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How ‘ghost work’ in Silicon Valley pressures the workforce, with Mary Gray

The phrase “pull yourself up by your own bootstraps” was originally meant sarcastically.

It’s not actually physically possible to do — especially while wearing Allbirds and having just fallen off a Bird scooter in downtown San Francisco, but I should get to my point.

This week, Ken Cuccinelli, the acting Director of the United States Citizenship and Immigrant Services Office, repeatedly referred to the notion of bootstraps in announcing shifts in immigration policy, even going so far as to change the words to Emma Lazarus’s famous poem “The New Colossus:” no longer “give me your tired, your poor, your huddled masses yearning to breathe free,” but “give me your tired and your poor who can stand on their own two feet, and who will not become a public charge.”

We’ve come to expect “alternative facts” from this administration, but who could have foreseen alternative poems?

Still, the concept of ‘bootstrapping’ is far from limited to the rhetorical territory of the welfare state and social safety net. It’s also a favorite term of art in Silicon Valley tech and venture capital circles: see for example this excellent (and scary) recent piece by my editor Danny Crichton, in which young VC firms attempt to overcome a lack of the startup capital that is essential to their business model by creating, as perhaps an even more essential feature of their model, impossible working conditions for most everyone involved. Often with predictably disastrous results.

It is in this context of unrealistic expectations about people’s labor, that I want to introduce my most recent interviewee in this series of in-depth conversations about ethics and technology.

Mary L. Gray is a Fellow at Harvard University’s Berkman Klein Center for Internet and Society and a Senior Researcher at Microsoft Research. One of the world’s leading experts in the emerging field of ethics in AI, Mary is also an anthropologist who maintains a faculty position at Indiana University. With her co-author Siddharth Suri (a computer scientist), Gray coined the term “ghost work,” as in the title of their extraordinarily important 2019 book, Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. 

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Image via Mary L. Gray / Ghostwork / Adrianne Mathiowetz Photography

Ghost Work is a name for a rising new category of employment that involves people scheduling, managing, shipping, billing, etc. “through some combination of an application programming interface, APIs, the internet and maybe a sprinkle of artificial intelligence,” Gray told me earlier this summer. But what really distinguishes ghost work (and makes Mary’s scholarship around it so important) is the way it is presented and sold to the end consumer as artificial intelligence and the magic of computation.

In other words, just as we have long enjoyed telling ourselves that it’s possible to hoist ourselves up in life without help from anyone else (I like to think anyone who talks seriously about “bootstrapping” should be legally required to rephrase as “raising oneself from infancy”), we now attempt to convince ourselves and others that it’s possible, at scale, to get computers and robots to do work that only humans can actually do.

Ghost Work’s purpose, as I understand it, is to elevate the value of what the computers are doing (a minority of the work) and make us forget, as much as possible, about the actual messy human beings contributing to the services we use. Well, except for the founders, and maybe the occasional COO.

Facebook now has far more employees than Harvard has students, but many of us still talk about it as if it were little more than Mark Zuckerberg, Cheryl Sandberg, and a bunch of circuit boards.

But if working people are supposed to be ghosts, then when they speak up or otherwise make themselves visible, they are “haunting” us. And maybe it can be haunting to be reminded that you didn’t “bootstrap” yourself to billions or even to hundreds of thousands of dollars of net worth.

Sure, you worked hard. Sure, your circumstances may well have stunk. Most people’s do.

But none of us rise without help, without cooperation, without goodwill, both from those who look and think like us and those who do not. Not to mention dumb luck, even if only our incredible good fortune of being born with a relatively healthy mind and body, in a position to learn and grow, here on this planet, fourteen billion years or so after the Big Bang.

I’ll now turn to the conversation I recently had with Gray, which turned out to be surprisingly more hopeful than perhaps this introduction has made it seem.

Greg Epstein: One of the most central and least understood features of ghost work is the way it revolves around people constantly making themselves available to do it.

Mary Gray: Yes, [What Siddarth Suri and I call ghost work] values having a supply of people available, literally on demand. Their contributions are collective contributions.

It’s not one person you’re hiring to take you to the airport every day, or to confirm the identity of the driver, or to clean that data set. Unless we’re valuing that availability of a person, to participate in the moment of need, it can quickly slip into ghost work conditions.

Lumineye helps first responders identify people through walls

Any first responder knows that situational awareness is key. In domestic violence disputes, hostage rescue or human trafficking situations, first responders often need help determining where humans are behind closed doors.

That’s why Megan Lacy, Corbin Hennen and Rob Kleffner developed Lumineye, a 3D-printed radar device that uses signal analysis software to differentiate moving and breathing humans from other objects, through walls.

Lumineye uses pulse radar technology that works like echolocation (how bats and dolphins communicate). It sends signals and listens for how long it takes for a pulse to bounce back. The software analyzes these pulses to determine the approximate size, range and movement characteristics of a signal.

On the software side, Lumineye’s app will tell a user how far away a person is when they’re moving and breathing. It’s one dimensional, so it doesn’t tell the user whether the subject is to the right or left. But the device can detect humans out to 50 feet in open air; that range decreases depending upon the materials placed in between, like drywall, brick or concrete.

One scenario the team gave to describe the advantages of using Lumineye was the instance of hostage rescue. In this type of situation, it’s crucial for first responders to know how many people are in a room and how far away they are from one another. That’s where the use of multiple devices and triangulation from something like Lumineye could change a responding team’s tactical rescue approach.

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Machines that currently exist to make these kind of detections are heavy and cumbersome. The team behind Lumineye was inspired to manufacture a more portable option that won’t weigh down teams during longer emergency response situations that can sometimes last for up to 12 hours or overnight. The prototype combines the detection hardware with an ordinary smartphone. It’s about 10 x 5 inches and weighs 1.5 pounds.

Lumineye wants to grow out its functionality to become more of a ubiquitous device. The team of four is planning to continue manufacturing the device, selling it directly to customers.

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Lumineye’s device can detect humans through walls using radio frequencies

Lumineye has just started its pilot programs, and recently spent a Saturday at a FEMA event testing out the the device’s ability to detect people covered in rubble piles. The company was born out of the Boise, Idaho cohort of Stanford’s Hacking4Defense program, a course meant to connect Silicon Valley innovations with the U.S. Department of Defense and Intelligence Community. The Idaho-based startup is graduating from Y Combinator’s Summer 2019 class.

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Megan Lacy, Corbin Hennen and Rob Kleffner

Slack co-founder Cal Henderson and Spark Capital’s Megan Quinn are coming to Disrupt SF

If there was one company at the top of everyone’s mind this year, it was Slack.

The now-ubiquitous workplace messaging tool began trading on the New York Stock Exchange in June after taking an unusual route to the public markets known as a direct listing. Slack bypassed the typical IPO process in favor of putting its current stock on to the NYSE without doing an additional raise or bringing on underwriter banking partners.

Slack co-founder and chief technology officer Cal Henderson and Slack investor and Spark Capital general partner Megan Quinn will join us on stage at TechCrunch Disrupt SF to give a behind the scenes look at Slack’s banner year, the company’s origin story and what convinced Quinn to participate in the business’s funding round years ago.

Early in his career, Henderson was the technical director of Special Web Projects at Emap, a UK media company. Later, he became the head of engineering for Flickr, the photo-sharing tool co-founded by Slack chief Steward Butterfield. In April 2009, he was reported to be starting a new stealth social gaming company with Butterfield, a project that would ultimately become Slack.

Quinn, for her part, added Slack to the Spark Capital portfolio in 2015, participating in the company’s $160 million Series E at a valuation of $2.8 billion. No small startup at the time, Slack already had 750,000 daily users and backing from Accel, Andreessen Horowitz, Social Capital, GV and Kleiner Perkins.

Quinn is a seasoned investor, known for striking deals with Coinbase, Glossier, Rover and Wealthfront, among others. She first entered the venture capital scene in 2012 as an investment partner at Kleiner Perkins, where she invested in early to mid-stage consumer tech startups. Quinn joined Spark Capital in 2015 to make growth-stage investments in companies across the board.

Before trying her hand at VC, she spent seven years in product management and strategic partnership development at Google and one year as the head of product at payments company Square.

Disrupt SF runs October 2 to October 4 at the Moscone Center in San Francisco. Tickets are available here.

Why startups ads are taking over the subway

But is transit still the best place to launch a direct-to-consumer brand?

If you’re a New Yorker, one of the easiest ways to keep up-to-date on the latest consumer products — furniture, beauty products, mobile apps, you name it — is to hop on the subway.

Even before you board, you may find yourself walking through a station filled with colorful startup ads. And once you’re actually on the train, you may find yourself surrounded by even more of those of ads.

It felt very different when I first moved to New York in 2013, back when the only companies that seemed to buy subway ads were local colleges, law firms and sketchy-sounding surgeons. Over the next few years, I noticed that the companies I wrote about in TechCrunch were starting to show up on the subway walls.

These ads are managed by Outfront Media, which has an exclusive contract with the MTA and says it’s worked with more than 150 startups and direct-to-consumer brands since 2018.

“Startups and DTC brands, now more than ever before, are looking for ways to raise awareness and gain market share among a heavy competitor set,” said Outfront’s chief product experience officer Jason Kuperman via email. “For these brands, it is all about testing and learning, and leveraging out-of-home (OOH) [advertising] and advertising on the subway allows them to do just that.”

Kuperman added that when they launch their subway campaigns, many of these startups are unknown, so they “find value in a permanent place to advertise that people pass through every day.”

From out-of-home to in transit

John Laramie, CEO of out-of-home advertising agency Project X, agreed that there’s been a big shift over the past few years.

He and I first spoke in 2011 about startups buying billboard ads alongside Silicon Valley’s main highway, Route 101. More recently, he told me, “Fast forward to the last four years, and who cares about the 101? It’s all about the New York City subway.”

Y Combinator-backed Holy Grail is using machine learning to build better batteries

For a long, long time, renewable energy proponents have considered advancements in battery technology to be the Holy Grail of the industry.

Advancements in energy storage has been among the hardest to achieve economically, thanks to the incredibly tricky chemistry that’s involved in storing power.

Now, one company that’s launching from Y Combinator believes it has found the key to making batteries better. The company is called Holy Grail and it’s launching in the accelerator’s latest cohort.

With an executive team that initially included Nuno Pereira, David Pervan and Martin Hansen, Holy Grail is trying to bring the techniques of the fabless semiconductor industry to the world of batteries.

The company’s founders believe that the only way to improve battery functionality is to take a systems approach to understanding how different anodes and cathodes will work together. It sounds simple, but Pereira says the computational power hadn’t existed to take into account all of the variables that go along with introducing a new chemical to the battery mix.

“You can’t fix a battery with just a component,” Pereira says. “All of the batteries that were created and failed in the past. They create an anode, but they don’t have a chemical that works with the cathode or the electrolyte.”

For Pereira, the creation of Holy Grail is the latest step on a long road of experimentation with mechanical and chemical engineering. “As a kid I was more interested in mechanical engineering and building stuff,” he says. But as he began tinkering with cars and became fascinated with mobility, he realized that batteries were the innovation that gave the world its charge.

In 2017 Pereira founded a company called 10Xbattery, which was making high-density lithium batteries. That company, launching with what Pereira saw as a better chemistry, encapsulated the industry’s problem at large — the lack of a holistic approach to development.

So, with the help of a now-departed co-founder, Pereira founded Holy Grail. “He essentially told me, ‘Do you want to take a step back and see if there’s a better way to do this?’ ” said Pereira.

The company pitches itself as science fiction coming from the future, but it relies on a combination of what are now fairly standard (at least in the research community) tools. Holy Grail’s pitch is that it can automate much of the research and development process to create new batteries that are optimized to the specifications of end customers.

“It’s hard for a human to do the experiments that you need and to analyze multidimensional data,” says Pereira. “There are some companies that only do the machine-learning part and the computational science part and sell the results to companies. The problem is that there’s a disconnection between experimental reality and the simulations.”

Using computer modeling, chemical engineering and automated manufacturing, Holy Grail pitches a system that can get real test batteries into the hands of end customers in the mobility, electronics and utility industries orders of magnitude more quickly than traditional research and development shops.

Currently the system that Holy Grail has built out can make 700 batteries per day. The company intends to  build a pilot plant that will make batteries for electronics and drones. For automotive and energy companies, Holy Grail says it will partner with existing battery manufacturers that can support the kind of high-throughput manufacturing big orders will require.

Think of it like bringing the fabless chip design technologies and business models to the battery industry, says Pereira.

Holy Grail already has $14 million in letters of intent with potential customers, according to Pereira, and is expecting to close additional financing as it exits Y Combinator.

To date the company has been backed by the London-based early-stage investment firm Deep Science Ventures, where Pereira worked as an entrepreneur in residence.

Ultimately, the company sees its technology being applied far beyond batteries as a new platform for materials science discoveries broadly. For now, though, the focus is on batteries.

“For the low volume we sell direct,” says Pereira. “While on high-volume production, we will implement a pilot line through the system… we are able to do the research engineering with the small ones and test the big ones. In our case when we have a cell that works, it’s not something that works in a lab, it’s something that works in the final cell.”