Biden was not campaigning in New Hampshire, and voting in the primaries does not preclude voters from casting a ballot in November’s general election.

Kramer estimates he spent about $500 to generate $5 million worth of media coverage. In September 2024, the FCC finalized a $6 million fine against him for orchestrating illegal robocalls.

Dissemination and Widening the Divide

Bots and automation play a significant role in the spread of disinformation on social media platforms like X/Twitter, where they are used to amplify false narratives, manipulate public opinion, and create an illusion of widespread consensus on controversial topics. These automated accounts can rapidly share misleading content, interact with genuine users, and engage in coordinated efforts to boost the visibility of particular posts, making it difficult for users to differentiate between organic engagement and orchestrated campaigns. Bots are often programmed to retweet specific hashtags, engage with inflammatory content, and follow real users to increase their credibility, all while pushing disinformation to the top of trending topics.

A striking example of how bots manipulate conversations occurred during the height of the COVID-19 pandemic. Bots were responsible for a large portion of the misinformation regarding vaccines and public health measures, artificially inflating the visibility of conspiracy theories and false information about the virus.

Dan Woods, a former CIA and FBI cybersecurity expert and previous Head of Intelligence at F5, has previously discussed the severe impact of bots on X/Twitter in conversations with Elon Musk. Woods estimated that up to 80% of Twitter’s active accounts could be bots, further underscoring the extent to which automation can distort online discourse. This issue was highlighted in Musk’s bid to acquire Twitter, where the billionaire raised concerns about the number of bot accounts, potentially inflating the platform’s user metrics and affecting ad revenue. Woods’ insights highlight the pervasive influence of automated disinformation networks, making the detection and removal of these bots a critical challenge for social media platforms.

AI offers the ability to significantly enhance the capabilities of social media bots by enabling them to create fully-realized, convincing personas. These bots can be equipped with intricate backstories, complete with fabricated personal details such as employment history, hobbies, and even educational backgrounds, making them indistinguishable from real users. AI-generated bots can interact with both real and other fake users in ways that create an illusion of authenticity through connections, mutual likes, comments, and follower networks. By simulating these interactions, AI-enhanced bots can gain credibility and trust within online communities, embedding themselves into social groups over time. OpenAI has recently been working to make their products more persuasive and emotionally engaging, although this work isn’t necessarily intended to be applied to social media.^, 

In addition, bots can use large language models (LLMs) to craft highly realistic posts on a wide range of topics, from personal updates to nuanced political opinions. These posts can be used to subtly promote disinformation, stir controversy, or reinforce certain narratives without appearing out of place. For example, a bot embedded in a political discussion group could post detailed opinions about policy changes, referencing relevant articles or statistics to appear knowledgeable. The bot could also engage with real users by commenting on their posts, offering opinions, or sharing content that matches their interests, all while blending seamlessly into the social fabric. This level of sophistication makes AI-enhanced bots powerful tools for influencing conversations, shaping public opinion, and spreading disinformation across social media platforms.

Future AI

TV news has long been considered the last bastion of trustworthiness because it unfolds live, in real-time, where events are broadcast as they happen. To many of us, this would seem next to impossible to fake. Unlike pre-recorded or edited media, live broadcasts have an instinctual sense of authenticity. While deepfakes and AI-generated videos can be created rapidly, the content they deliver is still limited by the need for pre-scripted material, and the requirement to generate the content – even if this only takes mere minutes.

However, with advancements in AI, it’s becoming conceivable that in the near future AI could generate video content, including news broadcasts, in real-time. This could lead to the unsettling possibility of entire “news” shows featuring AI-generated anchors who can deliver, interact with, and even react to real-world events in real-time, blurring the line between authentic and synthetic information on a level never before seen.

Emotionally intelligent AI is a rapidly developing field in which LLMs are able to understand and react to human feedback and emotions. When used by fake news or social media bots, this has the potential to be a highly manipulative tool for deepening social divides. These AI-driven bots can analyze and understand the emotional tone of real people’s posts, detecting anger, fear, frustration, or bias in real-time. By recognizing these emotional cues, the AI can craft responses that are perfectly tailored to amplify those feelings, further inflaming tensions and reinforcing echo chambers. This ability to exploit emotional vulnerabilities allows disinformation campaigns to manipulate individuals on a personal level, fueling polarization, and making divisive issues even more contentious.

Combating Fake and AI-generated Content

The Coalition for Content Provenance and Authenticity (C2PA) protocol is a standards-based initiative designed to address the growing problem of disinformation and fabricated media, particularly in the era of AI-generated content like deepfakes. Jointly developed by organizations like Adobe, Microsoft, Intel, and the BBC, it provides a framework for attaching verifiable metadata to digital media files, allowing creators to disclose key information about the origin and editing history of an image, video, or document. By embedding metadata directly into the media file, C2PA aims to ensure that audiences can verify whether a piece of content is genuine or has been altered, offering an accessible, standardized way to track digital content’s authenticity across the internet.