technology application and ethical considerations

Deepfake technology carries deep ethical implications, heightening concerns about misinformation and manipulation. By seamlessly blending fabricated content with reality, deepfakes undermine trust in the media and public discourse. And since people's images are exploited without their consent, this also puts personal safety at risk.

Trust issues are on the rise as distinguishing truth from lies becomes more challenging. Mitigating these ethical quandaries requires proactive measures, including robust detection systems and regulatory frameworks.

What are deepfakes?

Developments in generative artificial intelligence (genAI) and large language models (LLM) have given rise to deepfakes. The term “deepfake” is based on the use of deep learning (DL) to recreate new but fake versions of existing images, video or audio footage.

Deep learning is a special type of machine learning that involves “hidden layers.” This is a series of nodes in a neural network that perform mathematical transformations of real images into really good but fake ones. The more hidden layers there are in a neural network, the “deeper” it is. Neural networks, and especially recursive neural networks (RNN), are known for being quite good at image recognition tasks, so using them to create deepfakes is easy.

There are two main types of instruments. The first is generative adversarial networks (GANs), which pit two networks against each other. One network (the generator) creates a deepfake, and the other (the discriminator) tries to identify it as a fake. Constant battle improves the forger and the detector.

Another type is autoencoders, which are neural networks that learn to compress data and then recreate it. This allows data to be manipulated and deepfakes generated by changing the compressed version.

Criminal activity using deepfakes

There are countless legitimate uses for deepfakes today, in industries such as arts, entertainment and education. In the film industry, this technology could, for example, be used to de-age actors, allowing them to play younger versions of themselves without the need for makeup or stunt doubles. In the latest Indiana Jones film, actor Harrison Ford looked more than 40 years younger. Deepfakes are also used to “bring back to life” historical figures or events, providing a visual representation that adds depth and immediacy to the narrative.

But the problem is that deepfakes are used not only for legitimate purposes, this is especially critical for modern society, in which the vast majority of people get information about the world and form opinions based on content from the Internet. That is, anyone capable of creating deepfakes can spread misinformation and influence the masses into behavior that somehow furthers the faker's self-interest. Deepfake-based disinformation can wreak havoc on a micro- and macro-scale.

On a small scale, deepfakes can, for example, create personalized videos in which a relative appears to be asking for a sum of money to help them out of an emergency situation.

Globally, fake videos of famous world leaders making fictitious statements can provoke violence and even war.

Using synthetic content to carry out cyber attacks

Between 2023 and 2024, frequent phishing attacks and social engineering campaigns resulted in account breaches, asset and data theft, identity theft, and reputational damage to businesses across all industries.

An infamous deepfake attack was a fraud incident that affected a bank in Hong Kong in 2020. The manager received a call from the “company director” asking for authorization of the transfer as the company was about to make a takeover. Additionally, he received an email signed by the director and lawyer, which looked real, but both the document and the voice were fake. The manager made the transfer. Investigators were able to track the stolen funds and found that 17 people were involved in the fraud.

There is also a possible risk for insurance companies as fraudsters can provide evidence through deepfakes for illegal claims. Insurance fraud using fake evidence is not a new phenomenon. But while in the era of analog photography it required a lot of effort and experience, today image processing tools are part of any specialized software.

Attacks on medical infrastructure

While the threat of deepfakes in healthcare remains largely hypothetical, the industry is proactively addressing the threat. The concerns cover several key areas:

• false content can interfere with the dissemination of accurate health information, potentially undermining trust in reliable sources;

• Fraudsters can use convincing audio and visual materials to deceive patients by posing as medical professionals to obtain confidential data;

• Hackers can use synthesized audio to break into hospital systems.

Back in 2019, Israeli researchers demonstrated how MRI or CT scans could be altered using malware. As part of the demonstration, they hacked and edited medical 3D scans to add images of tumors. Radiologists were then brought in to interpret the results and were unable to distinguish between real and fake scans.

There are many motives for such attacks, including falsification of research evidence, insurance fraud, corporate sabotage, job theft, terrorism, etc.

Evidence in court proceedings

The spread of deepfakes can cause anyone to doubt the veracity of evidence. The fact that fake information can be both compelling and difficult to identify also raises concerns about how this technology could compromise the court's duty to find the truth.

How to protect yourself or your business from deepfakes?

Trying to bring perpetrators of deepfakes to justice is fraught with challenges. In addition to the difficulty of identifying offenders, manufacturers, like other cybercriminals, may operate across national borders. That said, while deepfakes have the potential to have widespread and dangerous consequences for our society, they remain largely unregulated.

However, there are several steps people can take on their own to reduce the risks associated with deepfake activity.

1. Publicity and vigilance. Knowledge is the first line of defense. Regular training sessions and seminars can equip company employees with the tools to distinguish between genuine and fraudulent content.

2. Secure communication channels. Ability to use encrypted communication channels and multi-factor authentication platforms for mission-critical business communications, especially those related to finance or sensitive internal matters.

3. Investing in cybersecurity. Cybercriminals are becoming masters of artificial intelligence, and stopping them may require fighting fire with fire.

There may not be a perfect solution to protect against the dynamic threat of deepfake fraud. As technology develops, people will find new ways to use it for both innocent and otherwise purposes. However, there are strategies that organizations and individuals can use to prevent deepfake fraud and mitigate its impact if it occurs.

Moreover, scientists, researchers, and tech company founders are now working together on ways to track and label AI content. Using a variety of methods and forming alliances with news organizations, they hope to prevent further erosion of the public's ability to understand what is true and what is not.

1. Manufacturers Sony, Nikon and Canon have begun developing ways to imprint special “metadata” that lists when and by whom a photo was taken at the exact moment the image was created.

2. Some companies, including Reality Defender and Deep Media, have created tools that detect deepfakes based on the underlying technology used by AI image generators.

But even if all the methods implemented are successful and all the big tech companies fully join them, people will still have to think critically about what they see on the Internet.

Addressing ethical, societal, and personal dilemmas requires a multifaceted approach to deepfake detection. A legal framework is also needed to protect the rights and privacy of individuals. Awareness, public awareness of the responsible use of AI must be woven into business operations, government initiatives and industry stakeholder pathways. Collaboration between technology developers, policymakers, researchers, and society at large is critical to overcome the challenges posed by deepfakes.

However, it's not all bad. This technology has enormous positive potential for the public. It opens the door to use cases that could bring amazing transformations to the world, such as improving accessibility for people with disabilities, educational tools to simulate various scenarios and events that would otherwise be inaccessible, or the invention of personalized virtual assistants capable of human interaction and virtual communication.