The sources of data for artificial intelligence include the Internet, external data feeds, employee feedback, and company sales and transaction systems, providing both qualitative and quantitative data for diverse applications.
The sources of data for artificial intelligence are diverse and can come from a variety of origins. These sources include:
- Internet: An extensive source of data, the internet provides a vast amount of unstructured and structured information from websites, social media, and other online platforms.
- External data feeds: These can comprise of data from other organizations, APIs, and services that provide real-time or historical data that can be used to inform AI models.
- Employee feedback: Valuable qualitative data can be collected through in-depth interviews, focus groups, or surveys among employees.
- Company sales and transaction systems: This is a source of quantitative data, such as company performance, customer transactions, sales patterns, and so on, which can be crucial for predictive analytics and other AI applications.
AI systems can also leverage both qualitative and quantitative data, incorporating findings from ethical considerations, industry applications such as self-driving cars and virtual butlers, and adopting recommendations like diversifying the engineering core and creating ethics certification for designers. When seeking sources, start with academic databases and follow through with more specific inquiries to locate data relevant to the AI topic in question.