A recent poll in China found 74% of respondents unhappy about the growing use of facial-recognition software
1923年末，胡適應上海商科大學佛學研究會去演講《哲學與人生》：…….那太子確是研究人生切要的問題，從意義上著想去找他以為比較適用的意義。…..意義有兩種來源：一種是從累積得來….. ；一種是由直覺得來…….直覺不過是熟能生巧的結果…….我希望諸君實行笛卡爾的懷疑態度，牢記蘇格拉底所說的：“未經考察過的生活是不值得活的” 這句話。
案: “直覺不過是熟能生巧的結果”由Herbert A. Simon等人以認知科學的方式實驗證明。
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人脸识别的雷池之界
许可：在数字化社会，人脸信息一旦被搜集就可能被永远保存。
詳細全文：
延伸專題：
【推翻傳統教育，塑造「不被 AI 取代的人才」（上）】
【監控大國：人工智能如虎添翼】
【發展 AI + 機械人上，日本也要失敗？（下）】
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CUP.COM.HK
AI 發展，或到瓶頸？ - *CUP
今天，要在無人駕駛、製藥、追蹤武肺患者等領域取得突破發展，
Jerome Pesenti, Facebook's head of AI, says that one round of training for the biggest AI models can cost "millions of dollars" in electricity consumption
ECONOMIST.COM
he cost of training machines is becoming a problem
Machine, learning
請試用 Facial recognition 和 New York Times 一起在 Google搜索，今年2020前半年，件數近2頁：
1. 2020.1.18 His tiny company, Clearview AI, devised a groundbreaking facial recognition app. You take a picture of a ...
Clearview
Before Clearview — a facial recognition app with a database of billions of photos, scraped from sites such as Facebook, Twitter and LinkedIn — was used by police
2. A Google research scientist explains why she thinks the police shouldn't use facial recognition software.
A Case for Banning Facial Recognition
Facial recognition software might be the world’s most divisive technology.
Law enforcement agencies and some companies use it to identify suspects and victims by matching photos and video with databases like driver’s license records. But civil liberties groups say facial recognition contributes to privacy erosion, reinforces bias against black people and is prone to misuse.
San Francisco and a major provider of police body cameras have barred its use by law enforcement, and IBM on Monday backed away from its work in this area. Some proposals to restructure police departments call for tighter restrictions on their use of facial recognition.
Timnit Gebru, a leader of Google’s ethical artificial intelligence team, explained why she believes that facial recognition is too dangerous to be used right now for law enforcement purposes. These are edited excerpts from our virtual discussion at the Women’s Forum for the Economy & Society on Monday.
Ovide: What are your concerns about facial recognition?
Gebru: I collaborated with Joy Buolamwini at the M.I.T. Media Lab, who led an analysis that found very high disparities in error rates [in facial identification systems], especially between lighter-skinned men and darker-skinned women. In melanoma screenings, imagine that there’s a detection technology that doesn’t work for people with darker skin.
I also realized that even perfect facial recognition can be misused. I’m a black woman living in the U.S. who has dealt with serious consequences of racism. Facial recognition is being used against the black community. Baltimore police during the Freddie Gray protests used facial recognition to identify protesters by linking images to social media profiles.
But a police officer or eyewitness could also look at surveillance footage and mug shots and misidentify someone as Jim Smith. Is software more accurate or less biased than humans?
That depends. Our analysis showed that for many, facial recognition was way less accurate than humans.
The other problem is something called automation bias. If your intuition tells you that an image doesn’t look like Smith, but the computer model tells you that it is him with 99 percent accuracy, you’re more likely to believe that model.
There’s also an imbalance of power. Facial recognition can be completely accurate, but it can still be used in a way that is detrimental to certain groups of people.
The combination of overreliance on technology, misuse and lack of transparency — we don’t know how widespread the use of this software is — is dangerous.
A maker of police body cameras recently discussed using artificial intelligence to analyze video footage and possibly flag law-enforcement incidents for review. What’s your take on using technology in that way?
My gut reaction is that a lot of people in technology have the urge to jump on a tech solution without listening to people who have been working with community leaders, the police and others proposing solutions to reform the police.
Do you see a way to use facial recognition for law enforcement and security responsibly?
It should be banned at the moment. I don’t know about the future.
You can watch our entire conversation about helpful uses of A.I. and its downsides here.
3. 2020/02/06 - Lockport High School in Lockport, N.Y., has adopted a facial recognition system for security. ... LOCKPORT, N.Y. — Jim Shultz tried everything he could think of to stop facial recognition technology from entering the public schools in Lockport, a small city 20 ...
4. The whole point of modern surveillance is to treat people differently, and facial recognition technologies are only a small part of that.
5.
2019/12/19 - Algorithms falsely identified African-American and Asian faces 10 to 100 times more than Caucasian faces, researchers for the National ... Technology for facial recognition is frequently biased, a new study confirmed. ... The majority of commercial facial-recognition systems exhibit bias, according to a study from a federal agency released on ... 20, 2019 , Section B, Page 5 of the ...
According to a poll, the number of bosses planning to deploy AI across their firms was 4% in 2020, down from 20% the year before
ECONOMIST.COM
Why do businesses seem to be cooling on using AI?
Businesses are finding AI hard to adopt
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臉部辨識技術/業務facial recognition tech/business，
Facial recognition system - Wikipedia
en.wikipedia.org › wiki › Facial_reco...
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by ...
History of facial ... · Techniques for face ... · Application · Controversies
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database. It is also described as a Biometric Artificial Intelligence based application that can uniquely identify a person by analyzing patterns based on the person's facial textures and shape.[1][2][3]
While initially a form of computer application, it has seen wider uses in recent times on mobile platforms and in other forms of technology, such as robotics. It is typically used as access control in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems.[4] Although the accuracy of facial recognition system as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless and non-invasive process.[5] Recently, it has also become popular as a commercial identification and marketing tool.[6] Other applications include advanced human-computer interaction, video surveillance, automatic indexing of images, and video database, among others.[7]
一般來說，人臉識別系統包括圖像攝取、人臉定位、圖像預處理、以及人臉識別（身份確認或者身份查找）。系統輸入一般是一張或者一系列含有未確定身份的人臉圖像，以及人臉資料庫中的若干已知身份的人臉圖象或者相應的編碼，而其輸出則是一系列相似度得分，表明待識別的人臉的身份。
目前人臉識別的算法可以分類為：
發展歷史[編輯]
人臉識別系統的研究始於20世紀60年代，80年代後隨著計算機技術和光學成像技術的發展得到提高，而真正進入初級的應用階段則在90年後期，並且以美國、德國和日本的技術實現為主；人臉識別系統成功的關鍵在於是否擁有尖端的核心算法，並使識別結果具有實用化的識別率和識別速度；「人臉識別系統」集成了人工智慧、機器識別、機器學習、模型理論、專家系統、視頻圖像處理等多種專業技術，同時需結合中間值處理的理論與實現，是生物特徵識別的最新應用，其核心技術的實現，展現了弱人工智慧向強人工智慧的轉化。[1]
2019年11月，全球首個人臉識別導航智能停車場於中國廣州K11啟用，當車主接受人臉註冊後，停車場可以提供車位實景導航服務，方便車主取車。有關技術正研究於香港K11採用[5]。
爭議[編輯]
臉部辨識系統雖然有其方便之外，但也衍生了許多資訊安全及隱私問題，加上現時臉部辨識系統並非十分精確，系統的演算法技術準確性相對較低，較容易出錯、缺乏相關法律和道德標準、具有侵犯隱形權的討論、以及政府很容易濫用這項技術，若應用在人權的犯罪防治工作上，則會引發歧視問題[6]。
【不願變成監控幫凶 IBM退出臉部辨識業務】；Amazon pauses police use of its facial recognition tech for a year
【不願變成監控幫凶 IBM退出臉部辨識業務】
國際商業機器（IBM）執行長克里希納(Arvind Krishna)8日在一封給美國國會的信函中，宣布將退出臉部辨識業務！！
IBM表示，IBM家族反對，而且絕對不容許使用任何科技，包括其它供應商提供臉部辨識技術，用來大規模監控、種族歸納，違反基本人權和自由，以及其它任何違反我們的價值和信任、透明原則的目的用途。
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Amazon.com Inc on Wednesday said it was implementing a one-year moratorium on police use of its facial recognition software, halting a business it long defended as many protested law enforcement brutality against people of color.
REUTERS.COM
Amazon pauses police use of its facial recognition tech for a year
A recent poll in China found 74% of respondents unhappy about the growing use of facial-recognition software
ECONOMIST.COM
As AI’s limits become apparent, humans will add more
Autumn is coming
批判[編集]
認識率[編集]
世界最高の顔認識システムでは静止画での認識率が99.5％に達する[38]。
顔認識は完全ではなく、条件が整わないと認識率が低くなる。カーネギーメロン大学ロボット工学研究所の Ralph Gross は顔の撮影された角度について「顔認識は真正面から顔を捉えるのを基本とし、そこから20度までは何とか認識できる。しかしそれ以上横向きになると問題が生じる」と説明している[5]。
他にも画面が暗い場合、サングラスをかけている場合、髪が伸びている場合、何かで顔の一部が隠れている場合、解像度が低い場合などに認識率が極めて低くなる[1]。
また、表情が変わると認識できないことが多い。カナダではパスポートの顔写真は無表情でなければならないとしている[39]。
有効性[編集]
技術評論家たちは、ニューアムに実際にデータベースに登録されている犯罪者がいたにもかかわらず、システムが犯罪者を一人も認識していないことに批判的である[40][41]。これは、顔認識システム導入による 34% の犯罪件数の低下という情報と矛盾しているが、犯罪の予防という観点で、バーミンガムでも同様のシステムが導入された[42]。
ボストンのジェネラル・エドワード・ローレンス・ローガン国際空港でも顔認識システムによるテロリスト識別という大規模な実験が行われたが、失敗に終わった[44]。
プライバシー問題[編集]
この技術の潜在的な利点を考慮したとしても、プライバシーの侵害という懸念が依然残っている。政府がビッグ・ブラザーの様に、国民1人1人を常に監視し、行動を把握するようになるのではないかと憂慮する者もいる。権力がそのような暴走を引き起こす可能性があることは、歴史が証明している[45]。
日本国内における批判[編集]
- 主に首都圏所在のショッピングセンターや大規模マンションに設置された顔認識システム搭載カメラのうち29台について、利用者や通行人などに対し断らないまま撮影が行われていることが明らかになっている。視聴者の性別・世代を分析し顧客分析に利用する目的があるとされており、カメラ設置業者側は「個人を特定しておらず問題はない」と主張しているが、有識者の間からは「商業目的では納得の行かない人も多いし、何らかの形でのルール整備が必要だ」などとの批判的な意見が多く聞かれる[46]。
- 情報通信研究機構は、JR西日本などの協力を得て、大阪駅構内の大阪ステーションシティに多数の顔認証カメラを設置し、構内の通行人の追跡を実施する実証実験を、2014年4月から実施する予定にしていた。ところが、計画が同年1月6日に報じられると共に、市民らから抗議が多数寄せられるようになり、2014年3月現在、実施の目処が立たない状態となっている。同機構やJR西日本などは「防災目的である」としているものの、勝手に顔を撮影された上、商業目的などに利用されることが懸念されているものと見られている[47]。
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