With the rapid rise and increased access to artificial intelligence, fraud concerns were predicted to disrupt the 2024 election as misinformation circulated throughout. In addition to influencing voters’ perceptions, AI has been used to suppress voter turnout and provide false statements made by candidates.
Major tech companies are actively responding to the deepfake issue through collaborative initiatives aimed at minimizing the risks associated with deceptive AI content. The “Tech Accord to Combat Deceptive Use of AI in 2024 Elections” was signed at the Munich Security Conference, and commits firms like Microsoft, Google, and Meta to develop technologies that detect and counter misleading content, particularly in the context of elections.
While these companies are making strides to combat deepfakes, it is important that the general public has an understanding of the potential threats created by deepfakes. As the vast amount of content on social media makes it extremely difficult to catch every instance of manipulated media, education on how to spot misleading content created by AI will be necessary. Otherwise, these fraudulent and deceptive uses of AI could impact the informed decisions of voters in future elections.
Understanding Deepfakes
A deepfake is synthetic media created using artificial intelligence and machine learning techniques. It typically involves manipulating or generating visual and audio content to make it appear as if a person has said or done something that they haven’t in reality. Deepfakes can range from face swaps in videos to entirely AI-generated images or voices that mimic real people with a high degree of realism.
In 2024, around 20 states passed regulations against election deepfakes after deepfake robocalls of President Joe Biden and Senator Lindsey Graham circulated to thousands of voters in New Hampshire and hundreds in South Carolina. Social media platforms have seen an increase in deepfakes and many experts have warned about the rapid spread of fraudulent content distributed by fake news outlets. With the lax verification process on some platforms, accounts mimicking refutable sources are able to easily post misleading information under the guise of legitimacy.
Identifying Suspicious Content
Adopting real-time deepfake detection systems that use different techniques to spot manipulated content will be necessary for platforms as deepfakes increase. Key components integral to deepfake detection include machine learning algorithms that scan for unusual patterns or errors, data comparison that analyzes the content with original sources, and segment inspection that spots signs of manipulation.
Companies are working around the clock to create solutions for rapid detection rather than preemptive blocking. They are also developing advanced digital watermarking techniques for authenticating AI-generated content and partnering with governments and academic institutions to promote ethical AI practices. Additionally, companies continuously update their detection algorithms and raise public awareness about deepfake risks through educational campaigns, demonstrating a strong commitment to addressing this emerging challenge.
In law enforcement, many agencies are integrating AI solutions into training protocols and partnering with software providers to better protect the public from the growing threat of deepfakes. Understanding the evolving landscape of AI-enabled crimes will be crucial in the development of counter-AI technologies, while continuous training for investigators will be necessary to recognize and combat AI-enabled threats.
Filtering Through Misinformation
Misinformation poses a growing challenge, especially during election periods where public trust in the democratic process is critical. AI-driven solutions like deepfake detection have become helpful tools in combating the spread of false narratives. By leveraging advanced algorithms, AI can rapidly analyze digital content and flag doctored images, videos, or misleading articles before they can reach a wide audience. This real-time filtration ensures that voters receive verified information, keeping a transparent electoral process and minimizing the potential for manipulation.
Beyond detection, AI can proactively identify trends in misinformation, allowing platforms and regulators to address emerging issues. By analyzing vast amounts of online data, AI highlights patterns and origins of false narratives. Integrating these tools into media platforms not only curbs the spread of fake content but also promotes accountability among content creators.
Elections in an AI-Powered Future
In an AI-powered future, elections will benefit from higher levels of security and transparency. By harnessing AI’s capabilities, governments and organizations can protect democratic institutions against interference while empowering citizens with truthful and trustworthy information. As these technologies evolve, the focus needs to remain on ethical use cases to ensure voters are confident in the electoral process.
