How AI is transforming Modern Data Governance
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A clip from Atlan's October 2023 masterclass with Forrester. Austin Kronz, Atlan's Director of Data Strategy, raises the garbage-in, garbage-out risk of reaching for an LLM by default. Raluca Alexandru, Analyst at Forrester, argues that AI projects surface risks teams had not considered, which brings governance and knowing where data comes from to the front.
Speakers
Austin KronzDirector of Data StrategyAtlan · Host- Raluca AlexandruAnalystForrester
Full transcriptSearchable
Austin Kronz
0:00 Well, it wouldn't be a future of the governance conversation if we didn't talk about AI a little bit. So I wanna break it down just like you did in your slides. A question first about just AI in organizations, and then I wanna talk about AI within data governance. So within organizations, it, it kind of seems like we're at this inflection point for the first time where there almost is this trust that, oh, there's probably an LLM that can do that, or I'm sure there's a way we could apply machine learning to this use case, right? And I think it's great in some respects, but it also amplifies the whole garbage in, garbage out.
0:33 So do you think AI can be a catalyst to maybe help data governance teams communicate the importance of, like, we don't we need to understand our data better before we can pursue these AI initiatives?
Raluca Alexandru
0:47 So let me put it like this. I don't think AI's gonna solve everybody's problems, as a lot of people hope. You know, there's must be a model that will help me solve this problem or get out of this situation, so I don't think that's gonna happen. But I, I do think that AI's gonna be a catalyst for underlying, well, the, the, the importance of data and the trust in data that we have, because now I think there's a lot of new questions popping up on, oh, are we actually doing this right? Because when I...
1:12 If looking at the risks of investing or starting up an AI applications within the organization will surface some of the possible risks that people didn't really think about it now, until now, or they will sort of make things real in terms of what are the consequences of me using some of my data to, to fit into a model, not be sure, the uncertainty of what's gonna come out of it, or how is that gonna be used for or against the organization in that sense. So there's a lot of fear of the unknown, I would say, not necessarily all rational fears around the applications.
1:45 Some of my colleagues just recently published at Forrester some interesting insights around the security and privacy questions around AI, and I think that fits in quite a, quite well into the governing AI type of conversation, right? That's one of the major fears that people out there have when they engage in this, in these initiatives. But it's definitely a catalyst to what I said, to bring forward the importance of a data governance program and having your right processes in place and building trust and being able to, yeah, to account for where your data comes from, what it means, and what it actually influences.
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