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There’s a huge gap between data science and subject matter experts (SMEs). While data scientists play a huge role in developing algorithms and methods, SMEs also play an important role in making crucial decisions about the machines through the leverage of information. We live in a world surrounded by data with only a fraction of it actually being used. That gap between SMEs and the data they need can easily be solved through access to machine learning software. It’s time to allow more people across the organization, who don't always have the technical know-how, to access the data to make informed decisions.
If we can democratize AI to be more easily accessible to an organization, we can start to close that gap and allow all Subject Matter Experts (SMEs) and citizen data science users to optimize AI within their practice.
What is democratization?
Democratization has a simple definition. It’s the act of making something easily accessible to everyone. Right now, AI is still quite specialized, but if we can open its availability to entire organizations across entire industries, there’s no question that the opportunities will be endless. Imagine being able to leverage a data engineer’s specific skills and brainpower, with the addition of AI and machine learning, to expand their research further and save measurable time in the process. One way of doing this is by enabling data specialists and SMEs to incorporate Automated Machine Learning (AutoML) into their work.
How can AutoML positively impact the work of subject matter experts?
With traditional machine learning (ML), there is more time-consuming manual labor, such as formulating data, analyzing algorithms, and performing other tasks required prior to the point that the actual ML can be used. By automating these processes with AutoML technologies, subject matter experts can optimize their time more efficiently.
Time and effort that would have been spent by data technicians, engineers, and other SMEs on utilizing traditional ML and depending on AI-specialized data scientists can now be used elsewhere.
What does the future of AI look like from an SME’s point of view?
We’re seeing steps taken that are getting us closer to officially recognizing AI democratization. Creating AutoML powered platforms that allow SMEs, including data engineers, to review, analyze and make decisions as if they themselves are the specialized data scientists, is a huge step to getting there. Data users can use AutoML without the need for specialized training or education, all the while being given resources and learning material that will provide them with a basic background and further knowledge about AI and its uses. All of these changes are a far cry from where we were even a few years ago, which proves that the democratization of AI is already here.
AutoML platforms allow enterprises to gain access to all the data they need on a larger scale.
Interested in learning how SORBA is using AI and ML solutions to allow enterprises to effectively analyze their data?
