# Deepfake of Pelosi (2019)

A slowed-down video of Nancy Pelosi, a form of cheapfake, spread widely on social media in May 2019, misleadingly making her appear intoxicated or impaired during a public speech.

The Deepfake of Pelosi (2019) refers to a manipulated video of Nancy Pelosi, then Speaker of the United States House of Representatives, that circulated widely on social media in May 2019. The video was not a deepfake in the technical sense of using [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) or [machine-learning](https://www.wikiprompt.org/wiki/machine-learning) to generate synthetic content, but rather a 'cheapfake' - a simple editing technique that slowed down the footage to approximately 75% of its original speed, altering the pitch of her voice and making her appear slurred or intoxicated. The incident became a landmark case in the public understanding of manipulated media, highlighting how low-tech alterations can be as deceptive as sophisticated AI-generated content.

The original footage was from a speech Pelosi gave at the Center for American Progress on May 23, 2019. The altered version, which first appeared on Facebook, was viewed millions of times across platforms including Facebook, Twitter, and YouTube. It was shared by prominent figures, including then-President Donald Trump, who tweeted the video without context. The spread prompted widespread media coverage and public debate about the nature of misinformation, the responsibility of social media platforms, and the potential for manipulated media to undermine democratic processes.

## Technical Nature and Distinction from Deepfakes

Unlike true deepfakes, which use [deep-learning](https://www.wikiprompt.org/wiki/deep-learning) and [neural-network](https://www.wikiprompt.org/wiki/neural-network) models to generate or replace faces, the Pelosi video was created through basic video editing. The slowdown was achieved by adjusting the playback speed and pitch, a technique that requires no specialized software or technical expertise. This distinction is crucial because it demonstrates that misinformation does not always require advanced technology; simple tools can be equally effective in deceiving audiences. The term 'cheapfake' was coined to describe such low-cost manipulations, contrasting with the high-resource requirements of AI-based deepfakes.

The video's effectiveness lay in its plausibility. Pelosi's speech was already delivered in a deliberate, measured tone, and the slowdown exaggerated this to the point of appearing unnatural. Viewers unfamiliar with her speaking style were more likely to accept the altered version as authentic. This case underscored the importance of media literacy and the need for platforms to develop policies for detecting and labeling manipulated content, regardless of its technical sophistication.

## Platform Responses and Policy Debates

Facebook initially refused to remove the video, citing its policy against censorship, but later added a warning label that described it as 'partly false' after fact-checkers flagged it. Twitter also declined to remove it, with CEO Jack Dorsey stating that the company would not delete content unless it violated specific rules. YouTube allowed the video to remain but demonetized it and added a fact-check link. These responses were inconsistent and drew criticism from researchers and lawmakers who argued that platforms needed clearer guidelines for handling manipulated media.

The incident accelerated discussions about content moderation policies. In the following months, major platforms began developing more robust frameworks for addressing synthetic and manipulated media. By early 2020, Facebook announced a policy to remove deepfakes that were likely to mislead, though it continued to allow 'parody' and 'satire'. Twitter introduced a similar policy in March 2020, labeling manipulated media that could cause harm. The Pelosi video became a reference point in these policy debates, illustrating the challenges of balancing free expression with the prevention of misinformation.

## Legal and Political Implications

The video raised questions about existing laws and their applicability to manipulated media. In the United States, there was no federal statute specifically addressing deepfakes or cheapfakes at the time. Some states, such as California, later enacted laws targeting deepfakes in political contexts, but these were not in place in 2019. Pelosi herself did not pursue legal action, but her office condemned the video as 'sexist trash' and called on platforms to take responsibility.

The incident also highlighted the gendered nature of disinformation. Pelosi, as a high-profile female politician, was subjected to a form of attack that played on stereotypes of female incompetence and intoxication. Researchers noted that women in politics are disproportionately targeted by such tactics, which aim to undermine their credibility and fitness for office. This aspect of the case drew attention from scholars studying the intersection of gender, media, and politics.

## Legacy and Influence on Misinformation Research

The Pelosi video became a case study in misinformation research, cited in academic papers and policy reports. It demonstrated that the threat of manipulated media is not limited to AI-generated content, and that simple edits can have significant real-world consequences. The term 'cheapfake' entered the lexicon of media scholars, complementing the more widely known 'deepfake'. Researchers at institutions like [stanford-ai-lab](https://www.wikiprompt.org/wiki/stanford-ai-lab) and [berkeley-ai-research](https://www.wikiprompt.org/wiki/berkeley-ai-research) incorporated the case into their analyses of information ecosystems.

The incident also influenced the development of detection tools and fact-checking methodologies. Organizations such as [xerox-parc](https://www.wikiprompt.org/wiki/xerox-parc) and [mit-csail](https://www.wikiprompt.org/wiki/mit-csail) explored automated methods for identifying manipulated videos, though these efforts faced challenges due to the subtle nature of the alteration. The case underscored the need for human oversight in addition to technical solutions, as automated systems often struggle to distinguish between benign edits and malicious manipulations.

## Broader Context and Ongoing Relevance

In the years following the incident, the landscape of manipulated media has evolved significantly. Advances in [generative-ai](https://www.wikiprompt.org/wiki/generative-ai) and [large-language-model](https://www.wikiprompt.org/wiki/large-language-model) technologies have made it easier to create realistic synthetic content, raising new concerns about authenticity and trust. However, the Pelosi video remains a reminder that not all misinformation requires cutting-edge technology. As of 2024, the video continues to resurface periodically on social media, often without context, demonstrating the persistence of such content.

The case also contributed to public awareness of media manipulation. Surveys conducted after the incident showed increased recognition among Americans of the potential for altered videos to deceive. This awareness has been accompanied by growing calls for media literacy education and platform accountability. The Pelosi video, though technically simple, has had a lasting impact on how society understands and responds to the challenge of digital misinformation.

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Source: https://www.wikiprompt.org/wiki/deepfake-of-pelosi-2019
License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
Last updated: 2026-09-14T04:14:07.716358+00:00