Alongside part one, I have a few additional predictions about the future of data. They are:
- Consumers will demand a better balance between technology, data, healthcare, and nature. Expectations of “More faster better now” will give way to an increased demand for quality over quantity with technology/data/AI. Alongside this, there will be an increased emphasis on code as craftsmanship, with broader industry adoption of apprenticeship to address talent shortages.
- Consumers will demand more opportunities be made available to them to take risks and create meaningful work for themselves and others. There will be increased public demand for safety nets to support risk taking, and increased interest in alternative financing models at the local/neighborhood level
- Consumers will demand more control of their data and the ability to profit from it. Differential privacy will gain wider industry adoption. Stronger, consumer-controlled markets for data will emerge.
- Devops-style thinking will gain increased adoption in data infrastructure, with data engineering, data science, and software engineering all moving towards shared best practices across their domains. We can expect to see increased investment in Bootstrap-style projects for data, to reduce variance without value.
- There will be a shift in thinking from “too big to fail” to “too big too succeed.” Consumers and businesses will grow increasingly wary of complex multinational giants in favor of small local businesses with more “skin in the game” in their community. Economies of scale will be replaced with economies of cooperation, as small players get better at leveraging low coordination/communication costs. Businesses that excel at working together to solve problems across decentralized, impromptu networks of stakeholders will win over monolithic providers that depend on their scale and org chart to get things done.