Elizabeth Holmes Through the Director’s Lens
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
"The Inventor," a chronicle of Theranos's storied downfall, premiered recently on HBO. Leapsmag reached out to director Alex Gibney, whom The New York Times has called "one of America's most successful and prolific documentary filmmakers," for his perspective on Elizabeth Holmes and the world she inhabited.
Do you think Elizabeth Holmes was a charismatic sociopath from the start — or is she someone who had good intentions, over-promised, and began the lies to keep her business afloat, a "fake it till you make it" entrepreneur like Thomas Edison?
I'm not qualified to say if EH was or is a sociopath. I don't think she started Theranos as a scam whose only purpose was to make money. If she had done so, she surely would have taken more money for herself along the way. I do think that she had good intentions and that she, as you say, "began the lies to keep her business afloat." ([Reporter John] Carreyrou's book points out that those lies began early.) I think that the Edison comparison is instructive for a lot of reasons.
First, Edison was the original "fake-it-till-you-make-it" entrepreneur. That puts this kind of behavior in the mainstream of American business. By saying that, I am NOT endorsing the ethic, just the opposite. As one Enron executive mused about the mendacity there, "Was it fraud or was it bad marketing?" That gives you a sense of how baked-in the "fake it" sensibility is.
"Having a thirst for fame and a noble cause enabled her to think it was OK to lie in service of those goals."
I think EH shares one other thing with Edison, which is a huge ego coupled with a talent for storytelling as long as she is the heroic, larger-than-life main character. It's interesting that EH calls her initial device "Edison." Edison was the world's most famous "inventor," both because of the devices that came out of his shop and and for his ability for "self-invention." As Randall Stross notes in "The Wizard of Menlo Park," he was the first celebrity businessman. In addition to her "good intentions," EH was certainly motivated by fame and glory and many of her lies were in service to those goals.
Having a thirst for fame and a noble cause enabled her to think it was OK to lie in service of those goals. That doesn't excuse the lies. But those noble goals may have allowed EH to excuse them for herself or, more perniciously, to make believe that they weren't lies at all. This is where we get into scary psychological territory.
But rather than thinking of it as freakish, I think it's more productive to think of it as an exaggeration of the way we all lie to others and to ourselves. That's the point of including the Dan Ariely experiment with the dice. In that experiment, most of the subjects cheated more when they thought they were doing it for a good cause. Even more disturbing, that "good cause" allowed them to lie much more effectively because they had come to believe they weren't doing anything wrong. As it turns out, economics isn't a rational practice; it's the practice of rationalizing.
Where EH and Edison differ is that Edison had a firm grip on reality. He knew he could find a way to make the incandescent lightbulb work. There is no evidence that EH was close to making her "Edison" work. But rather than face reality (and possibly adjust her goals) she pretended that her dream was real. That kind of "over-promising" or "bold vision" is one thing when you are making a prototype in the lab. It's a far more serious matter when you are using a deeply flawed system on real patients. EH can tell herself that she had to do that (Walgreens was ready to walk away if she hadn't "gone live") or else Theranos would have run out of money.
But look at the calculation she made: she thought it was worth putting lives at risk in order to make her dream come true. Now we're getting into the realm of the sociopath. But my experience leads me to believe that -- as in the case of the Milgram experiment -- most people don't do terrible things right away, they come to crimes gradually as they become more comfortable with bigger and bigger rationalizations. At Theranos, the more valuable the company became, the bigger grew the lies.
The two whistleblowers come across as courageous heroes, going up against the powerful and intimidating company. The contrast between their youth and lack of power and the old elite backers of Theronos is staggering, and yet justice triumphed. Were the whistleblowers hesitant or afraid to appear in the film, or were they eager to share their stories?
By the time I got to them, they were willing and eager to tell their stories, once I convinced them that I would honor their testimony. In the case of Erika and Tyler, they were nudged to participate by John Carreyrou, in whom they had enormous trust.
"It's simply crazy that no one demanded to see an objective demonstration of the magic box."
Why do you think so many elite veterans of politics and venture capitalism succumbed to Holmes' narrative in the first place, without checking into the details of its technology or financials?
The reasons are all in the film. First, Channing Robertson and many of the old men on her board were clearly charmed by her and maybe attracted to her. They may have rationalized their attraction by convincing themselves it was for a good cause! Second, as Dan Ariely tells us, we all respond to stories -- more than graphs and data -- because they stir us emotionally. EH was a great storyteller. Third, the story of her as a female inventor and entrepreneur in male-dominated Silicon Valley is a tale that they wanted to invest in.
There may have been other factors. EH was very clever about the way she put together an ensemble of credibility. How could Channing Robertson, George Shultz, Henry Kissinger and Jim Mattis all be wrong? And when Walgreens put the Wellness Centers in stores, investors like Rupert Murdoch assumed that Walgreens must have done its due diligence. But they hadn't!
It's simply crazy that no one demanded to see an objective demonstration of the magic box. But that blind faith, as it turns out, is more a part of capitalism than we have been taught.
Do you think that Roger Parloff deserves any blame for the glowing Fortune story on Theranos, since he appears in the film to blame himself? Or was he just one more victim of Theranos's fraud?
He put her on the cover of Fortune so he deserves some blame for the fraud. He still blames himself. That willingness to hold himself to account shows how seriously he takes the job of a journalist. Unlike Elizabeth, Roger has the honesty and moral integrity to admit that he made a mistake. He owned up to it and published a mea culpa. That said, Roger was also a victim because Elizabeth lied to him.
Do you think investors in Silicon Valley, with their FOMO attitudes and deep pockets, are vulnerable to making the same mistake again with a shiny new startup, or has this saga been a sober reminder to do their due diligence first?
Many of the mistakes made with Theranos were the same mistakes made with Enron. We must learn to recognize that we are, by nature, trusting souls. Knowing that should lead us to a guiding slogan: "trust but verify."
The irony of Holmes dancing to "I Can't Touch This" is almost too perfect. How did you find that footage?
It was leaked to us.
"Elizabeth Holmes is now famous for her fraud. Who better to host the re-boot of 'The Apprentice.'"
Holmes is facing up to 20 years in prison for federal fraud charges, but Vanity Fair recently reported that she is seeking redemption, taking meetings with filmmakers for a possible documentary to share her "real" story. What do you think will become of Holmes in the long run?
It's usually a mistake to handicap a trial. My guess is that she will be convicted and do some prison time. But maybe she can convince jurors -- the way she convinced journalists, her board, and her investors -- that, on account of her noble intentions, she deserves to be found not guilty. "Somewhere, over the rainbow…"
After the trial, and possibly prison, I'm sure that EH will use her supporters (like Tim Draper) to find a way to use the virtual currency of her celebrity to rebrand herself and launch something new. Fitzgerald famously said that "there are no second acts in American lives." That may be the stupidest thing he ever said.
Donald Trump failed at virtually every business he ever embarked on. But he became a celebrity for being a fake businessman and used that celebrity -- and phony expertise -- to become president of the United States. Elizabeth Holmes is now famous for her fraud. Who better to host the re-boot of "The Apprentice." And then?
"You Can't Touch This!"
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on new scientific theories and progress to give you a therapeutic dose of inspiration headed into the weekend.
Listen on Apple | Listen on Spotify | Listen on Stitcher | Listen on Amazon | Listen on Google
Here are the stories covered this week:
- The eyes are the windows to the soul - and biological aging?
- What bean genes mean for health and the planet
- This breathing practice could lower levels of tau proteins
- AI beats humans at assessing heart health
- Should you get a nature prescription?
Two-and-a-half year-old Huckleberry, a blue merle Australian shepherd, pulls hard at her leash; her yelps can be heard by skiers and boarders high above on the chairlift that carries them over the ski patrol hut to the top of the mountain. Huckleberry is an avalanche rescue dog — or avy dog, for short. She lives and works with her owner and handler, a ski patroller at Breckenridge Ski Resort in Colorado. As she watches the trainer play a game of hide-and-seek with six-month-old Lume, a golden retriever and avy dog-in-training, Huckleberry continues to strain on her leash; she loves the game. Hide-and-seek is one of the key training methods for teaching avy dogs the rescue skills they need to find someone caught in an avalanche — skier, snowmobiler, hiker, climber.
Lume’s owner waves a T-shirt in front of the puppy. While another patroller holds him back, Lume’s owner runs away and hides. About a minute later — after a lot of barking — Lume is released and commanded to “search.” He springs free, running around the hut to find his owner who reacts with a great amount of excitement and fanfare. Lume’s scent training will continue for the rest of the ski season (Breckenridge plans operating through May or as long as weather permits) and through the off-season. “We make this game progressively harder by not allowing the dog watch the victim run away,” explains Dave Leffler, Breckenridge's ski patroller and head of the avy dog program, who has owned, trained and raised many of them. Eventually, the trainers “dig an open hole in the snow to duck out of sight and gradually turn the hole into a cave where the dog has to dig to get the victim,” explains Leffler.
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”