* I can't know your monitor's calibration, your ambient light, or your phone's brightness. Obviously, this will affect the results. However, I am tracking local time of day and device type, from which we should be able to infer whether night mode and default calibration has any aggregate effects. Anecdotally, thus far, I haven't found any effects of Android vs. iPhone (N=34,000).
* The order is randomized. Where you start from can influence the outcome, but methodologically it's better to randomize so the aggregate results average over starting point. You can run the test several times to see how reliable this is for you.
* It's common practice in psychophysics to use two alternatives rather than three (e.g. blue, green, something in the middle). It would be a fun extension, which you can handle with an ordered logistic regression. The code is open if you want to take a shot at it: https://github.com/patrickmineault/ismyblue
* I am aware of most of the limitations of this test. I have run psychophysics experiments in a lab on calibrated CRTs during my PhD in visual neuroscience. *This is just entertainment*. I did this project to see if I could make a fun webapp in Vue.js using Claude Sonnet, and later cursor, given that I am not highly proficient in modern webdev. A secondary point was to engage people in vision science and get them to talk and think about perception and language. I think it worked!
My partner and I regularly disagree on blue vs green as the colours become more of a gray colour - might be interesting to randomise the brightness of the colours being displayed then seeing if the skew towards people perceiving blue Vs green changes as the colours become closer to gray.
I also often disagree on blue vs purple, which is inconvenient when we name the same coat two different colors.
I think my "blue" is a way more specific shade than most people (hue 192 here, whatever that means on an uncalibrated display). Likewise, I'll usually say "purple" before others.
My partner and I were well aware of the limitations, but it has clearly demonstrated our difference in perceptions in a way we were both happy with. Being able to see where your partner lands relative to you is deeply satisfying.
It was fun but I messed up the statistics! I had Redshift running, which (maybe you know) makes the colors more reddish. And I got a bluer than 98% of the population result. Turning off Redshift ... makes me instead greener than bluer.
I would guess the hackernews crowd has a higher percent of bluefilter installs since that is a very common topic. Probably also more agressive settings for the blue filter.
When done on my Xperia cell phone, even a small shift in screen orientation made the green leaners into obviously blue. Might be worthwhile capturing phone position if you can.
FAQ:
* I can't know your monitor's calibration, your ambient light, or your phone's brightness. Obviously, this will affect the results. However, I am tracking local time of day and device type, from which we should be able to infer whether night mode and default calibration has any aggregate effects. Anecdotally, thus far, I haven't found any effects of Android vs. iPhone (N=34,000).
* The order is randomized. Where you start from can influence the outcome, but methodologically it's better to randomize so the aggregate results average over starting point. You can run the test several times to see how reliable this is for you.
* It's common practice in psychophysics to use two alternatives rather than three (e.g. blue, green, something in the middle). It would be a fun extension, which you can handle with an ordered logistic regression. The code is open if you want to take a shot at it: https://github.com/patrickmineault/ismyblue
* I will release aggregate results on my blog, https://neuroai.science
* I am aware of most of the limitations of this test. I have run psychophysics experiments in a lab on calibrated CRTs during my PhD in visual neuroscience. *This is just entertainment*. I did this project to see if I could make a fun webapp in Vue.js using Claude Sonnet, and later cursor, given that I am not highly proficient in modern webdev. A secondary point was to engage people in vision science and get them to talk and think about perception and language. I think it worked!