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Question: How do business innovation and sustainability work together?


Dwayne Spradlin: A business, whether it’s a large business, a small and medium business, should be thinking about what’s profitable. Where is the product I should be taking the market? Who am I going to sell it to? Etcetera. How do I build the right communities? Customer communities, employee communities, partner communities and by the way all of those communities are sources of innovation.


That becomes part and parcel to this notion of a constant innovation model. In the open innovation world, these sustainable businesses are focused much less on having to invent every piece of what they do and much more in creating a sustainable structure with which they can constantly innovate. So, when you look at business that are now really learning how to tap their customer base user driven design.


Five years from now, everybody’s going to look back and say that was intuitive, but the reality is five years ago, which you actually had to do to have a user-driven design style business was not done very often. People really should try to get their hands dirty trying to make it work.


Today, companies that get the killer business model right can effectively mine their communities and can create constant innovation through the use of their communities and application of their business models will be the businesses that I think will strive in the 21stcentury, and it’s even more so because now we are living in a world where you can get to market instantly. You can outsource manufacturing and other structures instantly. So, it’s the better business model, it’s who are your communities and mine them effectively and creating a structure that you constantly innovate, that’s the wining ticket.




Question: How can open innovation companies leverage talent?



Dwayne Spradlin: From an organizational point of view, it really is about talent management. The tools are changing, but the words are often the same. It’s about attracting talent, developing talent, and retaining talent. So in this new world, we see much more of a shift towards variable talent models and certainly engaging open innovation is a structure that allows organizations to--maybe the next heads I hire, I don’t actually hire, I virtually hire them. I get access to them through some of the global open innovation networks, or I get access to them through finding the right partners to help me move ahead as a business and that may very well be a superior economic for me, as a business to manage risk and cost.


Looking at this through the open innovation lens, it’s also a way for me potentially to get the market better, faster and more cost effectively. It’s not just the offset of cost, but in a world where 7 billion people, 6 billion people, you’ve people all over the planet that may actually have better ideas to solve a problem. They may actually be able to bring to bear some kind of an idea from another industry that it would have never occurred to my organization.


Recorded on: June 3, 2009.


Dwayne Spradlin, CEO of InnoCentive, says sustainable companies must build communities and adopt a constant innovation model.

Does conscious AI deserve rights?

If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.

  • Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
  • Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
  • One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.

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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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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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.