correlation with causation. Just because two variables move together doesn’t mean that one caused the other. 

Comparative Analysis

In addition to crunching the numbers, doing a time-series analysis or comparing data over time to understand trends, any oddities or anomalies or any sudden shifts that might need a deeper look is yet another fact-checking skill worth honing. 

Sometimes it can also pay to look at the data across different regions or countries. For example, according to The Guardian, false information is flagged on Facebook 70% of the time when it’s in English, but when the same information appears in Spanish, it’s flagged only 30% of the time. 

Recognize Your Own Human Bias

Humans aren’t without our own inherent bias, and this bias can seep over into the AI and training materials as well as the deeper machine learning algorithms we rely on to help us fact-check information. 

Biases such as confirmation bias, or information that confirms our own pre-existing beliefs, as well as publication bias, or that studies reflecting positive information are more likely to be published than those which are neutral or negative, can go a long way in helping to support data-driven fact-checking efforts that are reliable and reputable. 

How Can Technology Help?

Both artificial intelligence and machine learning play a vital role in the fact-checking world. Many platforms, including fact-checking platforms like Full Fact in the UK, and Google’s Fact Check Explorer leverage one or both of these types of technologies to help them scan incredible amounts of information quickly and flag any potential issues. 

And although technology is great at crunching the numbers and sifting through vast amounts of content quickly, human judgment is still needed to understand the information in context and interpret it in a way that is meaningful. 

Current Fact-Checking Challenges

Although data-driven fact-checking is helping to stem the tide of misinformation, disinformation and fake news, it’s not without its challenges. Data overload is the most common. There are billions upon billions of pieces of data created every day on Facebook alone and it can be easy for both humans and machines to get overwhelmed. 

At times, the most visually-digestible versions of the information, usually charts, graphs and infographics, can be manipulated to support a specific point of view or narrative. Sometimes sources aren’t readily available or accessible which can lead to “verification gaps” which in turn hinder the process. 

How Do We Develop a Culture of Critical Thinking? 

One of the biggest steps we can take culturally is to promote the idea of skepticism. Be aware before blindly accepting any claim and particularly those which are tuned to draw out strong emotions such as political claims, societal or human rights abuses, public health claims and environmental issues among others.  

In addition, encouraging schools to incorporate life skills like data literacy and critical thinking as part of their curriculum can help build these skills in the next generation, which will likely have to grapple with this problem on a much larger and more deeply-ingrained level than what we’re currently dealing with. 

Different online platforms will rise and fall, and as we continue to progress well into the digital age, we shouldn’t rely on any one of them as our be-all,end-all “beacon” of truth. Expect that data-driven fact-checking will become even more essential to our daily lives and no longer be relegated to something that’s squarely in the realm of academics or engineers. By creating a society that values critical thinking and keen judgment, we can help minimize the impact of misinformation while helping to promote truth and credibility on a global scale.

Sherice Jacob

Sherice Jacob is a seasoned copywriter and content professional fluent in English, Spanish, and Catalan, with over 25 years of experience crafting high-converting copy. Passionate about AI, she enjoys exploring the new innovations and possibilities it brings to the world of content creation.

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