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Misleading Project Veritas Accusations of Google “Bias” Could Prompt Bad Law

Tomorrow, the Senate’s Judiciary Committee’s Subcommittee on The Constitution will hold a hearing on Google’s alleged anti-conservative bias and “censorship.”  In a video released last month, James O’Keefe, a conservative activist, interviews an unnamed Google insider. The film, which has been widely shared by conservative outlets and cited by Sen. Ted Cruz (R-TX) and President Donald Trump, stitches a narrative of Orwellian, politically-motivated algorithmic bias out of contextless hidden camera footage, anodyne efforts to improve search results, and presumed links between unrelated products. Although the film’s claims are misleading and its findings unconvincing, they are taken seriously by lawmakers who risk using such claims to justify needless legislation and regulation. As such, they are worth engaging (the time stamps throughout this post refer to the Project Veritas video that can be viewed here).

Search algorithms use predefined processes to sift through the universe of available data to locate specific pieces of information. Simply put, they sort information in response to queries, surfacing whatever seems most relevant according to their preset rules. Algorithms that make use of artificial intelligence and machine learning draw upon past inputs to increase the accuracy of their results over time. These technologies have been adopted to improve the efficacy of search, particularly in relation to the gulf between how users are expected to input search queries, and the language they actually use to do so. They are only likely to be adopted to the extent that they improve the user’s search experience. When someone searches for something on Google, it is in the interest of both Google and the user for Google to return the most pertinent and useful results.

Board game enthusiasts, economics students, and those taking part in furious public policy debates over dinner all may have reasons to search for “Monopoly.” A company that makes it the easiest for such a diverse group of people to find what they’re looking for will enjoy increased traffic and profit than competitors. Search histories, location, trends, and additional search terns (e.g. “board game,” “antitrust”) help yield more tailored, helpful results.

Project Veritas’ film is intended to give credence to the conservative concern that culturally liberal tech firms develop their products to exclude and suppress the political right. While largely anecdotal, this concern has spurred hearings and regulatory proposals. Sen. Josh Hawley (R-MO) recently introduced legislation that would require social media companies to prove their political neutrality in order to receive immunity from liability for their users speech. Last week, President Trump hosted a social media summit featuring prominent conservative activists and conspiracy theorists who claim to have run afoul of politically biased platform rules.

The film begins by focusing on Google’s efforts to promote fairer algorithms, which are treated as attempts to introduce political bias into search results. The insider claims that while working at Google, he found “a machine learning algorithm called ML fairness, ML standing for machine learning, and fairness meaning whatever they want to define as fair.” (6:34) The implication being that Google employees actively take steps to ensure that Google search results yield anti-conservative content rather than what a neutral search algorithm would. Unfortunately, what a “neutral” algorithm would look like is not discussed.

Although we’re living in the midst of a new tech-panic, we should remember that questions about bias in machine learning and attempts to answer them are not new, nor are they merely a concern of the right. Rep. Alexandria Ocasio-Cortez (D-NY) and the International Committee of the Fourth International have expressed concerns about algorithmic bias. Adequate or correct representation is subjective, and increasingly a political subject. In 2017, the World Socialist Web Site sent a letter to Google, bemoaning the tech giant’s “anti-left bias” and claiming that “Google is “’disappearing’ the WSWS from the results of search requests.”

However, despite the breathlessness with which O’Keefe “exposes” Google’s efforts to reduce bias in its algorithms, he doesn’t bring us much new information. The documents he presents alongside contextless hidden camera clips of Google employees fail to paint a picture of fairness in machine learning run amok.

One of the key problems with O’Keefe’s video is that he creates a false dichotomy between pure, user created signals and machine learning inputs that have been curated to eliminate eventual output bias. The unnamed insider claims that attempts to rectify algorithmic bias are equivalent to vandalism: “because that source of truth (organic user input) has been vandalized, the output of the algorithm is also reflecting that vandalism” (8:14).

But there is little reason to presumptively expect organic data to generate more “truthful” or “correct” outputs than training data that has been curated in some fashion. Algorithms sort and classify data, rendering raw input useful. Part of tuning any given machine learning algorithm is providing it with training data, looking at its output, and then comparing that output to what we already know to be true.

Feds Should Ask Tech Innovators to Seek Forgiveness, Not Permission

A fleet of driverless cars designed by Waymo, a project of Google’s parent company, Alphabet, is on the roads of Phoenix, Arizona. Last week, Waymo CEO John Krafcik announced that in the coming months the driverless cars will be part of the world’s first autonomous ride-hailing service. The recent news is a milestone in driverless car technology history, and it’s no exaggeration to claim that the technology behind these new cars has the potential to save hundreds of thousands – if not millions – of lives in the coming decades. Sadly, drones, another life-saving technology, have had a tougher time getting off the ground.

Waymo’s cars are not suddenly arriving on the scene. Google has been working on getting a driverless car on the road since 2009, and Waymo has been offering some lucky passengers in the Phoenix area rides since April. However, these cars had a driver at the wheel, just in case. The fleet now driving in Phoenix does not include safety drivers. 

This may prompt unease among some Phoenix residents. A clear majority of Americans are uncomfortable about getting into driverless cars. Yet human drivers are deadly. More than 90 percent of car crashes can be attributed to human error, and motor vehicle accidents killed an estimated 40,200 people on American roads last year.

The Foot in the Door on Internet Speech Regulation

Campaign finance has captured Congress’s attention once again, which rarely bodes well for democracy. Senators Amy Klobuchar, Mark Warner, and (of course) John McCain have introduced the Honest Ads Act. The bill requires “those who purchase and publish [online political advertisements]to disclose information about the advertisements to the public…”

Specifically, the bill requires those who paid for an online ad to disclose their name and additional information in the ad itself or in another fashion that can be easily accessed. The bill takes several pages to specify exactly how these disclosures should look or sound. The bill also requires those who purchase $500 or more of ads to disclose substantial information about themselves; what must be disclosed takes up a page and a half of the bill.

The Federal Election Commission makes disclosed campaign contributions public. With this bill, large Internet companies (that is, platforms with 50 million unique visitors from the United States monthly) are given that task. They are supposed to maintain records about ads that concern “any political matter of national importance.” This category goes well beyond speech seeking to elect or defeat a candidate for office.

Why does the nation need this new law? The bill discusses Russian efforts to affect the 2016 election. It mentions the $100,000 spent by “Russian entities” to purchase 3,000 ads. The bill does not mention that Mark Penn, a former campaign advisor to Bill and Hillary Clinton, has estimated that only $6,500 of the $100,000 actually sought to elect or defeat a candidate for office. It also omits Penn’s sense of perspective:

Hillary Clinton’s total campaign budget, including associated committees, was $1.4 billion. Mr. Trump and his allies had about $1 billion. Even a full $100,000 of Russian ads would have erased just 0.025% of Hillary’s financial advantage. In the last week of the campaign alone, Mrs. Clinton’s super PAC dumped $6 million in ads into Florida, Pennsylvania and Wisconsin.

Antitrust for Fun and Profit: The Democrats’ Better Deal (Part 3)

This continues Part 1 and Part 2 of my critique of the arguments for aggressive antitrust activism offered in Steven Pearlstein’s Washington Post article, “Is Amazon Getting Too Big,” which is largely based on a loquacious law review article by Lina Kahn of the Google-funded “New America” think tank. 

My previous blogs found no factual evidence to support claims of Pearlstein and Kahn that many markets (which must include imported goods and services) are becoming dominated by near-monopolies who profit from overcharging and under-serving consumers.  

Yet the wordiest Kahn-Pearlstein arguments for more antitrust suits against large tech companies are not about facts at all, but about theories and predictions.

The Fatal Conceit of the “Right to be Forgotten”

Intelligence Squared hosted a lively debate last week over the so-called “Right to be Forgotten” embraced by European courts—which, as tech executive Andrew McLaughlin aptly noted, would be more honestly described as a “right to force others to forget.”  A primary consequence of this “right” thus far has been that citizens are entitled to demand that search engines like Google censor the results that are returned for a search on the person’s name, provided those results are “inadequate, irrelevant, or no longer relevant.”  In other words, if you’re unhappy that an unflattering item—such as a news story—shows up as a prominent result for your name, you can declare it “irrelevant” even if entirely truthful and ask Google to stop showing it as a result for such searches, with ultimate recourse to the courts if the company refuses.  Within two months of the ruling establishing the “right,” the company received more than 70,000 such requests.

Hearteningly, the opponents of importing this “right” to the United States won the debate by a large margin, but it occurred to me that one absolutely essential reason for rejecting this kind of censorship process was only indirectly and obliquely invoked.  As even the defenders of the Right to be Forgotten conceded, it would be inappropriate to allow a person to suppress search results that were of some legitimate public value: Search engines are obligated to honor suppression requests only when linking some piece of truthful information to a person’s name would be embarrassing or harmful to that person without some compensating benefit to those who would recieve the information.  Frequent comparison was made to the familiar legal standards that have been applied to newspapers publishing (lawfully obtained) private information about non-public figures. In those cases, of course, the person seeking to suppress the information is typically opposed in court by the entity publishing the information—such as a newspaper—which is at least in a position to articulate why it believes there is some public interest in that information at the time of publication. 

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