这是一个很难回答的问题，因为在那之后，除了硬件的改进之外，几乎没有什么东西是具有重大积极意义的发明。虽然在20世纪80年代之前，有许多重大的发明只影响人们，但现在，因为它们在当时是不可行的。

见鬼。血统

移动电话。

第一个“无线手机”专利诞生于1908年，并且酝酿了很长一段时间(0G于1945年，1G于1979年在日本推出)，而现代2G数字手机直到1991年才出现。1993年才出现短信，1999年才出现互联网接入。

光学计算。似乎它应该存在更长的时间，但我目前找不到任何早于1982年的参考资料(相关技术，光学晶体管，直到1986年才出现)。

更好的用户界面。

今天的用户界面仍然很糟糕。我指的不是小的方面，而是大的、基本的方面。我不禁注意到，即使是最好的程序也仍然有一些接口，这些接口要么极其复杂，要么需要以其他方式进行大量的抽象思考，而且无法达到传统的非软件工具的易用性。

诚然，这是由于软件可以比传统工具做更多的事情。但这不是接受现状的理由。此外，大多数软件都做得不好。

In general, applications still lack a certain “just works” feeling are too much oriented by what can be done, rather than what should be done. One point that has been raised time and again, and that is still not solved, is the point of saving. Applications crash, destroying hours of work. I have the habit of pressing Ctrl+S every few seconds (of course, this no longer works in web applications). Why do I have to do this? It's mind-numbingly stupid. This is clearly a task for automation. Of course, the application also has to save a diff for every modification I make (basically an infinite undo list) in case I make an error.

解决这个问题其实并不难。在每个应用程序中都很难实现它，因为没有好的API可以做到这一点。编程工具和库必须显著改进，才能在所有平台和程序上轻松实现这些工作，适用于所有具有任意备份存储且不需要用户交互的文件格式。但在我们最终开始编写“好的”应用程序而不仅仅是足够的应用程序之前，这是必要的一步。

I believe that Apple currently approximates the “just works” feeling best in some regards. Take for example their newest version of iPhoto which features a face recognition that automatically groups photos by people appearing in them. That is a classical task that the user does not want to do manually and doesn't understand why the computer doesn't do it automatically. And even iPhoto is still a very long way from a good UI, since said feature still requires ultimate confirmation by the user (for each photo!), since the face recognition engine isn't perfect.

不确定1980年的情况，但人工智能社区几十年来一直是一个创意生成器，他们仍然在做。

我认为自20世纪80年代以来发明的最好的想法将是我们不知道的。要么是因为它们很小，无处不在，以至于不引人注意，要么是因为它们的受欢迎程度还没有真正起飞。

前者的一个例子是单击并拖动以选择文本的一部分。我相信这是1984年首次出现在麦金塔电脑上。在此之前，您有单独的按钮用于选择选择的开始和结束。相当繁重。

后者的一个例子是(可能是)可视化编程语言。我不是说像hypercard，我是说像Max/MSP, Prograph, Quartz Composer, yahoo pipes等。目前它们确实是小众的，但我认为，除了思想分享之外，没有什么能阻止它们像标准编程语言一样具有表现力和强大的功能。

可视化编程语言有效地加强了引用透明性的函数式编程范式。这对于代码来说是一个非常有用的属性。他们执行这一点的方式也不是人为的——这只是由于他们使用的比喻。

VPL让那些本来不会编程的人也能编程，比如有语言障碍的人，比如阅读困难的人，甚至只是需要简单节省时间的门外汉。专业程序员可能会对此嗤之以鼻，但就我个人而言，我认为如果编程成为一种真正无处不在的技能，就像识字一样，那就太好了。

就目前来看，VPL只是一个小众的兴趣，还没有真正成为主流。

我们应该做些什么不同的事情

all computer science majors should be required to double major- coupling the CS major with one of the humanities. Painting, literature, design, psychology, history, english, whatever. A lot of the problem is that the industry is populated with people that have a really narrow and unimaginative understanding of the world, and therefore can't begin to imagine a computer working any significantly differently than it already does. (if it helps, you can imagine that I'm talking about someone other than you, the person reading this.) Mathematics is great, but in the end it's just a tool for achieving. we need experts who understand the nature of creativity, who also understand technology.

But even if we have them, there needs to be an environment where there's a possibility that doing something new would be worth the risk. It's 100 times more likely that anything truly new gets rejected out of hand, rather viciously. (the newton is an example of this). so we need a much higher tolerance for failure. We should not be afraid to try an idea which has failed in the past. We should not fully reject our own failures- and we should learn to recognize when we have failed. We should not see failure as a bad thing, and so we shouldn't lie to ourselves or to others about it. We should just get used to it, because it is just about the only constant in this ever changing industry. Post mortems are useful in this regard.

One of the more interesting things, about smalltalk, I think, was not the language itself, but the process that was used to arrive at the design of smalltalk. The iterative design process, going through many many revisions- But also very carefully and critically identifying the flaws of the existing system, and finding solutions in the next one. The more perspectives, and the broader the perspectives we have on the situation, the better we can judge where the mistakes and problems are. So don't just study computer science. Study as many other academic subjects as you can get yourself to be interested in.