The Disconnect Between Biden’s Popular Policies and His Unpopularity 拜登政策受歡迎但很難轉化為支持度

2021年12月23日星期四

The Disconnect Between Biden’s Popular Policies and His Unpopularity 拜登政策受歡迎但很難轉化為支持度

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The Disconnect Between Biden's Popular Policies and His Unpopularity 拜登政策受歡迎但很難轉化為支持度
Can a Machine Learn Morality? 機器能夠學習道德嗎？

The Disconnect Between Biden's Popular Policies and His Unpopularity 拜登政策受歡迎但很難轉化為支持度
文/Nate Cohn
譯/陳韋廷拜登政策受歡迎但很難轉化為支持度 Over the past few years, many Democrats argued that there was a simple secret to electoral success: enact popular legislation. 過去幾年，許多民主黨人認為想要選舉成功有一個簡單的秘訣，即制定受歡迎的法案。 President Joe Biden tried to make that theory a reality. He enacted a big stimulus plan, a bipartisan infrastructure bill and has made progress toward pushing through an ambitious $2 trillion spending bill that has finally passed the House. 美國總統拜登試圖讓這一理論成為現實。他制定一項大規模經濟刺激計畫，一項兩黨都支持的基礎設施法案，並在推動一項雄心勃勃2兆美元支出法案上取得了進展，該法案最終在眾議院通過。 But so far, popular policies haven't made for a popular president. His approval ratings have slipped into the mid-40s, even though virtually all of his legislation commands majority support in the same surveys. In poll after poll, voters seem to give Biden no credit for his agenda. They say he hasn't accomplished much. They even say he hasn't helped them personally, even though he sent direct stimulus payments to most households and even more to parents. 但到目前為止，受歡迎的政策還未造就受歡迎的總統。他的支持率已下滑至四十多趴，即便他的所有立法在同樣調查中幾乎都獲得多數支持。在一次又一次的民調中，選民似乎沒有因拜登的政策而給他功勞。他們說他沒有取得多大成就，甚至說他沒有親自幫助他們，即便他向大多數家庭甚至是更多父母直接發放了經濟振興紓困金。 If anything, voters say he's made things worse. 其實，還有選民說他讓事情變更糟。 The disconnect between Biden's popular policies and his personal unpopularity is a little hard to understand. After all, voters do care about the issues. They've proved it by gradually sorting into ideologically divided parties over the past two decades. And it's clear that presidents can be punished for advancing an unpopular agenda. Just ask Barack Obama about the period after the Affordable Care Act was passed. 拜登受歡迎的政策和個人不受歡迎之間的脫節，有點讓人難理解。畢竟，選民確實關心這些問題。過去20年，他們逐漸劃分意識形態分裂的政黨，就證明這一點。很明顯，總統可能會因為推動不受歡迎的政策而遭懲罰。只要問問歐巴馬有關「可負擔健保法」通過後那段時期的情況就知道了。 But if voters often punish a president for pushing unpopular policies, they rarely seem to reward a president for enacting legislation. Instead, voters seem to reward presidents for presiding over peace and prosperity — in a word, normalcy. 如果選民經常懲罰一個推動不受歡迎政策的總統，他們似乎很少會因為總統制定法案而予以獎勵。相對的，選民似乎會獎勵總統帶來和平與繁榮，換句話說，帶來常態。 Today, Biden is not seen as presiding over the long-promised return to normalcy. Maybe that will change in the months ahead. But Biden's policy agenda is not expected to do much to help his approval rating so long as Americans do not believe that agenda responds to the most immediate issues facing the country. 目前，人們認為拜登並未帶領大家重返承諾已久的常態。也許情況在未來幾個月會改變。但是，只要美國人不認為拜登政策回應了國家面臨的最急迫問題，他的政策就不會對他的支持率有太大幫助。 The predominance of the economy in American public opinion is one of those basic and seemingly obvious findings of political science that is still somewhat hard to fully internalize. That's partly because it's at odds with how most individual voters — and especially politically engaged voters — think about politics. Most people back their party through the worst economic times; even the fastest economic growth wouldn't persuade them to back the president of the other party. 經濟在美國公眾輿論的主宰地位，是政治科學中基本且看似明顯的發現之一，但仍然有點難以讓人完全接納，部分是因為這跟多數個別選民對政治的看法不一致，尤其是積極參與政治的選民。大多數人在經濟最糟糕時期仍支持他們的政黨，即便是最快速的經濟成長，也無法說服他們支持另一個黨的總統。

Can a Machine Learn Morality? 機器能夠學習道德嗎？
文/Cade Metz
譯/陳韋廷機器能夠學習道德嗎？ Researchers at an artificial intelligence lab in Seattle called the Allen Institute for AI unveiled new technology last month that was designed to make moral judgments. They called it Delphi, after the religious oracle consulted by the ancient Greeks. Anyone could visit the Delphi website and ask for an ethical decree. 上個月，位於西雅圖的人工智慧實驗室艾倫人工智慧研究所研究人員，發表了設計用來做出道德判斷的新技術。他們以古希臘人諮詢的宗教神諭將它命名德爾菲。任何人都能造訪德爾菲的網站，詢問道德法令。 Joseph Austerweil, a psychologist at the University of Wisconsin-Madison, tested the technology using a few simple scenarios. When he asked if he should kill one person to save another, Delphi said he shouldn't. When he asked if it was right to kill one person to save 100 others, it said he should. Then he asked if he should kill one person to save 101 others. This time, Delphi said he should not. 麥迪遜威斯康辛大學心理學家奧斯特衛爾使用幾個簡單的場景測試這項技術。當他詢問，他是否應該殺一個人去救另一人時，德爾菲說他不應該。當他問為了救一百個人而殺死一個人是否正確時，德爾菲說他應該做，然後他又問道，他是否應該殺死一個人來救101個人，德爾菲這次則說他不應該這樣做。 Morality, it seems, is as knotty for a machine as it is for humans. 看來，機器與人類同樣都對道德問題感到傷腦筋。 Delphi, which has received more than 3 million visits over the past few weeks, is an effort to address what some see as a major problem in modern AI systems: They can be as flawed as the people who create them. 過去幾周被300多萬人次造訪的德爾菲是個艱難嘗試，為了處理被一些人認為是現代人工智慧系統的主要問題：它們可能跟創造它們的人一樣有缺陷。 Facial recognition systems and digital assistants show bias against women and people of color. Social networks like Facebook and Twitter fail to control hate speech, despite wide deployment of artificial intelligence. Algorithms used by courts, parole offices and police departments make parole and sentencing recommendations that can seem arbitrary. 臉部辨識系統與數位助理顯現出對女性及有色人種的偏見。儘管人工智慧被廣泛應用，但臉書與推特這樣的社群網路卻無法控制仇恨言論。法院、假釋辦公室與警察部門使用的演算法，提出的假釋和量刑建議可能看起來很武斷。 A growing number of computer scientists and ethicists are working to address those issues. And the creators of Delphi hope to build an ethical framework that could be installed in any online service, robot or vehicle. 愈來愈多電腦科學家與倫理學家致力解決這些問題。德爾菲的創造者希望建立一個道德框架，可安裝在任何線上服務、機器人或車上。 "It's a first step toward making AI systems more ethically informed, socially aware and culturally inclusive," said Yejin Choi, the Allen Institute researcher and University of Washington computer science professor who led the project. 領導該計畫的艾倫研究所研究員、華盛頓大學電腦科學教授崔藝珍（音譯）說：「這是讓人工智慧系統更具道德意識、社會意識與文化包容性的第一步。」 Delphi is by turns fascinating, frustrating and disturbing. It is also a reminder that the morality of any technological creation is a product of those who have built it. The question is: Who gets to teach ethics to the world's machines? AI researchers? Product managers? Mark Zuckerberg? Trained philosophers and psychologists? Government regulators? 德爾菲時而令人著迷，時而令人沮喪，時而令人不安。這也提醒我們，任何技術創造的道德都是創造者的產物。問題在於，誰來教授世界上的機器道德？人工智慧研究人員？產品經理？祖克柏？受訓過的哲學家和心理學家？政府監管部門？ While some technologists applauded Choi and her team for exploring an important and thorny area of technological research, others argued that the very idea of a moral machine is nonsense. 雖然一些技術人員稱讚崔藝珍及其團隊探索了一個重要而棘手的技術研究領域，但其他人認為，道德機器的想法本身就是無稽之談。

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