Once a week.
Subscribe to our weekly newsletter.
"Empathy Pill" Makes People Act More Fairly with Money
Researchers think they may have found a way to make people more empathetic. Perhaps one day in the future we'll be able to prescribe "kindness" pills.
What if there was a way to turn all the Ebenezer Scrooges of the world into kind, empathetic people? Researchers at the University of California, Berkeley, and the University of California, San Francisco, think it may be possible, some day.
With a little tweak in brain chemistry, researchers wrote in their paper, published in Current Biology, that they were able to make participants more generous. Just by dosing them with some dopamine.
The study was quite small, only 35 participants, but the test raises some questions that may help aid in future research. The participants were split into two groups, one that would receive a placebo and the other would take a pill containing tolcapone. The drug is typically used for Parkinson's patients to help prolong the effects of dopamine in the brain, and dopamine is a feel-good “reward” hormone. Neither group was aware of which pill they had taken.
The participants were then asked to take part in an “economic game” where the volunteers distributed wealth amongst themselves and a group of anonymous individuals. EurekAlert! writes, “After receiving tolcapone, participants divided the money with the strangers in a fairer, more egalitarian way than after receiving the placebo.”
One of the co-authors commented on the results, saying:
“We typically think of fair-mindedness as a stable characteristic, part of one’s personality. Our study doesn’t reject this notion, but it does show how that trait can be systematically affected by targeting specific neurochemical pathways in the human brain.”
The question will be if in the future we'll be able to tap into these traits and prescribe them to people in the future.
In his interview with Big Think, Nicholas Kristof from The New York Times, talked about how good storytelling can help turn people on to issues. Rather than highlighting the plight of a million people, tell readers a story about one — they're more likely to connect.
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
A leading British space scientist thinks there is life under the ice sheets of Europa.
- A British scientist named Professor Monica Grady recently came out in support of extraterrestrial life on Europa.
- Europa, the sixth largest moon in the solar system, may have favorable conditions for life under its miles of ice.
- The moon is one of Jupiter's 79.
Neil deGrasse Tyson wants to go ice fishing on Europa<div class="rm-shortcode" data-media_id="GLGsRX7e" data-player_id="FvQKszTI" data-rm-shortcode-id="f4790eb8f0515e036b24c4195299df28"> <div id="botr_GLGsRX7e_FvQKszTI_div" class="jwplayer-media" data-jwplayer-video-src="https://content.jwplatform.com/players/GLGsRX7e-FvQKszTI.js"> <img src="https://cdn.jwplayer.com/thumbs/GLGsRX7e-1920.jpg" class="jwplayer-media-preview" /> </div> <script src="https://content.jwplatform.com/players/GLGsRX7e-FvQKszTI.js"></script> </div>
Water Vapor Above Europa’s Surface Deteced for First Time<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="9c4abc8473e1b89170cc8941beeb1f2d"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/WQ-E1lnSOzc?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
The scent of sickness: 5 questions answered about using dogs – and mice and ferrets – to detect disease
Could medical detection animals smell coronavirus?
Study confirms the existence of a special kind of groupthink in large groups.
- Large groups of people everywhere tend to come to the same conclusions.
- In small groups, there's a much wider diversity of ideas.
- The mechanics of a large group make some ideas practically inevitable.
The grouping game<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE2Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMjI2MzA4OX0.RLrswIWbuEzHNqsw0F7EUrp9jPn7OulLPqCxcZT11ik/img.jpg?width=980" id="159b8" class="rm-shortcode" data-rm-shortcode-id="0feb15d2d7dde144c710c2f4f1e5350c" data-rm-shortcode-name="rebelmouse-image" data-width="2767" data-height="382" />
Some of the shapes used in the experiment
Credit: Guilbeault, et al./University of Pennsylvania<p>The researchers tested their theory with 1,480 people playing an online "Grouping Game" via Amazon's Mechanical Turk platform. The individuals were paired with another participant or made a member of a group of 6, 8, 24, or 50 people. Each pair and group were tasked with categorizing the symbols shown above, and they could see each other's answers.</p><p>The small groups came up with wildly divergent categories—the entire experiment produced nearly 5,000 category suggestions—while the larger groups came up with categorization systems that were virtually identical to each other.</p><p><a href="https://www.asc.upenn.edu/news-events/news/why-independent-cultures-think-alike-its-not-in-the-brain" target="_blank">Says Centol</a>a, "Even though we predicted it, I was nevertheless stunned to see it really happen. This result challenges many long-held ideas about culture and how it forms."</p><p>Nor was this unanimity a matter of having teamed-up like-minded individuals. "If I assign an individual to a small group," says lead author Douglas Guilbeault, "they are much more likely to arrive at a category system that is very idiosyncratic and specific to them. But if I assign that same individual to a large group, I can predict the category system that they will end up creating, regardless of whatever unique viewpoint that person happens to bring to the table."</p>
Why this happens<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE4NC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMjkzMDg0Nn0.u2hdEIgNw4drFZ2frzx0AJ_MAxIizuM98rdovQrIblk/img.jpg?width=980" id="d3444" class="rm-shortcode" data-rm-shortcode-id="5da57d66e388fad0f1c17afb09af90a7" data-rm-shortcode-name="rebelmouse-image" data-width="1440" data-height="822" />
The many categories suggested by small groups on the left, the few from large groups on the right
Credit: Guilbeault, et al./Nature Communications<p>The striking results of the experiment correspond to a <a href="https://www.nature.com/articles/s41562-019-0607-5" target="_blank">previous study</a> done by NDG that investigated tipping points for people's behavior in networks.</p><p>That study concluded that after an idea enters a discussion among a large network of people, it can gain irresistible traction by popping up again and again in enough individuals' conversations. In networks of 50 people or more, such ideas eventually reach critical mass and become a prevailing opinion.</p><p>The same phenomenon does not happen often enough within a smaller network, where fewer interactions offer an idea less of an opportunity to take hold.</p>