Explore the data

Hi, Ryan. In a recent Blue Sky post, you alluded to the future of education.

Are your early thoughts around where the platform is or should be headed, If it's to remain in RStudio platform or if it should merge more into the POSIT ecosystem?

These were primarily, again, professional customers at Posi, but also some folks that just wanted to upscale on R and Python.

I don't know if it's the primary reason or maybe I've just educated everybody at this point, But, really, I'm finding that people have less of an appetite to essentially learn R from scratch when they can just ask AI like, hey.

So because of that, I don't think I've delivered my intro to R, intro to Python workshop in, like, six months.

There could be other factors, but I really do think that's AI.

Alright? So that's and I I think that's directly attributed to AI.

But in a similar vein, we've been hosting a workshop that we developed last, like, November.

We get probably three, four, five requests every single week to deliver that workshop.

I mean, you can use AI for a lot of things, but there is, like, a there is a field there that's worth, you know, people being educated and how to educate, specifically how do you use AI for data science.

So people are very, very interested right now in, like, how to best use AI for data science.

If that's something that we're very focused on and, like, how can we deliver, you know, educational content on demand and live that really pertains to that.

I can't remember if Zach had to leave or not.

Weigh it in that poll and let's ask Ryan in his last three minutes.

I mean, when you say PhD, like that could be a PhD in anything.

So I I would really just say, like, as I mentioned before, I have zero regrets for getting a PhD.

Sounds like a lot of people didn't regret theirs.

I hope that you had a fantastic time today.

It feels like there's there's a little bit of a there's a little bit of a turn in the in the path.

And I think that that sentiment is shifting a little bit.

That was that always struck me as a little bit simplistic.

So let's make sure that we let's make sure that we keep engaging good people.

One was from NOR, and one was anonymous.

What do you think about that? It's an interesting question.

Like, I I haven't found the perfect analogy for this yet, but bioinformatics is definitely disrupted.

I think that AI is important, and it can do good things, but I am not taking anybody's word for it.

I think that one of the problems or one of the and and just by the way, just so that you understand so that you understand the filter through which all of this is being said, I am I just recently realized that I am what's called a skeptical optimist about AI.

I am watching what it's doing, and I am testing what it's doing, and I am kind of drawing conclusions as I go.

So skeptical optimist if you wanna if you wanna sign up for that camp.

I mean, first off, they're using AI basically as what Google should have been doing, like, twenty years ago.

And I will it's easier for me to get to this through the kind of through the software engineering perspective because people are using AI for software creation in a couple different ways.

It's basically giving you a better answer that's that's articulated more clearly.

But researchers also come to us and are like, hey.

And we're like, okay. Well, let's back up.

What was your prompt? And, like, let's look at the code together.

And then and then come back to me and say, like, well, I understood the old version, but I don't understand the new version.

I think that computationally reproducible research is really important, and I think an essential ingredient in that is understanding.

You know, it's gonna be cool, like, in five or ten years to look back on this and and and realize we've all been using Roman numerals the whole time.

Thank you so much for joining us today.

I'm curious what human aspects are you leaning into, especially as you mentioned your skeptical optimist, and I kind of agree with that phrasing.

Yeah. I mean, so it is it's a really interesting question.

And, I mean, in my case, what does it mean to be a good researcher, or what does it mean how can you support good research?

And, I mean, in my case, what does it mean to be a good researcher, or what does it mean how can you support good research?

And AI well, I'm I'm I'm gonna share a little conversation that I had with Claude, the agent, like, not too long ago.

AI is is an interesting tool in that, like, you can come to AI with a research question, and you can just put it to AI.

Like, I was in I I sat down. I was in a meeting, and the meeting wasn't going well.

Like, I was in I I sat down. I was in a meeting, and the meeting wasn't going well.

And I said to Claude, how can you achieve computationally reproducible research results when you're using a nondeterministic tool like AI?

And so I started a conversation with Claude.

It said, well, it's harder, but there's ways to do it, but that's not really the problem.

I mean, won't that just reinforce positive overclaiming?

It said, yeah. That's a really good question.

This might get worse before it gets better, which I was like, that's such a gangster answer.

But it also was really scary. I think one of the problems that I have with AI as a kind of faux collaborator is simply that it isn't a collaborator, that it is not teaching us to be vulnerable.

I was totally unprepared for Claude to be that, like, vulnerable.

It is not teaching us to be better.

And so I feel like it's kind of, encroaching on the nature of collaborative research, which I think is built on trust, and I think trust is built on vulnerability.

Like, it's hard I mean, it does, but you have to push it really hard.

I don't know the answer to that.

So I another thing that that Libby and I talked about a little bit earlier off offline was this notion of it's called Conway's Law Conway's Law.

Right? That can be bad, and that can be good.

I'm wondering, like, is AI creating patterns that are easy for us to consume, that fit into the organizations, that are easy for us to understand and communicate to other people?

So I think if I can just the the short summary of that is I rely on people to be people, and I rely on people to remind me how to be vulnerable and to build trust and, like, to collaborate.

But I'm not getting I'm not I'm not exercising that muscle very much with AI, so I rely on people for that.

And, you know, and those people are using AI, and I don't begrudge them that.

Does that does that get at it? Okay.

I don't know. What do you think?

So the idea of AI kind of distilling that into fielded, computable information, it's not that that's not a crazy idea.

Yeah. I will say this, that sometimes we work with electronic medical records, and this is one case where I almost feel like I I I might have a I might have a little love for AI because electronic medical records are very informative, and they are impossible to work with.

Like, now there's still hallucination and slop, so you have to trust and verify.

So the idea of AI kind of distilling that into fielded, computable information, it's not that that's not a crazy idea.

But, yeah, I I could I could I could see that as helping.

But, anyway, I became, like, a AI developer.

And I got laid off last year. So great stuff to be talking about, and I've been working on my own with my own company for the past year.

We can talk about, portfolios, technical interviews.

We can also talk about layoffs.

And there is a human side. We still need that.

Everybody can do it, but it doesn't mean that you are going to succeed.

And I'd love to direct this one to Dan first to see what Dan thinks.

Gregory, are you available to unmute and ask that one live?

I'm gonna highlight it in the slide and also put it in the chat.

I don't know. I've I've used AI here and there, but I don't feel good using it when I do because, you know, read about how it affects, you know, retention and your ability to actually grow skills or debug the code that you write or write with whenever you're using AI.

There he is. Yeah. My question is, like, what are your thoughts on generative I generative AI and kind of the whole idea of, agentic workflows, and we must embrace the machine spirits and their effect on the job market.

But, yeah, that's kinda my my thoughts, feelings, question.

So we just have to kinda find a way to to deal with it.

I feel like a lot of it is, like, saving face or showing that, like, they are the AI company of the future, that, like, there's all this pressure on everyone, on every board, on every CEO to to do something with AI.

How it affects the job market? I'm a little skeptical right now that the big cuts of these companies are actually from implementation of AI at their companies saving money.

So I feel like some of that is just, like, saving face on that.

I was talking to a friend at Amazon, and he was telling a development cycle that just yesterday, had a long chat, and I was asking him a lot of questions about what changed.

So change is there. Organizations are adapting to change.

And on the software engineering side, you know, agentic framework is going to be the future, especially for, you know, things that are not mission critical.

Having said so, for noncritical mission, AI is becoming a lot more of a productivity boosters, and there are some companies that are adopting it pretty fast.

Like, if I have a machine learning algorithm serving on the live to millions of customers, certainly not going to depend on AI to build a model for me and then, you know, show that model to our users.

It's real. It's here. And moving and training about how to build an agent is going to be a skill set that all of us need to build on.

So more productive. And, but, again, I'm very skeptical, in the I have a lot of opinions about this.

I feel like even though we don't agree sometimes, we have to follow.