It’s pretty annoying that people like Dennis Wall can use autism to get money and attention. Hannah Furfaro published a puff piece on him in Spectrum News: “How Dennis Wall became the ‘bad boy’ of autism research.”
He’s from the Cult of Silicon Valley:
It was a sunny California afternoon in January 2015 when Dennis Wall received an unexpected gift: ‘smart glasses’ made by Google that had failed to live up to their hype in the press.
An employee from the company pulled up to Wall’s lab at Stanford University in a sleek gray Tesla, popped open the sedan’s trunk and unloaded a brown cardboard box with long, dangling cords.
It was a scene straight out of the television comedy “Silicon Valley,” which satirizes the absurdity of the tech world. Wall’s ambition for the Google Glass, however, is dead earnest: He aims to help people with autism interpret others’ emotions.
So we’re going to read hype about another Silicon Valley thing that won’t live up to the hype.
Why is she using the word “sleek” to describe the Tesla? At least we know her neoliberal tech-worshipping bias is going to distort things from the beginning.
I haven’t actually watched Silicon Valley, but I was at a work meeting where one of the execs told a story about making a deal where he was stoked about his life resembling the show. We’re supposed to understand that this Wall guy has tech glamour.
When I think about it, it actually makes me laugh out loud that this Wall guy is out there with dead earnesty playing with toys and solving my social problems.
Many people with autism have trouble understanding social cues and emotions, and this can greatly limit how they fare in the world. Wall developed an algorithm that relies on artificial intelligence. His plan was to incorporate the algorithm into the glasses, so that someone wearing the glasses would see a tiny emoticon that matches the expression on the face of another person.
The algorithm was all set to go, and Wall had been waiting for the glasses to test his idea.
“It was lifesaving for us because we were desperate to get started,” he recalls.
That first sentence is a political statement. If the neurodiversity movement and disability rights movement more generally are correct, normal people greatly limit how we fare in the world. Maybe hire more of us and let us be weird without hassling us?
“An algorithm that relies on artificial intelligence” makes it sound like there’s something deeper going on than what’s going on. By “artificial intelligence,” she means machine learning. The idea of machine learning is that you want the computer to classify things for you, so you show it a bajillion examples. Based on that experience, the computer can try to classify new things it hasn’t seen before. So they show the computer a lot of labeled facial expressions, and the computer develops rules for classifying new faces. Supposedly, this will work better than the autistic person learning how to read facial expressions.
It’s incorrect that there’s a clear, 1-to-1 relationship between emotions and facial expressions. See the book How Emotions are Made for details. The premise of universal facial expressions behind a lot of autism research is empirically unsupported.
It’s an interesting problem in computer vision, but it’s probably not as good as talking to autistic people about feelings.
This project represents just one of Wall’s lofty ambitions. Among the others: trimming the number of questions — and, as a result, the amount of time — required to diagnose autism, using machine-learning techniques to treat and diagnose the condition, and crowdsourcing data to map the prevalence of autism in the United States.
The point of this is supposed to be that ambition is attractive or something?
If a psychologist said they did a factor analysis on a questionnaire, that would mean approximately the same thing without all the sexy machine learning talk.
Is the problem with autism that it takes too many questions to diagnose it? Why is knowing the exact prevalence of autism so important? It seems like he knows how to use a machine learning library and he knows how to build an app or a website, so the cure for autism must be something he can build with those tools!
And with his smarts and charisma, Wall seems like just the man to pull all of this off. In his trademark black high-top sneakers, skinny jeans and spiky dark hair, Wall fits right into the milieu in Silicon Valley (albeit less so at scientific conferences). He parlays his proximity to this area into powerful allies — including Thomas Insel, the former National Institute of Mental Health director who co-founded a startup called Mindstrong. (Insel served a stint at the Google spin-off Verily.) Wall also founded Cognoa, a company that aims to diagnose autism via an app on parents’ smartphones. Cognoa has raised more than $20 million in venture capital and is seeking approval from the U.S. Food and Drug Administration.
He also has an enormous penis.
You know who else doesn’t fit into the milieu at scientific conferences? Black people.
The constituency backing Dennis Wall is rich people who want to make money off people like me. He’s actually full of fail:
With these ideas and energy, Wall, at just 43, seems poised for success. But his execution of these ideas leaves something to be desired, his critics say.
Some of the stalwarts in the autism field view Wall’s work as “poor,” “pseudoscience,” and “dangerous.” Wall’s results are tantalizing, given their ambitious premise, but few of them stand up to scrutiny, they say. In 2012, for instance, Wall published findings suggesting he could shorten two gold-standard diagnostic tests for autism. But three years later, another team reported that they were unable to replicate this finding.
“He just keeps saying these things that are not true,” says Catherine Lord, director of the Center for Autism and the Developing Brain at New York-Presbyterian Hospital, and one of Wall’s most vocal critics. Lord created the two gold-standard tests and was part of the team that questioned Wall’s work.
Wall is “passionate” and “his heart is in the right place,” says Fred Shic, associate professor of pediatrics at the University of Washington in Seattle. But Shic, who also studies the use of artificial intelligence to improve autism screening, says Wall’s early work is flawed.
Wall’s 2012 algorithms boast nearly 100 percent accuracy, so despite their flaws, they make it difficult for others to publish anything with lower numbers — even work that is more rigorous. “It makes things harder for people who are trying to apply appropriate methods to these data-science approaches,” Shic says. He adds, though, that Wall’s recent work is more careful.
Wall’s results are “tantalizing?” I’m still not sure I understand why we need them at all. I’m not tantalized.
By “stalwarts” she means “unhip old people” (older than 43).
There’s not enough information to know what “accuracy” is supposed to mean here, but the number 100 sounds good. The way “careful” is used here, it implies that he has an appealing, reckless cowboy quality. His self-description, or whatever:
Wall, the self-described “bad boy” of autism research, goes quiet when he hears some of this criticism.
“I guess I just don’t worry about it because what we’re doing, for me, is so much more important than politics and my image and how I’m perceived in the field,” he says.
Someone that was actually special-interesting on their research wouldn’t find reporters to listen to them talk about what “bad boys” they are (does he want a spanking?).
With little support at home, Wall says he threw himself into sports and school to keep himself motivated. When he was around 11, he started running, and was so fast he was invited to join the U.S. Junior Olympics cross-country team. He traveled across the East Coast, and often placed in the top three.
Later, he and his brother took city buses or trains two hours each way to attend Boston College High School in Dorchester, a historic Boston neighborhood. The all-boys college preparatory school has an excellent reputation and a price tag to match; the brothers earned scholarships to help pay their way. Wall excelled in his studies, played lacrosse, swam and continued running. After school, he’d trade in his formal school shoes and collared shirt for sneakers and a skateboard — despite his mother’s disapproval. “[Skateboarding] is really physical, you know; it requires a lot of intensity, energy, balance and focus. For me, it was great,” he says. He still takes time to indulge in this hobby — three skateboards and two large surfboards adorn his office walls — or in other intense physical activity every day.
Jocks with longboards are insufferable. Watch interviews with Mark Gonzales and Rodney Mullen for actual interesting connections between autism and skateboarding.
What is going on in this picture?
Of course he’d wear Nikes. The sunglasses. The coat. It’s all too much.
The graphics are pristine because his board is either brand new or he doesn’t actually skate, ever (this is most likely).
It looks like he’s just jumping onto the board, from standing there with it. The tail is on the ground, and his back foot is way off the board. At best it’s the worst ollie nosegrab ever.
Wall’s curiosity took him to islands in southeast Asia and Tahiti, where he did field work chasing down new species of moss. “He would do these dumb things where he would go out overnight in the jungle and he’d get bitten by centipedes,” says Daniel Rubinoff, professor of entomology at the University of Hawaii. “He’s always been a bit crazily committed to his craft.”
Sure, his curiosity brought him on exotic colonial vacations.
He remembers having the realization that he had a lot to learn about autism, and a good starting place might be to examine the tools used to diagnose the condition. He began looking at the Autism Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R).
That’s a terrible starting place. The best place to start would be reading what autistic people write and watching what they post to YouTube.
The section about the poor quality of his research is called “Under pressure” to make it sound like he’s the victim.
These two tests, both developed by Lord in the 1980s, comprise standardized questions and criteria to guide clinicians making an autism diagnosis. But to Wall, the tests seemed much too time-consuming and vulnerable to human error.
“That subjectivity, whether conscious or unconscious or whatever, can impact our ability to identify a statistical signal,” he says. “What if it’s a ‘garbage in, garbage out’ problem?”
His skepticism set him on a path to make autism diagnosis more objective and efficient. He set out to use a machine-learning technique to truncate both tests. He cut down the ADOS from 29 behavioral ‘codes’ to just 8, and the ADI-R from 93 questions to just 7.
His team reported that the eight-code version of the ADOS performed with nearly 100 percent accuracy in a sample of 612 children with autism and 15 controls. The shortened ADI-R was also almost 100 percent accurate in a sample of 891 people with autism and 75 controls.
Getting diagnosed with autism took a day, and that included a lunch break, an IQ test, the ADOS-2, the MCMI (a personality test), and talking about my life story. I got a cool report about myself with some recommended work accommodations.
What’s the issue with subjectivity, really? I’d think it more to do with underdiagnosing women and minorities.
These results quickly came under scrutiny. In 2015, Lord and a team of computer scientists applied Wall’s shortened tests and reported that they could not reproduce either of the findings.
Their paper laid out a laundry list of design flaws in Wall’s ADOS project. For instance, the ADOS categorizes children into three categories: ‘autism,’ ‘autism spectrum’ and ‘non-spectrum.’ But Wall omitted children who score in the intermediate ‘autism spectrum’ range, and included only those easiest to distinguish from each other: those with the most severe features of autism and those without the condition.
The researchers also harshly criticized Wall’s statistical analysis. “It appears that no effort was made to evaluate the reliability or validity of their results aside from peripheral reporting of accuracy on the test data,” they wrote.
Matthew Goodwin, one of the researchers, says this is just one example among many of “one-shot” studies led by Wall. “Without reproducibility and transparency, it’s marketing and advertising,” Goodwin says. “I have not seen any wide-scale reproducibility of any of the results in autism and around diagnosis that Dennis has put out there.”…
“It just drives me crazy when he goes on and on and on as if he is solving that problem and then blaming it on the ADOS, which has nothing to do with that,” she says. And Wall’s suggestion that a quick diagnosis may be sufficient, she says, ignores the real issues families face: a shortage of well-trained clinicians and insurance reimbursement for the tests.
All this talk about doing science right hurts his feelings.
Wall’s supporters say some of these criticisms are too personal — and short-sighted.
“You can disagree with somebody and be frustrated by what they are doing, but you don’t go that far,” Rubinoff says.
And Wall’s wife, Abby, says the remarks cut deep. “This really hurts him to the core because he’s trying to do a mission that is personal to him but also really important work for the field,” she says. “My only guess is perhaps people who have one way of doing something, which we all find in life, have a hard time with change and perhaps even change in technology.”
Note the religious idea that technological progress is inherently good.