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People are trying to claim real videos are deepfakes. The courts are not amused

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Summary

Recent attempts to use deepfakes as evidence in court have been unsuccessful. Elon Musk's lawyers recently tried to argue that comments he made at a conference in 2016 could have been altered, but the judge did not accept this argument. Other defendants have also tried to use deepfakes as a defense, but have been unsuccessful. Experts are worried that as the technology becomes more prevalent, people may become more skeptical of real evidence and bad actors may weaponize this skepticism. Courts are adapting to these challenges, but the reverberations from AI fakes may still be felt. There is a danger of people not believing documented evidence of events, which could have corrosive effects.

Q&As

What is the "liar's dividend" and how is it being used in relation to deepfakes?
The "liar's dividend" is a term coined by law professors Bobby Chesney and Danielle Citron in a 2018 paper to describe the idea that as people become more aware of how easy it is to fake audio and video, bad actors can weaponize that skepticism.

What challenges do deepfakes present to privacy, democracy, and national security?
Deepfakes present challenges to privacy, democracy, and national security by being used to spread propaganda and disinformation, impersonate celebrities and politicians, manipulate elections, and scam people.

What are the consequences of denying real events that are documented by video recordings?
The consequences of denying real events that are documented by video recordings are that it has a corrosive effect on society and can lead to people no longer believing documented evidence of events such as police violence, human rights violations, or a politician saying something inappropriate or illegal.

What measures are courts taking to address deepfakes being used to rebut evidence?
Courts are taking measures to address deepfakes being used to rebut evidence by not buying claims of deepfaked evidence and ruling that public figures cannot simply say whatever they like in the public domain and then hide behind the potential for their recorded statements being a deep fake to avoid taking ownership of what they did actually say and do.

What are the implications of expecting more proof of evidence being real due to the prevalence of deepfakes?
The implications of expecting more proof of evidence being real due to the prevalence of deepfakes is that it could shut out people who don't have the resources to hire experts and make it more expensive and time-consuming for the other side to get that damning piece of evidence admitted.

AI Comments

👍 It is great to see that the courts are not buying claims of deepfaked evidence and that they are taking steps to ensure that justice is served.

👎 It is concerning that people are becoming more aware of how easy it is to fake audio and video, as this could lead to bad actors weaponizing that skepticism.

AI Discussion

Me: It's about how people are trying to use deepfakes to challenge the validity of real videos, and the implications this could have in the court system. Apparently, Elon Musk's lawyers tried to argue that a video of him speaking at a conference could have been fake, but the judge did not accept their argument.

Friend: Wow, that's pretty concerning. It seems like this could be a way for people to try and get away with lying and other unethical behavior.

Me: Exactly. It could also be a way to discredit real evidence, making it harder for people to get justice in court, especially if they don't have the resources to hire experts to prove the authenticity of the evidence. It's also worrying that this could lead to people doubting the validity of real events, like police violence or human rights violations, and it could be hard to reason about the world if there's no longer an accepted reality.

Action items

Research the legal implications of deepfakes and their potential use in court.
Create a plan for how to respond to accusations of deepfaked evidence.
Develop strategies to ensure that real evidence is not dismissed due to the prevalence of deepfakes.

Technical terms

Deepfakes: AI-generated images or videos that appear to show people saying or doing things they never actually said or did.
AI: Artificial Intelligence. A type of computer technology that can be used to create deepfakes.
Liar's Dividend: A term coined by law professors Bobby Chesney and Danielle Citron in a 2018 paper laying out the challenges deepfakes present to privacy, democracy, and national security. The idea is, as people become more aware of how easy it is to fake audio and video, bad actors can weaponize that skepticism.
CSI Effect: A phenomenon in which juries come to expect more proof that evidence is real, due to the prevalence of deepfakes.