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Home»AI & Censorship»EFF Joins Call for FTC to Drop Its Disastrous AI Policy Proposal
AI & Censorship

EFF Joins Call for FTC to Drop Its Disastrous AI Policy Proposal

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EFF Joins Call for FTC to Drop Its Disastrous AI Policy Proposal
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The Federal Trade Commission (FTC) in July issued a proposed policy statement “concerning the suppression of accuracy in artificial intelligence systems.” We urge the FTC to withdraw this misguided proposal and instead focus on its core strengths and mission to protect consumers. 

The new proposed policy builds on, and directly references, the Trump administration’s  “Preventing Woke AI in the Federal Government” executive order—a nightmare for civil liberties that seeks to strong-arm AI companies into modifying their models to conform with the its ideological agenda. In recently filed comments, EFF,  Public Knowledge, and Fight for the Future call for the FTC to stop its unconstitutional efforts to regulate lawful speech, override state laws, and intimidate AI developers into ideological alignment with the Trump administration.

The government may not install itself as the arbiter of truth.

In the joint comments, we outline three critical flaws within the latest proposed policy. First, it violates the First Amendment. The policy calls for the Commission to become the judge of which AI outputs meet an undefined standard of accuracy. Installing the FTC as the authority of this sort of viewpoint-based judgment is a prior restraint on speech. Additionally, the policy’s proposed solution to address speech concerns compounds, rather than properly limits, the likely harms to speech. As we say in our comments: the government may not install itself as the arbiter of truth. 

Second, it exceeds the FTC’s legal authority by claiming that its federal regulatory rules can override, or “preempt,” laws in states that have passed to regulate artificial intelligence use. This is clearly an attempt to target state laws the administration disagrees with. For example, the policy specifically criticizes Colorado’s automated decisionmaking law, which applies when automated technology is used to consider consequential decisions such as those around employment, access to housing, health care, and insurance. We noted to the FTC that characterizing this law as one that requires AI companies to “suppress accuracy,” or encourages deception, is itself inaccurate. In any case, the FTC lacks the authority to put its rules in place over state law, unless Congress directly delegates it that power. It has been given no such power here.

Third, the policy is vague and sets the stage for improper jawboning of AI developers and companies that use AI tools (deployers). Jawboning is a term for situations in which the government urges private companies or people to censor another’s speech. The proposal, as written, creates an enforcement regime that would put a thumb on the scale in favor of certain partisan speech and ideals. This will lead companies to censor only what the administration interprets as biased or untruthful. Yet, in our filing, we note that the FTC itself can’t define an objective standard for what “bias” means, conceding the “exact line of what constitutes bias may be difficult to draw.”

There is work the FTC should be doing to protect consumers in the age of AI. In our comments, we conclude by saying:

[We] implore the Commission to focus on its core strengths and the mission for which it is so urgently needed—promoting structural market competition and protecting consumers from real unfair and deceptive acts and practices—in both the burgeoning and critically important AI industry and across the broader technology marketplace.

EFF and our partners have always urged the FTC to police genuine deception in technology markets. We have also consistently opposed government efforts to dictate what private speakers may say. That’s why we urge the FTC to withdraw this proposal. 

You can read our full comments here. 

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#AlgorithmicBias #BigTechCensorship #DataRights #InternetFreedom #OpenInternet #PlatformAccountability
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