"Big data is valuable because it delivers evidence of how humans live. And we can use that evidence to make better decisions, write policies with better outcomes, and design more useful products and services. This evidence-based future relies on a nascent ecosystem of technologies which will expand alongside the science we use to make it all work in real time. Tools for data collection are a fundamental component, but processing all of the data is even more critical. Big data cannot be made useful without the application of artificial intelligence, but we also need improved bandwidth and compute processing power. On the social side, we have questions of privacy to work out. If all of our actions are collected as points of data, and if the purpose of the data collection is to make accurate predictions, what does that mean for individuals? Solutions, like differential privacy and federated learning, for example, offer some ideas for technological ways in which collective patterns can be established while protecting individuals. A final key component to success with big data is the concept of symmetrical knowledge. The goal is to design a system where the benefits are shared, allowing two-way transparency, so that we better understand ourselves as a collective, while also having a view on how the data is being collected and used, and holding data collectors accountable (Kelly, 2020)."