Digital innovation: from “tech problems” to “redesigning governance”
This is the fifth in a series of articles stemming from the National Academy of Public Administration’s Standing Panel on Technology Leadership as part of its Call to Action on Responsibly Using AI to Benefit Public Service at all Levels of Government. Please see our first blog, "A Call to Action: The Future of Artificial Intelligence and Public Service" second blog, "Artificial Intelligence and Public Service: Key New Challenges," third blog "Making Government AI-Ready Begins with an AI-Ready Workforce," and fourth blog Artificial Intelligence and Public Service: Key New Challenges."
In this age, progress depends on three fundamentals:
- Information technologies: developing tools to capture, store, analyze, and communicate data.
- Value chain applications: using data to coordinate larger and more complex systems of interaction.
- Governance: managing interactions to improve a group’s productivity, equity, and trust in authority.
At first, the Information Age focused on simple tasks like accounting and other record keeping. Then, as we used more data, we coordinated larger and more complex interactions, influencing customers as well as workers, for example. Quite recently we created far better digital substitutes for human skills and jobs. Such substitutions can be disruptive, even dangerous. The new challenge isn’t simply to make computers that people will use, it’s to use them for making and managing a better-governed world.
What’s different now and what should we do about it?
Information Age fundamentals are still about technologies, applications, and governance. But important things have recently and seriously changed.
As a result, we must move in the aggregate beyond “technology problems.” While those problems remain, we must, in addition, use digital power for responsible governance in an often more turbulent and conflicted world.
Let’s look briefly at the key trends, next steps, and examples calling for analysis, experimentation, and action.
- Digital technologies—to disruptive new power requiring multi-jurisdictional public sector invention, investment, and regulation. We use computing to understand the expected outcomes and uncertainties of systems and actions. Fortunately, under Moore’s Law, processor productivity (instructions/$) has been doubling every two years. Indexed at “1” in 1970, productivity grew roughly 1 million times bigger by 2010 (40 years = 20 doublings = 220). Far more important, it will rise to 1 billion (230) by 2030.
Let’s use a transportation analogy. If a dollar produced an inch of travel in 1970, Moore’s Law growth will produce a billion inches by 2030. That would be roughly 17,000 miles, or 5.7 trips from Boston to LA. Note: 97% of that will be from miles/$ growth AFTER 2020.
Compared to 1970, computers had become a million times more powerful in 2010, but they were still largely for numeric calculations and sorting text. Only a decade later, however, they were analyzing incredibly complex patterns in oceans of digitized Chess game movements, digitized sound (voice recognition), digitized video (picture identification), digitized vehicle control, digitized genes, and digitized almost anything.
A variety of serious recent predictions—by Oxford University, McKinsey, and other organizations—suggest that, because of this new power, as many as half of all current jobs will be automated enough by 2030 to require the job holders to find new work.
This has major implications, especially for the role of the public sector.
After early computing was funded by governments (for defense, space exploration, health care, etc.), the private sector stepped in by the late 1970s for profit-oriented investments, largely in digital marketing and customer services. Now, given new threats from a rapidly changing, digitally interoperable world, we need new government involvement. In protecting information accuracy, security, privacy, stability, etc., it has become extremely dangerous for a group or society to fall behind. To keep up, we need to rebuild the public sector role in digital invention, early investments, and standards. Success will require collaboration at scale with responsible other governments and the private sector.
Some examples for technology invention, investment, and collaboration could include:
- Low-cost, bottom-up, natural language systems. How about AI-based personalized conversations with children and the elderly? Both groups need support for active listening and responding. And, for these and other groups, reaching many individuals this way could be extremely valuable. Large language model AI is just getting started.
- Evidence-based analysis for government clients and the public. How about standardized, always-accessible data analysis to help citizens, as individuals or groups, gain accurate information about public and private services (Yelp on steroids)? How about systems to help them with obligations like their taxes? How about moderated, non-partisan, public/private collaboration to manage market spillovers and imperfections as they grow more dangerous?
- Disciplined engagement of stakeholder groups in evaluating government budgets. While ideas like this emerged decades ago, what can be done with the more powerful digital capabilities available today? Can we engage more stakeholders while making evaluations more fact-based, civil, and disciplined? (People often worry about slow and uninformed democratic procedures.)
- Value chains—to continued integration for larger, cross-boundary communities of interaction. Digital communications improve coordination largely by expanding specialization, scale, and transparency. New value chains can then be larger, quicker, more accurate, more accessible, more innovative. Thanks importantly to the internet, value chains have grown from simple internal tasks to processes that cross the boundaries of currently independent institutions, industries, and jurisdictions. The next phase of digital investment will focus more on the higher risks and returns of cross-boundary integration.
Examples for cross-boundary value chains could include:
- Improving coordination: For public service communities (multi-jurisdictional health care, multi-modal local transportation); industries (medical specialties, business education for specific regions); and jurisdictions (urban areas of less than 250,000 residents, areas requiring changes in land use due to changes in the climate, etc.).
- Restraining abuses of power: By making it easier for competitors from afar to enter an industry; by evaluating monopoly-oriented investments (using analytic teams that include consumer and labor experts); etc.
- Governance—to focus on goals considered unreachable until recently. To handle what’s coming, groups and societies need the three major governance goals of productivity, equity, and public trust. On the productivity front, U.S. performance has improved x%/year since 1970, with digital capabilities often cited as the major contributor. That improvement has been important, but it falls disturbingly short of the growth rate prior to 1970.
Even more disturbing have been trends with equity and public trust. In 1970, CEO incomes were 20 times larger than those of their average employees; by 2020 they were 260 times larger. In 1970, 82% of the U.S. population said that leaders made the right choices “most of the time;” by 2020, such optimism had fallen to 14%.
To turn these dangerous trends around, we need to use our best tools. But we haven’t been doing that. By and large, while digital innovation has made progress with productivity, it has basically been ignored for distributional equity and/or public trust in governance.
Now, however, with dangerous long-term trends combining with recent explosions in digital power, we need to reassess and rebuild how democratic environments support transformational change. What can we do to improve how technologists, institutional leaders, and the public work to facilitate and control society-wide innovation?
Examples for transformational innovation could include:
- For Collect, analyze, and disseminate data and recommendations that can usefully and safely become public. Prioritize low-cost services that can improve through digital learning rather than high-cost services that wait for “trickle down.” Think of public rather than private swimming pools, and public parks rather than country clubs. Think of digital rather than hard-copy textbooks, and of the infrastructure needed to make digital information accessible to all.
- For public trust. Provide low-cost and personalized digital public services, along with the transparency and accountability needed to make institutions and leaders accountable. If we publicize the performance of the coaches (and athletes) of high school, college, and professional teams, how about serious data analysis and evaluations in other settings?
- For social harmony. Gather, analyze, and disseminate information on the public dimensions of problems such as technology displacement, widespread uses of misinformation, privacy violations, system failures, etc. Given the importance of safety nets for smoothing job transitions, how about giving them priority for digital analysis, experimentation, and improvement?
What’s needed: awareness and action for an onrushing and very new digital future.
In the Information Age so far, we have done some amazing things. While early computers were so expensive that only a handful were expected to be sold, exponential cost-cutting has pushed us to virtually live on screens. Early on, we developed specialists and industries for “technology problems” requiring work mostly on the inside of existing institutions. The successful innovation today, however, is much bigger and very different than simply getting the computers to work.
Exponential digital innovation has been sustained for more than 50 years. But only quite recently has it led to hugely more powerful computers, larger and more complex “cross-boundary” value chains, and the threat of far more jobs being displaced. The digital leading edge has become transformational and disruptive.
In this “everything is digital” world, even survival is at stake. To develop the essential new relationships and communities we need, we must revaluate and redesign how groups and societies are governed. Success will depend far more on avoiding disaster than gaining perfection.
Our challenge is certainly more than a “technology problem.” As this brief argument has emphasized, we will need sustained and well-informed engagement and support, not only from the technology community, but also—on an urgent, important, and sustained basis—from senior leaders and the public.
This is our new necessity. Let’s use it as the new mother of invention and survival.
Image by iconicbestiary on Freepik