Assuring AI is used in responsible ways to transform government work is a central tenet of the AI framework model identified by SAP research. Three elements of this model — implementing proper work design, evolving the work culture and optimizing AI value for stakeholders — will help government appropriately incorporate AI technology to benefit the future of work.
Using AI to Improve How Work Is Done
Many governments have started exploring AI uses. For example, Bellevue, Wash., created a chatbot to answer common questions about the COVID-19 virus and health resources to help meet the surge in public demand for information. The chatbot delivered an online self-service tool in seven languages spoken by city residents.In most cases, AI is best suited to highly structured tasks that follow clear, consistent rules and use well-defined data sets. AI is also useful for the work of processing and analyzing massive data sets. In contrast, tasks that require in-depth data interpretation and understanding of process context will still be best performed by people.
To identify the best uses for AI technology, create a collaboration of data scientists and domain experts — the employees who work with business, operational and service delivery processes. These experts can help ensure AI models are trained correctly with appropriate objectives, decision rules and data inputs. The real-world knowledge of these employees is also important to validate the relevance, suitability and fairness of an AI model’s outputs.
When work processes are designed correctly, they will leverage AI to perform many of the repetitive, manual verification and analysis steps that employees handle today. This automated processing will free time for employees to perform the review, evaluation and decision-making steps that require human understanding and judgment.
Evolving the Work Culture
Changes to long-entrenched work roles and processes can raise resistance among employees. Of highest concern is that an employee’s work will become less important to the organization if much of it can be done by AI.Leaders can overcome these concerns by pointing out AI limitations and how it can raise human tasks to a higher level of knowledge, skill and contribution. Employee work will have an increased focus on effectiveness in areas such as creative service delivery, collaborative problem-solving and empathetic communication. In short, the clear-cut work will be done by a computer, while the more complex work will still be done by people.
AI adoption and its impact on the scope and tasks of employee work will be ongoing but evolutionary. The culture shift can also be a gradual and ongoing evolution, which will help the employees, managers and leaders to accept the changes.
Creating Stakeholder Value for AI Projects
Unrealistic expectations for AI technology, both positive and negative, influence how stakeholders perceive the value of a new AI project. It’s important to manage these expectations while also making a clear value case in the project’s budget justification.To help with expectations, promote the view of AI as a technology that allows computers and people to collaborate and improve the speed, ease and usefulness of selected work processes and data analyses. For the budget case, define project value measurements that show quantitative benefits for operations or public services. Consider looking first at areas offering the biggest potential for improvement, especially with AI process automation.
And although they may be harder to measure, any qualitative benefits gained from AI are important to consider as well. For example, using AI chatbots to handle routine information requests during the pandemic represented a clear value to the community. This value will continue as the organization is now better prepared to deliver services during a future crisis. And when citizens see positive outcomes from AI-driven services, they will support further innovative uses by government.
Maintaining AI Transparency
One factor contributing to the concern about giving AI too much control is the fact that it can become self-sustaining and independent of human guidance. For example, machine learning technology allows an AI algorithm to learn from its actions and adjust a decision flow or process automation accordingly, with no human intervention required. This learning capability can accelerate process automation, identify new areas for automation and respond quickly to changing conditions.However, a public sector organization must maintain controls over AI use to preserve adequate transparency. Policies and practices should also give employees and constituents confidence that AI technologies will be used in ways that are clear, traceable, secure, fair and protect personal privacy.
The New Future of Government Work
The ongoing impact of pandemic recovery will require the public sector to continue leveraging cultural and technological advancements to evolve how work is done. AI and machine learning are among the technologies that will help governments address current issues that hinder service and operational improvements including skill shortages, organizational silos, manual processes, massive data sets and legacy systems. By using AI to automatically process data or handle routine inquiries and tasks, governments can free employees to focus on the higher-level work that advances their organizations and their service to the public.To explore more thought leadership around AI, visit the SAP Institute for Digital Government.
