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Uber is rolling out a series of changes to its ride-hailing and on-demand food delivery apps, beginning Monday, as cities and states lift stay-at-home orders prompted by the COVID-19 pandemic.

The changes, which includes an online checklist for all users, limits on the number of passengers in vehicles and a face mask verification feature for drivers, aims to stop the spread of COVID-19, the company said Wednesday.

“This is not a problem that can only be solved by the drivers or only can be solved by the riders, it is everyone’s responsibility,” said Sachin Kansal, senior director of product management at Uber, during a webinar Wednesday announcing the changes.

User policing lies at the heart of these new policies. Riders and drivers as well as delivery workers and even restaurants that use Uber Eats will have the power to report unsafe COVID-19 behavior and give low ratings. For instance, a delivery worker can give feedback that a restaurant doesn’t have proper protocols in place, such as social distancing. Meanwhile, a restaurant can provide feedback if a delivery driver isn’t wearing a mask.

“These feedback loops between all the parties are extremely important for us to maintain safety,” Kansal said.

The new policies will remain for the next several months, according to Kansal, who added that “as the situation on the ground changes, we will evolve our policies as well.”

All Uber app users will now have to read and agree to an online checklist before picking up a rider or trying to hail a ride, according to the company. The online checklist requires riders and drivers to confirm that they have taken certain steps such as putting on a face mask and washing their hands to help stop the spread of COVID-19.

Uber will encourage drivers and riders to cancel trips — a move that in the past could result in a lower rating — if they don’t feel safe or the user is not wearing a face mask or cover. If drivers or riders give a low rating, they can now pick “no face cover or mask” along with the other traditional options such as “late for pickup,” “disrespectful” or “cleaniness.” If the user chooses the “no face cover” option in their review, the rider or driver will be sent a message informing them about the requirements of being on the Uber platform.

Kansal said Uber will take riders or drivers off the platform if they repeatedly violate these requirements.

Drivers will have verify they’re wearing a mask before accepting trips, using Uber’s existing driver selfie technology. The app also features a video tutorial on how to wear a mask.

The selfie technology, which has been in use since 2016, isn’t available on the rider app. Instead, riders will be policed by drivers. Riders are also asked to keep the window open, if possible.

For now, Uber isn’t adding shared rides, known as Uber Pool. The company has also put new restrictions on UberX and UberXL rides. Riders are no longer allowed to ride in the front seat, which Uber says will allow for more distance in the car. The change means UberX can have a maximum of three passengers in the vehicle.

Source: Tech Crunch

Amazon has received a fair amount of criticism for perceived inaction against seller price gouging during the COVID-19 pandemic. While the retail giant has made efforts to rein in the opportunist activity (pulling some half a million offending listings), critics have pointed to the company’s slow response, along with continued problems with a number of high-demand products sold through affiliates.

Today, however, the company’s VP of Public Policy, Brian Huseman, penned an open letter to Congress, asking lawmakers to make price gouging illegal during a national crisis. The executive notes that the policy has been an effective tool in states like Tennessee where such laws already exist.

“Our collaborative efforts to hold price gougers accountable have clarified one thing: to keep pace with bad actors and protect consumers, we need a strong federal anti-price gouging law,” Huseman writes. “As of now, price gouging is prohibited during times of crisis in about two-thirds of the United States. The disparate standards among states present a significant challenge for retailers working to assist law enforcement, protect consumers, and comply with the law.”

Jeff Bezos also addressed the issue in his annual shareholder letter last month, writing, “To accelerate our response to price-gouging incidents, we created a special communication channel for state attorneys general to quickly and easily escalate consumer complaints to us.”

The company has certainly taken some efforts to curb the act. As it notes, nearly 4,000 seller accounts have been suspended in the U.S. store for policy violations. But a cursory search for in-demand products yields plenty of prohibitively expensive listings for once-ubiquitous household products. Home cleaning supplies in particular have seen a massive spike in pricing.

We asked Thinknum to chart the price of Clorox-branded items from late last year through now and the graph speaks for itself:

As retail store shelves have gone bare, Amazon has become an essential lifeline for many — a fact that plenty of predatory sellers have been more than happy to capitalize on. Beyond essential supplies, prices have gone through the roof for a number of products currently in short demand, such as the Nintendo Switch, which has been squeezed through a combination of increased interest and supply chain issues.

The company rightfully notes that enforcing such policies as a matter of the law will be a kind of juggling act. “Put simply, we want to avoid the $400 bottle of Purell for sale right after an emergency goes into effect, while not punishing unavoidable price increases that emergencies can cause, especially as supply chains are disrupted,” Huseman writes. “Furthermore, any prohibitions should apply to all levels of the supply chain so that retailers and resellers are not forced to bear price gouging increases by manufacturers and suppliers.”

Source: Tech Crunch

So, an eight-year product veteran from Facebook and an internationally renowned barista walk into a coffee bar…

It’s not a joke. It’s the origin story for Taika, a new startup that’s aiming to bring natural stimulants to the masses through its juiced up coffee-beverages.

The two co-founders, Michael Sharon, an eight-year veteran of Facebook’s mobile product division, and Kalle Freese, a champion barista (it’s a thing) and the co-founder of Sudden Coffee are on a mission to bring consumers what Sharon calls “stealth health”.

 

Talk to any of Sharon’s friends and it’s plain to see that the man loves his coffee. While at Facebook he’d down pour overs in the morning and espresso shots throughout the day, but the side effects left him… “tweaky”.

So, like any good product designer and engineer, Sharon set out to try and make a better cuppa. The South African native developed a stack of different natural additives that he would add to his morning ‘joe in an effort to provide a steady source of stimulation — without any side-effects throughout the day.

The cornerstone of Sharon’s putatively potent potables is an ingredient commonly found in tea called L-theanine. “I had these compounds and these stacks that I was putting together for myself,” said Sharon. “[And] I realized they were super beneficial, but when i tried to get my friends interested and said ‘Here are the twenty things you need to buy,’ people would lose interest and walk away.”

It was in those moments that Sharon came up with the notion of “stealth health”, if his friends were rejecting his attempts to try out his curated stack of ingredients on their own, he’d just make a product that would package them into a handy beverage and foist them on an unwitting world.

Sharon stresses that his company is based on the latest science and that nothing that’s included in Taika’s coffee-based drinks is a novel compound or regulated substance. They’re all supplements that are known quantities in the wellness world.

“We are, as a company, we’re very much science aware and science supported,” said Sharon. “We’re not science blocked… The compounds that I’ve experimented with.. I’ve experimented with them myself and experimented with them on my partner and started this larger beta program.”

Bringing software-style beta testing to the beverage business

Sharon met Freese in 2018 after a two-and-a-half year hiatus from Facebook that saw the veteran product designer try his hand at kite surfing, wind surfing, surfing, photographing polar bears in Svalbard, and visiting the world’s only desert with fresh water lagoons.

That summer the coffee snob met the world’s best barista and a friendship was formed that would blossom into the partnership at the heart of Taika. Sharon had already made an investment in the coffee world through a small stake in Blue Bottle and was ready to take the plunge into startup land.

“When i met Kalle we started riffing on a whole bunch of insane ideas,” said Sharon. “After two months we were like… Why don’t we try to take some of these compounds and put together a formula.”

Since none of the compounds that the company uses need to be approved by the FDA, because they’re classified as “Generally Recognized As Safe”, Taika was able to begin formulating.

The company started off as a direct sales business, giving away coffee to friends and friends-of-friends. Then they started delivering to what Sharon called micro-kitchens. From there, the business grew and continued growing. the two co-founders began dropping off their brews at corporate offices.

Their first big human beta test was at the offices of the now-defunct legal startup Atrium. “They were — like — 80 people at that stage,” said Sharon. And they were also providing legal services to Taika as a newly launched startup. “They went through the coffee in the first two weeks,” said Sharon.

From the initial run of a regular coffee, the company added an oat milk latte and that’s when Sharon and Freese knew they were off to the races.

“This coffee is like secretly healthy,” said Sharon. “We have no added sugar in the coffee. We know coffee is a healthy compound and we have a bunch of these compounds that are very healthy but not widely known. This stealth-health concept stuck around.”

Taika includes a phone number for customer feedback on the packaging and the company is constantly tweaking its formulations. It’s now up to version 0.8 on its three drinks, which include a black coffee, an oat milk latte and a macadamia nut latte. The drinks also include functional ingredients like L-theanine, ashwagandha, and functional mushrooms like cordyceps, reishi, and lion’s mane. The company uses allulose as a sweetener, which doesn’t impact blood sugar levels and is better than table sugar, Sharon said.

“We definitely think that it’s healthy, but we don’t think you have to compromise on the taste,” said Sharon. “We asked ourselves what are the right extracts that we can use that will have an effect.. Everybody is different and everybody psychoactive compound effects people differently.. The compounds we put in this coffee are going to affect people differently.. 

Repeatedly, Sharon returns to the concept of providing a stealth way to introduce healthy compounds and chemicals into a consumer’s day and diet.

“There are established supply chains for these things,” said Sharon. “One of the first things we worked on was the formulation. We ended up with this specific mix of five. They helped us dial in the right headspace and they’re all natural compounds. These are things that have been consumed by humans for thousands of years.”

It’s working with the coffees. So far the company has sold 50,000 cans and it’s now available at stores across San Francisco including Buy Rite, Epicurian Trader, Rainbow Grocery and has even managed to make its way through COVID-19 shelter in place orders to the five Erewhon locations in Los Angeles.

Taika takes its name for the Finnish word for magic and, according to Sharon, it’s a good corollary for how the beverage makes you feel.

The company has raised $2.7 million in seed funding to date to take its product to market from firms like Kindred Ventures (which has backed companies like Coinbase , Blue Bottle Coffee , Postmates , Zymergen) and individual investors like James Joaquin.

And coffee is just the beginning, according to Sharon.

“If we’re able to take sugar and milk out of their day… and we’re not beating them over the head with the health aspects… there are a ton of products out there that we could turn into stealth health products,” he said.

Source: Tech Crunch

Facebook’s AI tools are the only thing standing between its users and the growing onslaught of hate and misinformation the platform is experiencing. The company’s researchers have cooked up a few new capabilities for the systems that keep the adversary at bay, identifying COVID-19-related misinformation and hateful speech disguised as memes.

Detecting and removing misinformation relating to the virus is obviously a priority right now, as Facebook and other social media become breeding grounds not just for ordinary speculation and discussion, but malicious interference by organized campaigns aiming to sow discord and spread pseudoscience.

“We have seen a huge change in behavior across the site because of COVID-19, a huge increase in misinformation that we consider dangerous,” said Facebook CTO Mike Schroepfer in a call with press earlier today.

The company contracts with dozens of fact-checking organizations around the world, but — leaving aside the question of how effective the collaborations really are — misinformation has a way of quickly mutating, making taking down even a single image or link a complex affair.

Take a look at the three example images below, for instance:In some ways they’re nearly identical, with the same background image, colors, typeface, and so on. But the second one is slightly different — it’s the kind of thing you might see when someone takes a screenshot and shares that instead of the original. The third is visually the same but the words have the opposite meaning.

An unsophisticated computer vision algorithm would either rate these as completely different images due to those small changes (they result in different hashes) or all the same due to overwhelming visual similarity. Of course we see the differences right away, but training an algorithm to do that reliably is very difficult. And the way things spread on Facebook, you might end up with thousands of variations rather than a handful.

“What we want to be able to do is detect those things as being identical because they are, to a person, the same thing,” said Schroepfer. “Our previous systems were very accurate, but they were very fragile and brittle to even very small changes. If you change a small number of pixels, we were too nervous that it was different, and so we would mark it as different and not take it down. What we did here over the last two and a half years is build a neural net based similarity detector that allowed us to better catch a wider variety of these variants again at very high accuracy.”

Fortunately analyzing images at those scales is a specialty of Facebook’s. The infrastructure is there for comparing photos and searching for features like faces and less desirable things; It just needed to be taught what to look for. The result — from years of work, it should be said — is SimSearchNet, a system dedicated to finding and analyzing near-duplicates of a given image by close inspection of their most salient features (which may not be at all what you or I would notice).

SimSearchNet is currently inspecting every image uploaded to Instagram and Facebook — billions a day.

The system is also monitoring Facebook Marketplace, where people trying to skirt the rules will upload the same image of an item for sale (say, an N95 face mask) but slightly edited to avoid being flagged by the system as not allowed. With the new system, the similarities between recolored or otherwise edited photos are noted and the sale stopped.

Hateful memes and ambiguous skunks

Another issue Facebook has been dealing with is hate speech — and its more loosely defined sibling hateful speech. One area that has proven especially difficult for automated systems, however, is memes.

The problem is that the meaning of these posts often results from an interplay between the image and the text. Words that would be perfectly appropriate or ambiguous on their own have their meaning clarified by the image on which they appear. Not only that, but there’s an endless number of variations in images or phrasings that can subtly change (or not change) the resulting meaning. See below:

Each individual piece of the puzzle is fine in some contexts, insulting in others. How can a machine learning system learn to tell what’s good and what’s bad? This “multimodal hate speech” is a non-trivial problem because of the way AI works. We’ve built systems to understand language, and to classify images, but how those two things relate is not so simple a problem.

The Facebook researchers note that there is “surprisingly little” research on the topic, so theirs is more an exploratory mission than a solution. The technique they arrived at had several steps. First, they had humans annotate a large collection of meme-type images as hateful or not, creating the Hateful Memes dataset. Next, a machine learning system was trained on this data, but with a crucial difference from existing ones.

Almost all such image analysis algorithms, when presented with text and an image at the same time, will classify the one, then the other, then attempt to relate the two together. But that has the aforementioned weakness that, independent of context, the text and images of hateful memes may be totally benign.

Facebook’s system combines the information from text and image earlier in the pipeline, in what it calls “early fusion” to differentiate it from the traditional “late fusion” approach. This is more akin to how people do it — looking at all the components of a piece of media before evaluating its meaning or tone.

Right now the resultant algorithms aren’t ready for deployment at large — at around 65-70 percent overall accuracy, though Schroepfer cautioned that the team uses “the hardest of the hard problems” to evaluate efficacy. Some multimodal hate speech will be trivial to flag as such, while some is difficult even for humans to gauge.

To help advance the art, Facebook is running a “Hateful Memes Challenge” as part of the NeurIPS AI conference later this year; this is commonly done with difficult machine learning tasks, as new problems like this one are like catnip for researchers.

AI’s changing role in Facebook policy

Facebook announced its plans to rely on AI more heavily for moderation in the early days of the COVID-19 crisis. In a press call in March, Mark Zuckerberg said that the company expected more “false positives”—instances of content flagged when it shouldn’t be—with the company’s fleet of 15,000 moderation contractors at home with paid leave.

YouTube and Twitter also shifted more of their content moderation to AI around the same time, issuing similar warnings about how an increased reliance on automated moderation might lead to content that doesn’t actually break any platform rules being flagged mistakenly.

In spite of its AI efforts, Facebook has been eager to get its human content reviewers back in the office. In mid-April, Zuckerberg gave a timeline for when employees could be expected to get back to the office, noting that content reviewers were high on Facebook’s list of “critical employees” marked for the earliest return.

While Facebook warned that its AI systems might remove content too aggressively, hate speech, violent threats and misinformation continue to proliferate on the platform as the coronavirus crisis stretches on. Facebook most recently came under fire for disseminating a viral video discouraging people from wearing face masks or seeking vaccines once they are available— a clear violation of the platform’s rules against health misinformation.

The video, an excerpt from a forthcoming pseudo-documentary called “Plandemic,” initially took off on YouTube, but researchers found that Facebook’s thriving ecosystem of conspiracist groups shared it far and wide on the platform, injecting it into mainstream online discourse. The 26-minute-long video, peppered with conspiracies, is also a perfect example of the kind of content an algorithm would have a difficult time making sense of.

On Tuesday, Facebook also released a community standards enforcement report detailing its moderation efforts across categories like terrorism, harassment and hate speech. While the results only include one a one month span during the pandemic, we can expect to see more of the impact of Facebook’s shift to AI moderation next time around.

In a call about the company’s moderation efforts, Zuckerberg noted that the pandemic has made “the human review part” of its moderation much harder, as concerns around protecting user privacy and worker mental health make remote work a challenge for reviewers, but one the company is navigating now. Facebook confirmed to TechCrunch that the company is now allowing a small portion of full-time content reviewers back into the office on a volunteer basis and according to Facebook Vice President of Integrity Guy Rosen, “the majority” of its contract content reviewers can now work from home. “The humans are going to continue to be a really important part of the equation,” Rosen said.

Source: Tech Crunch