It is essential to have access to data when training artificial intelligence systems. The reason for this is that products and services are rapidly moving from pattern recognition and insight generation to more sophisticated forecasting techniques and, therefore, making better decisions. [...] Making more data available and improving how it is used is also essential to addressing societal, climate, and environmental challenges. This will contribute to healthier, more prosperous, and more sustainable societies. ‘(European Commission, 2020:2-3’) This brief report was commissioned to highlight the importance of data for AI, and how unavailability and lack of accessibility to relevant sources negatively impact the development of AI applications. AI is currently being used to accelerate progress in vital health, agriculture, finance, and transport fields. The right data sources are crucial for AI to continue to develop evenly across all regions and areas. There are, however, still data gaps, and where data is available, it can be difficult to access and/or is of poor quality.
It is possible to learn machine learning concepts from big data because we have enough data. Using both structured and unstructured data, we can create more sophisticated algorithms for advanced AI training and machine learning. Algorithms can understand the patterns in the data they're working with, by using both structured and unstructured data.
Whenever one is doing research on this topic, one will need to understand that challenges related to the availability, accessibility, and quality of data have far-reaching consequences, and some can replicate or even exacerbate current inequalities. It is imperative to note that there are several initiatives working to solve these problems. When developing guidelines for implementing effective data governance practices, it is imperative to consider all stages of the data lifecycle and the AI development process. This is significant because it can mitigate and solve many of the issues companies face when it comes to cyber threats within their organizations. To realize the positive impact AI can have across a variety of fields and to ensure that communities and individuals are not harmed by its use, it is essential to have access to good-quality data for AI development.
