Datafication is the process of turning information, procedures, and systems into data that can be recorded, saved, analyzed, and processed. This process is important in the context of artificial intelligence (AI), as AI algorithms and models largely rely on vast amounts of high-quality data to train and make judgments. AI systems can get more precise and efficient as more data becomes available.
Additionally, Datafication gives AI systems the ability to process enormous amounts of data in real-time and allows them to forecast and decide much more quickly than they could previously. On the other hand, as data is produced and collected at an increasing rate, there are worries about privacy and security as well as the possibility of bias in AI systems if the data used to train them is not diverse and representative.
In conclusion, datafication has a significant impact on artificial intelligence (AI) by supplying the data needed to train AI systems, enabling real-time processing and predictions, but also by presenting crucial ethical and privacy concerns.
Reference:
The Concept of Datafication; Definition & Exampleshttps://policyreview.info/concepts/datafication