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Amaryllis Fox
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Chris Hadfield
Retired Canadian Astronaut & Author
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Why the days of addictive tech are numbered

Will the next wave of tech prioritize happiness over profit, or will app designers continue to rely on addictive habits?

Joscha Bach: I remember when the first search engines came around, and back then AltaVista was a very big thing. AltaVista tried to strike a balance between the inconveniences—in terms of advertising and so on that could put off the user—and the utility had for the user. So it would, for instance, mix search results with advertising. 

And at this point Google came along. Google was very small and inconsequential, and nobody really took it seriously. But it did an amazing thing: it did give people exactly what they wanted. It gave them a pretty much ad-free experience. It gave them exactly the search results that they wanted, the best ones, the closest ones to what people wanted to have. And Google dramatically outperformed AltaVista. AltaVista disappeared.

That was an amazing insight, to see that if you are in the dramatically scalable economy, like the Internet, where you have the biggest amount of competition that you can possibly have, you need to build a product that is optimally aligned with the interest of the users—unless you manage to get some kind of monopoly and can drive out other competition.

And so when we build new products in that space we have to think about how to build the most useful product. Not necessarily just the product that is going to make the biggest amount of money, that is going to have the most efficient business model in some sense or the best business case. Eventually, it’s going to be the product that is getting the most use by people. And people will find out that they will use what is most useful to them. In the long run, that’s going to be the stuff that is not addictive, that is hygienic, that serves the actual needs, that makes them more happy and fulfilled. And right now we mostly build applications that utilize the cravings of people, that make them addicted. People start checking their smartphones every few seconds to see if a new email arrived. But this new email is not going to make them more happy and fulfilled. Instead, it takes away their attention.

So I believe the next big movement in how we build technical systems will be hygienic technology. It will be how to build systems that are careful with our attention and how we use it, and that is careful with our way of living and what we want to achieve with the tools that we are building

Do we want to be at the mercy of our devices, or do we want to be fulfilled? Cognitive scientist Joscha Bach explains how the big decision we're coming to in tech ethics will mimic another moment in tech history: the battle of the search engines. In the late 1990s, AltaVista was one of the world's most used search engines—at least until a "small and inconsequential" startup called Google came along. AltaVista served ads, and Google didn't (not back then). For the public, the choice was easy; there's a reason you "Google" the weather rather than "AltaVista" it. We face the same decision now: will we choose tech that harvests our attention and sells it, like highly addictive social media apps; or will we choose tech that is useful to us—products that help us achieve our own goals? "Right now we mostly build applications that utilize the cravings of people, that make them addicted. People start checking their smartphones every few seconds to see if a new email arrived. But this new email is not going to make them more happy and fulfilled." In the long run, says Bach, technology that aligns with what people want wins. As long as we want the right things, the days of addictive tech are numbered. Joscha Bach's latest book is Principles of Synthetic Intelligence PSI: An Architecture of Motivated Cognition (Oxford Series on Cognitive Models and Architectures)

A new hydrogel might be strong enough for knee replacements

Duke University researchers might have solved a half-century old problem.

Photo by Alexander Hassenstein/Getty Images
Technology & Innovation
  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
  • The blend of three polymers provides enough flexibility and durability to mimic the knee.
  • The next step is to test this hydrogel in sheep; human use can take at least three years.
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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.

Hints of the 4th dimension have been detected by physicists

What would it be like to experience the 4th dimension?

Two different experiments show hints of a 4th spatial dimension. Credit: Zilberberg Group / ETH Zürich
Technology & Innovation

Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.

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How often do vaccine trials hit paydirt?

Vaccines find more success in development than any other kind of drug, but have been relatively neglected in recent decades.

Pedro Vilela/Getty Images
Surprising Science

Vaccines are more likely to get through clinical trials than any other type of drug — but have been given relatively little pharmaceutical industry support during the last two decades, according to a new study by MIT scholars.

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