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The Humintell Blog March 30, 2017

Emotion Recognition and Da Vinci

Is the Mona Lisa smiling?

There seems to be little doubt that we can learn a great deal through artwork, and a recent study on Leonardo Da Vinci’s famous Mona Lisa painting can help shed light on our facial recognition skills, as well.

This painting has long intrigued viewers, presenting an ambiguous facial expression that looks like a smile, despite a slight downturn in the mouth. A group of researchers at the University of Freiburg’s Medical Center sought to explore this issue, examining what the average person sees when they examine Da Vinci’s masterpiece.

Surprisingly, in almost every case, test subjects perceived an expression of happiness in the stately portrait. While many of us certainly do see the Mona Lisa as happy, what is truly surprising is the fact that this conclusion was shared by almost every single person studied. This sort of consensus is rare in scientific research.

In addition, the researchers explored some nuances of emotional recognition by presenting subjects with edited versions of the portrait, with varied expressions emphasizing either happiness or sadness. Essentially, they digitally altered the Mona Lisa’s mouth to craft four versions that had progressively more pronounced smiles and four that presented contrarily sad expressions.

The experiment proceeded in two parts. The first component simply involved exposing a series of test subjects to a copy of the Mona Lisa and the eight digitally edited versions in random orders. Subjects were asked to press buttons signifying whether the image was happy or sad, as well as reporting their level of confidence in this judgment.

The results were surprising. Not only were the original and happier versions invariably identified as smiles, but the participants were also able to more effectively judge these happy visages than the sad varieties. There were both more confident that what they saw was happiness and made those determinations more quickly than they did for the sad variations.

Emanuela Liaci, a PhD student and first author of the report, explained this result, saying: “It appears as if our brain is biased to positive facial expressions.”

While art critics have historically been divided on whether the Mona Lisa is smiling, a 2015 analysis of Da Vinci’s work found that he had employed a similarly ambiguous expression in at least one other painting. In both cases, a close-up of the painting reveals an uncertain expression, but viewing the painting with less focus or from a greater distance emphasized the smile.

This examination suggests that Da Vinci intended for viewers to see a smile in the Mona Lisa’s face but also to create doubt as to whether she was smiling. Could this intentional uncertainty be a reflection of the often ambiguous expressions that real people make? This would make sense, given the role of empathy that many artists see in their work.

Humintell is certainly excited to see more of this sort of research!

For more information on reading ambiguous expressions, check out our work here and here!

Filed Under: Emotion

The Humintell Blog March 23, 2017

Can We Learn Empathy from Robots?

Many people familiar with science fiction tend to have an ingrained fear and repulsion at what are seen as cold and unfeeling robots.

The idea of widespread artificial intelligence brings to mind terrifying visions from films such as The Terminator or The Matrix, both of which present an apocalyptic future where artificial intelligence turns on mankind with disastrous results. The basic concern seems to be that robots lack any sense of empathy towards their human creators.

However, many humans already struggle with empathy, and this problem is especially poignant in the field of medicine. Unfortunately, many patients struggle to effectively communicate their pain to doctors, the very people who are able to treat it. Granted, pain is a difficult thing to communicate, but there is some evidence that doctors are even worse at recognizing it than the general population.

This may be born out of necessity, as medical professionals are required to distance themselves emotionally from patients in order to conduct treatments in a scientific and objective fashion. That said, it creates problems in trying to understand and diagnose pain conditions.

Dr. Laurel Riek, a professor of computer science at the University of California, San Diego, actually sought to test whether doctors could properly recognize emotional expressions in their patients. In fact, when medical experts and laypeople were exposed to digitally simulated facial expressions, the clinicians proved to be much less accurate at recognizing pain.

While the study analyzed various emotions, including anger and disgust, recognition of pain represented the starkest disparity between the groups. Only 54 percent of medical professionals successfully identified pain as opposed to an 83 percent success rate for laypeople.

This experiment managed to simulate facial expressions, not from images of actual humans, but from computer generated imagery and an actual robot. This robot was created by analyzing a vast video archive depicting human expressions and using face-tracking software to graft those expressions onto the uncannily realistic rubber face of the robot, named Philip K. Dick.

Now, Dr. Riek is trying to use robots like Philip K. Dick to teach doctors how to better understand emotion. There is some precedent for this, as clinicians have often used robots as practice dummies for learning medicine.

But she has pointed out a major flaw in the use of these robotic training tools: “These robots can bleed, breathe, and react to medication… They are incredible, but there is a major design flaw – their face.” She explains that facial expressions are critical in communicating pain to doctors, not just in interacting with the patient but also in quickly diagnosing strokes or adverse reactions to medication.

This entire enterprise may strike many readers as highly ironic, given the cold, calculated image that science fiction has given us for artificial intelligence. Even the robot’s namesake was a prolific writer who dealt with the problem of robots’ lack of empathy. However, Dr. Riek’s work demonstrates how many varied applications such a powerful technology can have on better understanding emotions and facial expressions.

For more research on empathy and facial recognition, check out our past blogs here and here.

Filed Under: Emotion, Technology

The Humintell Blog March 15, 2017

Empathy and Facial Expressions

Do you think you’re good at reading other people’s facial expressions? You might be surprised!

While facial expressions provide a key insight into the emotions of other individuals, empathy may be even more important for laypeople to understand the emotions of fellow humans.

In a new study, Dr. Haotian Zhou from Shanghai Tech University and Professor Nicholas Epley from the University of Chicago asked a series of participants, let’s call them Group A, to review a series of emotionally charged photographs. Some photographs displayed depressing images, while others were cheerful or idyllic.

These participants were then asked to write down their emotional reactions to each photograph, and their faces were recorded with a video camera. Then, additional groups of participants were brought in to review these records, attempting to properly identify Group A’s emotional reactions.

These subsequent participants were divided into three categories. The first practiced “theorization,” and sought to determine Group A’s emotional reactions based on facial observation. They watched the video camera footage but were not told what the Group A participants were viewing.

This “theorization” cohort was contrasted with a group of participants who tried to identify emotional reactions based on the photographs alone, without exposure to the recorded expressions. This required them to empathize with how other individuals would feel in that situation.

Interestingly, the “simulation” group’s efforts proved to more effectively identify Group A’s expressions. In fact, the advantages of the simulation model were so striking that additional participants with access to both the video footage and the photographs were no more accurate than those that just examined the photographs.

While it may seem obvious to some of you that empathy would be a powerful tool in understanding other people’s emotions, most participants seemed to underestimate this potential. When given a choice between approaches, only a minority of participants selected the “simulation” method.

The study also examined whether it would be advantageous for participants to compare images of their own facial expressions with members of Group A. Hypothetically, this could have allowed them to better understand Group A’s emotions from video camera footage by comparing their own expressions with emotions. That said, those participants were no more accurate than other groups.

While this study underscores the power that empathy can have in promoting interpersonal understanding, we do not always have the ability to simulate other people’s experiences, as stimuli vary wildly beyond simple reactions to photographs.

It is at those times where micro expression reading is critical, but this study shows how difficult that can be without proper training. While the participants in this study were untrained, it would be revealing to see how Humintell staff, or those trained by Humintell, could have performed.

For more information on developing this skill click here.

Filed Under: Emotion

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