學術演講：6/22馬里蘭大學Frank Pasquale教授演講
| 時間：107年6月22日(五)下午2:00至4:00 | 報名時間：2018/5/21 - 2018/6/15 |
| 地點：國立臺灣大學社會科學院3樓梁國樹國際會議廳 （近辛亥路與復興南路口校門） | 聯絡人資訊： 林正皓 02-2351-1099#305 chlin5566@ntu.edu.tw |
| 合作單位：中央研究院法律學研究所、科技部數位經濟計畫AI分項、中央研究院社會學研究所、臺灣科技與社會研究學會 | |
講題：
黑箱社會：無所不在的數據演算法對公民社會的挑戰
After "Black Box Society": The Challenges of Secret Algorithms That Control Money and Information
主講人：
Prof. Frank Pasquale（美國馬里蘭大學法律學院教授）
主持人：
洪文玲理事長（台灣科技與社會研究學會）
Pasquale教授於2015年由哈佛大學出版社出版《黑箱社會：掌控信息和金錢的數據法則》一書，對於華爾街和矽谷產業界結構性地濫用資訊優勢，因此造成的系統性風險以及政府的監理失能，提出嚴厲的批判。本次演講邀請Pasquale教授討論這本書的主要論點以及這本書出版以後相關現象的發展，並將分析Facebook個資外洩醜聞的衝擊。
（本演講為英文，問答部分將提供翻譯）
講者介紹:
Prof. Frank Pasquale (Professor of Law, Carey School of Law, University of Maryland)
As an expert on the law of artificial intelligence, algorithms, and machine learning, Prof. Pasquale frequently presents on the ethical, legal, and social implications of information technology for attorneys, physicians, and government officials. Prof. Pasquale has advised business and government leaders in the health care, internet, and finance industries, including the U.S. Department of Health and Human Services, the U.S. House Judiciary and Energy & Commerce Committees, the Senate Banking Committee, the Federal Trade Commission, and directorates-general of the European Commission. He has also advised officials in Canada and the United Kingdom on law & technology policy.
演講介紹：
Frank Pasquale教授的演講將探討以演算法為基礎的自動化決策系統，應用於社會生活各面向後，可能產生諸多風險。在大數據時代中，人們每天在實體與虛擬世界的一舉一動，都被精細的紀錄，並且透過高效能的計算機演算，用以預測人們未來的行動。然而在享受大數據時代的便利與經濟效益時，被精細觀察和記錄的人們，卻少有反思：是哪些私人機構或哪些人，在蒐集、運算、散播人們的個人資訊，並預測人們的行動？本該限制私人機構濫用個人資訊，以獲取不當經濟競爭優勢的政府監理機制，是否稱職地守護市場競爭公平性與個人隱私權；抑或是成為管制俘虜（regulatory capture）？
Pasquale教授於2015年由哈佛出版社出<黑箱社會：掌控信息和金錢的數據法則>一書，對於華爾街和矽谷產業界結構性地濫用資訊優勢，因此造成的系統性風險以及政府的監理失能，提出嚴厲的批判，在全球法律與社會學界，享有極高聲譽。Pasquale教授認為私人機構濫用資訊優勢與政府監理失能的根源在於： 現有法律對行政監理的限制（例如：言論自由、營業秘密），以及高度複雜的演算法本身，對公眾而言，欠缺透明性。在本次演講中，Pasquale教授將詳細分析不透明的演算規則對於人民在名譽、線上搜尋與財產等層面的巨大影響與風險，並希望與台灣學界以及公眾一起討論如何透過強化資訊蒐集者的資訊揭露義務，以完善問責機制、並預防系統性風險。Pasquale教授也將進一步分析Facebook個資外洩醜聞的衝擊。本次演講將可對台灣政府與公民監督提供可資借鏡之處。
Every day, corporations are connecting the dots about our behaviors—silently scrutinizing clues left behind by our work habits and Internet use. The data compiled and portraits created are incredibly detailed, to the point of being invasive. However, who connects the dots about what firms are doing with this information? What is the role of the government, directly or indirectly, coordinating with those firms behind the scene? In his notable book, The Black Box Society: The Secret Algorithms That Control Money and Information (Harvard University Press, 2015), Prof. Pasquale argues forcefully that we all need to empower ourselves and to set limits on how big data affects our lives. In this speech, Prof. Pasquale will explain how and why black boxes exist, by giving us a tour of how computational intelligence has come to dominate three essential parts of our life: reputation, search, and finance, and the alternatives for the regulators.
Prof. Pasquale will reveal how powerful interests for the alliance of the government and private firms to abuse opacity and secrecy for-profit and explain ways to rein them in. Demanding transparency is only the first step. An intelligible society would further assure that crucial decisions of most essential firms involving people are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others. After gripping the dangers of runaway data and black box algorithms comprehensively, Prof. Pasquale proposes pragmatic reforms to improve the information economy, freedom and equality.
Since its publication in 2015, the firms of social media, search engine, and financial institutions have never slowed down to collect, process, and disseminate the data to maximize their interests. The failure of the regulating regime to address the secret and opaque algorithms not only infringes the right to privacy and freedom of speech but jeopardize the foundation stone of democracy. Prof. Pasquale, in this speech, will further analyze the leak of Facebook-Cambridge Analytica data scandal.
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