This is a time of reflection–for more reasons than one. I am writing this piece in the eleventh week of ‘working from home’ which has rapidly become the ‘new normal’. But even without the Covid-19 pandemic I would have been writing an editorial for Machine Learning at this point in time–albeit perhaps not in my back garden! After having had the privilege to serve the international machine learning community as Editor-in-Chief of the Machine Learning journal since July 2010, it is now the moment for me to step down and hand over the reigns. The previous decades have seen tremendous change in the practice and perception of machine learning research, accelerating in the last ten years in particular. When I started out as a young researcher the question whether computers could learn or think was confined to nerdy newsnet groups. Today, the Turing test might make an appearance as a plot device in mainstream movies, and machine learning and AI are seen as key technologies and even marketing narratives. Clearly, the research landscape has changed considerably. The question I want to consider here is: how do we as machine learning researchers respond to these changes?

中文翻译：

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对互惠研究的思考

这是一个反思的时间——原因不止一个。我正在“在家工作”的第十一周写这篇文章，这已迅速成为“新常态”。但即使没有 Covid-19 大流行，此时我也会为机器学习写一篇社论——尽管可能不在我的后花园！自 2010 年 7 月以来，我有幸担任机器学习杂志的主编，为国际机器学习社区服务，现在是我卸任并交出统治权的时候了。在过去的几十年里，机器学习研究的实践和认知发生了巨大的变化，特别是在过去十年中加速了。当我还是一名年轻的研究员时，计算机是否可以学习或思考的问题仅限于书呆子新闻网组。今天，图灵测试可能会在主流电影中作为情节设备出现，机器学习和人工智能被视为关键技术甚至营销叙事。显然，研究领域已经发生了很大变化。我想在这里考虑的问题是：作为机器学习研究人员，我们如何应对这些变化？