What is an AI DeepFake?

The term deepfake refers to videos, images, or audio of a real or fictitious person’s likeness or voice generated or substantially modified using deep learning, a subset of machine learning that  drives many AI  applications.

Lawmakers are grappling with the issue of regulating AI deep fakes and other manipulated media, particularly regarding elections.  Here are 8 key points to consider:

Goal of Regulation

The primary goal should be to protect voters and elections from deceptive media that influences voting decisions.

Type Of Conduct

The focus should be on manipulated media designed to mislead voters about elections (when, where, how to vote) or undermine election integrity (false claims of fraud).

Regulation Methods:

Options include requiring labels on deep fakes in campaign ads and potentially banning certain deep fakes, like those depicting candidates spreading misinformation.

Who Should Be Included

Regulation could target creators and distributors of deepfakes, as well as online platforms that allow them.

Informed Electorate:

Deepfakes can threaten an informed electorate by creating deceptive campaign ads. Labeling deepfakes can help mitigate this threat.

Election Integrity:

Deepfakes used to spread misinformation about fraud or other irregularities can undermin e trust in elections.  Regulation can help prevent this.

Protecting Candidates & Workers

Deepfakes can be used to intimidate or defame candidates and election workers. Existing laws like libel may be sufficient, but regulation could be explored.

Curbing Deceptive Discourse:

While regulating deep fakes used in broader political debates is tempting, the line between misinformation and opinion can be blurry.  Carve-outs may be needed to protect free speech.

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