One of the biggest challenges to deploying and scaling artificial intelligence is ensuring the data being used to train AI algorithms is accurate and timely. Using bad data hampers an organization’s ability to predict future trends and make meaningful business decisions.
Only when high-quality datasets drive AI algorithms can businesses gain valuable information and insight that can help them make critical decisions that could improve customer experience, brand loyalty, supply chain flow and more.
At its core, an accurate dataset provides a representative sample of the population. Given that 97% of the population owns some type of mobile device and 85% have smartphones, location data is well-positioned to provide an accurate accounting of the activities of a given population, especially when used to complement other data sources.
Location data can be used to gather insight into many different parts of a business, such as in-store foot traffic, consumer shopping behaviors or supply chain performance. The insights derived from location data can provide businesses with up-to-date, real-world context of how their customers interact with their company in the physical world.
In addition, businesses can utilize these insights to enable trendspotting and data-driven support for everything from monitoring their supply chain operations to determining the location of their next store. Ensuring that these algorithms are not biased based on the datasets used to train them is of utmost importance, not just for the accuracy of the results but for the business’s reputation.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/10/13/the-importance-of-evaluating-datasets-for-ai-development/?sh=57420cfb128d
Only when high-quality datasets drive AI algorithms can businesses gain valuable information and insight that can help them make critical decisions that could improve customer experience, brand loyalty, supply chain flow and more.
At its core, an accurate dataset provides a representative sample of the population. Given that 97% of the population owns some type of mobile device and 85% have smartphones, location data is well-positioned to provide an accurate accounting of the activities of a given population, especially when used to complement other data sources.
Location data can be used to gather insight into many different parts of a business, such as in-store foot traffic, consumer shopping behaviors or supply chain performance. The insights derived from location data can provide businesses with up-to-date, real-world context of how their customers interact with their company in the physical world.
In addition, businesses can utilize these insights to enable trendspotting and data-driven support for everything from monitoring their supply chain operations to determining the location of their next store. Ensuring that these algorithms are not biased based on the datasets used to train them is of utmost importance, not just for the accuracy of the results but for the business’s reputation.
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/10/13/the-importance-of-evaluating-datasets-for-ai-development/?sh=57420cfb128d
