The Age of Inauthenticity: AI-Fueled Election Interference and Generative AI Scams

Introduction

In the digital age, authenticity is under siege. Generative AI, with its ability to create realistic text, images, and audio, has opened up new avenues for deception and manipulation. From AI-aided dirty tricks in elections to sophisticated voice cloning scams, the consequences of AI-driven inauthenticity are far-reaching and pose a significant threat to trust and democracy.

AI-Aided Dirty Tricks and the Threat to Elections

In the 2020 New Hampshire primary, robocalls impersonating President Joe Biden were used in an attempt to influence voters. This incident highlights the ease with which AI-generated voice clones can be created and deployed for malicious purposes, raising concerns about the potential for widespread election meddling.

Beyond elections, voice cloning scams are on the rise. Fraudsters impersonate loved ones or company executives to extract money or sensitive information. These scams are becoming increasingly sophisticated, making them difficult to detect.

The Illusion of Digital Watermarking as a Solution

In response to the growing threat of AI-generated misinformation, many have suggested digital watermarking as a potential solution. However, digital watermarks are easily removable, rendering them ineffective in combating deepfakes and other forms of generative AI fraud.

Furthermore, there is a lack of consensus on how to watermark AI-generated text and audio, making it even more challenging to address the issue.

The Need for a Layered Approach to Authenticity

Getty Images CEO Craig Peters emphasizes the need for a layered approach to authenticity, recognizing the limitations of digital watermarking alone. He proposes a combination of metadata, provenance standards, and cryptographic hashes stored in immutable databases as a more robust solution. However, he acknowledges that even these measures are not foolproof and that further efforts are required to combat AI-generated fraud effectively.

The Urgency of Addressing the Problem

The sheer volume of AI-produced images in the past year surpasses the total photographs taken throughout history. This staggering statistic underscores the need for immediate action to mitigate the impact of AI-driven inauthenticity.

AI News and Developments

– Sam Altman is in talks with Middle Eastern investors and chipmakers to establish an AI computing chipmaker rivaling Nvidia.

– AI startup Cohere plans to raise up to $1 billion in further venture funding, potentially exceeding its previous valuations.

– Questions arise regarding the lofty valuations of high-flying generative AI startups, given their relatively low gross profit margins compared to the industry average.

– A new standard, Fairly Trained, aims to certify AI models as “fairly trained” by ensuring permission for copyrighted materials used in training.

– Controversy erupts as a Japanese literature prize is awarded to a novel partially written with ChatGPT’s assistance, sparking debates about AI’s role in literature.

Research Advancements and Ethical Concerns

– Google DeepMind’s system demonstrates impressive problem-solving capabilities in complex geometry problems, comparable to human competitors.

– Law enforcement’s use of facial recognition software raises ethical concerns. In Berkeley, California, police attempted to generate a lead in a cold case by using DNA-derived facial images and running them through facial recognition software. This practice has the potential to implicate innocent people due to the limitations and unreliability of such AI-powered technologies.

Conclusion

The age of inauthenticity demands a proactive response. Better regulation and understanding of AI software used by law enforcement are essential to mitigate the risks of misuse and protect innocent individuals. State and federal rules requiring police to comprehend the risks and take steps to minimize them are urgently needed.

We must demand transparency and accountability from AI developers and users, promoting ethical practices and ensuring that AI is used for the benefit of society, not to manipulate and deceive.