As the world's largest consumer of information technology, the US government has driven IT R&D for over a century. So what should the Feds do next? A gaggle of tech luminaries has a few suggestions.
In Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technology (pdf) Eric Schmidt (Google), Craig Mundie (Microsoft) and assorted science, engineering and academic heavies lay out a proposal. Some high points:
- A science of social computing. Can the few successful examples of crowdsourcing be analyzed to create engineering principles for designing large-scale, human-driven, information production systems?
- Automatic extraction of information. As our computer-mediated world produces more data, the need to extract actionable information without human latency grows.
- Autonomous robots. Reduce the need for fine-grained control of automated devices by people through better visual recognition, more flexible orientation, navigation, manipulation, and interaction, and new learning algorithms for intelligent behavior.
- Data collection, storage, and management. Standards that allow different organizations to create software tools that generate, manipulate, and analyze societally important data.
- Data quality. Detecting and correcting errors or inaccuracies in the data - automatically.
- Data privacy. Access limitations, retention requirements, reducing the risk of data loss or damage.
- Data stewardship. Tracking how, where, and when data are created and modified.
- Data integrity. Ensuring that data are not corrupted either accidentally or maliciously.
- Data storage engineering. Reliability, power consumption.
- Data management. Management across multiple storage technologies and multiple hierarchies, and with replication across multiple geographic locations.
- Change. Adapting new technology (e.g., nonvolatile RAM), performance requirements, and the need to provide consistent views of data worldwide.
- Data preservation. Long term data access and preservation beyond the durations of research grants.
- Scale-out systems. Internet-scale systems could provide powerful capabilities for scientific research, for making government data available to citizens, and for national security.
- Machine learning. People don't scale. We'll be working with information generated by machines and we need machines to connect the dots.
- Cross-media information extraction. Understanding speech, images, video, and unstructured data; translating speech and text to other languages. New data-driven (i.e. more storage) approaches promise to be effective.
- Data presentation and visualization. Humans process images much faster than words or numbers - so let's get better at presenting information that way.
There's more: educational initiatives for K-12; specific verticals that need focus; and improving budgeting and accounting.
The Storage Bits take
The Fed's record on technology is good - is there another country who's done better? - and for IT it's extraordinary. A few highlights:
- 1st big customer for Herman Hollerith - who later founded a forerunner company to IBM - and his punchcard accounting machines for the 1890 census.
- Funded the world's first interactive real-time computer system (Project Whirlwind) back when all computing was batch oriented.
- Big customer for early transistors and ICs for military use.
- ARPAnet, the prototype Internet.
- Supercomputer funding that has enabled many of the Internet-scale technologies.
America's unique system of public & private tech investment has driven the world's most dynamic IT industry. But American's current enthusiasm for spending cuts and the Republican's anti-science bias threatens the investments that will power the next century of IT innovation.
The report lays out a strong rationale for investment, but will anyone on Capitol Hill listen? Watch your representative and senators to see that they do.
Comments welcome, of course.