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Reasonably Accurate 馃馃 Transcript
Morning, everybody. This is one of the worst signs of the late Canadian fall. The reason being, this means winter is very much coming. This is the frost on the uh vehicle window comes off easy enough, but it means there's a good chance that snow is coming. And in fact, that's absolutely what's going to be happening.
Uh Most likely today, if not today, later this weekend. And you know, there are signals like this all the time. Um You've probably seen over the last few days uh in the mornings with mark videos, you know, all the leaves falling down, obviously, that's a huge indicator of fall.
This is a more concrete one of winter than fall. Um And I read a very similar um sort of article highlighting a signal um this morning from the Wall Street Journal and it was a signal where big banks and financial institutions are shifting to be more um around data brokerage um and data brokerage offering up custom data sets uh to their customers.
Um And it was interesting because, you know, traditionally, uh banks have done this for trading customers. Um and they have, you know, set up, hey based on these economic indicators is this, that, and the other thing, um, you know, and that's, that's understandable, that's a reasonable way for people to be making money.
Um, and to offer as a service. But, uh, where we're starting to see is that, that's shifting and that's a sort of a signal of a larger shift in the industry where people are very much now. Um, you know, seeing that data is a huge resource. And in fact, there was a great quote in this Wall Street Journal article where um one of the folks uh they had interviewed said, you know, data is oil and we're a massive refinery or a refinery ready to roll.
Um And I think that's going to happen more and more. Now, the interesting point in the Wall Street Journal article was there was actually um some concern for harvesting personal information because they're aggregating data from all these different sources. And they wanted to make sure that they weren't touching personal information because they've seen the backlash towards social media um companies for collecting privacy information.
And that's a really good sign and that's showing some internal restraint that's recognizing the risk. But of course, financial institutions are generally pretty decent at recognizing risk, whether they then act appropriately is really the question. Um But there's an entire uh layer of companies that are called data broke.
And what they do is they pull as many data sets as they can they correlate them, they normalize them and then they push that information out. A lot of the social media giants are consumers of that. A lot of political campaigns and parties consume that information and they are selling this information left right and center because it's valuable.
Now, the problem is is that there's very little regulation in certain jurisdictions around that type of activity. There's very little accountability and there's very little awareness from us from the users knowing where our information is going. This is really a tricky thing. I was talking to a friend about a project around data and a lot of things popped up that I don't think people actually examine or look at.
So we were talking about how you could trace sort of the genealogy of a piece of data, how you could tell at what point it was touched to was accessing it and what you were adding to it, what you were taking away from it, how you were correlating it.
Because at the end result, if you come up with the answer to a question based on a huge data set, if you don't know where that data comes from, how do you know that? That's a valid response to that question, right? And we see that a lot with machine learning where data is key, right?
Machine learning models are a dime a dozen. It's the quality of the data you put into it. But you also need to understand the history of that data, the limitations around that data's use. And we really need to be a lot more granular with these controls, a lot more granular with the awareness and perhaps some regulation in the broader community so that people can't just harvest data from anywhere and everywhere.
There's a lot of questions here. The me like the frosted windows, the article in the Wall Street Journal was sort of one more signal in an increasing river of signals that are saying this is going to be the major issue in the next 5 to 10 years is data brokerages, data sets available for sale, compiling cross referencing these data sets and the impact is going to have on us our communities and our companies.
There's big thoughts for Friday, but you know, I looked out the window at this and uh it's coming. So I thought, you know, why not roll that into something for a topic for today? What do you think about data brokerages? What do you think about compiling data sets?
How do you handle them on your own? Um Let me know, hit me up online at Mark NC A for those of you in the vlogs in the comments down below as always by email me at Mark N dot ca. I hope this is not your reality this morning.
I hope you are somewhere warm and sunny and are set up for a fantastic day. I'll talk to you online and, uh, on the show on Monday, enjoy the weekend.
