Archive for the ‘Technology’ Category
Michael Byrne has an intriguing article in Motherboard:
Researchers from the University of Southern California have developed a new machine learning tool capable of detecting certain speech-related diagnostic criteria in patients being evaluated for depression. Known as SimSensei, the tool listens to patient’s voices during diagnostic interviews for reductions in vowel expression characteristic of psychological and neurological disorders that may not be sufficiently clear to human interviewers. The idea is (of course) not to replace those interviewers, but to add additional objective weight to the diagnostic process.
The group’s work is described in the journal IEEE Transactions on Affective Computing.
Depression misdiagnosis is a huge problem in health care, particularly in cases in which a primary care doctor making (or not) the diagnosis. A 2009 meta-study covering some 50,000 patients found that docs were correctly identifying depression only about half the time, with the number of false positives outnumbering false negatives by a ratio of about three-to-one. That’s totally unacceptable.
But it’s also understandable. Doctors, especially general practitioners, will pretty much always overdiagnose an illness for two simple and related reasons: one, diagnosing an illness in error is almost always safer than not diagnosing an illness in error; two, eliminating with certainty the possibility of any single diagnosis requires more expertise/more confidence than otherwise. See also: overprescribing antibiotics.
A big part of the problem in diagnosing depression is that it’s a very heterogenous disease. It has many different causes and is expressed in many different ways. Figure that a primary care doctor is seeing maybe hundreds of patients in a week, for all manner of illness, and the challenge involved in extracting a psychiatric diagnosis from the vagaries of self-reported symptoms and interview-based observations is pretty clear. There exists a huge hole then for something like SimSensei.
The depression-related variations in speech tracked by SimSensei are already well-documented. “Prior investigations revealed that depressed patients often display flattened or negative affect, reduced speech variability and monotonicity in loudness and pitch, reduced speech, reduced articulation rate, increased pause duration, and varied switching pause duration,” the USC paper notes. “Further, depressed speech was found to show increased tension in the vocal tract and the vocal folds.” . . .
Since 3-wheel vehicles are regulated like motorcycles, the Elio Motors E1A would qualify for the car-pool (HOV) lane in California even if it has but a single occupant. This is an important point given The Wife’s commute. Plus it’s inexpensive to buy and to run and looks cool (to me).
In the NY Times Kate Murphy (of Murphy’s Law?) writes of modern tech support:
You may consider yourself even-keeled, the kind of person who is unflappable when those around you are losing their cool. But all that goes out the window when you call tech support. Then you fume. Your face turns red. You shout things into the phone that would appall your mother.
It’s called tech support rage.
And you are not alone. Getting caught in a tech support loop — waiting on hold, interacting with automated systems, talking to people reading from unhelpful scripts and then finding yourself on hold yet again — is a peculiar kind of aggravation that mental health experts say can provoke rage in even the most mild-mannered person.
Worse, just as you suspected, companies are aware of the torture they are putting you through.
According to a survey conducted last year by the industry groupInternational Customer Management Institute, or ICMI, 92 percent of customer service managers said their agents could be more effective and 74 percent said their company procedures prevented agents from providing satisfactory experiences.
Moreover, 73 percent said the complexity of tech support calls is increasing as customers have become more technologically sophisticated and can resolve simpler issues on their own.
Many organizations are running a cost-per-contact model, which limits the time agents can be on the phone with you, hence the agony of round-robin transfers and continually being placed on hold, said Justin Robbins, who was once a tech support agent himself and now oversees research and editorial at ICMI.
“Don’t think companies haven’t studied how far they can take things in providing the minimal level of service,” Mr. Robbins said. “Some organizations have even monetized it by intentionally engineering it so you have to wait an hour at least to speak to someone in support, and while you are on hold, you’re hearing messages like, ‘If you’d like premium support, call this number and for a fee, we will get to you immediately.’”
The most egregious offenders are companies like cable and mobile service providers, which typically have little competition and whose customers are bound by contracts or would be considerably inconvenienced if they canceled their service. Not surprisingly, cable and mobile service providers are consistently ranked by consumers as providing the worst customer support. . . .
Fereico Nejrotti reports at Motherboard:
Hi there. If you’re reading this piece, consider yourself lucky. Don’t take it for granted. Especially if you’re like the 62 percent of American adults who get their news from social media, as a recent Pew Research poll showed, and you usually find our posts on Facebook.
Facebook announced earlier this week that it will change the algorithm used to decide what every single user sees on their timeline. “Facebook was built on the idea of connecting people with their friends and family,” Lars Backstrom, engineering director at Facebook, said in a statement. “Our top priority is keeping you connected to the people, places and things you want to be connected to — starting with the people you are friends with on Facebook. That’s why today, we’re announcing an upcoming change to News Feed ranking to help make sure you don’t miss stories from your friends.”
Now, why we should care about this announcement, and how are the first two paragraphs of this piece related?
The changes announced by Facebook will mainly impact one of the most important values for Facebook’s brand and publisher-owned pages: “reach.” This value shows how many users will be shown a certain post. In other words, how many users see that single update on their timeline.
Worse and worse
This premise takes us to the point. The condition created by this policy is often called a “filter bubble.”
Social networks that use algorithms to define which updates are most relevant for their users tends to gradually supply the users with things that align with their established interests and opinions.
Take the recent media boom about Brexit, the controversial vote in the UK over whether to leave the European Union.
One pro-“Remain” Facebook user explained how hard has been for him to find posts from the opposing side. On the day the “Leave” campaign won, he looked for Facebook posts celebrating for the win—and came up short.
It wasn’t only about his News Feed list: He also tried to use the Facebook search function, also to no avail. It wasn’t that there were no posts about how great the Leave victory was. It was that Facebook, having identified him as a Remain voter, just wasn’t allowing him to see them.
It’s not just the opinions expressed in posts, but also where they’re coming from. Facebook has a double interest here: On one side, it needs to be able to charge publishers money who want more exposure. On the other, it needs to boost the number of user interactions on the social network. . .
Frightening. It reminds me of the masses being fed soma in Brave New World.
Facebook hides from you an entire world of opinions and outlooks that differ from your own. That is unhealthy, mentally, spiritually, ethically, morally, and probably in some other ways. Not illegal, though, so they will continue to do it.
Mene, mene, tekel, upharsim: Mosquitoes Have Developed Resistance to Every One of Our Malaria-Fighting Tools
Note that the article, foreboding as it is, is one of a series. And truly, take the impact of climate change (in spreading this mosquito that has evolved to resist all our tools by expanding the mosquito’s habitat, northward into the U.S., not to mention the upcoming famines) and add to that the growing list of systemic failure in our most fundamental institutions (about which I earlier blogged), the warning does seem not totally off the wall, as it were.
We unfortunately live in interesting times.
Bob Wachter has a very interesting and detailed (five parts) report at Backchannel of how design and procedural flaws resulted in a patient’s being given a dose of antibiotics 29 times what it should have been. His article begins:
The nurses and doctors summoned to the hospital room of 16-year-old Pablo Garcia early on the morning of July 27, 2013, knew something was terribly wrong. Just past midnight, Pablo had complained of numbness and tingling all over his body. Two hours later, the tingling had grown worse.
Although Pablo had a dangerous illness—a rare genetic disease called NEMO syndrome that leads to a lifetime of frequent infections and bowel inflammation—his admission to the University of California, San Francisco Medical Center’s Benioff Children’s Hospital had been for a routine colonoscopy, to evaluate a polyp and an area of intestinal narrowing.
At 9 o’clock that night, Pablo took all his evening medications, including steroids to tamp down his dysfunctional immune system and antibiotics to stave off infections. When he started complaining of the tingling, Brooke Levitt, his nurse for the night, wondered whether his symptoms had something to do with GoLYTELY, the nasty bowel-cleansing solution he had been gulping down all evening to prepare for the procedure. Or perhaps he was reacting to the antinausea pills he had taken to keep the GoLYTELY down.
Levitt’s supervising nurse was stumped, too, so they summoned the chief resident in pediatrics, who was on call that night. When the physician arrived in the room, he spoke to and examined the patient, who was anxious, mildly confused, and still complaining of being “numb all over.”
He opened Pablo’s electronic medical record and searched the medication list for clues that might explain the unusual symptoms.
At first, he was perplexed. But then he noticed something that stopped him cold. Six hours earlier, Levitt had given the patient not one Septra pill—a tried-and-true antibiotic used principally for urinary and skin infections — but 38½ of them.
Levitt recalls that moment as the worst of her life. “Wait, look at this Septra dose,” the resident said to her. “This is a huge dose. Oh my God, did you givethis dose?”
“Oh my God,” she said. “I did.”
The doctor picked up the phone and called San Francisco’s poison control center. No one at the center had ever heard of an accidental overdose this large—for Septra or any other antibiotic, for that matter—and nothing close had ever been reported in the medical literature. The toxicology expert there told the panicked clinicians that there wasn’t much they could do other than monitor the patient closely. . .
But read the whole thing. The meat of the article is laying out all the factors that led to the overdose.