Wednesday, May 23, 2018

visiting a website without buying through it binds user to arbitration for offline purchase, court finds

Himber v. Live Nation Worldwide, Inc., 2018 WL 2304770, No. 16-CV-5001(JS) (E.D.N.Y. May 21, 2018)

In this decision, the court compels arbitration because the plaintiff had (1) previously purchased tickets from Live Nation’s website and, perhaps more surprisingly, independently because he had (2) visited the website, though not purchased tickets, to find the ticket prices for the relevant transaction.  Himber saw that the tickets he wanted were $49.50 each, but that there was a $15.25 online-service fee added to the price of each ticket. He decided to go to the box office, which was 20 minutes away, to buy the tickets and avoid the fee. But at the box office was charged an additional $6 per ticket, a charge that was not disclosed on the website. Given that it is impossible to avoid the $6 charge at the box office, he argued that the true price of a ticket was $55.50, and that Live Nation’s advertising was deceptive under GBL §§ 349 and 350.

The court found that the homepage and virtually all interior pages of the website state that use of the site is subject to the Terms of Use, with each page advising users that they agree to abide by those terms if they continue past the page and use the site, and with each page providing a hyperlink directly to the Terms of Use.  “[I]n the context of agreements made over the internet, New York courts find that binding contracts are made when the user takes some action demonstrating that they have at least constructive knowledge of the terms of the agreement, from which knowledge a court can infer acceptance.” In other words, “[w]here there is no evidence that the offeree had actual notice of the terms of the agreement, the offeree will still be bound by the agreement if a reasonably prudent user would be on inquiry notice of the terms,” a determination turning on the “ ‘[c]larity and conspicuousness of arbitration terms.’ ”  Himber didn’t “sufficiently contest that the layout and language of the website provided reasonably conspicuous inquiry notice of the arbitration provision when he used the website to purchase tickets.” The court gave short shrift to the argument that a user who only used the website to find out what shows were available would have no reason to read the ToU far enough to understand their claim to cover every interaction, online or off, between the parties, even though the beginning of the ToU states: “Welcome! The following are the terms of use (‘Terms’) that govern your use of the Live Nation sites and applications where this appears (collectively, the ‘Site’).”

The court found that Himber manifested assent to be bound by the Terms of Use when he used the website, which gave reasonable notice of the terms, whether or not a user ultimately purchased tickets. “A user who actually notices the Terms of Use … would not be reasonable in believing that provisions following the first paragraph apply only to users purchasing tickets online, not at the box office,” given the language that the terms “govern your use of the [website]” (emphasis added) unqualified by later language stating or reasonably suggesting that the terms apply only to users making online purchases. [Is that what an ordinary consumer would expect “use” to mean in the context of a ticket sales website?  Somehow I doubt it.]

Anyway, even if the scope of the arbitration provision were an issue for the court and not the arbitrator, it was broad enough to cover these claims because it covered “Any dispute or claim relating in any way to your use of the Site, or to products or services sold or distributed by us or through us.”  Himber’s claims depended on the conflict between the prices advertised on the website and the true, unavoidable price, so his claim was related to the use of the website.

Himber also failed in his argument that Live Nation was judicially estopped from taking this position because Ticketmaster, its affiliate, took a contrary position in two earlier, unrelated cases. In those cases, Ticketmaster argued that its arbitration clause wasn’t unconscionable because a customer was free to buy tickets at a box office without being bound by the arbitration clause.  But here, the claims were based on the use of the website to get information + going to the box office, not going to the box office alone, so there was no conflict.

Nor did Himber’s argument that any agreement to arbitrate was induced by misrepresentation get any traction.

Amicus brief in FanDuel right of publicity case

Mark McKenna & I wrote an amicus brief in the FanDuel case, in which the Indiana Supreme Court is being asked to interpret its state's right of publicity law.  We argue that the First Amendment precludes right of publicity laws that go beyond advertising and Zacchini-style unauthorized recording of live performances.

It takes an Empire to hold Dr. Seuss back: court revisits TM claim and rejects liability for mashup

Dr. Seuss Enterprises, L.P. v. ComicMix LLC, No. 16-CV-2779-JLS, 2018 WL 2306733 (S.D. Cal. May 22, 2018)

Twentieth Century Fox Television v. Empire Distribution, Inc., 875 F.3d 1192 (9th Cir. 2017), interprets and applies the test from Rogers v. Grimaldi, 875 F.2d. 994 (2d Cir. 1989), and convinced the district court to grant judgment on the pleadings to defendants here, who are trying to produce a Star Trek/Dr. Seuss mashup, Oh! The Places You’ll Boldly Go.  Previously, the district court relied on a footnote in Rogers indicating that the Second Circuit wouldn’t apply Rogers to confusingly similar titles.  But in Empire, the Ninth Circuit held that the Rogers test was applicable to titles generally, there being no point in changing the rule when the plaintiff asserted rights in a title and some danger in doing so, given that the First Amendment interests at stake come from the defendant’s expressive use and that titles are inherently less likely to convey association, authorship, or endorsement than other “marks.”

Dr. Seuss argued that the title wasn’t chosen for artistically relevant reasons but was chosen to “borrow from the rights holder or avoid the drudgery of creating something fresh.”  But the bar for artistic relevance is low, and it couldn’t be said that the title wasn’t at all relevant to the content; rather, it described the content of the book.

Nor was the title explicitly misleading.  Even survey evidence isn’t sufficient to show explicit misleadingness. “To be relevant, evidence must relate to the nature of the behavior of the identifying material’s user, not the impact of the use.”  There was no statement that Dr. Seuss endorsed or was involved in Boldly, and in fact the copyright page states that “[t]his is a work of parody, and is not associated with or endorsed by CBS Studios or Dr. Seuss Enterprises, L.P.” “Although the effectiveness of these disclaimers is disputed by Plaintiff, what cannot be disputed is that there is no statement in Boldly to the contrary.”  Nor was copying the lettering and font of the title and many characters relevant—that wasn’t enough to be an “explicit misstatement.”

However, the court clarified and limited its holding (which is just going to lead to more motion practice, this time based on ESS (the Pig Pen/Play Pen case)).  Last time, the court didn’t address the plaintiff’s claimed trademark rights in fonts and illustration style on the cover and in the contents of the book.  These remain for further litigation.  (Where Rogers and Dastar will meet, along with the various Sleptone cases).

Three stripes, three strikes: 9th Circuit wades into irreparable harm in TM again

The court of appeals affirmed a preliminary injunction against one Skechers shoe for infringing the unregistered trade dress of the Adidas Stan Smith shoe, but reversed the grant of an injunction against another shoe that allegedly infringed and diluted the Adidas three-stripe mark.  [PS: I don’t care that Adidas doesn’t capitalize its name; while I will respect the wishes of natural persons on this, Adidas lacks any comparable dignity interest.  I’m not a full prescriptivist, but I have standards.]

“The Stan Smith has become one of adidas’s most successful shoes in terms of sales and influence since its release in the 1970s.” It was called “ultimate fashion shoe” by i-D magazine and received other extensive media coverage, including appearances on lists of the most important or influential sneakers of all time, which are apparently things that exist, and earned industry accolades such as Footwear News’s 2014 “Shoe of the Year.” The Stan Smith is Adidas’s top-selling shoe of all time, selling more than 40 million pairs worldwide.

Adidas also claimed several hundred million dollars in annual domestic sales of products bearing the Three-Stripe mark, which is heavily advertised and promoted.
Skechers Cross Court shoe
Adidas defined its Stan Smith trade dress as having: (1) “a classic tennis-shoe profile with a sleek white leather upper”; (2) “three rows of perforations in the pattern of” adidas’s Three-Stripe mark; (3) “a defined stitching across the sides of each shoe,” (4) “a raised mustache-shaped colored heel patch, which often is green”; and (5) “a flat tonal white rubber outsole.”  The court found that the district court’s finding of secondary meaning was supported by ample evidence, including Skecher’s own copying and its use of [ugh] “metadata tags on its website that directed consumers who searched for ‘adidas Stan Smith’ to the page for the Onix shoe.… We agree with the district court that ‘the only reason “adidas Stan Smith” is a useful search term is that consumers associate the term with a distinctive and recognizable shoe made by adidas.’ ”  

Likely confusion was also supported by substantial evidence, given the high degree of similarity between the shoes and the other Sleekcraft factors. “Minor differences, including the use of Skechers’s logo, do not negate the overall impression of similarity between these two shoes.” The court also agreed that the copying and the use of metatags supported the inference that Skechers intended to confuse consumers. The court distinguished Multi Time Machine because that case involved a retailer and not the competitor itself, so Amazon’s “use of the metadata was not probative of its intent to exploit the existing secondary meaning of a competitor’s mark or trade dress,” which doesn’t make a lot of sense.  Eric Goldman has more to say about this.

As to the Stan Smith injunction, the court of appeals reiterated that “[e]vidence of loss of control over business reputation and damage to goodwill [can] constitute irreparable harm,” “so long as there is concrete evidence in the record of those things.” Here, Adidas’s Director of Sport Style Brand Marketing “testified to the significant efforts his team invested in promoting the Stan Smith through specific and controlled avenues such as social media campaigns and product placement,” and Adidas presented evidence regarding “its efforts to carefully control the supply of Stan Smith shoes and its concerns about damage to the Stan Smith’s reputation if the marketplace were flooded with similar shoes.” Adidas also presented survey evidence showing that approximately 20% of surveyed consumers believed Skechers’s Onix was made by, approved by, or affiliated with adidas. (The court also reiterated its conclusion about Skecher’s bad intent because of metatags.) 

This extensive marketing and tight control of supply demonstrated that Adidas had built a specific reputation around the Stan Smith with “intangible benefits.” The surveys demonstrated that those intangible benefits would be harmed if the Onix stays on the market because consumers would be confused about the source of the shoes.  [I still don’t understand this reasoning. The testimony discussed goes to brand value, not to damage to brand value through greater availability of knockoffs, which even this court just calls a “concern” and which Adidas doesn’t seem to have provided evidence about. The benefits of the Stan Smith reputation also aren’t intangible, though they may legitimately be hard to measure.  In addition, there is indeed a market for scarcity in itself—Veblen goods—but I have to wonder if something that has sold 40 million pairs can really qualify.]

Anyway, the court of appeals also affirmed the finding of likely success on the merits for confusion and dilution [ugh] of the three-stripe mark by the Cross Court shoe, but not the preliminary injunction. Though there were differences between the designs, “the district court was permitted to discount these differences in conducting its factual determination regarding similarity,” especially given the closely related products. There was no clear error in finding that Skechers’s intent in selecting its mark [NB query whether this is a “mark” at all] weighed in Adidas’s favor. “When one party knowingly adopts a mark similar to another’s, reviewing courts presume that the defendant will accomplish its purpose, and that the public will be deceived.” That also supported the district court’s finding that Skechers intended to deceive the public.  

[So a presumption of copying from knowledge + similarity leads to a presumption of confusion and of intent to deceive.  I understand why this view developed, but it is highly circular and seems to double-count similarity, which is more problematic the less exact the similarity is, as here.  Skechers presumably thought it was far enough away from the three-stripe mark, and while we might fear its own self-interest distorting its judgment of distance, we should probably be focusing on the distance and not Skechers’ hypothetical mental state.]

The court of appeals reasoned similarly about dilution—so similarly that it noted that there was “substantial overlap between [the dilution] factors and the Sleekcraft factors.” Actually, there is mostly overlap between the dilution factors and the factors that help determine whether a mark is famous, but that’s a story for another day. For the same reasons that the district court didn’t clearly err in finding likely confusion, it didn’t clearly err in finding likely dilution.

The majority then parted ways with the dissent on the preliminary injunction, specifically the issue of irreparable harm.  Adidas argued that the Cross Court harmed its ability to control its brand image because consumers who see others wearing Cross Court shoes would associate the allegedly lesser-quality Cross Courts with Adidas and its mark. But the record didn’t support that theory (as opposed to a different theory, mentioned by the dissent, that Adidas could somehow have suffered if the Skechers buyer could benefit from others believing she was wearing Adidas shoes).

The Adidas theory of harm relied on the notion that Skechers was viewed by consumers as a lower-quality, discount brand, and Adidas as a premium brand. Even assuming the latter, the former wasn’t shown by the record. The only evidence was from Adidas employees, who testified that Skechers sold at a lower price point, but not that the price point was because of lower quality.  One employee testified that, within Adidas, Skechers was viewed as inferior, but that didn’t show how the general consumer viewed them, even assuming that employee testimony was reliable evidence of the reputation of a competitor.

Further, Adidas’s theory of harm was in tension with its post-sale confusion theory.  It would be implausible to argue point of sale confusion, given the Cross Court’s numerous Skechers logos and other identifying features. Instead, the only theory was  that someone else looking at a Cross Court shoe “from afar or in passing” might not notice the Skechers logos and thus might mistake it for an Adidas. But how would such confused consumers “be able to surmise, from afar, that those shoes were low quality? If the ‘misled’ consumers could not assess the quality of the shoe from afar, why would they think any differently about adidas’s products? How could adidas’s “premium” brand possibly be hurt by any confusion?”

By contrast, Adidas presented evidence of irreparable harm in the form of its extensive marketing efforts for the Stan Smith and its careful control of the supply of Stan Smiths. “Thus, even post-sale confusion of consumers from afar threatens to harm the value adidas derives from the scarcity and exclusivity of the Stan Smith brand.” [How?  With forty million pairs, minus losses from wear, in circulation, how would a consumer infer anything about exclusivity even if every other person she saw were wearing something like the Stan Smith design?  I remember when everyone in my seventh grade class wore Benetton, but even I knew that was a concentrated environment and not widely representative.  The more you talk this scenario out, the more classist and ugly it gets, although it is sadly not an implausible theory of human behavior.] But there was no comparable argument or evidence for the Cross Court.

Judge Clifton dissented as to the three-stripe mark injunction, agreeing with INTA that infringement is the loss of control over reputation, and the loss of control is irreparable harm.  [On its own terms, this is fallacious.  The scenario perhaps equivalent to negligence—something may happen to the reputation due to the infringer’s behavior, and it would be the infringer’s fault—but it’s just a chance, rather than a realized event, until the lost control actually affects the reputation, just as negligent driving may not cause any harm.]

The dissent also argued that lost prestige from diminished exclusivity due to post-sale confusion was irreparable injury, as was customer diversion in itself.  And here we learn the source of the dissent’s conviction: his firm’s past representation of LV!

About thirty years ago, when I was in private practice, my law firm was retained by Louis Vuitton to combat the sale of cheaper imitations. Some were … knock-offs, such as bags with a similar looking “LW” mark or products that Louis Vuitton probably wouldn’t dream of making, such as baseball caps coveredwith dozens of “LV” marks. Many of the items were sold at locations, like swap meets and flea markets, where few would expect to find real Louis Vuitton products. Prices were often a tiny fraction of what the real thing cost, and it was unlikely that the purchasers thought that they were walking away with genuine Louis Vuitton merchandise. Leaving the legal arguments aside, it wasn’t a surprise to me (and still isn’t) that Louis Vuitton was concerned and was willing to expend considerable effort to protect its trademark. As Professor McCarthy described, if the prestige of carrying a bag with the Louis Vuitton trademark could be obtained at a fraction of the price, and if viewers could not tell the difference, the value of the trademark would be in jeopardy. And, if someone did confuse the cheap imitation for the real thing, the lesser quality of the imitator could further imperil the perceived value of the Louis Vuitton products and trademark.

Though the majority [rightly] considered this reasoning counterintuitive in the post-sale confusion scenario, the dissent found it perfectly logical and “well established in the law as a basis for a claim of dilution.” [See also: one reason dilution isn’t a real thing.]  The dissent would have honored the district court’s finding of blurring: “Skechers’ infringement undermines adidas’s substantial investment in building its brand and the reputation of its trademarks and trade dress” and that “Skechers’ attempts to ‘piggy back’ off of adidas’s efforts by copying or closely imitating adidas’s marks means adidas loses control over its trademarks, reputation, and goodwill.”

The dissent also argued that the district court’s reliance on the testimony of Adidas employees to establish Skecher’s market reputation wasn’t clearly erroneous. “A marketing professional has to be knowledgeable about consumer perceptions of his own brand, in this case adidas, and also of competitors, including Skechers.”

But the dissent’s real disagreement was with the majority’s view that Adidas had to show that there was a difference in reputation.  “Instead, the loss by adidas of control over its mark was by itself irreparably harmful.” The district court should have been given discretion to so find.

Suck and blow: surgical device ads lead to $12 million in compensatory and punitive damages for competitor

SurgiQuest v. Lexion Medical, Inc., No. 14-382-GMS, 2018 WL 2247216 (D. Del. May 16, 2018)

The parties, which make medical equipment, sued each other for false advertising.  A jury returned a verdict in favor of Lexion under the Lanham Act and Delaware’s Unfair Competition Law, and awarded $2.2 million in compensatory damages and $10 million in punitive damages. Here, the court rejects various motions.

If I understand the technology correctly, the parties’ devices are used during surgery to manage the gases that enter the patient’s body.  Lexion’s Insuflow device heats and humidifies gas, which reduces hypothermia by preventing the removal of moisture from the patient. In 2010, SurgiQuest told the FDA that the AirSeal System removed moisture from the patient and keeps tissues moist. SurgiQuest instructed its sales representatives that AirSeal did “essentially the same thing” as Lexion’s Insuflow system. However, SurgiQuest did humidity tests in 2012, and its engineer concluded that the AirSeal “dehydrates the abdominal cavity . . . chilling the patient,” which is the exact opposite of Insuflow. Even after SurgiQuest’s CEO and head of marketing learned about the test results, SurgiQuest still instructed its sales representatives to state that AirSeal performed essentially the same function as Insuflow.

There was evidence that SurgiQuest knew that AirSeal would suck air into the abdomen, and that gas, and surgical smoke when present in the abdomen, would leak out of the trocar (a surgical instrument used for withdrawing fluid from a body cavity).  Surgical smoke is a dangerous byproduct of energy-based surgical instruments.  SurgiQuest called its product an “AirSeal” despite its knowledge that the AirSeal didn’t preclude the passage of fluids, even though surgeons expected that trocars had seals to preclude fluid passage. SurgiQuest claimed that the AirSeal maintained stable pneumoperitoneum when it had advertised that this meant no gas could escape during a procedure.

SurgiQuest trained its sales representatives that the AirSeal did not suck air into the abdomen and that gas and smoke did not escape from the AirSeal trocar due to the “AirSeal” functionality. When customers inquired, the sales representative did demonstrations to show that no air could get sucked into the abdomen. Evidence at trial indicated that SurgiQuest knew that this capability was an important selling point and if they told the truth there would be “doctors that look at you like you just ran their mother over in a car” and it would lead to a decline in sales. A potential acquirer backed out of a potential acquisition of SurgiQuest, calling the air entrainment issue a “serious problem,” indicating that their sales numbers would be much less if people knew the truth.

SurgiQuest also knew that air could exacerbate subcutaneous emphysema, and altering the concentration of carbon dioxide gas in the abdomen is “typically undesirable for the safety of the patient” and even increases the risk of a fire or explosion.

SurgiQuest also knew that smoke could escape through the top of the trocar and that its filter was a particle filter that could not filter out toxic and carcinogenic gasses. Nonetheless, SurgiQuest trained its sales reps that AirSeal removed carcinogenic gasses from the smoke and advertised that AirSeal provided “smokeless laparoscopy,” and that surgeons and operating personnel were protected from the danger of surgical smoke.

However, the court indicated that concerns over patient safety were “baseless,” given that the FDA reviewed and approved a number of the statements Lexion pointed to at trial and that surgeons from top hospitals use the AirSeal device routinely, including top robotic surgeons at the hospital at which Lexion’s own expert practiced.

SurgiQuest argued that no reasonable jury could have awarded monetary damages because Lexion failed to provide sufficient evidence that its false statements had a causal link to Lexion’s lost sales.   But Lexion presented a witness who testified that, as a result of being “misled” by SurgiQuest’s false statements that its AirSeal product wouldn’t draw operating room air into the abdoment, he stopped using Lexion’s Insuflow product and switched to AirSeal product. Though he stopped using the AirSeal immediately once he learned the truth, Lexion never got the account back. Similarly, a “robotic coordinator” [great job] at a hospital testified that she was told AirSeal did not suck air into the abdomen, which partially affected the hospital’s purchasing decision.  Another witness identified multiple consumer accounts that believed AirSeal heated and humidified, and stopped buying or reduced their purchases from Lexion as a result; a witness who testified that his hospital system purchased fewer Insuflow devices because they were using AirSeal, which did the exact same thing as Lexion’s products; and a SurgiQuest sales representative who testified SurgiQuest targeted Lexion’s customers by telling them AirSeal performed identically to Insuflow, and that they could justify the cost of their purchase by getting rid of Insuflow. At one hospital, Lexion lost an account that produced revenue of $100,000 per year.  Thus, the evidence at trial was sufficient to support a verdict that the false advertising had a causal connection to Lexion’s loss.

The court also rejected challenges to the jury instructions.  These included: “[i]f literal falsity is found, Lexicon does not need to prove actual deception of consumers to recover damages for false statements made by SurgiQuest.” SurgiQuest argued that this wasn’t a correct statement of the law for money damages, but the court noted that Lexion provided evidence of actual deception and of a causal connection between the false statements and damages.

The court also instructed that “[e]vidence of actual[ ] confusion is difficult to find and even a few incidents may[,] therefore[,] be probative,” relying on analogous trademark cases.  Even if that wasn’t ok (which it should be), this wasn’t a damages instruction but a liability instruction for misleadingness, and SurgiQuest was only challenging the damages award. Likewise, the instruction “[i]f a party demonstrates that the defendant has intentionally set out to deceive the public and its conduct in this regard is of an egregious nature, a presumption arises that consumers are, in fact, being deceived” was also about misleadingness, and Lexion showed literal falsity, making presumptions irrelevant.

SurgiQuest also argued that the court improperly allowed Lexion sales representatives to testify about what customers told them, but this wasn’t hearsay because the statements weren’t provided for the truth about the AirSeal’s capabilities, but rather for what consumers thought the AirSeal could do (which evidenced their confusion).  Likewise, the court instructed the jury that evidence that SurgiQuest sales reps misunderstood the device’s capabilities “may be probative to establish customer or purchasing deception or other evidence.”  The court again reasoned that trademark precedents could apply, making salesperson confusion probative of consumer confusion because salespersons are in the position to influence a purchasing decision.  Given the evidence, the jury didn’t need to infer confusion, though: the  salespersons made literally false statements.

Under Delaware law, punitive damages are available when the defendant’s conduct exhibits a wanton or willful disregard for the rights of the plaintiff, which requires a conscious indifference or an “I don’t care” attitude.  SurgiQuest argued that there was little evidence of deception, particularly given the disclosures about the product to the FDA and in the Instructions for Use (“IFU”) provided to customers. SurgiQuest argued that most of the challenged statements were isolated incidents, from a handful of sales representatives to a very limited number of customers.  Given the evidence of knowing falsity recited above—and the harm that falsity could cause—the court found the evidence sufficient for punitive damages.

However, the court denied Lexion a permanent injunction.  Lexion argued that its loss of market share was sufficient evidence of irreparable harm, but SurgiQuest rejoined that because the jury found that it did not violate the Delaware Deceptive Trade Practices Act, which requires that there be a pattern of deceptive conduct not merely isolated statements or conduct, that the false statements couldn’t be the cause of on-going or irreparable harm. The court agreed, even though those two things (isolated statements and hard-to-measure lost market share) don’t contradict one another.  [Compare to the recent Adidas v. Skechers case, which does accept lost market share as irreparable harm.]

The balance of hardships also weighed against the injunction because enjoining the use of the tradename “AirSeal” would require SurgiQuest to change the registration of the device with government agencies, including the FDA, and the registration and use of the name dates back to 2009, but Lexion did not plead any claims on this tradename until 2016, nor any damages before 2013.

Lexion argued that the public interest would be served by an injunction because the false advertising related to patient and OR staff safety. SurgiQuest responded that prominent laparoscopic surgeons in top United States hospitals use AirSeal, and that an injunction could impact the surgical community’s access to the relevant equipment, which could impact the quality of laparoscopic surgeries, including robotic surgeries that are performed with the AirSeal each day. “Because surgeons across the country are using both products, the court finds this factor weighs against a permanent injunction.”

The court also denied disgorgement of profits. The Third Circuit considers: “(1) whether the defendant had the intent to confuse or deceive, (2) whether sales have been diverted, (3) the adequacy of other remedies, (4) any unreasonable delay by the plaintiff in asserting his rights, (5) the public interest in making the misconduct unprofitable, and (6) whether it is a case of palming off.” Intent and public interest in making misconduct unprofitable weighed in favor of disgorgement, and palming off was inapplicable, but sales diversion weighed against disgorgement. “Lexion’s trial evidence showed a wide variety of reasons completely independent of SurgiQuest, such as cost, contracts, product failures and surgeon preference that contributed to Lexion’s declining revenues.” And the fact that the parties’ products were incompatible “is a legitimate and lawful business fact, which cannot support damages or a theory of diverted sales for false advertising.” Moreover, testimony from both parties’ witnesses demonstrated that the selection of which device to use was a matter of surgeon preference.  

Adequacy of other remedies also weighed against disgorgement. Lexion never achieved more than a 4-5% market share, even when SurgiQuest was not on the market. Only 1-2% percent of surgeons even want the heated and humidified gas that Lexion’s accessories provide. Thus, the jury rejected Lexion’s claim for 95% of SurgiQuest’s revenue as damages.

Plaintiff’s delay also weighed against disgorgement. Lexion didn’t plead any false advertising claims concerning air entrainment (including the trademark AirSeal) or smoke statements until May 2016, more than 2 years after the litigation began, yet claimed that the false statements began at least as early as 2012, and relied on information publicly available in 2009-2010.

Nor was this case exceptional in terms of the substance or SurgiQuest’s litigation behavior. “While the case has been hotly contested, and has been marked by a tremendous number of disputes, these are typical realities of high-stakes litigation between competitors in a market presenting an opportunity for enormous profits. For the most part, both sides defended their respective positions throughout this litigation in apparent good faith.” For similar reasons, there was no prejudgment interest award.

Wednesday, May 16, 2018

Is this "diet" soda script too close to Diet Coke's?

I have to admit, I might expect it to be a Coca-Cola product.  What's more, it's made in the US, not Brazil, and seems to be a copy of Guarana Antarctica, a Brazilian beverage.

But in that sleep what dreams of liability may come?

When you sue a competitor for false advertising, be prepared to get sued back.  In this pair of opinions, most of the parties’ claims against each other survived, paving the way for a messy trial.

GhostBed, Inc. v. Casper Sleep, Inc., 2018 WL 2213002, No. 15-cv-62571-WPD (S.D. Fla. May 3, 2018)

GhostBed and Nature’s Sleep (hereinafter GhostBed), owned by the same family, sued Casper, a competitor in the online mattress business, for various causes of action.  Nature’s Sleep alleged that it was among the first in the mattress business to deliver a “bed in a box” concept direct to consumers: a mattress vacuum-sealed in a box, which inflates when the packaging is open, though Casper did well after its launch in 2014.  In 2015, Nature’s Sleep launched a competing DTC company, GhostBed.

Casper argued that GhostBed copied many of its product features, website design, and marketing techniques, down to the name, GhostBed, “designed for customers to associate the ‘ghost’ name with Casper based on the popular cartoon character ‘Casper the Friendly Ghost.’” Casper thus sued for trademark infringement and false advertising under the Lanham Act, along with related state law claims.

GhostBed accused Casper of intentionally infringing Nature’s Sleep’s “BETTER SLEEP FOR BRIGHTER DAYS” and false advertising; in this opinion, the court granted Casper partial summary judgment on the false advertising claims.

GhostBed registered (with two ‘s’s). ICS, apparently a known cybersquatter, registered (one s). In 2015, Casper allegedly arranged for users who visited the one-s site to be redirected to Casper’s website. GhostBed argued that this constituted direct or contributory infringement and violated ACPA.  Casper argued that it didn’t register or use the domain name.  AdMarketplace, “a company hired as part of an advertising campaign by Casper, had some role in the redirection” to Casper’s site.  The ACPA claim only imposes liability for using a domain name if a person “is the domain name registrant or that registrant’s authorized licensee.” Multiple factual issues, also including damages, precluded summary judgment on these claims.

Likewise, alleged infringement of Nature’s Sleep’s unregistered mark, BETTER SLEEP FOR BRIGHTER DAYS, couldn’t be decided on summary judgment.  Whether Casper’s use of BETTER SLEEP in commerce preceded Nature’s Sleep’s use was disputed.

GhostBed also alleged that Casper engaged in false advertising by: (1) posting false and misleading comments about GhostBed on the internet; (2) coercing mattress reviewers into posting fake, favorable reviews of Casper mattresses on the internet; (3) utilizing search engine optimization techniques to increase visibility of favorable Casper content on the internet; and (4) entering into settlement agreement with three mattress reviewers that resulted in elimination of negative reviews of Casper content.

These claims failed because, first, GhostBed didn’t provide evidence that Casper posted false/misleading comments about GhostBed. GhostBed argued that Casper’s use of affiliate relationships with online reviewers was “part of a concerted effort to reward reviewers to post favorable reviews and ‘strong-arm’ reviewers into posting fake positive reviews of Casper’s mattresses.” However, GhostBed didn’t prove that this conduct involved false or misleading statements that deceived consumers.  Casper also purchased the Google Ad Word “Ghostbed” and directed that an ad saying “Why Buy a Copycat?” and “Surely you Meant Casper” would appear as a sponsored link in search results when users googled “GhostBed.” “Here, the Lanham Act claim fails because these are not false or misleading statements of fact. Instead, these are advertisements suggesting Casper’s opinion that GhostBed is a copycat and that the consumer should also investigate Casper’s mattress.”

GhostBed argued that Casper manipulated search results with negative SEO techniques that caused favorable Casper mattress reviews to appear higher in search results and unfavorable Casper reviews to appear lower.  But this “common marketing strategy” wasn’t an actionable false or misleading “statement.”  So too with entering into settlement agreements with online mattress reviewers to remove negative reviews of Casper mattresses.

Ghostbed, Inc. v. Casper Sleep, Inc., 2018 WL 2213008, No. 15-cv-62571-WPD (S.D. Fla. May 3, 2018)

Here, the court denies GhostBed’s motion for summary judgment on Casper’s claims for trademark infringement/false advertising.

Casper alleged that GhostBed used Casper’s name in social media posts, creating a likelihood of customer confusion and that a Google AdWords campaign stating “GhostBed vs. The Competition—Pick your Ghost Carefully” contributed to consumer confusion by associating Casper with “Casper the Friendly Ghost.” Use of the trademark “GhostBed” also allegedly caused consumer confusion with the trademark “Casper.” Given Casper’s numerous allegations of consumer confusion. GhostBed’s argument that the confusion is de minimis was a question for trial.

Whether GhostBed’s use of the phrase “SuperNATURAL Comfort” misled consumers into believing that Ghostbed mattresses are made from all-natural fibers, or just suggested a connection with the “ghost” in “GhostBed,” was a question of fact for the factfinder at trial.  So too with whether GhostBed’s claim of being in business for 15 years was true because it could legitimately attach its length in business to that of its related company, Nature’s Sleep. There were also factual issues about whether GhostBed falsely represented reviews as “Verified Purchaser[s]” on when GhostBed practically gave the product to the reviewer for free (at a 99% discount) in violation of the terms of use defining a “Verified Purchaser.”

In a slightly different scenario, GhostBed’s “GhostBed vs. Casper Mattress Review” stated that Casper didn’t offer a matching mattress foundation. This statement was initially true when made, in April 2016, and was updated at some point after GhostBed became aware that the statement was no longer true, but it was unclear whether GhostBed timely corrected the statement once it became false. “While Plaintiffs do not have an obligation to monitor a competitor’s offerings minute-to-minute to correct a comparison that may later become untrue, Plaintiffs do have an obligation not to make misleading statements in advertising. A fact finder could find that a substantial delay, if there was one, in correcting a statement that became untrue, was misleading.”  This is actually more defendant-favorable than other rulings on the subject, which do find falsity the moment the claim becomes false (although of course the amount of damages from a short-term falsity may be limited).

Finally, an image GhostBed’s website depicted the Google logo and falsely reported that GhostBed had a 4.99 rating (a non-existent rating). The creator stated that it was designed to poke fun at Casper’s purported 4.9 rating—“they have a 4.9 rating. I put ours at 4.99.” Misleadingness and damages were factual issues.

Other claims were only raised as state law (FDUTPA) claims. Casper targeted an article written by non-party Ryan Monahan of Honest Reviews, LLC, a purported affiliate of GhostBed: “Casper’s Newest Product Might Be at the Expense of Animal Cruelty.” The article could suggest that Casper sources its down feathers from suppliers who “live pluck” birds, but again this was a factual issue, as was whether GhostBed “used social media to harass Casper’s customers who posted comments about Casper’s mattresses online” in a way that was unfair or deceptive under FDUTPA.

Tuesday, May 08, 2018

TM exam question: the right of publicity v. comparative advertising

What if Coco Chanel had been the plaintiff in Smith v. Chanel?  This question made me very happy, and I got a bunch of interesting answers on my final:

Kim Kardashian is famous for being famous. She is a highly successful influencer whose Instagram endorsements cost hundreds of thousands of dollars. She has lent her name to a perfume, KARDASHIAN BY KIM. Beautified also sells perfume. Beautified begins an ad campaign that states, “If you like Kardashian by Kim, you’ll love Beautified, with the same yummy smell but a lower price!” Assume there are no choice of law or other procedural issues. Explain why Beautified is or is not liable on Kardashian’s right of publicity claim under California law.

exercise company affiliation and ad revenue don't make diet review into commercial speech

GOLO, Inc. v. HighYa, LLC, 2018 WL 2086733, No. 17-2714 (E.D. Pa. May 4, 2018)

The court here declines to apply the Lanham Act to “companies that generate income through websites that review the products of others, without selling any products of their own.” GOLO sells a weight loss dieting program that can be purchased through its website. Defendants are review websites that purportedly assist consumers; HighYa has a marketing affiliation with a limited number of suppliers (e.g., BowFlex Max Trainer), but both defendants’ principal source of revenue comes from ads.  GOLO contested the fairness and accuracy of defendants’ online reviews, leading to revision on one site and removal on the other, but GOLO wanted to recover for the initial period.

Defendants’ editorial reviews principally rely on “publicly available information,” rather than defendants’ own use or testing. GOLO’s website contained a description of its program, backed by references to research purportedly supporting the merits of the program. Defendants’ editorial reviews primarily, if not exclusively, critiqued the statements in that description. HighYa’s editorial review spurred dozens of comments from purported users, with an average customer rating of 2.8 out of 5 stars. The link “was posted” across different social media platforms, one of which contained the statement: “Weight-loss #scams are everywhere. Is GOLO one of them?”

GOLO alleged that the title, “GOLO Weight Loss Diet Reviews – Is it a Scam or Legit?” was misleading; much of the review was was based on an outdated version of the GOLO program site; and  the focus of the GOLO program was not simply combatting “insulin resistance,” as the review states. The challenged portions were eventually removed.

The BrightReview article appeared in a similar form. The average customer rating was 2 out of 5 stars, with three purported users giving “highly negative ‘reviews.’ ” GOLO challenged statements about its study evidence and claims.

GOLO alleged that the websites were “designed to appear trustworthy, [and to] resemble internet versions of more traditional consumer review publications”  but were owned by or secretly related to the competitors of the products defendants review.

False advertising and false association claims only apply to commercial speech. Though there was a specific product reference, the articles still weren’t ads.  On their face, the reviews didn’t promote any competing product, and didn’t explicitly propose a commercial transaction. The court analogized to Tobinick v. Novella, 848 F.3d 935 (11th Cir. 2017). As there, the defendants “gained no direct economic benefit from readers of the reviews’ decision,” and “[t]he content of the reviews had no direct bearing on the revenue generated by traffic to the site.”  To the extent that the reviews were based only on the content of GOLO’s website, “[t]he value of such a review to consumers may be limited,” but that didn’t make it an ad.  Ad-based financial benefit was merely incidental to the content.

The Lanham Act does allow liability “if websites purporting to offer reviews are in reality stealth operations intended to disparage a competitor’s product while posing as a neutral third party.”  However, GOLO hadn’t plausibly pleaded that these review sites were shams.

Although “in the absence of discovery, a plaintiff’s ability to confirm what might be well-founded suspicion is limited,” that wasn’t enough here.  The court considered the general content of the sites, including the fact that defendants responded to GOLO’s objections by amending the reviews and specifically advising readers that changes to the reviews were based on further information provided by GOLO. “Such conduct does not plausibly support an inference that the purpose of the reviews is to create an advantage for competing products.” Defendants also disclosed the commercial relationship with BowFlex and other commercial affiliations, which made the allegedly covert competition less plausible.  And to the extent that GOLO pled that defendants’ revenues were a product of web traffic, the favorable/unfavorable nature of a review seemed irrelevant; sellers might even promote favorable reviews.

Nor did the affiliation with BowFlex render this a Lexmark situation in which “one competitor directly injures another by making false statements about his own goods or the competitor’s goods and thus inducing customers to switch.” “The review discussing GOLO’s dieting program does not at all reference, or provide a direct link to any exercise equipment, let alone to Bowflex.” Even if there were a prompt to try exercise, it doesn’t follow that diet and exercise compete; GOLO designed its program to work with exercise.  While direct commercial competition isn’t an “absolute” requirement, these observations bore on the plausibility of the conclusory allegation that defendants’ websites were covert competitors.

With Lanham Act false advertising and state coordinate claims out of the way, only a Pennsylvania trade libel claim remained.  But Pennsylvania has a one-year statute of limitations for trade libel claims, running from the date of the first publication. GOLO alleged that HighYa’s initial review was posted in “March 2016,” and filed on June 16, 2017. GOLO argued that the revised version of the article was published within the limitations period, and that it was re-published when HighYa posted links to it through its social media accounts. But the only HighYa social media post referenced dates back more than a year before filing, and GOLO didn’t object to the revised article.

As for user comments, GOLO’s allegation that HighYa was the true source of the comments “on information and belief” was insufficient in the context of the other allegations.

As to BrightReviews, GOLO didn’t adequately plead falsity. Each challenged statement was prefaced with language indicating that they are observations based primarily on GOLO’s website: “ ‘The 2010 study [was] performed with diabetics, not otherwise healthy individuals looking to optimize insulin...[T]his seems to be their target market;...None of [GOLO’s] studies appear to be peer reviewed for accuracy...;...and [W]e didn’t encounter any clinical evidence on leading medical websites...that directly linked insulin management...and weight loss.’ ” Though GOLO argued that these statements were inaccurate, it didn’t address whether those observations could reasonably and fairly been made based upon the information posted on its website at the time.

GOLO also argued that the reviews created a false impression that its product was a scam, citing low the average user rating; HighYa’s Twitter post, which stated, “Weight-loss #scams are everywhere. Is GOLO one of them?”; the initial title of the article, “GOLO Weight Loss Diet Reviews – Is it a Scam or Legit?”; and the fact that the reviews would appear prominently in web searches for GOLO. But in the context of the review, the court didn’t see an accusation of “a scam in the illegal, fraudulent sense, as compared to communicating that the product might not produce its intended result.”

Monday, May 07, 2018

Content Moderation at Scale, 2/2

You Make the Call: Audience Interactive (with a trigger warning for content requiring moderation)

Emma Llanso, Center for Democracy & Technology & Mike Masnick, Techdirt

Hypo: “Grand Wizard Smith,” w/user photo of a person in a KKK hood, posts a notice for the annual adopt-a-highway cleanup project.  TOS bans organized hate groups that advocate violence.  This post is flagged for review.  What to do?  Majority wanted takedown, but 12 said leave it up, 12 flag (leave up w/a content warning), 18 said escalate, and over 40 said take down.  Take down: he’s a member of the KKK.  Keep up: he’s not a verified identity; it doesn’t say KKK and requires cultural reference point to know what the hood means/what a grand master is.  Escalate: if the moderator can only ban the post, the real problem is the user/the account, so you may need to escalate to get rid of the account.

Hypo: “glassesguru123” says same sex marriage is great, love is love, but what do I know, I’m just a f----t.  Flagged for hate speech. What to do?  83 said leave it up.  5 for flag, 2 escalate, 1 take it down.  Comment: In Germany, you take down some words regardless of content, so it may depend on what law you’re applying.  Most people who leave it up are adding context: not being used in a hateful manner. But strictly by the policy, it raises issues, which is why some flag it.

Hypo: “Janie, gonna get you, bitch, gun emoji, gun emoji, is that PFA thick enough to stop a bullet if you fold it up & put it in your pocket?”  What to do? 57 take it down, 27 escalate, and 1 said leave it up/flag the content.  For escalate: need subject matter expert to figure out what a PFA is.  [Protection from Family Abuse.] Language taken from Supreme Court case about what constituted a threat.  I wondered whether there were any rap lyrics, but decided that it was worrisome enough even if those were lyrics.  Another argument for escalation: check if these are lyrics/if there’s an identifiable person “Janie.” [How you’d figure that out remains unclear to me—maybe you’ll be able to confirm that there is a Janie by looking at other posts, but if you don’t see mention of her you still don’t know she doesn’t exist.]  Q: threat of violence—should it matter whether the person is famous or just an ex?

Hypo: photo of infant nursing at human breast with invitation to join breast milk network.  Flagged for depictions of nudity. What to do? 65 said leave it up, 13 said flag the content, 5 said escalate, and 1 said take it down.  Nipple wasn’t showing (which suggests uncertainty about what should happen if the baby’s latch were different/the woman’s nipple were larger).  Free speech concerns: one speaker pointed that out and said that this was about free speech being embodied—political or artistic expression against body shame.  You have this keep-it-up sentiment now but that wasn’t true on FB in the past.  Policy v. person applying the policy.

Hypo: jenniferjames posts a site that links to Harvey Weinstein’s information: home phone, emails, everything— “you know what to do: get justice” Policy: you may not post personal information about others without their consent.  This one was the first that I found genuinely hard.  It seemed to be inciting, but not posting directly and thus not within the literal terms of the policy. I voted to escalate.  Noteworthy: fewer people voted. Plurality voted to escalate; substantial number said to take it down, and some said to leave it/flag it.  One possibility: the other site might have that info by consent!  Another response would block everything from that website (which is supposed to host personal info for lots of people).

Hypo: Verified world leader tweets: “only one way to get through to Rocket Man—with our powerful nukes. Boom boom boom. Get ready for it!”  Policy: no specific credible threats.  I think it’s a cop out to say it’s not a credible threat, though that doesn’t mean there’s a high probability he’ll follow up on it. I don’t think high probability is ordinarily part of the definition of a credible threat. But this is not an ordinary situation, so. Whatever it is, I’m sure it’s above my pay grade if I’m the initial screener: escalate. Plurality: leave it up. Significant number: escalate.  Smaller number of flag/deletes.  Another person said that this threat couldn’t be credible b/c of its source; still, he said, there shouldn’t be a presidential exception—there must be something he could say that could cross the line. Same guy: Theresa May’s threat should be treated differently.  Paul Alan Levy: read the policy narrowly: a threat directed to a country, not an individual or group.

Hypo: Global Center for Nonviolence: posts a video, with a thumbnail showing a mass grave. Caption: source “slaughter in Duma.”   “A victorious scene today,” is another caption apparently from another source. I wasn’t sure whether victorious could be read as biting sarcasm. Escalate for help from an area expert. Most divided—most popular responses were flag or escalate, but substantial #s of leave it up and take it down too. The original video maybe could be interpreted as glorifying violence, but sharing it to inform people doesn’t violate the policy and awareness is important. The original post also needs separate review. If you take down the original video, though, then the Center’s post gets stripped of content. Another argument: don’t censor characterizations of victory v. defeat; compare to Bush’s “Mission Accomplished” when there were hundreds of thousands of Iraqis dead.

Hypo: Johnnyblingbling: ready to party—rocket ship, rocket ship, hit me up mobile phone; email from City police department: says it’s a fake profile in the name of a local drug kingpin. Only way we can get him, his drugs, and his guns off the street. Policy: no impersonation; parody is ok. Escalate because this is a policy decision: if I am supposed to apply the policy as written then it’s easy and I delete the profile (assuming this too doesn’t require escalation; if it does I escalate for that purpose). But is the policy supposed to cover official impersonation?  [My inclination would be yes, but I would think that you’d want to make that decision at the policy level.] 41 said escalate, 22 take down, 7 leave it up, 1 flag. Violate user trust by creating special exceptions.  Goldman points out that you should verify that the sender of the email was authentic: people do fake these.  Levy said there might be an implicit law enforcement exception. But that’s true of many of these rules—context might lead to implicit exceptions v. reading the rules strictly.

1:50 – 2:35 pm: Content Moderation and Law Enforcement
Clara Tsao, Chief Technology Officer, Interagency Countering Violent Extremism Task Force, Department of Homeland Security

Jacob Rogers, Wikimedia Foundation: works w/LE requests received by Foundation. We may not be representative of different companies b/c we are small & receive a small number of requests that vary in what they ask for—readership over a period of time v. individual info. Sometimes we only have IP address; sometimes we negotiate to narrow requests to avoid revealing unnecessary info.

Pablo Peláez, Europol Representative to the United States: Cybercrime unit is interested in hate speech & propaganda. 
Dan Sutherland, Associate General Counsel, National Protection & Programs Directorate, U.S Department of Homeland Security: Leader of a “countering foreign influence” task force. Work closely w/FBI but not in a LE space.  Constitution/1A: protects things including simply visiting foreign websites supporting terror.  Gov’t influencing/coercing speech is something we’re not comfortable with. Privacy Act & w/in our dep’t Congress has built into the structure a Chief Privacy Officer/Privacy Office. Sutherland was formerly Chief Officer for Civil Rights/Civil Liberties.  These are resourced offices w/in dep’t and influence issues.  DHS is all about info sharing, including sensitive security information shared by companies.

Peláez: Europol isn’t working on foreign influence. Relies on member states; referrals go through national authorities.  EU Internet Forum brings together decisionmakers from states and private industry. About 150-160 platforms that they’ve looked at; in contact w/about 80. Set up internet referral management tool to access the different companies.  Able to analyze more than 54,000 leads.  82% success rate.

Rogers: subset of easy LE requests for Wikipedia & other moderated platforms—fraudulent/deceptive, clearly threats/calls to violence. Both of those, there is general agreement that we don’t want them around. Some of this can feed back into machine learning.  Those tools are imperfect, but can help find/respond to issues. More difficult: where info is accurate, newsworthy, not a clear call to violence: e.g., writings of various clerics that are used by some to justify violence. Our model is community based and allows the community to choose to maintain lawful content.

LE identification requests fall into 2 categories: (1) people clearly engaged in wrongdoing; we help as we can given technical limits.  (2) Fishing expeditions, made b/c gov’t isn’t sure what info is there. Company’s responsibility is to educate/work w/company to determine what’s desired and protect rights of users where that’s at issue.

YT started linking to Wikipedia for controversial videos; FB has also started doing that.  That is useful; we’ll see what happens.

Sutherland: We aren’t approaching foreign influence as a LE agency like FBI does, seeking info about accounts under investigation or seeking to have sites/info taken down. Instead, we support stakeholders in understanding scope & scale & identifying actions they can take against it. Targeted Action Days: one big platform or several smaller—we focus on them and they get info on content they must remove. 

Peláez: we are producing guidelines so we understand what companies need to make requests effective.  Toolkit w/18 different open source tools that will allow OSPs and LE to identify and detect content.

What Machines Are, and Aren’t, Good At
Jesse Blumenthal, Charles Koch Institute: begins with a discussion that reminds me of this xkcd cartoon.

Frank Carey, Machine Learning Engineer, Vimeo: important to set threshold for success up front. 80% might be ok if you know that going in.  Spam fighting: video spam, looks like a movie but then black screen + link + go to this site for full download for the rest of the 2 hours.  Very visual example; could do text recognition.  These are adversarial examples. Content moderation isn’t usually about making money (on our site)—but that was, and we are vastly outnumbered by them. Machine learning is being used to generate the content.  It’s an arms race. Success threshold is thus important.  We had a great model with a low false positive rate, and we needed that b/c if it was even .1% that would be thousands of accounts/day. But as we’d implement these models, they’d go through QA, and within days people would change tactics and try something else. We needed to automate our automation so it could learn on the fly.

Casey Burton, Match: machines can pick up some signs like 100 posts/minute really easily but not others. Machines are good at ordering things for review—high and low priority.  Tool to assist human reviewers rather than the end of the process. [I just finished a book, Our Robots, Ourselves, drawing this same conclusion about computer-assisted piloting and driving.]

Peter Stern, Facebook: Agrees. We’re now good at spam, fake accounts, nudity and remove it quickly.  Important areas that are more complicated: terrorism.  Blog posts about how we’ve used automation in service of our efforts—a combo of automation and human review.  A lot of video/propaganda coming from official terrorist channels—removed almost 2 million instances of ISIS/Al Qaeda propaganda; 99% removed before it was seen. We want to allow counterspeech—we know terror images get shared to condemn. Where we find terror accounts we fan out for other accounts—look for shared addresses, shared devices, shared friends. Recidivism: we’ve gotten better at identifying the same bad guy with a new account. Suicide prevention has been a big focus. Now using pattern recognition to identify suicidal ideation and have humans take a look to see whether we can send resources or even contact LE.  Graphic violence: can now put up warning screens, allow people to control their experience on the platform.  More difficult: for the foreseeable future, hate speech will require human judgment. We have started to bubble up slurs for reviewers to look at w/o removing it—that has been helpful.  Getting more eyes on the right stuff. Text is typically more difficult to interpret than images.

Burton: text overlays over images challenged us. You can OCR that relatively easily, but it is an arms race. So now you get a lot of different types of text designed to fool the machine.  Machines aren’t good at nuance.  We don’t get too much political, but we see a lot of very specific requests about who they want to date—“only whites” or “only blacks.”  Where do you draw the line on deviant sexual behavior? Always a place for human review, no matter how good your algorithms.

Carey: Rule of thumb: if it’s something you can do in under a second, like nudity detection, machine learning will be good at it.  If you have to think through the context, and know a bunch about the world like what the KKK is and how to recognize the hood, that will be hard—but maybe you can get 80% of the way.  Challenge is adversarial actors.  Laser beam: if they move a little to the left, the laser doesn’t hit them any more. So we create two nets, narrow and wide. Narrow: v. low false positive rate. With wider net that goes to review queue.  You can look at confidence scores, how the model is trained, etc.

Ryan Kennedy, Twitch?: You always need the human element.  Where are your adversaries headed?  Your reviewers are R&D.

Burton: Humans make mistakes too. There will be disagreement or just errors, clicking the wrong button, and even a very low error rate will mean a bunch of bad stuff up and good stuff down. 

Blumenthal: we tend not to forgive machines when they err, but we do forgive humans. What is an acceptable error rate?

Carey: if 1-2% of the time, you miss emails that end up in your spam folder, that can be very bad for the user, even if it’s a low error rate.  For cancer screening, you’re willing to accept a high false positive rate.  [But see mammogram recommendations.] 

Stern, in response to a Q about diversity: We are seeking to build diverse reviewers, whose work is used for the machine learning that builds classifications.  Also seeking diversity on the policy team, b/c that’s also an issue in linedrawing. When we are doing work to create labels, we try to be very careful about whether we’re seeing outlying results from any individual—that may be a signal that somebody needs more education.We also try to be very detailed and objective in the tasks that we set for the labelers, to avoid subjective judgments of any kind.  Not “sexually suggestive” but do you see a swimsuit + whatever else might go into the thing we’re trying to build. We are also building a classifier from user flagging.  User reports matter and one reason is that they help us get signals we can use to build out the process.

Kennedy, in response to Q about role of tech in dealing w/ live stream & live chat: snap decisions are required; need machines to help manage it.

Carey: bias in workforce is an issue but so is implicit bias in the data; everyone in this space should be aware of that. Training sets: there’s a lot of white American bias toward the people in photos.  Nude photos are mostly of women, not men. You have to make sure you’re thinking about those things as you put these systems in place.  Similar thing w/wordnet, a list of synonyms infected w/gender bias. English bias is also a thing.

Q: outsourced/out of the box solutions to close the resource gap b/t smaller services and FB: costs and benefits?

Burton: vendors are helpful.  Google Vision has good tools to find & take down nudity.  That said, you need to take a look and say what’s really affecting our platform.  No one else is going to care about your issues as much as you do.

Carey: team issues; need for lots of data to train on, like fraud data; for Vimeo, nudity detection was a special issue b/c we don’t have a zero nudity policy.  We needed to ID levels of nudity—pornographic v. HBO. We trained our own model that did pretty well. Then you can add human review. But off the shelf models didn’t allow that.  Twitch may have unique memes—site tastes are different.  Vendors can be great for getting off the ground, but they might not catch new things or might catch too many given the context of your site.

Kennedy: vendors can get you off the ground, but we have Twitch-specific language.  Industry standards can be helpful, raising all ships around content moderation.  [I’d love to hear from someone from reddit or the like here.]

Q re automation in communication/appeals: Stern says we’re trying to improve. It’s important for people to understand why something did/didn’t get taken down. In most instances, you get a communication from us about why there was a takedown. Appeals are really important—allow more confidence in the process b/c you know mistakes can be corrected.  Always a conundrum about enabling evasion, but we believe in transparency and want to show people how we’re interacting w/their content. If we show them where the line is, we hope they know not to cross.

Burton: There are ways to treat bots differently than humans: don’t need to give them notice & can put them in purgatory. We keep info at a high level to avoid people tracking back the person who reported them and going after them.

David Post, Cato Institute

Kaitlin Sullivan, Facebook: we care about safety, voice, and fairness: trust in our decisionmaking process even if you don’t always agree w/it. Transparency is a way to gain your trust.  New iteration of our Community Standards is now public w/full definition of “nudity” that our reviewers use. We also want to explain why we’re using these standards. You may not agree that female nipples shouldn’t be allowed (subject to exceptions such as health contexts) but at least you should be able to understand the rule.  Called us “constituents,” which I found super interesting.  Users should be able to tell whether there is an enforcement error or a policy decision.  We also are investing more in appeals; used to have appeals just for accounts, groups, pages. We’ve been experimenting w/individual content reviews, and now we have an increased commitment to that.  We hope to have more numbers than IP, gov’t requests, terror content soon.

Kevin Koehler, Automattic: 30% of internet sites use WordPress, though we don’t host them all. Transparency report lists what sites we geoblock due to local law & how we respond to gov’t requests. We try to write/blog as much as we can about these issues to give context to the raw numbers. Copyright reports have doubled since 2015; gov’t info requests 3x; gov’t takedowns gone up 145x from what they once were. Largely driven by Russia, former Soviet republics, and Turkey; but countries that we never heard from before are also sending notices, sometimes in polite and sometimes in threatening terms.

Alex Walden, Google: values freedom of expression, opportunity, and ability to belong.  400 hours of content uploaded every minute. Doubling down on machine learning, particularly for terrorist content. Including experts as part of how we ID content is key.  Users across the board are flagging lots content; the accuracy rates of ordinary users are relatively low, while trusted flaggers are relatively high in accuracy. 8 million videos removed for violating community guidelines, 80% flagged by machine learning. Flagà human review. Committed to 10,000 reviewers in 2018.  Spam detection has informed how we deal w/other content.  Also dealing w/scale by focusing on content we’ve already taken down, preventing its reupload.  Also important that there’s an appeals process. New user dashboard also shows users where flagged content is in the review process—was available to trusted flaggers, but is now available to others as well.

Rebecca MacKinnon, New America’s Open Technology Institute: Deletions can be confusing and disorienting. Gov’ts claim to have special channels to Twitter, FB to get things taken down; people on the ground don’t know if that’s true. Transparency reports are for official gov’t demands but it’s not clear whether gov’ts get to be trusted flaggers or why some content is going down. Civil society and human rights are under attack in many countries—lack of transparency on platforms destroys trust and adds to sense of lack of control.

Human rights aren’t measured by lack of rules; that’s the state of nature, nasty brutish and short. We look to see whether companies respect freedom of expression. We expect that the rules are clear and that the governed know what the rules are and have an ability to provide input into the rules, also there is transparency and accountability about how the rules are enforced.  Also looking for impact assessment: looking for companies to produce data about volume and nature of information that’s been deleted or restricted to enforce TOS and in response to external requests.  Also looking in governance for whether there’s human rights impact assessment.  More info on superusers/trusted flaggers is necessary to understand who’s doing what to whom. We’re seeing increasing disclosure about process over time.

If the quality of content moderation remains the same, then more journalists and activists will be caught in the crossfire.  More transparency for gov’ts and people could allow conversations w/stakeholders who can help w/better solutions.

Koehler: reminder that civil society groups may not be active in some countries; fan groups may value their community very strongly and so appeals are an important way of getting feedback that might not otherwise be available.  Scale is the challenge. 

Post asked about transparency v. gaming the system/machine learning [The stated concern for disclosing detection mechanisms as part of transparency doesn’t seem very plausible for most of the stuff we’re talking about.  Not only is last session’s point about informing bots v. informing people a very good point, “flagged as © infringement” is often pretty clear without disclosing how it was flagged.]

Sullivan: gaming the system is often known as “following the rules” and we want people to follow the rules. They are allowed to get as close to the line as they can as long as they don’t go over the line.  Can we give people detailed reasons with automated removal?  We have improved the information we have reviewers identify—ask reviewers why something should be removed for internal tracking as well as so that the user can be informed.  A machine can say it has 99% confidence that a post matches bad content, but that’s different—being transparent about that would be different.

Koehler: the content/context that a user needs to tell you the machine is doing it wrong is not the same content that the machine needs to identify content for removal: nudity as a protest, for example.

Content Moderation at Scale, DC Version

Foundations: The Legal and Public Policy Framework for Content

Eric Goldman gave a spirited overview of 230 and related rules, including his outrage at the canard that federal criminal law hadn’t applied to websites until recently—he pointed out that online gambling and drug ads had been enforced, and that Backpage was shut down based on conduct that had always been illegal despite section 230.  Also a FOSTA/SESTA rant, including about supplementing federal prosecutors with state prosecutors with various motivations: new enforcers, new focus on knowledge which used to be irrelevant, and new ambiguities about what’s covered.

Tiffany Li, Yale ISP Fellow: Wikimedia/YLS initiative on intermediaries: Global perspective: a few basic issues. US is relatively unique in having a strong liability framework. In many countries there aren’t even internet-specific laws, much less intermediary-specific.  Defamation, IP, speech & expression, & privacy all regulated.  Legal issues outside content are also important: jurisdiction, competition, and trade. Extremist content, privacy, child protection, hate speech, fake news—all important around the world.

EU is a leader in creating law (descriptive, not normative claim).  There is a right to receive information, but when rights clash, free speech often loses out. (RTBF, etc.)  E-Commerce Directive: no general monitoring obligation.  Draft copyright directive requires (contradictorily) measures to prevent infringement.  GDPR (argh).  Terrorism Directive—similar to anti-material support to terror provisions in US.  Hate speech regulations.  Hate speech is understood differently in the EU. Germany criminalizes a form of speech US companies don’t understand: obviously illegal speech; high fines & short notice & takedown period.  AV Services directive—proposed changes for disability rights.  UK defamation is particularly strong compared to US.  New case: Lewis v. FB, in which someone is suing FB for false ads w/his name or image.

Latin America: human rights framework is different.  Generally, many free expression laws but also regulation requiring takedown.  Innovative as to intermediary liability but also many legislative threats to intermediaries, especially social media.

Asia: less intermediary law generally.  India has solid precedent on intermediary liability: restrictions on intermediaries and internet websites are subject to freedom of speech protections.  China: developing legal system. Draft e-commerce law tries to put in © specifically, as well as something similar to the RTBF. Singapore: proposed law to criminalize fake news.  Privacy & fake news are often wedges for govts to propose/enact greater regulation generally.

Should any one country be able to regulate the entire world?  US tech industry is exporting US values like free speech.

Under the Hood: UGC Moderation (Part 1)
Casey Burton, Match: Multiple brands/platforms: Tinder, Match, Black People Meet.  Over 300 people involved in community & content moderation issues, both in house and outsourced. 15 people do anti-fraud at; 30 are engaged fulltime in content moderation in different countries.  Done by brand, each of which has written guidelines.  Special considerations: their platforms are generally where people who don’t already know each other meet. Give reporters of bad behavior the benefit of the doubt.  Zero tolerance for bad behavior.  Also not a place for political speech; not a general use site: users have only one thing on their minds. If your content is not obviously working towards that goal you & your content will be removed. Also use some automated/human review for behavior—if you try to send 100 messages in the first minute, you’re probably a bot.  And some users take the mission of the site to heart and report bad actions. Section 230 enables us to do the moderation we want.

Becky Foley, TripAdvisor: Fraud is separate from content moderation—reviews intended to boost or vandalize a ranking.  Millions of reviews and photos.  Have little to no upfront moderation; rely on users to report. Reviews go through initial set of complex machine learning algorithms, filters, etc. to determine whether they’re safe to be posted. A small percentage are deemed unsafe and go to the team for manual review prior to publication. Less than 1% of reviews get reported after they’re posted.  Local language experts are important.  Relevance is also important to us, uniquely b/c we’re a travel site.  We need to determine how much of a review can go off the main focus.  E.g., someone reviews a local fish & chips shop & then talks about a better place down the street: we will try to decide how much additional content is relevant to the review.

Health, safety & discrimination committee which includes PR and legal as well as content: goal is to make sure that content related to these topics is available to travelers so they’re aware of issues. There’s nobody from sales on that committee. Strict separation from commerce side.

Dale Harvey, Twitter: Behaviors moderation, which is different from content moderation. Given size, we know there’s stuff we don’t know. In a billion tweets, 99.99% ok is 10,000 not ok, and that’s our week. Many different teams, including information quality, IP/identity, threats, spam, fraud.  Contributors: have a voice but not a vote—may be subject matter experts, members of Trust & Safety Council—organizations/NGOs from around the world, or other external or internal experts.

Best practices: employee resilience efforts as a feature. The people we deal with are doing bad things; it’s not always pleasant. Counseling may be mandatory; you may not realize the impact or you may feel bravado.  Fully disclose to potential employees if they’re potentially going to encounter this.  Cultural context trainings: Silicon Valley is not the world.  Regular cadence of refreshers and updates so you don’t get lost.  Cross functional collaborations & partnerships, mentioned above.  Growth mindset.

Shireen Keen, Twitch: real time interactions. Live chat responds to broadcast and vice versa, increasing the moderation challenge. Core values: creators first.  Trust and safety to help creators succeed. When you have toxicity/bad behavior, you lose users and creators need users on their channels. Moderation/trust & safety as good business. Community guidelines overlay the TOS, indicating expectations.  Tools for user reporting, processing, Audible Magic filtering for music, machine learning for chat filtering. Goal: consistent enforcement.  5 minute SLA for content.  

Gaming focus allowed them to short circuit many policy issues because if it wasn’t gaming content it wasn’t welcome, but that has changed. 2015 launched category “creative,” still defining what was allowed. Over time have opened it further—“IRL” which can be almost anything.  Early guidelines used a lot of gaming language; had to change that.  All reported incidents are reviewed by human monitors—need to know gaming history and lingo, how video and chat are interacting, etc.  Moderators come from the community. Creators often monitor/appoint moderators for their own channels, which reduces what Twitch staff has to deal with. Automated detection, spam autodetection, auto-mod—creator can choose level of auto-moderation for their channel. 

Sean McGillivray, Vimeo: largest ad-free open video platform, 70 million users in 150 countries.  A place for intentional videos, not accidental (though they’ll take those too).  No porn.  [Now I really want to hear from a Tube site operator about how it does content moderation.]  Wants to avoid being blocked in any jurisdiction while respecting free speech.  5 person team (about half legal background, half community moderation background) + developer, working w/others including community support, machine learning.  We get some notices about extremist content, some demands from censorship bodies around the world. We have algorithmic detection of everything from keywords to user behavior (velocity from signupàaction).  Some auto-mod for easy things like spam and rips of TV shows. Some proactive investigation, though the balance tips in favor of user flagging. We may use that as a springboard depending on the type of content. Find every account that interacted w/ a piece of content to take down networks of related accounts—for child porn, extremist content.  We can scrub through footage pretty quickly for many things. 

There are definitely edge cases/outliers/oddballs, which is usually what drives a decision to update/add new policy/tweak existing policy.  When new policy has to be made it can go to the top, including “O.G. Vimeans”—people who’ve been w/the community from the beginning.  If there’s disagreement it can escalate, but usually if you kill it, you clean it: if user appeals/complains, you explain.  If you can’t explain why you took it down, you probably shouldn’t have taken it down.  There’s remediation—if we think an account can be saved, if they show willingness to change behavior or explain how they misunderstood the guidelines, there’s no reason not to reverse a decision. We’re not parents and we don’t say “because I said so.”

Challenges: we do allow nudity and some sexual content, as long as it serves an artistic, narrative or documentary purpose. We have always been that way, and so we have to know it when we see it. He might go for something more binary, but that’s where we are. We make a lot of decisions based on internal and external guidelines that can appear subjective (our nipple appearance/timing index).  Scale is an issue; we aren’t as large as some, but we’re large and growing with a small team.

We may need help w/language & context—how do you tell if a rant to the camera is a Nazi rant if you can’t speak the language?

Bots never sleep, but we do.

Being ad free: we don’t have a path to monetization.  We comply w/DMCA. No ad-sharing agreement we can enter into w/them.  Related: we have pro userbase.  Almost 50% of user are some form of pro filmmaker, editor, videographer. They can be very temperamental. Their understanding of © and privacy may require a lot of handholding.  It’s more of a platform to just share work. We do have a very positive community that has always been focused on sharing and critique in a positive environment.  That has limited our commitment to free speech—we remove abusive comments/user-to-user interaction/harassing videos.  We also have an advantage of just dealing w/videos, not all the different types of speech, w/a bit of comments/discussion.  Users spend a lot of time monitoring/flagging and we listen to them.  We weight some of the more successful flaggers so their flags bubble up to review more quickly.

Goldman: what’s not working as well as you’d like?

Foley: how much can we automate w/o risking quality? We don’t have unlimited resources so we need to figure out where we can make compromises, reduce risk in automation.

McGillivray: you’re looking to do more w/less.

Keen: Similar. Need to build things as quickly as possible.

Harvey: Transparency around actions we take, why we take those actions. Twitter has a significant amount of work planned in that space.  Relatedly, continuing to share best practices across industry & make sure that people know who to reach out to if they’re new in this space.

Burton: Keep in mind that we’re engaged in automation arms race w/spambots, fake followers, highly automated adversaries. Have to keep human/automated review balanced to be competitive.

Under the Hood: UGC Moderation (Part 2)
Tal Niv, Github: Policy depends a lot on content hosted, users, etc. Github = world’s largest software development platform. The heart of Github is source control/version system, allowing many users to coordinate on files with tracked changes. Useful for collaboration on many different types of content, though mostly software development.  27 million users worldwide, including individuals & companies, NGOs, gov’t.  85 million repositories. Natural community.

Takedowns must be narrow.  Software involves contribution of many people over time; often a full project will be identified for takedown, but when we look, we see it’s sometimes just a file, a few lines of code, or a comment.  15 people out of 800 work on relevant issues, e.g., support subteam for TOS support, made of software programmers, who receive initial intake of takedowns/complaints.  User-facing policies are all open on the site, CC-licensed, and open to comment.  Legal team is the maintainer & engages w/user contributions.  Users can open forks. Users can also open issues.  Legal team will respond/engage.  List of repositories as to which a takedown has been upheld: Constantly updated in near real time, so no waiting for a yearly transparency report.

Nora Puckett, Google
Legal removals (takedowns) v. content policies (what we don’t want): hate speech, harassment; scaled issues like spam and malware.  User flags are important signals. Where request is sufficiently specific, we do local removals for violation of local law (general removals for © and child exploitation).  Questions we prompt takedown senders to answer in our form help you understand what our removal policies are.  YT hosts content and has trusted flaggers who can be 90% effective in flagging certain content.  In Q4 2017, removed 8.2 million videos violating community guidelines, found via automation as well as flags and trusted flags.  6.5 million were flagged by automated means; 1.1 million by trusted users; 400,000 by regular users.  We got 20 million flags during the same period  [?? Does she mean DMCA notices, or flags of content that was actually ok?].  We use these for machine learning: we have human reviewers verifying automated flags are accurate and use that to train machine learning algorithms so content can be removed as quickly as possible. 75% of automatically flagged videos are taken down before a single view; can get extremist videos down in 8 hours and half in less than 2 hours. Since 2014, 2.5 million URL requests under RTBF and removed over 940,000 URLs since then. In 2018, 10,000 people working on content policies and legal removal.

Best practices: Transparency. We publish a lot of info about help center, TOS, policies w/ exemplars.

Jacob Rogers, Wikimedia Foundation: Free access to knowledge, but while preserving user privacy; self-governing community allowing users to make their own decisions as much as possible. Where there are clear rules requiring removal, we do so. Sometimes take action in particularly problematic situations, e.g. where someone is especially technically adept at disrupting the site/evading user actions. Biannual transparency report. No automated tools but tools to rate content & draw volunteers’ attention to it.  E.g., will rate quality of edits to articles.  70-90% accurate depending on the type of content. User interaction timeline: can identify users’ interactions across Wikipedia and determine if there’s harassment going on.  Relatively informal b/c of relatively small # of requests. Users handle the lion’s share of the work. Foundation gets 300-500 content requests per year.  More restrictive than many other communities—many languages don’t accept fair use images at all, though they could have them.  Some removals trigger the Streisand effect—more attention than if you’d left it alone.

Peter Stern, Facebook: Community standards are at core of content moderation.  Cover full range of policies, from bullying to terrorism to authentic ID and many other areas. Stakeholder engagement: reaching out to people w/an interest in policies.  Language is a big issue—looking to fill many slots w/languages.  Full-time and outsourced reviewers.  Automation deals w/spam and flags for human review and prioritizes certain types of reports/gets them to people w/relevant language/expertise. Humans play a special role b/c of their ability to understand context.  Training tries to get them to be as rigid as possible and not interpret as they go; try to break things down to a very detailed level tracking the substance of the guidelines, now available on the web.  It only takes one report for a policy violation to be removed; multiple reports don’t increase the likelihood of removal, and after a certain point automation shuts off the review so we don’t have 1000 people reviewing the same piece of content that’s been deemed ok. Millions of reports/week, usually reviewed w/in 24 hours. Route issues of safety & terrorism more quickly into the queue.

Most messaging explains the nature of the violation to users.  Appeals process is new—will discuss on Transparency panel. 

Resiliency training is also part of the intake—counseling available to all reviewers; require that for all our vendors who provide reviewers. Do audits for consistency; if reviewers are having difficulty, then we may need to rewrite the policy.

Community integrity creates tools for operations to tools, e.g. spotting certain types of images.

Strategic response team. E.g., there’s an active shooter.  Would have to decide whether he’s a terrorist, which would change the way they’d have to treat speech praising him. Would scan for impersonation accounts.

Q: how is content moderation incorporated into product development pipeline?

Niv: input from content moderation team—what tools will they need?

Puckett: either how current policies apply or whether we need to revise/refine existing policies—a crucial part.

Rogers: similar, review w/legal team. Our product development is entirely public; the community is very vocal about content policy and will tell us if they worry about spam/low quality content or other impediments to moderation.

Stern: Similar: we do our best to think through how a product might be abused and that we can enforce existing policies. Create new if needed.