紐時賞析／AI時代的資訊科學該怎麼教？

How Do You Teach Computer Science in the AI Era?

AI時代的資訊科學該怎麼教？

Carnegie Mellon University has a well-earned reputation as one of the nation’s top schools for computer science. Its graduates go on to work at big tech companies, startups and research labs worldwide.

卡內基美隆大學是美國電腦科學院校的佼佼者，遠近馳名，畢業生投入全球各地大型科技企業、新創公司及研究機構。

Still, for all its past success, the department’s faculty is planning a retreat this summer to rethink what the school should be teaching to adapt to the rapid advancement of generative artificial intelligence.

即便過去成就斐然，該系的教職員仍計畫今年夏天舉行共識營，思考學校授課內容以適應生成式人工智慧的快速進展。

The technology has “really shaken computer science education,” said Thomas Cortina, a professor and an associate dean of the university’s undergraduate programs.

該校電腦科學學院教授兼本科課程副院長科締納說，AI科技「確實震撼了資訊科學教育」。

Computer science, more than any other field of study, is being challenged by generative AI.

與其他研究領域相比，資訊科學正受到生成式AI的挑戰。

The AI technology behind chatbots such as ChatGPT, which can write essays and answer questions with humanlike fluency, is making inroads across academia. But AI is coming fastest and most forcefully to computer science, which emphasizes writing code, the language of computers.

像ChatGPT這類聊天機器人背後的AI科技，正在學術界開疆闢土，它們能像人類一樣流利地撰寫論文與回答問題。但是AI正以最快、最有力之姿進入資訊科學領域，而該領域又強調編寫程式碼，也就是電腦的語言。

Big tech companies and startups have introduced AI assistants that can generate code and are rapidly becoming more capable. And in January, Mark Zuckerberg, Meta’s CEO, predicted that AI technology would effectively match the performance of a midlevel software engineer sometime this year.

大型科技企業與新創公司紛紛推出能產生程式碼的AI助手，並能快速提升能力。今年一月，Meta執行長兼共同創辦人祖克柏預測，AI科技將在今年某個時間點與中級軟體工程師的表現相當。

Computer science programs at universities across the country are now scrambling to understand the implications of the technological transformation, grappling with what to keep teaching in the AI era. Ideas range from less emphasis on mastering programming languages to focusing on hybrid courses designed to inject computing into every profession, as educators ponder what the tech jobs of the future will look like in an AI economy.

如今全美大學中的資訊科技學程忙著理解科技轉型的影響，苦思AI時代該保留哪些授課內容。教育工作者思考著在AI經濟時代，未來的科技工作樣貌為何，並提出各式想法，從減少要求學生對程式語言的掌握，到設計將運算注入各行各業的混合課程。

Heightening the sense of urgency is a tech job market that has tightened in recent years. Computer science graduates are finding that job offers, once plentiful, are often scarce. Tech companies are relying more on AI for some aspects of coding, eliminating some entry-level work.

隨著科技就業市場在近年的緊縮，更加劇這股緊迫感。資訊科學畢業生發現曾經充足的工作機會如今變得稀少。科技企業在部分編碼已愈來愈依賴AI，並減少入門工作機會。

The National Science Foundation is funding a program, Level Up AI, to bring together university and community college educators and researchers to move toward a shared vision of the essentials of AI education. The 18-month project, run by the Computing Research Association, a research and education nonprofit, in partnership with New Mexico State University, is organizing conferences and round tables and producing white papers to share resources and best practices.

美國國家科學基金會正資助一項名為「AI升級」的計畫，彙集大學與社區學院的教育工作者和研究人員，探討AI教育必要的共同願景。計畫為期18個月，由非營利的研究與教育組織電腦研究協會與新墨西哥州立大學合作經營，透過組織各式會議與圓桌論壇、發布白皮書，分享資源並精進實務經驗。

文／Steve Lohr　譯／江昱蓁