[英]Allen Downey：自由的未來，使用者/讀者的新定義（圖靈訪談）

Allen B. Downey是富蘭克林歐林工程學院的電腦科學副教授，曾執教於韋爾斯利學院、科爾比學院和加州大學伯克利分校。他先後獲麻省理工學院電腦科學碩士學位和加州大學伯克利分校電腦科學博士學位。Downey已出版十餘本技術書，內容涉及Java、Python、C++、概率統計等，深受專業讀者喜愛。他是自由書籍的倡導者，也是Google公司前客座科學家。他的最新Think系列書還有Think Complexity: Complexity Science and Computational Modeling、Think Python。

In Think Stats you mentioned that you are exploring new methodologies. Is that your book Think Bayes is a complement and extension to Think Stats?

Yes. The goal of Think Stats is to introduce basic statistical tools for working with real data. It is more practical than most books about mathematical statistics, and of course it takes advantage of computational tools and the simplicity of Python.

Think Bayes is the next step. The computational approach to Bayesian analysis makes it much easier to understand and work with. If you have read Think Stats, you know everything you need to know for Think Bayes.

You have a series called Think like Computer Scientists, how computer scientists’ ways of thinking differentiate from other people?

Computer scientists tend to be good at debugging, which is a thinking skill that is useful throughout engineering, science, and other disciplines. And object-oriented thinking is something I find myself applying to other kinds of knowledge. I would like to see computer science become more interdisciplinary, more connected to other fields.

And also you have a series called Think, which you write for the people who know how to program. How programmers’ ways of thinking differentiate from other people?

If you know how to program, you can use that knowledge to learn other things. When I learn something new, I find myself wanting to write programs that take the new ideas and express them in code. While I am debugging the programs, I am also clarifying my understanding, and sometimes I find new ways of thinking about the topic.

You have mentioned that “You can do a lot of exciting engineering starting in the first semester, and use that to motivate exploration in math, computation and science.” Do you think that computer science can be best ignited by interests-driven engineering education?

Yes, I think the motivation works both ways. It is more interesting to learn programming if you can apply it immediately to real-world problems. And once you learn to program it provides access to many other topics.

How do your books serve the need as textbooks? Are there any important or interesting feedbacks from your students?

Feedback is an important part of my development process. I often ask students to read a chapter and then I give them a reading quiz. If most of them pass, I know the chapter works, and I can spend class time on other topics, clarifying points of confusion, and helping students who are having trouble. If the students have a hard time with the quiz, I can go back and rewrite the chapter.

Online courses nowadays are very popular, do you think that this would be the future of education? And how online courses could best integrate with traditional way of teaching?

I think there are some kinds of learning that work well in online classes, but in my classes students have to wrestle with open-ended projects, they often work in small teams, and we meet frequently to discuss their progress, solve problems, and plan next steps. I think those things are hard to do in an online class.

Your extensive use of Wikipedia shows your confidence in credibility of it, what would you expect its role in the future?

Most references in my books are to Wikipedia. The articles on topics in computer science, math, and statistics tend to be very good. Some of them are hard for beginners to understand, so one of my goals is to provide enough material, in my book, to allow the reader to go on and read the Wikipedia article.

But the biggest reason I refer to Wikipedia it is freely available all over the world. Many readers of my books do not have access to extensive libraries, it would not do much good to refer to books they can’t get to.

In our time, the advance of science is growing faster than ever. People rely more and more on the information online, instead of traditional publications. Does it mean that traditional publication will die one day?

I hope so! The traditional publishing model made sense when books were expensive to produce and distribute. Electronic publication changes all that, but it is taking a long time to figure out what the future of publishing will look like.

As you know, iTuring has been a promoter of free books, what do you see in the future of free books? And self-publishing?

A free book is not just a book under a different license. It is really a different product, and a different relationship between authors and readers.

A free book is the root of a tree of potential adaptations, translations, and entirely new books that branch out from the original. Free books transform readers into proof-readers, editors, anthologists, correspondents, contributors, collaborators, writers and authors.

Do you intentionally use everything that is free and open in your work and in your life? For example, Arduino, Ubuntu, etc.

Absolutely. Using free software has changed my expectation of what it means to be a reader, or a user, or a consumer. When I use materials created by other people, I expect to be able to modify them, combine them, create something new, and then distribute what I’ve created.
It is often tempting to use more restrictive software, but whenever I do, I find myself trapped. I end up with something that solves 90% of the problem, but then the other 10% is impossible. So now I use free tools for almost all of my work.

As there are so many branches in computer science, how could one be sure that what one has learned today will be useful in the future?

I know a lot of people worry about this, but I don’t. When I learn something new, no matter how random, it seems like it always turns out to be useful, often in surprising ways. As long as you keep learning new things, your knowledge will never be obsolete.

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