機器學習與情色產業的問題

Bruce Schneier 提到了最近幾個剛好相關的議題,關於機器學習在情色產業使用時遇到的隱私議題:「Technology to Out Sex Workers」。

第一個提到的是 PornHub 用機器學習辨識演員以及各種「其他資訊」,這邊引用的報導是 TechCrunch 的「PornHub uses computer vision to ID actors, acts in its videos」:

PornHub is using machine learning algorithms to identify actors in different videos, so as to better index them.

The computer vision system can identify specific actors in scenes and even identifies various positions and… attributes.

第二個提到的是花名與真實身份連在一起的問題:

People are worried that it can really identify them, by linking their stage names to their real names.

最後是提到 Facebook 已經有能力這樣做,而且已經發生了:

Facebook somehow managed to link a sex worker's clients under her fake name to her real profile.

Her sex-work identity is not on the social network at all; for it, she uses a different email address, a different phone number, and a different name. Yet earlier this year, looking at Facebook’s “People You May Know” recommendations, Leila (a name I’m using using in place of either of the names she uses) was shocked to see some of her regular sex-work clients.

這個議題與 Mass surveillance 有點像...。

大規模監控會無形壓抑少數意見

前陣子看到的這篇報導,在討論大規模的監控帶來的影響:「Mass surveillance silences minority opinions, according to study」。而 Bruce Schneier 這幾天也提到了這個問題:「Mass Surveillance Silences Minority Opinions」。

原始的論文出自「Under Surveillance: Examining Facebook's Spiral of Silence Effects in the Wake of NSA Internet Monitoring」這邊。

論文作者從 Facebook 上的行為來分析,說明大規模的監控會使得少數意見不敢發聲,對於社會多元性的負面影響。