UNITED STATES OF AMERICA 

FEDERAL TRADE COMMISSION 

WASHINGTON, D.C. 20580 

Office of Commissioner 

Noah Joshua Phillips 

Dissenting Statement of Commissioner Noah Joshua Phillips 

Regarding the Combatting Online Harms Through Innovation Report to Congress 

June 16, 2022 

In December 2020, as part of the 2021 Appropriations Act, Congress tasked the Federal 

Trade Commission with conducting a study and reporting on whether and how artificial 

intelligence (“AI”) could be used to identify, remove, or take other appropriate action to address 

a variety of online harms.1

 Congress also required the FTC to recommend reasonable policies 

and procedures for using AI to combat these online harms, and any legislation to “advance the 

adoption and use of [AI]” for these purposes.2 I do not believe we conducted the requisite study, 

and I do not think the report on AI issued by the Commission (“AI Report” or “Report”) takes 

sufficient care to answer the questions Congress asked. The Report gives short shrift to how and 

why AI is being used to combat the online harms identified by Congress. Instead, the Report 

reads as a general indictment of the technology itself. I respectfully dissent. 

The FTC was given 12 months to conduct this study, and another six to prepare the 

Report and submit it to Congress. Rather than use this time to solicit input from all relevant 

stakeholders, the Commission chose to conduct a kind of literature review. I have tremendous 

respect for the career staff who worked hard to put this report together, but tasking one staff 

member to read and summarize select academic articles and news reports on AI does not 

constitute an adequate study. While academics and reporters have useful perspectives that should 

be considered, they should not be the only views represented. The Report has no information 

gleaned directly from individuals and companies actually using AI to try to identify and remove 

harmful online content, precisely what Congress asked us to evaluate. To address this, the 

Commission could have asked for such information. It could have put out a request for 

information giving all stakeholders the opportunity to provide information and views.3 The 

1 Consolidated Appropriations Act, 2021, Pub. L. No. 116-260, 134 Stat. 1182 (2020), 

https://www.congress.gov/116/plaws/publ260/PLAW-116publ260.pdf. 

2 Id. 

3 We do this routinely even where Congress has not asked us to prepare a report. Recently, the Commission sought 

to educate itself on subjects by issuing requests for information on topics such as factors that could have contributed 

to the infant formula shortage and contract terms that could harm consumers. See Solicitation for Public Comments 

on Factors that May Have Contributed to the Infant Formula Shortage and Its Impact on Families and Retailers 

(May 24, 2022), https://www.regulations.gov/document/FTC-2022-0031-0001; Solicitation for Public Comments on 

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Commission’s approach here departs from typical practice. In the past, the Commission has 

prepared congressional reports by issuing compulsory process, interviewing market participants, 

or conducting surveys.4 I do not understand why we did not follow this approach for this AI 

Report.5 

Take, for example, the Report’s discussion of how AI can be used to combat fake 

reviews, a target of recent FTC enforcement.

6

 Congress specifically directed us to study whether 

and how AI can be used to identify and remove fake reviews. The Report acknowledges that 

many large platforms use machine learning tools, often in conjunction with human review, to 

spot and remove fake reviews. Presumably, they do so for a reason. It would have been useful to 

ask the platforms how they view the efficacy of these tools.7 We did not do that. The closest the 

Report comes is to cite the results of a survey done by Fakespot, a company that developed a 

machine learning tool to help identify potentially fake reviews, which found that approximately 

31 percent of product reviews on Amazon, Walmart, eBay, Best Buy, Shopify, and Sephora 

Contract Terms that May Harm Consumers (Aug. 5, 2021), https://www.regulations.gov/document/FTC-2021-0036-

0022. 

4 See, e.g., Fed. Trade Comm’n, 2021 Report on Ethanol Market Concentration (Dec. 2021), 

www.ftc.gov/system/files/documents/reports/2021-report-ethanol-market-concentration/p063000_-

_2021_report_on_ethanol_market_concentration.pdf (relying on publicly available information and interviewed 

market participants); Fed. Trade Comm’n, Cigarette Report for 2020 (Oct. 2021), 

https://www.ftc.gov/system/files/documents/reports/federal-trade-commission-cigarette-report-2020-smokelesstobacco-report-2020/p114508fy20cigarettereport.pdf (issuing compulsory process in order to put together the report 

every year since 1967); Fed. Trade Comm’n, Virtual Worlds and Kids: Mapping the Risks (Dec. 2009), 

www.ftc.gov/sites/default/files/documents/reports/virtual-worlds-and-kids-mapping-risks-federal-trade-commissionreport-congress/oecd-vwrpt.pdf (surveying 27 online virtual worlds and obtained information directly from six 

specific virtual worlds); Fed. Trade Comm’n, Marketing Food to Children and Adolescents (July 2008), 

https://www.ftc.gov/sites/default/files/documents/reports/marketing-food-children-and-adolescents-review-industryexpenditures-activities-and-self-regulation/p064504foodmktingreport.pdf (issuing compulsory process); Fed. Trade 

Comm’n, Marketing Violent Entertainment to Children: A Review of Self-Regulation and Industry Practices in the 

Motion Picture, Music Recording & Electronic Games Industries (Sept. 2000), 

https://www.ftc.gov/system/files/documents/reports/marketing-violent-entertainment-children-review-selfregulation-industry-practices-motion-picture/vioreport.pdf (conducting surveys over a three month period). 

5 I have supported reports to Congress that did not include stakeholder input, but these reports were much narrower 

in scope and did not include recommendations for legislation. See, e.g., Fed. Trade Comm’n, Social Media Bots and 

Deceptive Advertising (Jul. 2020), ttps://www.ftc.gov/news-events/news/press-releases/2020/07/ftc-sends-reportcongress-social-media-bots-deceptive-advertising; Fed. Trade Comm’n, Shipping to Non-Foreign Areas (Apr. 

2020), https://www.ftc.gov/news-events/news/press-releases/2020/04/ftc-sends-report-congress-retailers-shippingpolicies. 

6 See, e.g., In the matter of Sunday Riley Modern Skincare, LLC, FTC File No. 1923008 (2019), 

https://www.ftc.gov/legal-library/browse/cases-proceedings/192-3008-sunday-riley-modern-skincare-llc-matter. 

7 It would likewise have been useful to ask smaller platforms about their experience using AI to deal with fake 

reviews. For example, we could have asked review platform Trustpilot about its experiences using a combination of 

AI and human review to identify and remove fake reviews. Trustpilot, Fighting fake reviews and misuse, 

https://www.trustpilot.com/trust/combating-fake-reviews. As is so often the case, the conversation the Report 

attempts to have only about “Big Tech” ought to be had as conversation about the technologies and business 

practices in question. 

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websites were unreliable.8 (This is, of course, an example of using AI to combat fake reviews.) 

The Report notes that automated detection efforts are worthwhile, but seemingly based on the 

fact that there are still fake reviews on the internet, concludes that the AI detection of fake 

reviews is not good enough. But there is no discussion of whether human review is any better at 

finding fake reviews – perhaps the question to ask in answering our congressional query. And 

there is zero attempt at a cost-benefit analysis. Does the time and money saved by using AI tools 

to detect and remove fake reviews outweigh the costs of the AI tools missing some percentage of 

fake reviews? Who knows? Congress deserves a better attempt at answering their question.9 

While many of the academics and reporters cited in the Report have important 

perspectives that we properly considered, the document does include some curious citations. 

(The public should not fail to read the footnotes.) Citing the AI Decolonial Manyfesto10 and the 

Twitter feeds of individuals, for example, is not the level of rigor that I expect to underpin an 

FTC report to Congress. The Report also frequently cites to the work and opinions of individuals 

currently employed by the FTC. While I am glad that the FTC has staff with interest and 

expertise in this area, I am concerned that the quantity of self-reference here calls the objectivity 

of the document into question. A report that includes recommendations, especially 

recommendations for legislation, will necessarily reflect the personal opinions of a majority of 

the Commission. Still, we should at least endeavor to produce a report that reflects the full 

diversity of experiences and viewpoints on these important issues concerning AI. 

8 Fakespot, US Online Shopping Ratings & Reviews Analysis Report (2021), 

useful information when considering policy recommendations. 

9 The Report’s discussion of whether AI can be used to identify counterfeit products will also leave a careful reader 

wanting. It lists four companies (eBay, Etsy, Facebook, and Alibaba) that have indicated that they use automated 

tools and declares that the efficacy of these tools cannot be determined. We should at least have asked. In May 2021, 

Amazon released a Brand Protection Report describing its efforts to protect its consumers, brands, sellers, partners, 

and store from counterfeits and fraud. It issued a second report in June 2022. Amazon Brand Protection Report (June 

asking whether and how AI can be used to identify counterfeit products should at least acknowledge companies’ 

2022), https://www.aboutamazon.com/news/small-business/amazons-brand-protection-report. A report to Congress 

public statements on the efficacy of their automated tools. We need not be credulous of those claims, of course; but 

if we have reason to doubt company claims, we should say so, and why. 

governances will emerge from community and situated contexts, questioning what currently constitutes hegemonic 

10 AI Decolonial Manyfesto, https://manyfesto.ai/index.html?s=03. The document states: “Notions of decolonial 

narratives. Decoloniality is not merely diversity and inclusion; removing the echoes of coloniality in AI will require 

reparations for present and past material and epistemic injustice and dispossession. These reinventions of AI 

governance will acknowledge the expertise that comes from lived experience, and will create new pathways to make 

it possible for those who have been historically marginalized to have the opportunity to decide and build their own 

dignified socio-technical futures. Decolonial governance will recognize, in a way that Western-centric governance 

structures historically have not, how our destinies are intertwined. We owe each other our mutual futures.” I am not 

sure what that means. 

https://www.fakespot.com/2021holidayreport. Fakespot’s survey and the AI Report both note that there was 

disparity among these websites. For example, the Best Buy website had a fake review percentage of 8.1 percent, 

while Walmart had a fake review percentage of 37.6 percent. If the Commission had reached out to Walmart and 

Best Buy we might have been able to determine some of the reasons for the discrepancies, which would have been 

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I do not believe the Reports spends enough time grappling seriously with the benefits and 

costs of using AI to combat online harms, and it spends too much time on detours out of the 

topics Congress identified for the Commission to study. One example is the plight of the 

information technology workforce. We were not asked to opine on employer-employee relations, 

an area where the FTC lacks jurisdiction and expertise and on which we are ill-suited to provide 

Congress with advice. The Report also preoccupies itself with advocating for researchers and 

journalists to have broader access to companies’ AI tools. On the flip side, it also criticizes 

technology companies that fund AI research, mostly based on the opinions of a few cited 

individuals. The history of American consumers benefitting from private sector research is long 

and rich, and it is far from clear why AI should be treated differently. But leaving that aside, the 

point is that all these issues are beyond our remit. 

The Report also states: “the only effective ways to deal with online harm are laws that 

change the business models or incentives allowing harmful content to proliferate.” Nothing in 

this Report actually supports this broad statement, and in fact it describes a variety of different 

business models, each of which it associates with the online harms in question.11 To be sure, our 

new(ish) technological capability for anyone to share anything they want with the world carries 

with it substantial problems, but that is not tied to a particular business model. If the Report has a 

view of which business models need to change and how, it should say so. 

Finally, I cannot shake discomfort with the Report’s discussion of using “inoculation 

theory” to “prebunk” the public against harmful content. Congress did not ask for an evaluation 

of the notion that alleged “misinformation” is a clearly identifiable harm against which people 

can and should be “inoculated,” and a government agency should tread carefully before crediting 

such strategies. How to moderate content at scale and what role the government should play has 

proven one of the most vexing public policy questions of our time. People have very different 

views.12 

On policy, I generally agree with the topline conclusion that government and companies 

should “exercise great caution in either mandating the use of, or over-relying on, [AI] tools even 

for the important purpose of reducing harms.”13 And the Report also provides a sufficient basis 

to conclude that humans should continue to be involved in combatting the online harms Congress 

identified. There are many questions around the current reliability and effectiveness of AI tools, 

11 For example, the Report discusses AI being used by Microsoft to find phishing and spam in Outlook, which is 

licensed to customers, and Facebook using AI to look for scams in Facebook Marketplace, which generates revenue, 

at least in part, from advertisements. Those are different business models; as is Bumble, a dating service that sells 

subscriptions and uses AI tools to blur automatically nude images shared within a chat. Bumble, With Bumble’s 

Private Detector, You Have Control Over Unsolicited Nudes, https://bumble.com/en-us/the-buzz/privatedetector. 

12 In its discussion of content moderation, the Report treats Twitter as a model. It describes the company as the 

“most outspoken platform” on content moderation issues, quotes its policy extensively, and implicitly praises 

Twitter’s “open internet principles” which, according to the Report, “prioritiz[e] ‘human choice and control’ over 

algorithms” and “promot[e] healthy conversations.” Fed. Trade Comm’n, Combatting Online Harms Through 

Innovation Report to Congress, 64, 70 (June 2022). Not everyone believes that Twitter’s content moderation 

policies should be the subject of imitation. 

13 Fed. Trade Comm’n, Combatting Online Harms Through Innovation Report to Congress, 5 (June 2022). 

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so it seems prudent to hold off on requiring their use as a matter of law and excluding from that 

use human intervention. The Commission should, however, take care that its enforcement actions 

do not have the effect of disincentivizing companies from employing human review. Last year, 

the Commission brought a case against ad exchange OpenX for violations of the Children’s 

Online Privacy Protection Act (“COPPA”) and Section 5 of the FTC Act.

14 OpenX claimed to 

take a unique human and technological approach to traffic quality and employed human review 

to assure compliance with its policies and to classify websites. OpenX’s human review failed. 

But it was only the human review that provided the “actual knowledge” needed for the 

Commission to obtain civil penalties under COPPA. If OpenX had relied entirely on automated 

systems, it might have avoided monetary liability. I voted for the case, but warned in my 

concurring statement that we should “weigh the instinct to penalize against the desire to foster a 

commercial environment where care is taken.”15 The Report reaffirms my view that we should 

exercise caution not to disincentivize human review. 

Had the Commission sought input from stakeholders and engaged in more than a cursory 

analysis of the effectiveness of AI tools in combatting the harms identified by Congress, I could 

have signed on to the Report. It did not. It did go beyond the questions posed into a discussion of 

a variety of topics, which raised standalone concerns. For these reasons, I cannot vote in favor of 

this Report. 

14 U.S. v. OpenX Technologies, Inc., Civil Action No. 2:21-cv-09693 (C.D. Cal. 2021), https://www.ftc.gov/legallibrary/browse/cases-proceedings/1923019-openx-technologies-inc. 

15 Concurring Statement of Commissioner Noah Joshua Phillips Regarding United States v. OpenX Technologies, 

Inc. (Dec. 15, 2021), 

https://www.ftc.gov/system/files/documents/public_statements/1598947/commissioner_phillips_concurring_stateme 

nt_open_x_final.pdf. 

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