人工智能、仪表盘与人类决策：与梅兰妮·托里对话

欢迎回到PolicyViz播客。

Welcome back to the PolicyViz podcast.

我是你们的主持人约翰·施瓦比什。

I'm your host, John Schwabish.

本周节目中，我邀请到了来自东北大学的梅兰妮·托里。

On this week's episode of the show, I am joined by Melanie Tory from Northeastern University.

我们讨论了仪表盘。

We talk about dashboards.

希望你们已经看过我关于仪表盘的帖子。

Now hopefully you've seen my post on dashboards.

如今我不太喜欢它们了。

I am not a big fan these days.

我认为，我们主要通过手机消费媒体，这意味着仪表盘和数据工具在触达更广泛受众方面正变得越来越无效。

I think the way we are consuming media mostly on our phones means that dashboards and data tools are becoming less and less useful to reach those broader audiences.

与那些有特定用途和特定受众的内部仪表盘不同，我联系梅兰妮是因为她发表了一篇非常有趣的文章，探讨了那些在工作中使用仪表盘的人实际上是如何使用它们的，或者在很多情况下根本不用它们。

Different from internal dashboards which have a specific use case and specific audience, but I reached out to Melanie because she has a really interesting paper on how people who are using dashboards internally for their work actually use them or in many cases don't use them.

所以我们首先花了大量时间讨论仪表板以及这项特定研究，还有梅兰妮对仪表板使用和创建者的看法。

So we first spent a lot of time talking about dashboards and this particular study and Melanie's perspectives on dashboard use and creators.

然后我们转向了她最近在不同情境下关于人工智能和大语言模型的研究。

And then we've transitioned to some of her work, more recent research on AI LLMs in different contexts.

我认为你会觉得这非常有趣。

And I think you're gonna find it really interesting.

她有一些有趣的初步发现，以及关于人工智能和数据可视化的不同视角，特别是在我们花了一些时间讨论的那篇论文的具体案例中。

She has some interesting early findings and different perspectives on AI and data visualization specifically and in the particular use case of the one paper that we spend a bit of time talking about.

这是一场非常有趣的对话。

Really interesting conversation.

如果你是仪表板用户、仪表板创建者，或者正在思考人工智能将如何影响你的生活、医疗保健，或者作为一名数据可视化从业者，那么这一集非常适合你。

I think you're really gonna enjoy it if you're a dashboard user, dashboard creator, if you're thinking about how AI is going to impact your life or your health care or as a data visualization practitioner, this is the episode for you.

那么我们开始吧。

So here we go.

这是我和梅兰妮·托里的对话，你只能在这里的PolicyViz播客中听到。

Here's my conversation with Melanie Tory and you only get it here on the PolicyViz podcast.

嗯，教授，您好。

Well, hello, professor.

你好。

Hello.

谢谢您邀请我参加节目。

Thanks for having me on the show.

很高兴有你来。

It's great to have you.

谢谢你来参加。

Thanks for coming on.

我们上次见面已经过去很久了。

It's been a while since I saw you last.

我都记不清了。

I don't even know.

我上次在Viz会上见过你吗？

Did I even see you at at Viz?

我当时在Viz。

I was at Viz.

我觉得我可能在那里见过你，不过。

I think I might have seen you there, but Yeah.

我在那里见到了很多人。

I saw a lot of people there.

那里人很多。

There's a lot of people.

很多人。

A lot of people.

而且有一刻，非常小的酒吧里挤满了人，

And at one point, a lot of people in a very small bar,

那是

which was

特别有趣。

which was super entertaining.

但是啊。

But yeah.

我花了好多时间，我想那是西海岸的Viz派对。

I spent a lot of time I think that was the West Coast Viz party.

我觉得组织者急着想把酒票用完，好回家或者回酒店。

I think the organizers were trying desperately to get rid of their drink tickets so they could go home, or back to the hotel.

那还挺有趣的。

So That's pretty funny.

我待了一阵子，但整个活动下来，我挺累的。

Stayed for a while, but the whole thing, I was pretty tired.

好的。

Okay.

所以你有很多工作在进行。

So you've got a lot of work going on.

有一篇你的论文，现在已经有两三年了，我特别想聊聊关于仪表板的内容。

There's one particular paper of yours that's now, you know, two, three years old that I I definitely wanna talk about about dashboards.

但为什么不先做个自我介绍呢？让那些不熟悉你或你工作的人了解一下？

But why don't we start with introductions for folks who are not familiar with you or not familiar with your work?

所以，你知道的，你目前在哪里？你的工作主要关注哪些方面？

So, you know, where are you, and and, you know, what does your work tend to focus on?

是的。

Yeah.

当然。

Sure.

我是东北大学的实践教授，隶属于鲁研究所，该研究所位于缅因州波特兰的东北大学校区。

So I'm a professor of the practice at Northeastern I'm based at the Rue Institute, which is Northeastern's campus in Portland, Maine.

东北大学实际上在各地设有多个校区，这只是其中之一。

Northeastern actually has a bunch of different campuses all over the place, so this is one of them.

我想我们或许有点不同寻常，因为我们专注于三件事。

And we're a little bit unusual, I suppose you might say, in that we focus on three things.

第一是研究。

One is research.

因此，我在这里领导一个研究团队，同时我们还开展研究生教育，并设有嵌入式的创业加速器。

So I lead a research team here, but we also have graduate education, and we have an embedded entrepreneurship accelerator.

这使得我们在大学中显得有些不同。

So that makes us a little bit different as a university.

我们的使命之一是与产业界紧密合作，推动缅因州的经济活动，助力本地科技经济的发展。

And part of our mission is to work really closely with industry and foster a bit of economic activity in the state of Maine to help grow the tech economy here.

这意味着我的团队会开展一些关于数据可视化和人机数据交互的纯理论研究。

So that means that my group does sort of pure research in data visualization and human data interaction.

但我们也会与企业合作伙伴、非营利组织等开展大量应用型项目，做一些比普通大学更贴近实际和实用的工作。

But we also do a lot of applied work with company partners, nonprofits, and so on to try to do a little bit more applied and practical things than you might get in a normal university.

这些工作主要集中在缅因州和新英格兰地区的商业社群，还是遍布各地？

And is most of that work with, the business communities that tend to be in Maine and New England, or is it just everywhere?

可能 anywhere，但我们主要聚焦于缅因州和新英格兰地区。

Could be anywhere, but we've mostly focused, yeah, Maine and New England.

是的。

Yeah.

是的。

Yeah.

好的。

Okay.

这说得通。

That makes sense.

这说得通。

That makes sense.

好的。

Okay.

所以我最初联系你，是因为我脑子里一直有个问题：制作仪表板是否值得我们花时间？

So I I reached out initially because I've had this question in my head for a while about whether dashboards are worth our time to create.

我找到了你和林·巴特拉姆等人关于仪表板用户的数据语音实践与挑战的研究。

And I found your study with Lynn Bartram and others, finding their data voice practices and challenges of dashboard users.

然后我最近在我的博客上发表了一篇文章，谈了谈我的看法：尤其是在当前的媒体环境下，我认为仪表板并没有那么有用。

And then I recently posted a blog post on my thoughts about, you know, why, especially now in our current media environment, why I don't think they're they're very useful.

所以我想深入探讨这个问题，但我想先请你简要介绍一下这项研究，让大家了解我们讨论的背景。

So I wanna dive into this, but I I wanna sort of maybe, ask you first to give folks a summary of the work so they know kinda where we're coming from.

当然可以。

Sure.

这项研究是我们对仪表板用户进行的访谈研究。

So this particular study was an interview study we did with people who are users of dashboards.

这些用户主要是组织内部使用的仪表板用户。

So these are, and and this was in particular dashboards that are internal to organizations.

我们并没有关注面向公众的仪表板，那可能会有些不同。

So this wasn't looking really at public facing dashboards, which might be a little different.

但我们很好奇，人们实际上是如何使用仪表板的？

But we were curious to know, how are people actually using dashboards in practice?

这种实际使用方式是否与可视化社区和可视化工具开发者所认为的用户使用方式一致？

And is that actual use aligned with the way that the visualization community and the visualization tool developer community is thinking that people are using dashboards?

是的。

Yeah.

当时我在Tableau软件公司工作，所以我们是一家构建仪表板的公司。

I was working at Tableau Software at the time, so we were a dashboard building company.

我们与大量构建仪表板的分析师有密切接触，因为他们是我们直接的用户。

And we had a lot of contact with analysts who build dashboards because they were our direct users.

但我们实际上对最终使用仪表板的人了解不多，因为这些人某种程度上与我们隔了一层。

But we actually didn't have much insight into the people who were ultimately using the dashboards because those were, in some ways, a hop away.

对吧？

Right?

他们是我们的客户的客户，这么说吧。

They are our customers' customers, if you will.

所以我们想知道，他们收到的仪表板是否满足了他们的需求？

And so we wanted to know, you know, are the dashboards that they get meeting their needs?

还是说我们还能做更多事情来支持这些人更好地使用数据？

Is it or is there more we could be doing to support these folks in working with data?

对。

Right.

好的。

Okay.

因此，这主要是一项定性研究，你访谈了大约二十到二十四位来自不同行业的人。

And so this was primarily a qualitative study, and you talked to was about, like, twenty, twenty four people who are in a variety of sectors.

对。

Right.

大约有二十人左右，其中大多数是仪表板的最终用户。

It was 20 ish people and rough the majority were dashboard end users.

我想二十人中大概有七位是构建仪表板的分析师，因为我们还想了解分析师认为自己可以做些什么来帮助用户更有效地使用数据。

I think maybe seven of the 20 were analysts who were building dashboards because we also wanted the perspective of the what did analysts think that they could be doing to help their users, be more effective?

对吧？

Right?

因此，是的，这项研究覆盖了多个行业和多种工具。

And so, yeah, it was across variety of sectors, across a variety of tools.

我们并没有将范围限定在Tableau上。

We didn't limit it to Tableau.

我们对任何类型的仪表板都感兴趣。

We were interested in dashboards of any kind.

无论是Power BI、Tableau还是自定义开发的仪表板，从最终用户的角度来看，它们的功能大体相似，因此并不重要。

Dashboards, whether they're Power BI or Tableau or custom built, largely all kind of function the same from the end user's point of view anyway, so it didn't matter.

是的。

Yeah.

而且，我们也很好奇哪些做法有效、哪些无效，以及这些仪表板是否如我们所想的那样被使用。

And, yeah, we were curious to know what works, what doesn't, and are they being used the way we think they are.

所以我想给你一个机会谈谈哪些有效、哪些无效，最终的结论是什么。

So I wanna I wanna give you a chance to talk about what works and what doesn't, what the bottom line was.

但我发现一个有趣的现象：Tableau，但我猜这对许多仪表板公司来说都类似，而且不仅仅是Tableau和Power BI，即使用户只隔了两步，这仍然不是重点——我的意思是，我猜市场团队或许会关注这一点，但我觉得这很有趣，因为用户仍然必须点击。

But I do find it striking that Tableau but I I I'm guessing this is similar for lots of dashboarding companies and, you know, beyond Tableau and Power BI that, like, even though the user is two steps away, that that's still not a focus of the I mean, I'm I'm guessing, like, the marketing team sort of focus on it, but, like, I just find that fascinating that, like, The U like, people still have to click.

复选框有用吗？

Like, does the checkbox work?

下拉菜单有用吗？

Does the drop down work?

我不确定这是否算个真正的问题，但我觉得挺有意思的是，公司并没有把这当作重点。

Like, I'm not sure I have a real question here for you, but, like, I just find it fascinating that that was not a focus of the of the company.

公司。

Company.

是的。

Yeah.

我同意你的看法。

I'm with you on that.

这让我也感到惊讶。

It was surprising to me too.

对。

Yeah.

但某种程度上这也能理解，因为真正深度使用产品的是那些用桌面版来制作仪表板的分析师，我们可以假设他们了解最终用户的需求。

But in some ways, it makes sense because the people who are deeply using the product are the analysts using the desktop product to build the dashboards, and we can kind of assume that they know what their end users' needs are.

对。

Right.

因此，他们也是一个更难接触到的群体。

And so the they're also a harder population to reach.

对吧？

Right?

当然。

For sure.

我们数据库里的所有人都是分析师、数据管理员等等，没错。

We have all of the people who were in the database are all the analysts and the data admins and so on and Right.

而不是最终用户。

Not the end users.

对。

Right.

对。

Right.

对。

Right.

对。

Right.

是的。

Yeah.

这完全说得通。

That that totally makes sense.

而他们才是购买产品的人。

And they're and they're the ones that are paying for the product.

所以对。

So Right.

我明白了。

I get it.

这只是说真的。

It's just a yeah.

总之。

Anyway.

好的。

Okay.

那么这里的重点是什么？

So what's the bottom line here?

你们都发现了什么？

What did what did you all find?

有趣的是，我们发现仪表板并没有像商业圈所有人预期的那样被使用。

Well, what was super interesting was we kinda found that dashboards weren't being used the way that everybody in the biz community thought they were.

对吧？

Right?

我们都以为用户会去仪表板上寻找并回答自己的问题。

We all kind of thought you the user will go to the dashboard and answer their questions.

而仪表板的设计者，他们的职责就是设计出能回答所有用户问题的仪表板。

And the dashboard, you know, the dashboard designer, that's their role is to design the dashboard so that all the users' questions can be answered.

因此，我们普遍的心理模型是：用户访问仪表板，找到答案，任务就完成了。

And so we the prevailing mental model was user goes to the dashboard, answers their question, all is done.

是的

Mhmm.

但我们真正发现的是，仪表板更像是进入数据的入口。

But what we really found out is that it was almost like the dashboard was the portal to the data.

也就是说，那是用户开始的地方。

Like, that was the place that the user started.

他们去那里获取数据，然后对数据做他们需要做的任何事情。

They go there, get their data, and then they do whatever they need to do with it.

有些问题他们可以直接在那里回答。

And there's some questions they can just answer there.

这很好。

That's great.

但还有很多其他事情，人们想做的，而仪表板只是起点。

But there were a whole bunch of other things that people wanted to do that the dashboard was just the starting place.

我的意思是，你认为那些将这些仪表板用于内部工作的人，和使用更公开仪表板的人之间，存在根本性的区别吗？

I mean, so do you think that there's a fundamental difference between these folks who are using these for their internal work purposes and a a more public dashboard?

我就随便选一个吧，因为它能给我们一个具体的参考。

And I'm just gonna pick one just because it gives us a grounding.

经合组织有一个更好的生活指数。

So the OECD had this better life index.

这是专门定制的。

It was a custom build.

做得非常漂亮。

It was a beautiful thing.

你知道，真的很酷。

You know, it's really cool.

但只是为了给我们一些思考的素材。

But just to give us, like, something to think about.

那个网站上你可以移动滑块、选择、筛选，也就是一些基本的操作。

So that was on a website where you could, you know, move sliders and you can pick and you can filter and, you know, sort of your your basic thing.

但这个工具是为公众开发的。

But that was developed for the public to use.

你认为你研究中的人们，他们的行为与访问经合组织网站的人有根本性的不同吗？

Do you think the folks in your study that their behavior is fundamentally different than someone going to the OECD website?

我认为唯一的不同在于，我们研究中的人们可能更有目的性。

I think only in that the folks in our study were kind of maybe more purpose driven.

他们必须使用这些数据来完成工作的一部分，而嗯。

Like, they had to use this data to get part of their job done, Whereas Mhmm.

对于一些访问经合组织仪表板的人来说，这可能也成立，但很多人只是出于兴趣去那里。

That might be true for some people going to that OECD dashboard, but a lot of people might be going there just out of interest.

是的。

Yeah.

而且这对他们需要交付的任务来说并不是至关重要的。

And it's it's not of critical importance to something they need to deliver on.

对。

Right.

这可能是主要的区别。

That's probably the major difference.

嗯嗯。

Mhmm.

这说得通。

That makes sense.

是的。

Yeah.

所以这些有任务的人，他们需要回答一个问题或一组问题。

So these folks who have a task, they need to answer a question or a set of questions.

他们主要将这些仪表板作为进入数据的入口。

They're primarily using these dashboards as an entry way to actually just get to the data.

对。

Do you Right.

你有没有发现，人们这样做的原因是这些仪表板设计得不好吗？

Did you find that it like, what was the reason that that's what people were doing was because the dashboards weren't designed well?

是因为，我记得有一个人在做健身房会员相关的事情。

It was because, you know, I remember there was one person that was, like, doing gym membership stuff.

所以我猜这个人并不是什么计算机科学家，也不是统计学博士。

So I'm guessing that person isn't, like, you know, like a computer scientist or, a PhD in stat.

对在健身房工作的人没有丝毫贬低的意思。

No shade on people working in gyms.

但你知道，他并不是那种深入搞数据的人。

But, you know you know, not a, you know, deep data person.

是的。

Yeah.

对。

Yeah.

我觉得我们这边的大多数人也是这样。

I think that was true of most of the people in our stuff.

对吧？

Right?

这些人呢，数据确实是他们工作的一部分，但并不是他们日常的核心任务。

These are folks who you know, data's gotta be part of their job, but it's not their day to day life.

这并不是他们工作中的全部内容。

It's not everything they do in their job.

而且在大多数情况下，他们也不是数据专家。

And for the most part, they're not data experts.

然后我们有几个人原本是数据专家，后来晋升到了领导岗位。

Then we had a couple of folks who had been data experts and then moved their way into leadership roles.

他们确实具备这些专业知识，但没有时间。

So they did have that expertise, but no time.

但大多数人都是普通人，你知道的，不是数据专家，但

But most of the people were average folks who, you know, weren't data experts, but

没错。

Right.

必须以某种方式使用数据来回答问题、为上级制作报告等等类似的事情。

Had to use the data in some way to answer questions, to build reports for their managers, etcetera, things like this.

但他们仍然主要依赖仪表板，下载数据，进行探索，或者制作所需的图表或幻灯片。

And yet they're still going to the dashboards for the most part and downloading the data and exploring it or making the graph or the slide that they need to make.

是的

Yeah.

这是一个非常普遍的主题。

That was a super common theme.

我们实际上称之为数据导出。

We called it the data dump, actually.

甚至我们的一些参与者也称其为数据导出。

And even some of our participants called it, you know, taking a data dump.

你去仪表板是因为那里是你获取数据的地方。

You go to the dashboard because that's where you get your data.

你把数据导出到Excel或其他电子表格中，然后用它来回答你的问题。

You dump the data out into Excel Excel or some other spreadsheet, and then you can answer your questions with it.

我们甚至有一些分析师告诉我们，他们构建的仪表板本质上是数据导出界面。

We even had some analysts tell us that they had built dashboards that were essentially data dump interfaces.

嗯

Mhmm.

他们甚至有点不好意思告诉我们，他们竟然用 Power BI 或 Tableau 这样的工具做出了这样的东西，因为这并不是这些工具的设计初衷。

And they were almost embarrassed to tell us that this is what they had used their tool like Power BI or Tableau to produce because that's not the intent of those tools.

但它确实满足了用户的需求。

But it it served a need for their users.

对吧？

Right?

他们的用户有一种非常简单的方式，可以无需了解任何 SQL，就能进行类似数据库查询的操作，获取数据，然后灵活地做任何他们想做的事。

Their users have this really simple way to go and do what was essentially a database query, but without having to know any SQL, get their data, and then it's flexible, and they can do whatever they want with it.

当然。

Sure.

没错。

Right.

所以他们实际上是用它来让数据对最终用户来说更熟悉、更直观，而不是为了探索分析的目的。

So they're so they're using it as a way to make the data more familiar feeling and looking for the end user, not necessarily for the purpose of exploration.

是的。

Yeah.

这其实是一堆杂七杂八的东西。

It was a real mix of things.

对吧？

Right?

比如，很多人提出了各种问题，而这个仪表板通过你期望在仪表板中看到的所有可视化元素，很好地回答了这些问题。

Like, there were a lot of questions that people had that the dashboard was designed well to answer using all the visuals that you would expect in a dashboard.

这些场景非常好。

And and those scenarios are great.

但还有一些分析性问题，仪表板的设计根本无法很好地满足。

But then there were also question analytical questions people had that the dashboard wasn't designed well to be able to meet.

因此，他们不得不采取一些别扭的变通方法，或者把数据导出，才能回答这些问题。

So that would be one reason that they would have to go through awkward workarounds or dump out the data to try to answer those questions.

还有很多使用场景并不涉及分析，而是更偏向于沟通，嗯。

And there were a whole lot of use cases that didn't involve analysis, but rather sort of communication Mhmm.

比如，他们需要有人获取当月的销售数据，然后以某种方式重新整理，提供给管理层或在整个组织内分发。

Where, for example, they would have someone would have to get the the numbers for the current month for their sales, let's say, and repackage that in some way for leadership or for distribution throughout the organization.

这可能意味着要将数据汇总到更高的层级，因为管理层不想看到所有这些详细数字。

And that might mean, you know, rolling it up to a higher level of detail because leadership doesn't wanna see all those detailed numbers.

他们只想了解整体情况。

They just want the big picture.

嗯。

Mhmm.

这可能意味着围绕这些数字讲一个故事。

It might mean sort of spinning a story around those numbers.

对吧？

Right?

比如，我不仅仅想告诉你这个月的数字是多少。

Like, I don't just wanna tell you what the number is this month.

我想分享我的看法。

I wanna tell you my take

关于是的。

on Yeah.

为什么是这样，当时发生了什么，背景是什么。

Why it is that way, what was going on, like, what's the context.

我想重新包装一下，让它看起来更美观或者更适合我的受众。

I wanna repackage it maybe, make it look prettier or make it look different for my audience.

是的。

So Mhmm.

所以他们除了回答问题之外，还在做大量的这种数据重新包装和沟通工作。

So they were doing a lot of this kind of repackaging and communication communication of of the the data data in addition to just answering questions with it.

是的。

Mhmm.

所以我想深入探讨一下这两类群体。

So I wanna dig in on just sort of these two of these groups.

一类是设计良好的仪表板，另一类是沟通方面。

On the dashboards that were well designed and then on the communication side.

因为很多人会说，一个设计糟糕的仪表板就是个差劲的仪表板。

Because I think a lot of people would say a poorly designed dashboard is therefore a bad dashboard.

但听起来，在你的研究中，即使是设计良好的仪表板也没有完全满足用户的需求。

But it sounds like, in in your study at least, it even the well designed dashboards didn't quite meet the user's needs.

所以你认为这是因为没有充分理解最终用户吗？

So do you think that is just not understanding your end user?

还是说仪表板本身并不能实现我们以为它应该实现的功能？

Is that just dashboards don't quite do what we think they are supposed to do?

你觉得这一类情况背后到底发生了什么？

Like, what do you think is going on with that group?

我认为这两种情况都有，具体取决于使用场景。

I think it's kind of both of those things depending on the use case.

是的。

Yeah.

我给你举一个例子，有一个仪表板我认为设计得并不好，

So I'll give you one example of a dashboard that I think was not well designed for Okay.

因为用户使用它的目的和仪表板的设计不匹配。

The purpose that the end user was using it for.

这个用户在一家电信公司工作，需要获取每月的数据，也就是我之前提到的那种使用场景。

So this one, this one user worked at a telecom company and had to get monthly numbers, kind of the use case I was talking about before.

因此，她使用的仪表板被设计为显示某个月份的所有数据。

And so the dashboard that she was using was designed to give all of the numbers for a given month.

她可以进入后设置一系列筛选条件，比如选择‘我想看一月份的数据’，然后就能看到所有需要的数据。

So she could go in, set a bunch of filters, set it to like, I want to see the numbers for January, and she's got all the numbers there she needs.

但她真正需要为领导做报告的是将当月与上月进行对比，并展示差异。

But what she really needed to do for her report to leadership was to compare the current month to last month and show the difference.

而这个特定的仪表板一次只能显示某一个月的快照数据。

And this particular dashboard would only show you the snapshot of one month at a time.

因此，她不得不进行一套非常繁琐的操作：先加载一月份的数据，设置筛选条件，然后手动把所有数字记在笔记本上或另一个电子表格中。

So she had to go through this really super awkward workflow of loading up January, set that filter, write down all the numbers either in a notebook or in a separate spreadsheet manually.

天哪。

Wow.

然后把筛选条件改为二月，再记下所有数字，最后手动计算差值。

Change the filter to February, write down all those numbers, and then compute the difference.

而这是一个非常简单的事情，如果仪表板的设计者知道它会被用于这种对比用途，本可以设计成直接进行这种比较，从而节省她大量的工作。

And that's a a really simple thing that the dashboard could have been designed to make that direct comparison, saving her tons and tons of work had the dashboard designer known that it would be used for that comparative use case.

所以我认为，这至少是仪表板设计者的一个失误，他们没有充分理解这个仪表板的所有用户以及所有可能的使用方式。

So that I think is a case of failure on the dashboard designer's part, at least to understand who are all of the users of this dashboard and what are all of the ways of use.

对。

Right.

而且，你认为这一点也适用于那些需要创建其他类型产品的人，比如叙事性报告、简报手册或幻灯片吗？

And and do you think that also applies to the users who needed to create some sort of other product, more of the narrative storytelling briefing books slide deck?

比如，如果A是仪表板的设计者，他们知道B到Q这些人都要从仪表板中制作PowerPoint幻灯片的话。

Like, I guess if person a is the dashboard designer and they know that, you know, person persons b through q have to make PowerPoint slides out of the dashboard.

我觉得你会设计出一种能促进这种最终用途的仪表板。

I feel like you would build that dashboard in a way to facilitate that end use.

不过，也许也不一定。

Also, maybe not.

我认为在某种程度上确实如此，也许他们本可以在这方面做得更好一些。

I think that that's true to some extent that that maybe they could have been able to do that a little bit more.

但我还认为，当前的仪表板工具在支持最终用户真正想要的灵活使用方式上存在不足。

But I also think that this is a place where our current dashboard tools just fail to support the kinds of flexible use that the end users would really like to have.

嗯哼。

Mhmm.

对吧？

Right?

比如，如果你能直接进入仪表板，作为最终用户，无需进入复杂的编辑模式，也不用了解构建仪表板的工具的内部机制，就能直接把柱状图改成饼图，因为这才是你希望看到的方式，那该多好？

Like, wouldn't it be nice if you could go into your dashboard and as an end user, without having to go into some kind of deep edit mode and understand all of the inner workings of the tool that built the dashboard, could you just, like, change the encoding of a bar chart into a pie chart because that's how you wanna see it?

是的。

Yeah.

或者，你能否更改配色方案，使其符合你对最终用户的审美需求？

Or could you change the color scheme to make it what you think is beautiful for your end users?

或者，你能否筛选部分内容或进行汇总？

Or could you filter out parts or do roll ups?

比如，还有很多其他操作，比如添加注释、围绕数据讲述故事。

Like, there's a lot of or add annotations, add story around it.

如果他们能拥有更多这种灵活的混合功能，这些人就能在仪表板工具中完成更多工作，而无需失败后转回手动流程。

Like, if they had more of this flexible sort of mash it up functionality to them, then these folks would have been able to do a lot of more of that work in the dashboarding tool without having to sort of fail out and go back to a more manual process Yeah.

比如在 Excel 或 PowerPoint 或其他工具中。

In Excel or PowerPoint or whatever else.

对。

Right.

所以，关于这篇论文，我想问你的最后一个问题是，这个问题稍微超出了研究范围，因为你的研究聚焦于内部使用场景。

So the last question on this paper I wanted to ask you is a little beyond the study because your study was focusing on internal use cases.

但这项工作是否让你对面向外部用途的仪表板有了更多思考？

But did the work lead you to have more thoughts about dashboards for external purposes?

比如回到经合组织，或者像 Tableau Public 这样的平台。

So we could go back to the OECD or just like Tableau Public.

对吧？

Right?

或者别的什么。

Or or whatever.

比如，这有没有让你对人们一般如何使用仪表板产生一些想法或见解？

Like, did it give you any thoughts or insight on how you think people are using dashboards sort of generally speaking?

我认为这即使我们研究的是骨髓群体，也反映了仪表板的普遍使用情况。

I think it probably speaks to dashboard use in general even though we studied the bone marrow population.

我怀疑仪表板适用于一组固定的功能。

My suspicion is that dashboards are useful for a fixed set of functions that they they support.

对吧？

Right?

它们擅长向广泛受众分发信息。

They're good at distributing information to a wide audience.

嗯。

Mhmm.

它们适合作为权威信息源。

They're good at being a sort of source of truth.

对吧？

Right?

它们记录了数据在当前时刻或过去历史中的状态。

They document the state of the data at the current time or perhaps through past history.

对吧？

Right?

它们在信息传播这类功能上表现不错。

They're good at those sort of circulation of information functions.

嗯。

Mhmm.

它们并不一定是进行数据探索的好工具，尤其无法回答设计者未曾想到的新问题。

They're not necessarily great tools for data exploration, certainly not for answering novel questions that the designer didn't think of.

对，嗯。

And Mhmm.

设计者很可能无法预见到所有用户可能想通过仪表板回答的问题。

That designer is probably not going to think of all of the possible questions that someone might wanna answer with their dashboard.

对。

Right.

所以这正是仪表盘工作方式的一个特性。

And so that's just it's sort of a it's a property of the way dashboards work.

是的。

Yeah.

它们有点僵化，只擅长处理一小部分特定任务，而其他许多事情则根本做不了或做得不好。

They're a little bit inflexible and fixed to a small set of things that they do well and a bunch of other things that they just don't do or don't do well.

是的。

Yeah.

我的帖子中提到的一个观点是，如今超过一半的人，尤其是全球范围内，甚至在美国，主要通过手机访问互联网。

I mean, one of the points that I made in my post was that, you know, more than half of people now, especially globally, but even in The United States are are primarily using their mobile phone for their Internet access.

我不确定仪表盘是否适用于移动设备，我甚至不敢肯定。

And I'm just not sure that dashboards I'm not even saying I'm not sure.

仪表盘在手机上根本用不了。

Dashboards just don't work on mobile phones.

对吧？

Right?

就像，它们太小了，无法完成所有的筛选、搜索和下拉操作。

Like, that's just not they're just too small to do all the filtering and searching and drop down stuff like that.

而且我在想，我们稍后会谈谈人工智能，因为你知道，现在我们得聊聊人工智能。

And I I wonder if you think and we'll we'll talk about AI in a second because, you know, we've gotta talk about AI these days.

但我好奇，你是否认为数据和媒体消费方式的改变，应该影响我们如何为公众设计仪表板？

But I I wonder if you think that the way in which consumption of data and media is changing changes how we should be thinking about creating dashboards in this public for this public use.

是的。

Yeah.

正如我所说，我认为仪表板有其存在的价值。

I like I said, I think dashboards serve their purpose.

嗯。

Mhmm.

但我们不该假设它们能满足所有人对数据的需求。

But we shouldn't assume that they're gonna meet all needs of people with data.

人们会有更多样化、更有趣的问题，而这些是仪表板无法应对的。

Like, people are way more flexible and interesting questions that we can't anticipate, and a dashboard can't handle that.

对。

Right.

是的。

Yeah.

好的。

Okay.

非常有趣。

Really interesting.

我敢肯定，现在有很多仪表板创作者正在对我们大喊大叫，挥舞着拳头。

I'm sure there's a lot of dashboard creators who are yelling at us right now and shaking their fist.

所以我们稍后会听到他们的意见。

So we'll we'll hear from them later on.

我想聊聊你最近的一些新工作。

I wanna turn to some of the the newer work that you're doing.

你有两篇非常不同的论文，我想问问你。

You've got kinda like two very different papers I wanted to ask you about.

一个是心脏界面，我觉得它有个缩写。

One is the heart interface, which I think has an abbreviation.

是的。

Yes.

人工智能实时赋能医疗保健。

Health care enabled by AI in real time.

所以这将引导我们谈到接下来的几个不同方面。

So this is gonna get us to a number of different things at at one point.

那我们从这里开始好吗？

So why don't we start there?

这个项目是和谁合作的？它主要关注什么？

Who is that project with, and and what is that project focusing on?

对。

Yeah.

这是我自从来到东北大学以来一直在参与的一个大型合作项目。

That's a really big collaborative project I've been working on since I started here at Northeastern.

这个项目是我们鲁研究所与当地医院缅因健康机构，以及医疗科技公司Nehaan Coden Digital Health Solutions之间的合作。

It's a collaboration between us here at the Rue Institute and a a local hospital, Maine Health, as well as a health care technology company, Nehaan Coden Digital Health Solutions.

这个项目最初的想法是，我们或许能够提升重症监护环境中的患者护理，特别是心脏胸外科重症监护室，所有接受过开胸手术的患者都会在这里康复。

And this project started with the idea that we might be able to enhance patient care in intensive care settings, particular the cardiothoracic ICU, where all patients go to recover after they've had open heart surgery.

嗯。

Mhmm.

我们的想法是，人工智能是否有可能通过提前预测患者病情是否恶化并走向不良结局，来帮助医护团队更好地照护这些患者？

And the idea was, could is it possible that an AI would be able to help the care team better care for these patients by predicting ahead of time if they were going downhill and heading for some adverse outcome?

我们能否在人类察觉之前就提前预测到？

Could we predict that ahead of time before the humans could have?

嗯。

Mhmm.

让人类医护人员提前知晓，这样他们或许能更早介入，从而帮助一些患者避免严重的不良后果。

Let the humans know, and then maybe they might be able to intervene earlier and, and save some of these patients from pretty nasty outcomes.

对。

Right.

所以这个项目的核心是，你知道的，我根本不是AI开发者。

And so this project was all about, you know, I'm not an AI developer at all.

我没法构建这种预测性AI。

I couldn't build this kind of predictive AI.

但幸运的是，我有一些非常优秀的同事可以做到。

But, fortunately, I have great colleagues who can.

所以我们的想法是构建一个AI预测器，并围绕它设计一个界面。

And so the idea was to build an AI predictor, build an interface around that.

这是我的团队的职责，最终将它部署在ICU中，并通过临床试验进行测试——我们还没做到这一步，但最终目标是验证人类加上AI是否比单独的人类能取得更有效的结果。

That was my team's job, that could then be ultimately deployed in the ICU and tested through a clinical trial, which we haven't got to yet, but that's ultimately the goal, to see if humans plus an AI could have more effective outcomes than humans alone.

很有趣。

Interesting.

所以这是在对患者的实时医疗或健康数据进行预测性分析吗？

And so this is doing predictive analytics on the real time, I guess, health care or health information from the patient?

没错。

Exactly.