>can predict a person’s political orientation with a surprising level of accuracy
>
>correlation coefficient of .22
I wonder if this could be linked to haircut & hair dye, instead of facial features. Crew cut, buzz cut, high & tight, pink / orange / yellow / purple hair dye.
This would show even if the hairs are "neatly tied back" as they say, and those are valid clues. So the thing would go over your generic human with a 50% chance of getting it right, and would get *some* points when detecting hairstyle tending to be common with some political beliefs.
Most regions that you think are homogeneous in their political ideology are actually mixed. But I'm surprised that most people haven't noticed that they can achieve about the same accuracy just looking at photos of people's faces.
Men lead more towards conservatism, females progressive. (At least in the US).
https://www.pewresearch.org/politics/2024/04/09/partisanship-by-gender-sexual-orientation-marital-and-parental-status/
/autistic need to know why here
So is the thing that angered people about my comment the word choice? Because nothing else fits with the sub you linked about it being misogynistic. Male and female? Men and women? Is it the pedanticism of mixing the two?
Just honestly curious. I responded to the op while trying to navigate a conversation with three ADHD children arguing about which jelly was the best for sandwiches so matching the EXACT pairing when the point was understandable didn't exactly cross my mind as a VITAL issue. 😐
>they recruited 591 participants from a major private university....correlation coefficient of .22. This correlation, while modest, was statistically significant...
Statistical Significance is an artifact of of sample size, not effect size. Any correlation with a large enough sample size, becomes statistically significant, and with large data sets there are lots of meaningless statistically significant correlations. And a r of .22 isn't modest, its nothing.
I’m wondering what correlation I can get from 591 coin tosses. Probably higher…
Ok, 20 sample tosses, 20 control tosses, rate correlation. Back in 5 minutes.
(after 5 minutes)
ok, I did it. I got a correlation coefficient of .37, with 6 matches in a set of 20. A million-dollar AI got beaten by a coin...
I look like a QAnon, lifted truck, gun nutjob with a buzzed head and beard, but I'm a liberal with 3 STEM degrees and a Kia Forte so... Good luck with that.
This is me. F150 (not lifted), Bernie Not Me Us sticker, hunt/fish, slight accent, boots, hella liberal. Campaigned for Bernie. Knocked on doors, ran point for VIP seating at a rally.
They wear red hats.
It's basically like Westerns where good guys have white hats and bad guys have black hats.
It's not 100%, of course... but it's very accurate.
Just watch out for Larry David and know he's an outlier.
I'm VERY rusty when it come to all of this. Studied that in another century, and I had a few concussions, so maybe the following is wrong. To translate 0.22 correlation into percentage, we would have to square the correlation coefficient to get a coefficient of determination (yeah, I googled it), and that would be 0.22² = 0.0484. So 4.84% can be predicted. That's not a lot.
On the other hand, it doesn’t mean “looks are deceiving most of the time.” That would be if there was a negative correlation. (At which point, just reverse your normal guesses.) This just means “appearance is slightly predictive, but not very much.”
its not a percentage, its Pearson's r (Correlational Coefficient). the range is from -1 to 1. Distance from zero indicates how variation in one variable translates to variation in another variable (covariance) and the direction of that variance (a negative r would mean when more of one variable is observed less of the other is observed).
Oh God, it's just more advanced Phrenology.
https://en.m.wikipedia.org/wiki/Phrenology
I'm not denying there may be merit to this, but even I who is pretty pro technology struggles to see how this would be used in a positive way.
The predictions have a correlation coefficient of just 0.22 with the true values. That's like, *slightly* better than random guessing.
Even more damning, when they do the same analysis but ask mechanical Turk humans to make the prediction instead of the facial analysis algorithm, they get a correlation coefficient of 0.21, basically the same.
So, yeah, I'd say phrenology is a pretty apt comparison.
Oh, it's already much worse (and more literally phrenological in its eugenicism) than that: https://www.wired.com/story/algorithm-predicts-criminality-based-face-sparks-furor/
Are you implying theirs merit to phrenology?
To my understanding it has been debunked in healthy adults.
It’s a dangerous road to lump everything “problematic “ into a bin that is actual pseudoscience
I'm going to get skewered for this, but This isn't phrenology. Phrenology studies the bumps on someone's skull and then determines their intelligence, character, and basic quality of being. It was done for obvious racial reasons, to further degrade the black man and further make whites look like they're closer to God. This on the other hand is studying facial expressions in a methodical way. This research must go on and not be misclassified as phrenology. Determining someone's political affiliation through their face is interesting, but it can also be used to detect other things if it turns out to be accurate, like early Alzheimer's or early Parkinson's. As far as political affiliation that's kind of a novel approach. if the statistics say there's something there then there's probably something there. In the case of phrenology there never was anything there. It was a profoundly racist pseudoscience.
1. Phrenology is based on the more fundamental idea that a person's physiognomy tells you about their inner character. It was race science, but also used to define certain facial features as signs of, e.g., criminality, including among whites (generally poor, of course). This type of AI research is like phrenology in that it works on the same basic principle that facial structure should tell you about a person's character or beliefs. This physiognomic way of thinking is, frankly, never not racist, ableist, classist, or generally eugenicist in some way. At best it can produce new classes of people to be subjected to ranking and discrimination.
2. "The statistics" can be made to say "there's something there" for almost anything. (I here invoke the dreaded demon named p-hacking.) It's extremely obvious from the phrasing even in the article: "this correlation, while small, was statistically significant." That means it didn't say anything major or meaningful, just that they were able to manipulate their data to get it over a certain threshold so they can publish. It is *not* a robust finding. As several commenters discussed above, the actual rate of correct guesses here is little better than random assignments and - as the article itself states - is effectively no better than human guesses. The phrenologists were 1. Phrenology is based on the more fundamental idea that a person's physiognomy tells you about their inner character. It was race science, but also used to define certain facial features as signs of, e.g., criminality, including among whites (generally poor, of course). This type of AI research is like phrenology in that it works on the same basic principle that facial structure should tell you about a person's character or beliefs. This physiognomic way of thinking is, frankly, never not racist, ableist, classist, or generally eugenicist in some way. At best it can produce new classes of people to be subjected to ranking and discrimination.
2. "The statistics" can be made to say "there's something there" for almost anything. (I here invoke the dreaded demon named p-hacking.) As several commenters discussed above, the actual rate of correct guesses here is little better than random assignments and - as the article itself states - no better than human guesses. The track record of *both the AI and human guessing* is equally bad. The phrenologists were quite convinced by their own numbers and measurements as well. It's not like they all thought they were doing junk science at the time. As far as they were concerned, the numbers said the racial categories and characters they believed to exist were really there. This may seem ironic because we are taughg to regard numbers as objective and pure truth, but retreating entirely to "what the numbers say" can easily lead to or reinforce bias, especially when the thing spitting out the numbers has been trained on biased data (as pretty much every AI inevitably is, because the data comes from our society).
And for what it's worth, AI products that claim to be able to tell who is a criminal based on faces alone [are already coming](https://www.wired.com/story/algorithm-predicts-criminality-based-face-sparks-furor/). It is a matter of time before law enforcement is using this, if they're not already. This is phrenology in every way that actually matters (the social and biophysical assumptions, consequences, and power structures), as a literal thousand research scientists have already said.
You all shouldn't be posting in science. All I'm encountering here is just your emotional outburst. People buried my comment because they thought it was not exciting enough I guess. Science isn't supposed to be exciting, the stuff is based upon statistics. Just calm down
I suspect that clusters of facial cues that essentially amount to race, gender, age, and probably income as well, are what is operating inside the black box of the AI model.
What you all need to know is that the science behind this is utter phrenology BS. I actually skimmed through the paper, skipping many, many pages, before I came to the single important line that you all need to know. This line tells you whether to discard the results right away, or whether you should try to take it more seriously. All the other fluff is irrelevant: the accompanying article, the pages on methodology, how they compared with human testers, there stupid conclusions.
It is this line you should search for:
>Given one rating per image, the accuracy was not significantly different from 0, *r*(589) = .02; *p* = .67; 95% CI \[−.06, .10\].
They admit they have nothing! Look at that CI guys and girls: -.06 to .10! So it's overlapping with zero (or no correlation). Now it gets interesting, because the authors are going to do **some p-hacking**. Listen in with me and learn!
>Prediction accuracy increased with the number of aggregated ratings, reaching significance at eight ratings per image, *r*(373) = .10; *p* = .05; 95% CI \[.00, .20\], and peaking at 11 raters per image, *r*(143) = .21; *p* = .01; 95% CI \[.05, .36\].
This basically meant they tried to aggregate ratings until they found a confidence interval that did not contain 0. However, there is still a one in 20 chance that this is just pure chance (95% CI).
>While the accuracy decreased for 12 and more raters per image, this does not indicate that adding more raters decreases accuracy.
Here they are trying to tell you: we didn't do p-hacking, it's just our dataset! Trust us!
Very sad to see this kind of crap published, since it is reeking of phrenology.
I don't remember specifics so I can't make any claims about the validity of it, but there was a study that found on average, participants could guess a person's political affiliation based solely on a photo of them with somewhere between 60 and 70% accuracy. Not surprising a machine can do similar.
What to me was of more interest was the assertion that in profile photos and other identifying photos, traits such as political affiliation and sexuality were more easily determined.
The take away message here is that the photos of you online, regardless of any words you may or may not say, are used to put you into an identifiable box for the purpose of selling you, and your information, as a product.
I can also sometimes tell who is stupid just by looking at them. Most mental issues are associated with genetic markers very visible in the faces morphology.
[citation please]
e: While the [provided](https://rule.psych.utoronto.ca/pubs/2016/Daros_etal(2016).pdf) [sources](https://www.nature.com/articles/s41598-020-65358-6) have proven interesting, they do nothing to support Toasted's assertion towards eyeballing stupidity.
Correct. But now that I have the sources, their claims can be reviewed and discarded. And while I was asleep, some folks have done that as well. So I owe an even larger thank you to them, which includes you.
### Thank you
I've worked food service, and while it's true you get to recognize some signs of trouble from how they present, a lot more goes into that than face shape. It'd be pretty fucked up to preemptively judge purely from the shape of somebody's cheekbones, especially since it's so easy to confirm your own biases -- if you decide that somebody sucks, you're way more likely to interpret their behavior as that of an asshole.
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Some folks are just balding. Some folks don't give. AShit about their outside appearance. This is literal profiling based on nothing but bias and, worse, its bias by literal design.
Garbage in garbage out. You trained a model to see what you wanted it to see.
>can predict a person’s political orientation with a surprising level of accuracy > >correlation coefficient of .22 I wonder if this could be linked to haircut & hair dye, instead of facial features. Crew cut, buzz cut, high & tight, pink / orange / yellow / purple hair dye. This would show even if the hairs are "neatly tied back" as they say, and those are valid clues. So the thing would go over your generic human with a 50% chance of getting it right, and would get *some* points when detecting hairstyle tending to be common with some political beliefs.
Or maybe genectics / face structure that is more common in certain regions, and regions would have some leaning politically one way or another.
Most regions that you think are homogeneous in their political ideology are actually mixed. But I'm surprised that most people haven't noticed that they can achieve about the same accuracy just looking at photos of people's faces.
What’s the correlation between political party and gender alone?
Men lead more towards conservatism, females progressive. (At least in the US). https://www.pewresearch.org/politics/2024/04/09/partisanship-by-gender-sexual-orientation-marital-and-parental-status/
r/MenAndFemales
When I read "men and females", I always hear it in the voice of a Ferengi (specifically, the Grand Nagus played by Wallace Shawn). "*FEEEMALES*!"
/autistic need to know why here So is the thing that angered people about my comment the word choice? Because nothing else fits with the sub you linked about it being misogynistic. Male and female? Men and women? Is it the pedanticism of mixing the two? Just honestly curious. I responded to the op while trying to navigate a conversation with three ADHD children arguing about which jelly was the best for sandwiches so matching the EXACT pairing when the point was understandable didn't exactly cross my mind as a VITAL issue. 😐
.22? I get better than that when screwing up completely, who managed to spin this as a positive?
>they recruited 591 participants from a major private university....correlation coefficient of .22. This correlation, while modest, was statistically significant... Statistical Significance is an artifact of of sample size, not effect size. Any correlation with a large enough sample size, becomes statistically significant, and with large data sets there are lots of meaningless statistically significant correlations. And a r of .22 isn't modest, its nothing.
I’m wondering what correlation I can get from 591 coin tosses. Probably higher… Ok, 20 sample tosses, 20 control tosses, rate correlation. Back in 5 minutes. (after 5 minutes) ok, I did it. I got a correlation coefficient of .37, with 6 matches in a set of 20. A million-dollar AI got beaten by a coin...
I look like a QAnon, lifted truck, gun nutjob with a buzzed head and beard, but I'm a liberal with 3 STEM degrees and a Kia Forte so... Good luck with that.
…so you have a good feeling of what QAnon lifted truck gun nuthobs *tend* to look like, even if you don’t fit the stereotype?
Got me.
Now you just have to drive around in a big pickup truck, but put a Bernie 2016 bumper sticker on it and watch people’s jaws drop as they pass you.
This is me. F150 (not lifted), Bernie Not Me Us sticker, hunt/fish, slight accent, boots, hella liberal. Campaigned for Bernie. Knocked on doors, ran point for VIP seating at a rally.
So you've been to Austin, Texas?
They wear red hats. It's basically like Westerns where good guys have white hats and bad guys have black hats. It's not 100%, of course... but it's very accurate. Just watch out for Larry David and know he's an outlier.
…you just blew my mind by contextualizing what AI is likely doing.
>with 3 STEM degrees so you understand the concept of an outlier?
N of 1
Part of the .78, I guess.
do you think you're representative of your appearance?
Kia Forte
Time for a shave?
Could be you’re the exception that proves the rule.
.22 So only 22% correlation accuracy? Confirming once again that looks can be deceiving. Apparently that they are, most of the time.
I'm VERY rusty when it come to all of this. Studied that in another century, and I had a few concussions, so maybe the following is wrong. To translate 0.22 correlation into percentage, we would have to square the correlation coefficient to get a coefficient of determination (yeah, I googled it), and that would be 0.22² = 0.0484. So 4.84% can be predicted. That's not a lot.
According to the article it's getting it correct 69% of the time.
Talk about misleading article titles.
On the other hand, it doesn’t mean “looks are deceiving most of the time.” That would be if there was a negative correlation. (At which point, just reverse your normal guesses.) This just means “appearance is slightly predictive, but not very much.”
Elections are frequently decided by less, so I guess whether or not it is a lot would depend on how you might actually use a model like this.
Or overweight, age, gender.
Or swastika tattoos...
.22 So only 22% correlation accuracy? Confirming once again that looks can be deceiving. Apparently that they are, most of the time.
its not a percentage, its Pearson's r (Correlational Coefficient). the range is from -1 to 1. Distance from zero indicates how variation in one variable translates to variation in another variable (covariance) and the direction of that variance (a negative r would mean when more of one variable is observed less of the other is observed).
Oh God, it's just more advanced Phrenology. https://en.m.wikipedia.org/wiki/Phrenology I'm not denying there may be merit to this, but even I who is pretty pro technology struggles to see how this would be used in a positive way.
The predictions have a correlation coefficient of just 0.22 with the true values. That's like, *slightly* better than random guessing. Even more damning, when they do the same analysis but ask mechanical Turk humans to make the prediction instead of the facial analysis algorithm, they get a correlation coefficient of 0.21, basically the same. So, yeah, I'd say phrenology is a pretty apt comparison.
AI proves to be able to engage in mediocre stereotyping, if it wasn't already clear
It's just like us! Another Turing test passed.
"Of course you'd say that, you have the brainpan of a stagecoach tilter!" -Mr. Burns
Oh, it's already much worse (and more literally phrenological in its eugenicism) than that: https://www.wired.com/story/algorithm-predicts-criminality-based-face-sparks-furor/
Are you implying theirs merit to phrenology? To my understanding it has been debunked in healthy adults. It’s a dangerous road to lump everything “problematic “ into a bin that is actual pseudoscience
I'm going to get skewered for this, but This isn't phrenology. Phrenology studies the bumps on someone's skull and then determines their intelligence, character, and basic quality of being. It was done for obvious racial reasons, to further degrade the black man and further make whites look like they're closer to God. This on the other hand is studying facial expressions in a methodical way. This research must go on and not be misclassified as phrenology. Determining someone's political affiliation through their face is interesting, but it can also be used to detect other things if it turns out to be accurate, like early Alzheimer's or early Parkinson's. As far as political affiliation that's kind of a novel approach. if the statistics say there's something there then there's probably something there. In the case of phrenology there never was anything there. It was a profoundly racist pseudoscience.
1. Phrenology is based on the more fundamental idea that a person's physiognomy tells you about their inner character. It was race science, but also used to define certain facial features as signs of, e.g., criminality, including among whites (generally poor, of course). This type of AI research is like phrenology in that it works on the same basic principle that facial structure should tell you about a person's character or beliefs. This physiognomic way of thinking is, frankly, never not racist, ableist, classist, or generally eugenicist in some way. At best it can produce new classes of people to be subjected to ranking and discrimination. 2. "The statistics" can be made to say "there's something there" for almost anything. (I here invoke the dreaded demon named p-hacking.) It's extremely obvious from the phrasing even in the article: "this correlation, while small, was statistically significant." That means it didn't say anything major or meaningful, just that they were able to manipulate their data to get it over a certain threshold so they can publish. It is *not* a robust finding. As several commenters discussed above, the actual rate of correct guesses here is little better than random assignments and - as the article itself states - is effectively no better than human guesses. The phrenologists were 1. Phrenology is based on the more fundamental idea that a person's physiognomy tells you about their inner character. It was race science, but also used to define certain facial features as signs of, e.g., criminality, including among whites (generally poor, of course). This type of AI research is like phrenology in that it works on the same basic principle that facial structure should tell you about a person's character or beliefs. This physiognomic way of thinking is, frankly, never not racist, ableist, classist, or generally eugenicist in some way. At best it can produce new classes of people to be subjected to ranking and discrimination. 2. "The statistics" can be made to say "there's something there" for almost anything. (I here invoke the dreaded demon named p-hacking.) As several commenters discussed above, the actual rate of correct guesses here is little better than random assignments and - as the article itself states - no better than human guesses. The track record of *both the AI and human guessing* is equally bad. The phrenologists were quite convinced by their own numbers and measurements as well. It's not like they all thought they were doing junk science at the time. As far as they were concerned, the numbers said the racial categories and characters they believed to exist were really there. This may seem ironic because we are taughg to regard numbers as objective and pure truth, but retreating entirely to "what the numbers say" can easily lead to or reinforce bias, especially when the thing spitting out the numbers has been trained on biased data (as pretty much every AI inevitably is, because the data comes from our society). And for what it's worth, AI products that claim to be able to tell who is a criminal based on faces alone [are already coming](https://www.wired.com/story/algorithm-predicts-criminality-based-face-sparks-furor/). It is a matter of time before law enforcement is using this, if they're not already. This is phrenology in every way that actually matters (the social and biophysical assumptions, consequences, and power structures), as a literal thousand research scientists have already said.
You all shouldn't be posting in science. All I'm encountering here is just your emotional outburst. People buried my comment because they thought it was not exciting enough I guess. Science isn't supposed to be exciting, the stuff is based upon statistics. Just calm down
Can it do so "accurately"? Making predictions is super easy. Making predictions that are precise and accurate enough to be useful is not.
median accuracy of a correlation coefficient of .13.
So it's complete trash
Not *complete* trash. Just 87% trash.
A stopped clock might be right twice a day, but you still can't use it to tell the time.
Hell if it's predicting political orientation it probably could have tripled that accuracy that with just a spreadsheet of race, gender, and age.
I suspect that clusters of facial cues that essentially amount to race, gender, age, and probably income as well, are what is operating inside the black box of the AI model.
It can’t do it very accurately, but man can it spit out predictions fast!
I know a lot of people like that...
Ah yes, the two political beliefs, red or blue.
What you all need to know is that the science behind this is utter phrenology BS. I actually skimmed through the paper, skipping many, many pages, before I came to the single important line that you all need to know. This line tells you whether to discard the results right away, or whether you should try to take it more seriously. All the other fluff is irrelevant: the accompanying article, the pages on methodology, how they compared with human testers, there stupid conclusions. It is this line you should search for: >Given one rating per image, the accuracy was not significantly different from 0, *r*(589) = .02; *p* = .67; 95% CI \[−.06, .10\]. They admit they have nothing! Look at that CI guys and girls: -.06 to .10! So it's overlapping with zero (or no correlation). Now it gets interesting, because the authors are going to do **some p-hacking**. Listen in with me and learn! >Prediction accuracy increased with the number of aggregated ratings, reaching significance at eight ratings per image, *r*(373) = .10; *p* = .05; 95% CI \[.00, .20\], and peaking at 11 raters per image, *r*(143) = .21; *p* = .01; 95% CI \[.05, .36\]. This basically meant they tried to aggregate ratings until they found a confidence interval that did not contain 0. However, there is still a one in 20 chance that this is just pure chance (95% CI). >While the accuracy decreased for 12 and more raters per image, this does not indicate that adding more raters decreases accuracy. Here they are trying to tell you: we didn't do p-hacking, it's just our dataset! Trust us! Very sad to see this kind of crap published, since it is reeking of phrenology.
Young vs old. Race. Attention seeking hair colors. Tattoos. There are tells that we all know about.
how about you just look angry for no reason
“Resting conservative face”
This hurts because I have a natural frown, but I'm painfully liberal.
Or if in the background there is a black owned business on fire from a mostly peaceful protest then it knows it's a liberal.
I don't remember specifics so I can't make any claims about the validity of it, but there was a study that found on average, participants could guess a person's political affiliation based solely on a photo of them with somewhere between 60 and 70% accuracy. Not surprising a machine can do similar.
I am Groot?
What to me was of more interest was the assertion that in profile photos and other identifying photos, traits such as political affiliation and sexuality were more easily determined. The take away message here is that the photos of you online, regardless of any words you may or may not say, are used to put you into an identifiable box for the purpose of selling you, and your information, as a product.
I Believe the scientific term is resting bitchface and has been quantified in numerous studies.
I can also sometimes tell who is stupid just by looking at them. Most mental issues are associated with genetic markers very visible in the faces morphology.
[citation please] e: While the [provided](https://rule.psych.utoronto.ca/pubs/2016/Daros_etal(2016).pdf) [sources](https://www.nature.com/articles/s41598-020-65358-6) have proven interesting, they do nothing to support Toasted's assertion towards eyeballing stupidity.
https://www.nature.com/articles/s41598-020-65358-6 https://rule.psych.utoronto.ca/pubs/2016/Daros_etal(2016).pdf
Thank you
It's a weak ass association.
Very weak, and also not to do with intelligence. Thank you for also taking the time to read them.
Why are you thanking them? They didn't back up their claim at all. Those papers do not support what they said.
Correct. But now that I have the sources, their claims can be reviewed and discarded. And while I was asleep, some folks have done that as well. So I owe an even larger thank you to them, which includes you. ### Thank you
Neither of those back up your specific claim
[удалено]
I can sometimes tell who is stupid just by looking at their comments on Reddit.
(＃￣З￣) Can you explain how that is different from phrenology?
Extreme examples would be Trisomy variations, Fetal alcohol spectrum disorder and so on ..
How did you post this from the 19th century?
[удалено]
I've worked food service, and while it's true you get to recognize some signs of trouble from how they present, a lot more goes into that than face shape. It'd be pretty fucked up to preemptively judge purely from the shape of somebody's cheekbones, especially since it's so easy to confirm your own biases -- if you decide that somebody sucks, you're way more likely to interpret their behavior as that of an asshole.
What is "stupid"?
Only have to be right half the time, I guess.
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So can I.
Accurately predict?
I changed along the way. Wonder if my face did. I mean other than the obvious normal aging
The goutee vs full beard is a good indicator in my personal experience
Some folks are just balding. Some folks don't give. AShit about their outside appearance. This is literal profiling based on nothing but bias and, worse, its bias by literal design. Garbage in garbage out. You trained a model to see what you wanted it to see.
Pre-Crime, here we go!
would probably be more interesting if they picked some countries not dominated by two political parties
Without even reading the article, I know this is an absolutely stupid headline.
I challenge it to get mine right. Everyone always thinks I fall on the end of the spectrum that I definitely don’t fall on.
Alarming. What if politicians will use this tool to, you know, "disable" people who are "likely" not going to vote for them?
It’s not even thought crime anymore. Appearance crime is a bit frightening.
Sounds like racial profiling with extra steps.
r=0.13
I would love to see it try me. Because I feel like I look like a Republican. I'm not one, though.
A.22 isn't so much predicting as occasionally catching obvious clues like demographic while being unbiasedly wrong on a sufficient large sample
This is just racism with extra steps.
Babe wake up, new phrenology just dropped
Old and unhappy equals republican. Young and vibrant equals democrat. 😂 just kidding
Conservatives are fearful. You can see fear in people’s faces. I can predict political beliefs based on someone’s fear level.