Most of the time, I just use it to scrape original data from screenshots taken from research papers where the data is not provided as a table. I would say 7/8 of these figures are scatter plots from experimental measurements.
If you have a publicly available photo of yourself (e.g. public social media), it's possible to match that to your genomic sequence. I.e. you already have to be anonymous online to have a chance that a private company cannot reidentify you.
Seems like the technique only works in highly controlled scenarios (e.g. you have tens of phenotypes and images and want to have a better than random chance of assigning one to the other):
> Nevertheless, re-identification risk in the wild does not appear to be especially high. While we observe a success rate as high as 25%, this is only achieved when the genomic dataset is extremely small, on the order of 10 individuals. In contrast, success rate for top 1 matching drops quickly and is negligible for populations of more than 100 individuals. Moreover, it should be kept in mind that this result assumes that we can predict the phenotypes perfectly.
That's a good catch. This study uses images for reidentification. I wonder which other factors, not contained in an image could be used for reidentifying someone and by how much that would increase the reidentification accuracy.
