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| author | adamhrv <adam@ahprojects.com> | 2019-04-19 01:52:41 +0200 |
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| committer | adamhrv <adam@ahprojects.com> | 2019-04-19 01:52:41 +0200 |
| commit | 76725707f1114a534e0c4f49282827e35da99358 (patch) | |
| tree | 4edd9876eb0b2731c0edc59448daa141c6e87ec5 /site/content/pages/datasets/msceleb/index.md | |
| parent | d6f5b32dd1bcbfaa4aedbaee547ad2a64d2bc8f3 (diff) | |
add images
Diffstat (limited to 'site/content/pages/datasets/msceleb/index.md')
| -rw-r--r-- | site/content/pages/datasets/msceleb/index.md | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/site/content/pages/datasets/msceleb/index.md b/site/content/pages/datasets/msceleb/index.md index fac40bc2..c353eca0 100644 --- a/site/content/pages/datasets/msceleb/index.md +++ b/site/content/pages/datasets/msceleb/index.md @@ -19,7 +19,7 @@ authors: Adam Harvey ### sidebar ### end sidebar -Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the Internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals images and use this to accelerate reserch into recognizing a target list of one million individuals from their face images "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig] +Microsoft Celeb (MS Celeb) is a dataset of 10 million face images scraped from the Internet and used for research and development of large-scale biometric recognition systems. According to Microsoft Research who created and published the [dataset](https://www.microsoft.com/en-us/research/publication/ms-celeb-1m-dataset-benchmark-large-scale-face-recognition-2/) in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals images and use this to accelerate research into recognizing a target list of one million individuals from their face images "using all the possibly collected face images of this individual on the web as training data".[^msceleb_orig] These one million people, defined by Microsoft Research as "celebrities", are often merely people who must maintain an online presence for their professional lives. Microsoft's list of 1 million people is an expansive exploitation of the current reality that for many people including academics, policy makers, writers, artists, and especially journalists maintaining an online presence is mandatory and should not allow Microsoft or anyone else to use their biometrics for research and development of surveillance technology. Many of names in target list even include people critical of the very technology Microsoft is using their name and biometric information to build. The list includes digital rights activists like Jillian York and [add more]; artists critical of surveillance including Trevor Paglen, Hito Steryl, Jill Magid, and Aram Bartholl; Intercept founders Laura Poitras, Jeremy Scahill, and Glen Greenwald; Data and Society founder danah boyd; and even Julie Brill the former FTC commissioner responsible for protecting consumer’s privacy to name a few. @@ -75,6 +75,8 @@ What the decision to block the sale announces is not so much that Microsoft had Until now, that data has been freely harvested from the Internet and packaged in training sets like MS Celeb, which are overwhelmingly [white](https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html) and [male](https://gendershades.org). Without balanced data, facial recognition contains blind spots. And without datasets like MS Celeb, the powerful yet inaccurate facial recognition services like Microsoft's Azure Cognitive Service also would not be able to see at all. + + Microsoft didn't only create MS Celeb for other researchers to use, they also used it internally. In a publicly available 2017 Microsoft Research project called [One-shot Face Recognition by Promoting Underrepresented Classes](https://www.microsoft.com/en-us/research/publication/one-shot-face-recognition-promoting-underrepresented-classes/), Microsoft leveraged the MS Celeb dataset to analyze their algorithms and advertise the results. Interestingly, Microsoft's [corporate version](https://www.microsoft.com/en-us/research/publication/one-shot-face-recognition-promoting-underrepresented-classes/) of the paper does not mention they used the MS Celeb datset, but the [open-access version](https://www.semanticscholar.org/paper/One-shot-Face-Recognition-by-Promoting-Classes-Guo/6cacda04a541d251e8221d70ac61fda88fb61a70) published on arxiv.org explicitly mentions that Microsoft Research tested their algorithms "on the MS-Celeb-1M low-shot learning benchmark task." We suggest that if Microsoft Research wants to make biometric data publicly available for surveillance research and development, they should start with releasing their researchers' own biometric data instead of scraping the Internet for journalists, artists, writers, actors, athletes, musicians, and academics. |
