AI Needs Data to Function Properly

Often, people hear the term AI or artificial intelligence and think the service or system was able to reach the point of success as AI all on its own. However, what people do not really know is that in order to have functional AI, the program needs a vastly significant amount of data to use. Many experts are starting to believe that AI needs data more than data needs AI.

This belief essentially shatters the idea that AI is the answer to all tech issues. We have seen AI have several successes, with ChatGPT being incredibly successful and autonomous cars becoming more commonly produced and seen. However, in order to truly be effective, AI needs a lot more work to be done than simply developing the service. The data collection is essential to all forms of AI.

To break it down, it can be simply compared to human intelligence.

Humans virtually never innately know things. In some way, shape, or form, humans have to be taught in order to have an idea on different parts of life. AI works this way as well. It does not innately know all of the answers to the world, unless it has been programmed with the necessary data. For example, for AI programs that generate text, it needs to have data involving words, grammar, sentence structure, and more implemented into the programing. Without this key database, the AI would not be able to generate any text, as it would have no basis to build upon.

A strong data management foundation is key to AI production.

When viewing the relationship between data and AI, it can get a little complicated. AI needs data in order to thrive but data does not need AI. Data has been collected, analyzed, and recorded for centuries without the use of AI; AI has never existed without data.

For those looking to create or use AI, you must prepare data.

In order to prepare data, there are additional systems that can be built to hold the data and even analyze it. The best method for data collection for AI services and systems can be described as back-office modernization. The data has to be dependable and trustworthy in order for the AI to be accurate. It is easiest to find reliable data with data that is tracked from its creation and processing. This starts in the “middle” and “back” offices of data collection.

The back office can be described as a data factory. It is the thing responsible for collecting, verifying, analyzing, and distributing data. Having a strong back office data management system means that the work done at the front of the office, the AI, will be reliable.

Sometimes, data and AI are in a catch-22 relationship.

AI is extremely helpful in sifting through data, but it needs data in order to do that. This means that in the current stage of AI development that is happening in the world, there is still a lot of work that needs to be done. Even once it seems all the data necessary for an AI system has been collected, odds are there is still more needed, and it will need to be updated. Parts of life change daily. Words used, jobs done, etc. all change constantly. This means AI systems will need constant data updates in order to remain aware of changes occurring.