Tag: AI

AI is everywhere. I can’t seem to get away from stories on the technology in 2023, and while I don’t know that I’ve found it that helpful, I keep looking at it because it’s becoming a pervasive technology that most enterprises will experiment with in some way. There is a look at generative AI in the Enterprise in the O’Reilly Radar, which tracks how technology is changing and influencing the world.

The report talks about most of the respondents to a survey using AI, which makes sense as the people responding likely have some interest in the technology. I always take these trends with a grain of salt as people who are busy and not interested might not respond. Only a small percentage of uninterested people will actually answer these things.

As I look at the numbers with that in mind, I find it interesting that about half of the users think AI will lead to greater productivity and a small number (4%) think this means less headcount. However, only a minority (41%) have been using this for over a year. That likely means in most cases that people are experimenting like I am. This isn’t a pervasive technology in the enterprise, though I’d argue that while DevOps might be in use in most enterprises, I wonder if it’s in use in most projects at most enterprises. Culture change is hard for most people and I still meet lots of people who aren’t trying to get better at building software.

The big challenge in many companies is finding appropriate business cases. I think that’s my struggle as well, in trying to think about how to use AI to write or build code, I struggle to think of how to prompt or what to prompt. Often by the time I define the problem, I can just write the code. If I were scaffolding out basic classes or tables, maybe I’d feel differently, but as our CTO put it, we spend most of our time figuring out the problem, not writing the code. There are legal concerns, but those are from a minority of respondents. I have a meeting with our legal department soon, which will help me iron out some of my concerns and get guidance.

Interestingly, 77% of people are using AI in programming, with about half of those using it for work. I don’t know if we’ve done a good job understanding the IP/copyright issues here, so that’s surprising. I would guess in many organizations that don’t sell software, they don’t care about this at all. If they get code from an AI that was copied from somewhere else, if it works, who cares?

I find that much of the code generated isn’t great. It’s junior developer level, which might not matter to many organizations. After all, they employ junior developers, and some employ senior developers with 6 months of experience 10-20 times over who write that level of code. If the AI does it faster, all the better.

I think AI is a technology that is going to impact our lives as technical and data professionals. Whether you use it to write code or use it as a glorified search engine, it’s a tool that you want to understand and develop some skill with. Writing prompts and learning how to navigate an AI system is helpful. If it actually gives you something useful, even better. And if you learn more about building models and prompt engineering, you might find yourself with some interested opportunities in the future as I expect those jobs to grow in number across the next few years.

Steve Jones

Listen to the podcast at Libsyn, Spotify, or iTunes.

I ran across an article on the best AI meeting assistants, which can help you with note-taking and summarization tasks. Most of these cost money, but there was something that struck me about these tools.

They aren’t allowed for a lot of my meetings.

At Redgate, I’m not sure if these are allowed. Our policy is to seek permission before using a tool, so I’ve sent a query off for more information. In many of my customer meetings or in Microsoft meetings, I’ve been told these tools aren’t allowed as there isn’t sufficient data security to allow their usage.

I think a lot of people are concerned about their data when these AI LLMs (large language models) are involved and if their data is being used to train future models. If it is, then that could be a security problem. Already many people and organizations are upset about their data sets being used for training without their knowledge. Not everyone agrees.

I don’t quite know how I feel about this issue, but I do think there ought to be guidelines and discussions about how data is used, and where data is stored (or where it transits a network). Certainly, organizations might need to set this in place to ensure their employees aren’t exposing confidential or internal data in ways that could increase their risk of a breach. After all, without any guidelines or rules, you may have no recourse if employees just use tools and data escapes your network.

At Redgate, we’ve begun experimenting with SQL Prompt and AI. As of now, we’ve had quite a few queries about how customer data is being used. Our EAP EULA notes that schema information will leave your network, but not data in rows. That might be a problem or might not, but it’s important to disclose that, which we’ve done.

I’d like to think that as hardware power increases and models become more mature, we’ll stop having to send data for many AI-related tasks away from a device that might perform a task. At some point, I hope your mobile phone or laptop can process the AI model without a network connection, which would be helpful for data security.

AI is here to stay, and we have to learn how to work with it, and where it works well. It feels a little like we haven’t really answered many of these questions as an industry or inside our organizations. That’s something that needs to change and quickly as the number of places AI is being used continues to rapidly increase.

Steve Jones

Listen to the podcast at Libsyn, Spotify, or iTunes.