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What are the most effective deepfake detection techniques for journalists?

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Visual clues

2

Metadata analysis

3

Machine learning models

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Human verification

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Here’s what else to consider

Deepfakes are synthetic media that manipulate the appearance or voice of a person or a scene using artificial intelligence. They can be used for entertainment, education, or activism, but also for deception, propaganda, or misinformation. As a journalist, you need to be able to spot and verify deepfakes before you report on them or use them as sources. In this article, you will learn about some of the most effective deepfake detection techniques and tools that can help you do that.

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    Mila Banerjee
    Pronti AI Outfit Generator: Helping Consumers and Fashion Retailers find outfit inspiration by leveraging data…
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    Anaida Fernando
    Information Security Analyst @ Compare the Market | MSc | PgCHPE | BSc (Hons) | Certified in Cybersecurity (CC) | AWS…
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    Amiani Linda
    Aspiring Diplomat | Multimedia Journalist - MCK018979
    1

1 Visual clues

By using your own eyes and common sense, or tools like InVID or Forensically, you can detect deepfakes by looking for visual clues that reveal inconsistencies or anomalies in the image or video. These clues may include facial distortions such as blurred edges, mismatched lighting, or unnatural expressions; eye movements such as lack of blinking, irregular pupils, or unrealistic reflections; lip synchronization such as delays, gaps, or misalignments between the audio and the video; and background details like missing or duplicated objects, warped perspectives, or sudden changes.

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    Anaida Fernando

    Information Security Analyst @ Compare the Market | MSc | PgCHPE | BSc (Hons) | Certified in Cybersecurity (CC) | AWS Cloud Practitioner | XRY

    • Report contribution

    Deepfakes often fall short of capturing subtle nuances and imperfections that are characteristic of authentic human behaviour. Pay close attention to facial movements, lip-syncing accuracy, and vocal intonation. educate yourself on best practices for identifying and mitigating the impact of manipulated media. Educate yourself on best practices for identifying and mitigating the impact of manipulated media.

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    Amiani Linda

    Aspiring Diplomat | Multimedia Journalist - MCK018979

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    Source Verification: Verify the original source of the content by cross-referencing it with reliable, trusted sources. Contact the alleged creator or subject of the video or image to confirm its authenticity. Reverse Image/Video Search: Use tools like Google Reverse Image Search or specialized deepfake detection platforms to search for similar content on the internet. Deepfakes often have subtle inconsistencies in facial features, such as mismatched eye movements, blinking irregularities, or unnatural skin tones. Pay close attention to these details.

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    Algie Desucatan

    Loan Processor | Writer | Prompt Engineer

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    Be skeptical and curious about any audiovisual content you encounter online or offline. Do not accept everything at face value but question its origin, purpose, context, evidence, etc. Use multiple sources and perspectives to cross-check any information you receive. Do not rely on one source or perspective but seek out diverse and credible ones that can provide different viewpoints on the same topic

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2 Metadata analysis

To detect deepfakes, you can examine the metadata of the image or video. This information can describe its origin, format, and characteristics. For example, you can check the file name, size, and type to see if it has been edited, compressed, or converted. Additionally, you can look at the creation and modification dates to determine if the file has been altered or tampered with. Moreover, you can look at camera model settings and location to see if the file was captured by a specific device or in a specific place. Lastly, Exif data is a standard format for storing metadata in images and videos. You can use tools like ExifTool or Metapicz to extract, display, or modify the metadata of a media file.

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    Amiani Linda

    Aspiring Diplomat | Multimedia Journalist - MCK018979

    • Report contribution

    Analyze Metadata: Examine the metadata of the file to check for inconsistencies or signs of manipulation. This can include timestamps, geolocation data, and editing software information.

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3 Machine learning models

A more advanced way to detect deepfakes is to use machine learning models that can compare the image or video with a large database of real or fake examples and generate a score or a label that indicates its likelihood of being authentic or manipulated. For example, FaceForensics++ is a framework that can detect and classify deepfake videos based on facial features and movements; DeepFakeLab is a tool that creates and detects deepfake videos using various algorithms and techniques; and Deepware Scanner is an app that scans and verifies images and videos using a neural network and a blockchain system. You can use these models online or offline, depending on your needs and preferences. However, it's important to note that machine learning models are not infallible and can be fooled by new or sophisticated deepfake methods.

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4 Human verification

The final way to detect deepfakes is to rely on human verification, which involves contacting the original source, author, or subject of the image or video and asking them to confirm or deny its authenticity. To do this, you can reach out to the person or organization who published or shared the media file and ask for more information or evidence. You can also contact the person or entity that appears in the media and ask for their consent or opinion. Additionally, you can consult with experts, colleagues, or fact-checkers who have more knowledge or experience on the topic or technique. Tools like Whois, TinEye, and Google Reverse Image Search can help you find contact details, origin, or similar images of a media file.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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    Mila Banerjee

    Pronti AI Outfit Generator: Helping Consumers and Fashion Retailers find outfit inspiration by leveraging data, context, and personal items. Our AI shifts the experience from typing to visualizing.

    • Report contribution

    The realism of AI/ML models is progressing at a rate that it is difficult to keep up to. What today we can sensorily (visual or auditory clues) discern is not real will evolve to imperceptible. Future tools, regulations, and systems may allow us an edge to identify but the best defense is to cultivate a well rounded critical thinking mindset. Well rounded in understanding many motivations, many sources, and many perspectives.

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    Amiani Linda

    Aspiring Diplomat | Multimedia Journalist - MCK018979

    • Report contribution

    Deepfake technology is continually evolving, and detection techniques must keep pace with these advancements. Journalists should stay informed about the latest developments in deepfake detection and collaborate with experts in the field to enhance their verification capabilities.

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