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Whether we like it or not, the age of big data is upon us. Since 2012, it is estimated that data collection has been growing at a rate of 50% per year, and it shows no signs of slowing down.
This is a problem for records managers. As is, there are nearly too many records to realistically deal with. If something is not done, soon records managers will find themselves overwhelmed and overworked.
We shouldn’t despair though, because there are many options being explored to solve this crisis. Some of these methods include fuzzy sets logic, deep learning, and machine learning. All of these are different forms of artificial intelligence, and each helps automate a different process. The only problem is, it’s not records managers who are doing the exploring. Nearly all the progress and discussion in this field is being made by software engineers and computer scientists.
Initially, this might not be seen as a problem. Of course, those are the people at the head of the field; they are the experts. Artificial intelligence as a solution to managing big data is of course going to come from computer scientists, right? Sure, but the problem isn’t that records managers aren’t pushing the boundaries, it’s that they seemingly aren’t interested in them at all.
But why is this the case? Surely for their own interests, records managers would be concerned with the direction of their own field. The topic of automation of the profession was most popular during the late 1980’s and early 1990’s. With all the advances in artificial intelligence and automation since that point, this seems out of place. So why then is the modern discourse lacking?
Perhaps they feel the market is not ready for automation of records management. As recently as 2015, it appears as if companies were still reluctant to adopt artificial intelligence into managing their records. The technology is available, but is likely too expensive and not accurate enough at this point in time. So records managers believed it wasn’t worth investing time in because employers didn’t see themselves using it.
But as the technology used in machine learning becomes more refined, the price of these systems will come down. Not only that, but at the same time their effectiveness will climb. Once developers reach the point where machine learning is both cheap and effective, it will see mainstream integration; the systems will keep improving as long as technology does, in general. This means that it is not a matter of if these systems will be implemented, but when.
Records managers seem to lack the technical skills and knowledge to deal with artificial intelligence in their field. The solution to this problem will likely arise from a dedicated computational archival science. This program should allow future records managers to make the most of automation in their job.
Artificial intelligence is constantly becoming more effective and cost efficient. Experts are predicting that soon we won’t be coding machines, but teaching them. And it doesn’t matter if records managers approve of this idea, it will be moving forward with or without them. And this is the real danger.
Automation in some form will be coming to the profession of records management at some point. It is inevitable. It is important for records managers to have a say in how it comes to be, because it is their job that will be most effected by it. They cannot resist it any longer. History is full of examples of people resisting automation in the workforce, and the workers always lose.
But records managers should not fear being replaced, or at least not fear it more than anyone else. Actual people will still be needed to act as records managers, because machines are not going to replace people entirely anytime soon. Rather, artificial intelligence will be a tool used to make managing records easier. Records managers and machines will compliment one another, advancing the field further.
For example, machine learning could aid data integration and analytics, which is useful for data already being managed. But there will always be a new flow of incoming data. Records managers will need to be present to distinguish new forms of data and how they should be managed. Automation can organize data already stored, which frees the records manager to focus on newly created incoming data.
The rate of data collection is trending upwards and shows no signs of stopping. This means there will be even more demand for skilled records managers familiar with handling big data. Those who have the skills and knowledge to traverse the big data world will flourish. Those who don’t will likely fall behind.
Automation will only be as useful as records managers allow it to be. By ignoring it entirely, they run the risk of development without their input. Computer scientists cannot read minds, and if we want to take advantage of the tools they offer us, communication is key. Artificial intelligence might seem daunting, but its purpose is first and foremost to aid; no profession stays the same forever. trending, records managers need all the help they can get.