Sharing Project Amber with the mental health community

New open source resources to help researchers collect and interpret electroencephalography (EEG) data for mental health measurement

Today at the Sapien Labs Symposium, my colleague Vlad Miskovic presented insights from Project Amber, an early stage mental health project at X. Amber’s small team of of neuroscientists, hardware and software engineers, machine learning researchers and med-tech product experts have been developing prototype technologies to help tackle the huge and growing problem of mental health. After three years of exploration, we recently wrapped up our work at X. Now we are making our technology and research findings freely available in the hope that the mental health community can build upon our work.

Poor mental health is a huge and growing problem globally. The World Health Organization estimated in 2017 that 322M people globally suffer from depression and 264M from anxiety. The COVID-19 pandemic is causing widespread psychological distress, affecting even more people.

One of the challenges is that it is truly difficult to assess mental health, both for people who are distressed and for health care providers who are not experts in mental health. With 1000 possible symptom combinations, depression manifests differently in different people. Today’s assessment of mental health mostly relies on asking people a series of questions in a conversation with a clinician or via surveys such as the PHQ-9 or GAD-7, which are subjective. While it is important to capture the subjective experience of a person living with mental health problems, the field is missing objective measures that are commonplace in other areas of health. For example, people with diabetes and their doctors routinely measure blood glucose and use these data to make adjustments to insulin, diet and exercise regimes — but there is no equivalent for depression or anxiety.

Amber’s moonshot: Finding a biomarker for depression

Our journey started by asking the question: what if we could make brain waves as easy to measure and interpret as blood glucose, and use them as an objective measurement of depression? Our approach was to marry cutting-edge machine learning techniques with a 96-year-old technology to measure electrical activity in the brain: electroencephalography (EEG)

We were inspired by neuroscience studies showing that certain patterns of electrical activity in the brain correspond with depression symptoms. For example, many depressed people find that things that once brought them pleasure no longer do so; they don’t experience the reward that follows a positive experience. By designing specific game-like tasks that people complete while their brain activity is being measured using EEG, scientists can gauge processing within the brain’s reward system. It turns out that the brain response following a win in the game — an event related potential (ERP) — is subdued in people who are depressed, compared to those who are not.

Image for post
Difference in reward response among depressed and non-depressed people
(unpublished data from Amber feasibility study with Florida State University)

This blunted brain response is a reliable effect that has been shown in many studies, which we replicated in our own study carried out in partnership with Greg Hajcak and his team at Florida State University.

However, these studies were done in neuroscience research labs. They require expensive specialist equipment and highly trained EEG experts to collect, process and interpret the data. For EEG to come out of the lab and into the real world as a mental health assessment tool in a primary care doctor’s office, counseling centre or psychiatric clinic, it needs to become more accessible and usable at scale.

Our project at X focused on three areas:
1) Making EEG data easier to collect
2) Making EEG data easier to interpret
3) Understanding how this technology might be applied in the real world

The rest of this post lays out our work and insights in each of these areas.

Making EEG data easier to collect: The Amber EEG system

Our team set out to develop an easy-to-use, low-cost, portable, research-grade EEG system.

Image for post
Hardware engineer Gabriella Levine (left), neuroscientist Sarah Laszlo (right) testing early Amber prototypes

We built many prototypes of bioamplifiers, headsets and sensors, and tested them in feasibility studies at X and at Florida State University. 

Image for post
A selection of the Amber EEG prototypes

In our final prototype the headset slips on like a swim cap and can be put on by anyone with minimal training, taking around three minutes to set up. It uses three dry sensors arranged along the midline at Fz, Cz, Pz, the most important channels for ERP assessments of reward and cognitive function. The accompanying bioamp can support up to 32 channels, so it’s possible to connect a standard headset with some modifications. Amber’s system can be used to collect resting state EEG and event-related potentials with our software that time-locks a task to the EEG measurement.

Image for post
Amber’s final EEG prototype: Headset, sensor strip and bioamp

Making EEG data easier to interpretApplying machine learning techniques to EEG signal

Our team also explored how new approaches in machine learning can be applied to interpreting EEG data. To make EEG data usable by mental health researchers and clinicians more broadly — i.e. outside electrophysiology labs and neurology clinics — it would be helpful to have automated ways to denoise the signals at scale, and to determine which aspects of the EEG signal are relevant. Collaborating with the team at DeepMind, we adapted methods from unsupervised representation learning to address these challenges. We set out our findings in a paper that is currently under review.

First, we demonstrated that representation learning approaches such as autoencoders could be leveraged to effectively denoise EEG signals without a human EEG expert in the loop. This is important to enable processing EEG data at scale. Second, we offer a proof of concept that it’s possible to extract interpretable features that are relevant to mental health. We used these features obtained from disentangling autoencoders to predict several clinical labels such as major depressive disorder and generalized anxiety disorder, based on a clinical interview by a mental health expert. Unlike previous studies, we were able to do this for an individual participant (rather than a group), which is essential to make it useful in a clinical setting. The methods were capable of recovering usable signal representations from single EEG trials. This means that it may be possible to derive clinically useful information from brain electrophysiology with far fewer data samples than what is traditionally used in research labs, which often rely on hundreds of experimental trials.

Understanding how this technology might be applied in the real world: Insights from user research

Over the course of our project, we conducted over 250 interviews with potential users of this technology. We spoke to people with lived experience of mental health problems and with clinicians of all kinds, including counsellors, therapists, psychiatrists, clinical psychologists, social workers, primary care practitioners and pediatricians. We tested how Amber’s proposition of introducing a new, more objective measure of depression and anxiety resonated with them, how they might use it in their daily lives and professional practice, and what the challenges might be in introducing such a radical new approach.

Here are three key insights from our user research:

  1. Mental health measurement remains an unsolved problem. Despite the availability of many mental health surveys and scales, they are not widely used, especially in primary care and counseling settings. Reasons range from burden (“I don’t have time for this”) to skepticism (“Using a scale is no better than using my clinical judgement”) to lack of trust (“I don’t think my client is filling this in truthfully” and ”I don’t want to reveal this much to my counsellor”). These findings were in line with the literature on measurement-based mental health care. Any new measurement tool would have to overcome these barriers by creating clear value for both the person with lived experience and the clinician.
  2. There is value in combining subjective and objective data. People with lived experience and clinicians both welcomed the introduction of objective metrics, but not as a replacement for subjective assessment and asking people about their experience and feelings. The combination of subjective and objective metrics was seen as especially powerful. Objective metrics might validate the subjective experience; or if the two diverge, that in itself is an interesting insight which provides the starting point for a conversation.
  3. There are multiple use cases for new measurement technology. Our initial hypothesis was that clinicians might use a “brainwave test” as a diagnostic aid. However, this concept got a lukewarm reception. Mental health experts such as psychiatrists and clinical psychologists felt confident in their ability to diagnose via clinical interview. Primary care physicians thought an EEG test could be useful, but only if it was conducted by a medical assistant before their consultation with the patient, similar to a blood pressure test. Counsellors and social workers don’t do diagnosis in their practice, so it was irrelevant to them. Some people with lived experience did not like the idea of being labelled as depressed by a machine. By contrast, there was a notably strong interest in using technology as a tool for ongoing monitoring — capturing changes in mental health state over time — to learn what happens between visits. Many clinicians asked if they could send the EEG system home so their patients and clients could repeat the test on their own. They were also very interested in EEG’s potential predictive qualities, e.g. predicting who is likely to get more depressed in future. More research is needed to determine how a tool such as EEG would be best deployed in clinical and counseling settings, including how it could be combined with other measurement technologies such as digital phenotyping.

Much of our research was conducted in the US and the UK in partnership with Shift, a nonprofit based in London. This report by Shift details the research and the findings. (Report added on 15 December 2020.)

Opening up Amber to the world

We didn’t succeed in our original goal of finding a single biomarker for depression and anxiety. It is unlikely that one exists, given the complexity of mental health. Yet there’s no question that there is a huge opportunity for technology to enable better measurement.

This will empower individuals and their healthcare provider to better match intervention options to an individual’s needs, to measure the impact of those interventions, and ultimately promote better mental health. While the promise of emerging measurement techniques like EEG/ERP and digital phenotyping is very exciting, it is still early days. There are many pitfalls on the path to making tech-enabled mental health measurement work in the real world, and more research needs to be done.

For this reason we’ve decided to make Amber’s technology and insights available to the global mental health community. We believe we can make a bigger and faster impact on this huge problem by sharing our work freely.

Today, we are open-sourcing our hardware designs, visualizer and stimulus software of the Amber prototype EEG system and putting the code on Github. We are also pledging the free use of our patents and applications listed in this patent pledge. We are making these resources available so that mental health researchers have all of the specifications, code, and permissions they would need to rebuild our EEG system, or design their own based on it. In addition we are donating 50 assembled Amber prototype devices to Sapien Labs for use by researchers worldwide as part of their Human Brain Diversity Project which supports EEG research globally, with an emphasis on low-income countries and underrepresented groups.

We hope that open-sourcing our EEG system and publishing our machine learning techniques will be of value not just to EEG experts, but also to the wider mental health research community who were perhaps put off by the complexity and cost of working with EEG before. Addressing today’s challenges will require new partnerships between scientists, clinicians, technologists, policymakers, and individuals with lived experience. Now more than ever, more diverse voices, more multi-disciplinary collaboration, and more open sharing of knowledge are needed to unlock better mental health for everyone.

To learn more about Amber’s technology and user research, please visit the following links:

Please note: The Amber EEG System is a prototype investigational device and has not been evaluated by the US Food and Drug Administration or any other regulatory agency for any purpose, including a medical purpose.

This blog was first published on 2 November 2002 and updated on 15 December 2020 with links to the Shift user research report.

Financial Times: ‘You Can’t Cast Half the Population As Villains and the Other Half As Victims’

The tech executive on how she makes ‘moonshots’ a reality at X

By Hannah Kuchler
Photos by Maggie Shannon

This article was published on 5 December 2018 as part of the Financial Times Series Women in 2018: The Change Makers.
Copyright The Financial Times Limited 2018
Read the original on FT.com (subscription required) or the FT’s Medium blog.

Thanks to Obi Felten, there are self-driving cars on the streets, internet-beaming balloons in the sky and burritos delivered by drones. Felten is chief translator for the “moonshooters”. The team she heads at X, owned by Google’s parent company Alphabet, helps innovators ready their technologies for the real world. X is used to incubate the Silicon Valley giant’s most daring projects — known as “moonshots” because they are supposedly as audacious as launching a spacecraft to the moon.

Fluent in both engineer and earthling, the 46-year-old German explains her unusual role. “I am a translator. No, I’m serious,” she insists, as I smile. “I’m really good at translating between engineers, technical people and non-technical people, who sometimes don’t understand each other.”

Felten is a rare female leader in the technology industry, where maverick men are more usually celebrated. But the questioning spirit she applies to her day job has led her to challenge this male-dominated world to open up to women. She was among those to join the recent walkout of Google employees over the company’s handling of sexual harassment allegations.

After more than two decades working for global tech companies, Felten is adept at bridging different cultures and disciplines. Born to academic parents in Berlin, she witnessed her first big change as a teenager when the Wall came down. She studied philosophy and psychology at Oxford before getting swept up in the dotcom boom as a product manager for eToys.com. After marketing more conventional Google products, such as Chrome and Maps, she joined X.

© Maggie Shannon

As politicians and regulators grapple with social networks that leak data, perhaps even damaging democracy, and smartphones are accused of warping our minds and manners, Silicon Valley needs translators more than ever.

“There’s this misconception that technology is built by technologists in this bubble and then it gets thrown out into the world. That’s partly because there have been bad examples of exactly that happening,” Felten says. “We don’t want to make that mistake. Yes, technology will shape society, but society also has the obligation to shape the technology and make sure it is deployed to solve humanity’s problems and not just create new ones.”


X is possibly the most exciting thing that has ever happened to a suburban shopping mall. The bland, beige structure in Mountain View, California, a couple of miles from Google’s main campus, has been transformed into a workshop to change the world.

In the lobby are examples of outlandish projects that have “graduated” from the lab. There’s a self-driving bubble car with no steering wheel, now part of Waymo, Alphabet’s self-driving car unit. Then there’s the Loon balloon, with the translucency of a jellyfish, launched in July to extend internet access around the world. It was used to bring connectivity to Puerto Rico after Hurricane Maria, and will soon be flying over Kenya.

Felten first heard about these projects six years ago while talking to the scientist Astro Teller, X’s “captain of moonshots”. “I asked him all these questions,” she says, “like, ‘Is it legal to fly balloons over countries? Have you talked to any governments about it? Are you going to partner with phone companies or compete with them? Do you have a business plan?’”

Teller said these were good questions — but his engineers were mostly working on technical problems. “And he looked at me and he said, ‘Why don’t you come here and help us?’”

X’s philosophy is that it is easier to invent a solution that is “10X” — a tenfold improvement on a current idea — than to improve it by 10 per cent. “If you free yourself from preconceived notions, then you can be more creative,” Felten says.

They begin by tackling the hardest part of the problem. This approach is called #monkeyfirst: Teller has written that if you are trying to teach a monkey to recite Shakespeare on a pedestal, you should not be tempted to start by building the pedestal.

With this in mind, Wing, a drone delivery unit that graduated from X, is starting with food precisely because it’s so difficult: hot meals have to be delivered quickly, and demand is uneven.

Teams are pushed to test products in the real world as soon as possible. When X tested semi-autonomous cars on Googlers, they learnt an important lesson: even if you tell people to watch the road, they don’t when they think the car is driving itself, so it’s safer to design a fully autonomous car.

Felten believes other tech companies could learn from bringing in users to test products and even involving them in product development. Silicon Valley should be open to outside voices, be they partner companies or regulators, and by hiring staff from a variety of backgrounds, she says.

Testing helps X to fail fast — but it still prefers to fail quietly. Felten had not yet joined the company when Google Glass, its smart eyewear, arrived, complete with skydivers at Google’s conference and a feature in Vogue. But she vows X will never be so splashy again. “The engineers all thought of it as a prototype, but the world received it as a product because of the way we positioned it,” she says.

Technology will shape society, but society also has the obligation to shape technology.”

It soon became clear that Glass was not useful enough to consumers for them to put up with wearing a weird mini-computer on their face. It was, however, convenient in businesses, where an enterprise edition is now used by engineers and doctors.

Even in Silicon Valley, where praising failure has become a cliché, it can be hard to abandon an idea. Felten sets “kill” criteria with her teams: they agree that if certain things happen, they will dump the project. “We accept that we’re going to fail a lot of times, because the more audacious your endeavour is… the more likely you’re going to fail along the way,” she says.


When Felten arrived on the West Coast from the UK, she was surrounded by men. In London, she had role models from other industries or in politics. But in Silicon Valley, large tech companies are almost all run by men. About 80 per cent of technical positions are filled by men, and 70 per cent of all roles. Venture capital is even more male, with female start-up founders receiving just 2 per cent of VC dollars last year.

This situation inspired Felten to become an “active” rather than a “latent” feminist. “I actually sought out other women, because I realised quickly that was a shortcut to finding the really talented people,” she says.

Simmering discontent with the Silicon Valley status quo burst into the open last year when Susan Fowler, a former software engineer at Uber, wrote powerfully about how sexual harassment was ignored at the company. Her post led to an investigation at Uber, which contributed to the departure of chief executive Travis Kalanick. “Susan’s blog post was a watershed,” Felten says. “The fact that it changed Uber, the way it kicked that off, is a really extraordinary thing.”

© Maggie Shannon

Admitting she may be an “incurable optimist”, Felten sees some improvement in the Valley since then, with more women demanding change and more men committing to improving women’s lives at work. As momentum built in the #MeToo movement, women increasingly reported harassment and denounced tech companies, including Google, for their treatment of the female workforce.

A recent New York Times article claimed that two senior Google executives had left with significant departure packages, one of $90m, despite allegations of sexual harassment that internal investigations found credible. One director at X also left following reports of sexual harassment but did not receive a payout.

The story provoked a Google-wide walkout, with employees of both sexes accusing the company of hypocrisy for not living up to its professed values of diversity and inclusion. “I didn’t even think about not participating,” Felten says. “I thought it was a great idea. It was a statement to draw attention to some of the issues. Everyone here was incredibly supportive.”

Google responded to some of the organisers’ demands, including dropping forced arbitration for sexual harassment claims. But many employees have said it needs to do more to close the gender gap. I ask Felten if, given her position, she thought there were other ways of pushing Google to take action. She begins by talking about promoting diversity. The list starts to sound like many well-meaning efforts in tech companies — but Felten is, of course, thinking bigger.

“When we grew up, it was very much like, you’re a girl or you’re a boy, right. In high schools here, people talk about gender fluidity. But what if we actually think about it much more in terms of femininity and masculinity?

“So yes, we need to empower women and our girls, and teach them how to adopt some masculine traits because those still get you propelled in the way society works at the moment. But let’s also give boys and men permission to use some of the more feminine traits. I almost think it’s harder for a boy to be feminine than it is for a girl to be masculine.”

We need to teach girls how to adopt some masculine traits. But let’s also give boys and men permission to use some more feminine traits

A less binary approach might also help calm the gender debate. A men’s rights movement is simmering on the internet and inside Google, where engineer James Damore was fired last year for circulating a memo that, among other things, said women were biologically better suited to “jobs in artistic or social areas” than engineering.

Felten is unconvinced. “You can’t cast half the population as villains and the other half as the victims. A, I think that’s not great for women either. I don’t want to be cast as a victim. And B, there’s many, many men who are incredibly supportive,” she says.

Is that the 10X idea for solving discrimination against women? I ask. Felten cups her hands on her face. “I don’t know,” she says. But she thinks making our workplaces more inclusive can only help us to crack the world’s biggest challenges. “Think about it. If you brought all this talent to the table that’s currently neglected, not just in our society but in countries across the globe, you would have all that much more brain power to apply to these problems.”

Felten’s list of problems to solve is “endless”: she is excited about using algorithms to understand biological data and applying machine learning to improve food production. But the biggest — or #monkeyfirst — challenge may be tackling climate change. X has done several projects in the area. Some have failed; others, such as Dandelion, which brings geothermal energy into people’s homes, are now companies.

“If we don’t solve climate change within the next generation or so, then there will be a tipping point where it will become much more difficult,” Felten says. “It’s really hard — and it’s definitely a moonshot.”

Hannah Kuchler is an FT correspondent in San Francisco

Copyright The Financial Times Limited 2018

© 2018 The Financial Times Ltd. All rights reserved.

Helmholtz Horizons: Living in modern times

Helmholtz Horizons
6 November 2018
Berlin
Keynote
“Solving problems that matter: Insights from X, Alphabet’s moonshot factory”


Obi delivered the closing keynote of Helmholtz Horizons, a summit for European scientists and science policy makers. The Helmholtz Association of German Research Centres (Helmholtz-Gemeinschaft Deutscher Forschungszentren) is the largest scientific organisation in Germany, a union of 18 scientific-technical and biological-medical research centers.

The Atlantic: Google X and the Science of Radical Creativity

How the secretive Silicon Valley lab is trying to resurrect the lost art of invention

By Derek Thompson
Photos by Justin Kaneps

This article about X was the cover story of The Atlantic November 2017 issue.
Copyright The Atlantic 2017
Excerpt below. Read the full article on TheAtlantic.com

III. The Fail

Astro Teller likes to recount an allegorical tale of a firm that has to get a monkey to stand on top of a 10-foot pedestal and recite passages from Shakespeare. Where would you begin? he asks. To show off early progress to bosses and investors, many people would start with the pedestal. That’s the worst possible choice, Teller says. “You can always build the pedestal. All of the risk and the learning comes from the extremely hard work of first training the monkey.” An X saying is “#MonkeyFirst”—yes, with the hashtag—and it means “do the hardest thing first.”

But most people don’t want to do the hardest thing first. Most people want to go to work and get high fives and backslaps. Despite the conference-keynote pabulum about failure (“Fail fast! Fail often!”), the truth is that, financially and psychologically, failure sucks. In most companies, projects that don’t work out are stigmatized, and their staffs are fired. That’s as true in many parts of Silicon Valley as it is anywhere else. X may initially seem like a paradise of curiosity and carefree tinkering, a world apart from the drudgery required at a public company facing the drumbeat of earnings reports. But it’s also a place immersed in failure. Most green-lit Rapid Eval projects are unsuccessful, even after weeks, months, or years of one little failure after another.

At X, Teller and his deputies have had to build a unique emotional climate, where people are excited to take big risks despite the inevitability of, as Teller delicately puts it, “falling flat on their face.” X employees like to bring up the concept of “psychological safety.” I initially winced when I heard the term, which sounded like New Age fluff. But it turns out to be an important element of X’s culture, the engineering of which has been nearly as deliberate as that of, say, Loon’s balloons.

Kathy Hannun told me of her initial anxiety, as the youngest employee at X, when she joined in the spring of 2012. On her first day, she was pulled into a meeting with Teller and other X executives where, by her account, she stammered and flubbed several comments for fear of appearing out of her depth. But everyone, at times, is out of his or her depth at X. After the meeting, Teller told her not to worry about making stupid comments or asking ignorant questions. He would not turn on her, he said.

Hannun now serves as the CEO of Dandelion, an X spin-off that uses geothermal technology to provide homes in New York State with a renewable source of heating, cooling, and hot water. “I did my fair share of unwise and inexperienced things over the years, but Astro was true to his word,” she told me. The culture, she said, walked a line between patience and high expectations, with each quality tempering the other.

X encourages its most successful employees to talk about the winding and potholed road to breakthrough invention. This spring, André Prager, a German mechanical engineer, delivered a 25-minute presentation on this topic at a company meeting, joined by members of X’s drone team, called Project Wing. He spoke about his work on the project, which was founded on the idea that drones could be significant players in the burgeoning delivery economy. The idea had its drawbacks: Dogs may attack a drone that lands, and elevated platforms are expensive, so Wing’s engineers needed a no-landing/no-infrastructure solution. After sifting through hundreds of ideas, they settled on an automatic winching system that lowered and raised a specialized spherical hook—one that can’t catch on clothing or tree branches or anything else—to which a package could be attached.

In their address, Prager and his team spent less time on their breakthroughs than on the many failed cardboard models they discarded along the way. The lesson they and Teller wanted to communicate is that simplicity, a goal of every product, is in fact extremely complicated to design. “The best designs—a bicycle, a paper clip—you look and think, Well of course, it always had to look like that,” Prager told me. “But the less design you see, the more work was needed to get there.” X tries to celebrate the long journey of high-risk experimentation, whether it leads to the simplicity of a fine invention or the mess of failure.

Because the latter possibility is high, the company has also created financial rewards for team members who shut down projects that are likely to fail. For several years, Hannun led another group, named Foghorn, which developed technology to turn seawater into affordable fuel. The team appeared to be on track, until the price of oil collapsed in 2015 and its members forecast that their fuel couldn’t compete with regular gasoline soon enough to justify keeping the project alive. In 2016, they submitted a detailed report explaining that, despite advancing the science, their technology would not be economically viable in the near future. They argued for the project to be shut down. For this, the entire team received a bonus.

Some might consider these so-called failure bonuses to be a bad incentive. But Teller says it’s just smart business. The worst scenario for X is for many doomed projects to languish for years in purgatory, sucking up staff and resources. It is cheaper to reward employees who can say, “We tried our best, and this just didn’t work out.”

Recently, X has gone further in accommodating and celebrating failure. In the summer of 2016, the head of diversity and inclusion, a Puerto Rican–born woman named Gina Rudan, spoke with several X employees whose projects were stuck or shut down and found that they were carrying heavy emotional baggage. She approached X’s leadership with an idea based on Mexico’s Día de los Muertos, or Day of the Dead. She suggested that the company hold an annual celebration to share stories of pain from defunct projects. Last November, X employees gathered in the main hall to hear testimonials, not only about failed experiments but also about failed relationships, family deaths, and personal tragedies. They placed old prototypes and family mementos on a small altar. It was, several X employees told me, a resoundingly successful and deeply emotional event.

No failure atx has been more public than Google Glass, the infamous head-mounted wearable computer that resembled a pair of spectacles. Glass was meant to be the world’s next great hardware evolution after the smartphone. Even more quixotically, its hands-free technology was billed as a way to emancipate people from their screens, making technology a seamless feature of the natural world. (To critics, it was a ploy to eventually push Google ads as close to people’s corneas as possible.) After a dazzling launch in 2013 that included a 12-page spread in Vogue, consumers roundly dissed the product as buggy, creepy, and pointless. The last of its dwindling advocates were branded “glassholes.”

I found that X employees were eager to talk about the lessons they drew from Glass’s failure. Two lessons, in particular, kept coming up in our conversations. First, they said, Glass flopped not because it was a bad consumer product but because it wasn’t a consumer product at all. The engineering team at X had wanted to send Glass prototypes to a few thousand tech nerds to get feedback. But as buzz about Glass grew, Google, led by its gung-ho co-founder Sergey Brin, pushed for a larger publicity tour—including a ted Talk and a fashion show with Diane von Furstenberg. Photographers captured Glass on the faces of some of the world’s biggest celebrities, including Beyoncé and Prince Charles, and Google seemed to embrace the publicity. At least implicitly, Google promised a product. It mailed a prototype. (Four years later, Glass has reemerged as a tool for factory workers, the same group that showed the most enthusiasm for the initial design.)

But Teller and others also saw Glass’s failure as representative of a larger structural flaw within X. It had no systemic way of turning science projects into businesses, or at least it hadn’t put enough thought into that part of the process. So X created a new stage, called Foundry, to serve as a kind of incubator for scientific breakthroughs as its team develops a business model. The division is led by Obi Felten, a Google veteran whose title says it all: head of getting moonshots ready for contact with the real world.

Obi Felten leads Foundry, a division of X tasked with turning scientific breakthroughs into marketable products. (Justin Kaneps)

“When I came here,” Felten told me, “X was this amazing place full of deep, deep, deep geeks, most of whom had never taken a product out into the world.” In Foundry, the geeks team up with former entrepreneurs, business strategists from firms like McKinsey, designers, and user-experience researchers.

One of the latest breakthroughs to enter Foundry is an energy project code-named Malta, which is an answer to one of the planet’s most existential questions: Can wind and solar energy replace coal? The advent of renewable-energy sources is encouraging, since three-quarters of global carbon emissions come from fossil fuels. But there is no clean, cost-effective, grid-scale technology for storing wind or solar energy for those times when the air is calm or the sky is dark. Malta has found a way to do it using molten salt. In Malta’s system, power from a wind farm would be converted into extremely hot and extremely cold thermal energy. The warmth would be stored in molten salt, while the cold energy (known internally as “coolth”) would live in a chilly liquid. A heat engine would then recombine the warmth and coolth as needed, converting them into electric energy that would be sent back out to the grid. X believes that salt-based thermal storage could be considerably cheaper than any other grid-scale storage technology in the world.

The current team leader is Raj B. Apte, an ebullient entrepreneur and engineer who made his way to X through parc. He compares the project’s recent transition to Foundry to “when you go from a university lab to a start-up with an A-class venture capitalist.” Now that Apte and his team have established that the technology is viable, they need an industry partner to build the first power plant. “When I started Malta, we very quickly decided that somewhere around this point would be the best time to fire me,” Apte told me, laughing. “I’m a display engineer who knows about hetero-doped polysilicon diodes, not a mechanical engineer with a background in power plants.” Apte won’t leave X, though. Instead he will be converted into a member of the Rapid Eval team, where X will store his creative energies until they are deployed to another project.

Raj B. Apte, the leader of Project Malta, which seeks to store wind power in molten salt (Justin Kaneps)

Thinking about the creation of Foundry, it occurred to me that X is less a moonshot factory than a moonshot studio. Like MGM in the 1940s, it employs a wide array of talent, generates a bunch of ideas, kills the weak ones, nurtures the survivors for years, and brings the most-promising products to audiences—and then keeps as much of the talent around as possible for the next feature.

Derek Thompson is a staff writer at The Atlantic, where he writes about economics, technology, and the media. He is the author of Hit Makers and the host of the podcast Crazy/Genius.

Copyright The Atlantic 2017

Chautauqua Institution: Living in modern times

Chautauqua Institution summer season
26 June 2017
Chautauqua, New York
Keynote
“Living in modern times: The past, present and future of invention (and innovation)”


Obi delivered the opening lecture of the 2017 Chautauqua Institution summer season. Chautauqua Institution is a community on the shores of Chautauqua Lake in southwestern New York state that comes alive each summer with a unique mix of fine and performing arts, lectures, interfaith worship and programs, and recreational activities. Previous speakers include Franklin Delano Roosevelt, Hillary Clinton, Ruth Bader Ginsburg, Tarana Burke, Arthur Brooks.

Watch the full lecture

Article on this talk

Obi Felten discusses moonshots and the power of innovation to make sci-fi a reality

By Brian Contreras
Photos by Cam Buker
This article was published on 26 June 2017
Copyright The Chautauquan Daily
Read the original on Chqdaily.com

Photo: Cam Buker

Xerox PARC scientist Alan Kay once said, “The best way to predict the future is to invent it.”

Obi Felten opened her Monday morning lecture with this quote, in turn opening the 2017 Chautauqua season as well as Week One and its theme of “Invention,” which asks, among other questions, what it might take for humanity’s next “giant leap.”

In her capacity as head of getting moonshots ready for contact with the real world at X (formerly Google X), Felten knows a thing or two about invention, not to mention the future. At X, she has worked with ideas that seem straight out of science fiction; they might seem more at home on the silver screen, but these inventions could one day be real, at least if Felten has her way.

After opening with Kay’s quote and enumerating a number of the cutting-edge inventions her X team has worked on, Felten launched full-steam into outlining what X does, and perhaps more urgently, what her lengthy job title actually consists of.

“We call ourselves the moonshot factory,” Felten said, “and we aim to solve large problems in the world with the help of technology.”

Though the work itself is hard, the moonshot team’s process is seductively simple. First, identify a problem (and not just any problem, but a big one, the sort that impacts “millions or even billions of people”). Then, propose a solution, no matter how outlandish, how seemingly impossible, it is. Finally — and this is where the difficult work of invention comes in — “turn (that) fiction into reality.”

Though making these moonshots real is never easy, Felten said it’s worth it. An optimist about the power of technology to make the world a better place, she cautioned against thinking of the current era as a uniquely disruptive one; as poet Alan Kirsch noted, all generations tend to think they live in periods of fundamental change.

That said, Felten made clear the modern age is by no means lacking in disruption, especially of the technological sort. She pointed to the internet in particular as having enabled an enormous paradigm shift in what is possible.

“We live in San Francisco, and my children think it’s completely normal to have breakfast with my parents, who live in Germany,” Felten said.

Felten acknowledged that the enormous potential of these emergent technologies has not been distributed equally. But through X, she and her team are working to change that.

For instance, she said, over half the world’s population lacks access to the internet. It was this global inequity that Felten and her team set out to solve with Loon, their balloon-based internet accessibility project.

Following a concise history of the balloon as a disruptive technology — from hot air balloonist Auguste Piccard to NASA and Bell Labs’ 1950s “communication satellites” — Felten outlined Loon’s modern quest to create airborne, data-transmitting balloons that could float through the sky and bring internet access to those on the ground below.

But the project was not without its failures.

“Our balloons were supposed to last 100 days,” Felten said. “The first balloons lasted five days.”

Ultimately, however, innovative responses to the durability question and other issues were successful, and the Loon project took flight (both literally and metaphorically) during a 2013 test in New Zealand. It was then that a rural sheep farmer, Charles, became the first human being to ever use Wi-Fi transmitted via balloon.

These days, Loon’s devices can last up to 190 days, and while they’re at it, provide LTE speeds to those who might otherwise have gone without internet. They even helped provide emergency communications capacities when destructive floods hit the Peruvian coast this past March.

But Loon is far from the only moonshot that Felten has worked on while at X. After all, as she puts it, humanity is currently in the midst of a “fourth industrial revolution.” Internet balloons are but one of many projects her team has in progress.

Perhaps the most publicized of these moonshots has been the self-driving car, a which has since graduated into its own company, the headlines-making Waymo.

The idea of a self-driving car is not without precedent. Leonardo da Vinci — the most iconic of inventors — designed one as far back as 1478. But with its movements preprogrammed and the only terrain it was suited for being a theater stage, da Vinci’s concept still had a long way to go  before it achieved Jetson-esque viability. From General Motors’ automated highway dioramas at the 1939 World’s Fair, through the 1971 launch of an automated Mars rover, to scientists at the Bundeswehr Uni Munich finally creating the first truly independent vehicle in the 1980s; the path to self-driving cars has been a long and circuitous one.

Obi Felten, Center, Speaks With Chautauquans On The Back Porch Of The Amphitheater Following Her Lecture On Monday, June 26, 2017.
CAM BUKER/STAFF PHOTOGRAPHER

But this narrative reached its climax in the mid-2000s, when the Defense Advanced Research Projects Agency launched a contest to see who could develop the best self-driving car. From 2004 to 2007, teams from Stanford and Carnegie Mellon Universities dueled back and forth to build the smartest, longest-running vehicle; it wasn’t until 2009 when members of both teams united under the Google self-driving car project that Felten’s moonshot began the trudge toward realization. All this time, though, the moonshot team stayed focused.

“The problem we’re trying to solve is safety,” Felten said. “Because 1.2 million people die on the road each year, and 94 percent of those accidents are caused by human error.”

The project’s work paid off in very real, human terms last year, when a blind man in Austin, Texas, took the world’s first truly autonomous ride in one of the team’s self-driving cars.

There is still a ways to go before their moonshot gets to its proverbial moon, Felten said, “but it’s exciting to see that we’re (turning) science fiction into reality.”

But with revolutionary projects like internet balloons or self-driving cars, Felten warned that it’s easy to get sucked into “the great myth of the lonely genius inventor.” Though people imagine the likes of Thomas Edison or Steve Jobs creating their legendary inventions in isolation, groups like X work hard to foster teamwork, communication and partnerships across any number of different industries and disciplines.

The myth of individualism isn’t the only concept that threatens to impede innovation, however; more than anything else (including funding), Felten sees a fear of failure as the single largest threat to inventing one’s way to a better future.

“To be audacious, you have to be humble,” Felten said. “And you have to expect that most of what you work on will not work.”

This is not abstract for Felten, either; her moonshot team takes pride in its failed projects. For instance, their abandoned Project Foghorn sought to turn ocean water into clean, efficient car fuel but was unable to overcome the steep competition with cheap oil. When it was ultimately shut down, all team members received bonuses for their decision to abandon the (at least temporarily) intractable concept.

As her lecture drew to a close, Felten returned to cultural fears about, rather than hopes for, new technologies. At first, she acknowledged the potential for new technology to widen, rather than bridge, gaps in socioeconomic class and quality of life; she also noted discomfort with the capacity for job automation to cause widespread unemployment.

But even if “we need to adapt” to keep pace with rapidly changing technological capacities, Felten ultimately sees this disruption as providing humanity with the opportunity to create for itself a more hospitable, equitable planet.

“We have a choice about which world we want to live in,” she said.

Felten presented essentially two versions of the future: one in which “the largest beneficiaries of invention are … the innovators, the shareholders, the investors,” or one where “innovation doesn’t just come from the hands of companies …  but from anywhere.”

Either way, the choice between those two potential paths is in the hands of people, not their tools.

“Technology of course will not solve all our problems, and there is no doubt that it will create some new ones,” she said. “But it is up to us how we use technology to make a better future for ourselves and for generations to come.”