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Emotional Exhaustion: Is Empathy a Choice?

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Life offers endless opportunities to test your empathy—the ability to feel for and with others—sometimes to its breaking point: A rally that breaks out in violence; an earthquake that devastates hundreds of thousands in another country; a homeless person standing on the street outside your job; a friend whose cancer returns.

The average person feels some sort of empathy in response to these situations and, in the best of cases, is motivated to help. Maybe you donate money to the Red Cross, put your last $10 bill into that downtrodden person’s hand, or drive your friend to chemo. But in certain conditions, our empathy turns to exhaustion as we anticipate that caring will invest too much of our emotional resources in an outcome over which we have no control.

If you’ve felt the latter, you’re likely not a psychopath (characterized by a lack of feeling empathy for others). You’re probably just experiencing emotional exhaustion.


Emotional exhaustion occurs when your emotional reserves feel limited or drained, dampening your ability to feel empathy or compassion for others. This is often a matter of scale: While empathy for one person’s suffering may feel manageable, research shows that the greater the number of people in need at once, the less compassion people feel for them. “People are motivated to avoid the costs of empathizing with multiple suffering victims,” Daryl Cameron, a social psychologist at the University of Iowa, tells mental_floss. This phenomenon is known as “collapse of compassion.”

There are real consequences to caring deeply for the struggles of others. After all, when you empathize, you do more than just feel concern; it’s not uncommon for an empathizing person to “take on the sensory, motor, visceral, and affective states” of another, known as experience sharing, according to Jamil Zaki, a social scientist at Stanford. In a study about empathy [PDF], Zaki uses the example of a crowd watching a tightrope walker becoming physically tense, anxious, even sweaty, as they watch the person teeter high above them.

Yet even babies will crawl toward and attempt to comfort other crying babies. There are specific neurons in your brain called mirror neurons that play a role in helping you to understand the intentions and actions of others, and to gauge the cost of them on your own physiology.


To limit these “costs” of empathy, we’re more likely to “turn off” or deny our empathy for people through subtle acts of “dehumanization,” which, says Cameron, simply means “denying others’ mental states, thinking they have less capacity to think, feel or have conscious experiences.” This is more likely to happen in cases where we feel that our emotional investment will not pay off—say, when those others belong to a group we identify as unlike ourselves or stigmatized individuals, such as drug addicts. “We’re sensitive to the costs and benefits of empathy. We entertain the risks and rewards of empathy for others, and that can shape how much empathic behavior we engage in,” Cameron says.

One of Cameron’s findings, outlined in a recent study in the journal Social, Psychological and Personality Science, is that if a person thinks of empathy as a limited emotional resource, they’re likely to limit instances of empathy for a stigmatized target. However, if that scale is flipped and people are instead encouraged to think of their empathy as renewable, emotional exhaustion can be staved off.

Cameron and his research team engaged in two nearly identical studies. In the first, 173 participants were split into two groups and asked to read about a hypothetical adult black male named Harold Mitchell who was homeless either because he struggled with drug addiction—considered a highly stigmatized condition—or because of an illness out of his control, which lacks stigma. “They were asked, 'To what degree do you think it would be emotionally exhausting or draining to help him?' and we gave them the expectation that they would receive an appeal for help from this individual at some point,” Cameron says.

The results of this first study showed that people felt helping the drug addict Harold Mitchell would be “more exhausting” than those who assessed the blamelessly ill Harold Mitchell, says Cameron.

The second study kept the same stimuli, though they had a larger sample of 405 people. The only stimuli they changed, says Cameron, was that “we told people that the empathy appeal would be inspiring and rewarding.” The feeling of exhaustion towards the stigmatized drug addict Harold Mitchell went away in participants in the second study, Cameron says, because the researchers had presented a scenario in which helping him replaced “emotional costs with emotional rewards.”

Though Cameron is the first to say that their study is not necessarily representative of the general public because the sample population “tilts white and liberal, people in their mid-thirties, somewhat educated,” these studies suggest “we may have more control and flexible choice over when and for whom we feel empathy,” he says.


Zaki suggests we have an essential, automatic component to empathy—a built-in biological leaning toward caring for the suffering of others—but that our empathetic response is at the same time highly contextual. In the "tightrope" study, Zaki notes that in children, experience sharing—when we take on the feelings and even movements of others—may initially develop as an "undifferentiated response" to the emotions, he writes. "However, over time, children learn and internalize social rules, such as group membership, that produce motives to feel empathy in some cases but not others.”

Cameron suggests this is another avenue around which they could build experiments. “We could look at perceptions of social norms of those around you," he says. "Do your friends and family value empathy?”

And of course, one can’t ignore the effects of media—social and otherwise—we're all so relentlessly exposed to now. “With social media you have more demands on your empathy from the sheer amount of information about others’ lives presented to you,” says Cameron. “It may force us to be more strategic about when to feel empathy.”

Most interesting, however, is the plasticity of empathy, which appears to be highly susceptible to expectation and suggestion. “If our effect did generalize, one thing it does suggest is that what you think empathy is going to be like might matter quite a bit,” Cameron says. “If I tell you [empathy] is a renewable resource, not limited, something self-fulfilling and regenerative, you might make essentially different decisions on how to approach your empathy—and potentially be more expansive.”

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Land Cover CCI, ESA
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European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]


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