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Artificial Intelligence and Systems Thinking in the Public Sector

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By Mauricio Covarrubias
May 13, 2022

The development of artificial intelligence (AI) technologies has had a profound impact on the way governments work and design policies. Its applications touch areas such as health services, transportation and security. Public servants are using AI to help them make welfare payments and immigration decisions, answer citizen inquiries and classify health care cases, among many other activities.

AI tools could improve the efficiency and quality of many public sector procedures. For example, they could offer citizens the opportunity to participate from the beginning in the service design process and to interact with the state in a more agile, effective and personalized way. In its report Artificial Intelligence in Society, the OEDC points out that, if properly designed and implemented, AI technologies could be integrated throughout the policymaking process, support reforms and improve public sector productivity.

AI Is Not a Panacea

The possibilities of AI are so wide and growing that it is expected to be a core tool used to face current and future challenges. However, AI cannot be a panacea for all our complex problems. Historically, new technologies have promised to solve immediate and specific problems, but over time they prove unsustainable. Therefore, we must acknowledge the limitations of this innovation, explore ways to overcome constraints and conceptualize novel ways to harness AI.

In The Innovative State, Beth Simone Noveck Beth— a professor at Northeastern University, where she directs the Burnes Center for Social Change—points out that adopting the right technologies can create new opportunities to improve the efficiency and agility of the public sector and, if used well, improve its legitimacy, which is important today when trust in government has been eroded.

We argue that the systems approach can contribute to the “good use” of AI on the one hand, by allowing government agencies to understand complex problems more accurately and consequently formulate more effective policies. On the other hand, the systems approach can favor the application of AI, giving rise to more sustainable holistic innovative solutions and, as part of this, allowing the risks associated with it to be reduced, by providing a powerful framework to evaluate the possible domino effects.

Systemic Reality and Sustainable Solutions.

Based on the article, “New Superpower in the Making: Awareness-Based Collective Action” by Otto Scharmer, Senior Lecturer at the Sloan School of Management at Massachusetts Institute of Technology (MIT), we can say that COVID-19 has become one of the most effective and impactful teachers of our time. The microscopic pathogen of about 0.000125 millimeters has given us an advanced lesson in systems thinking and interdependence to the more than 7.8 billion people on the planet.

Some of us have already learned this lesson intellectually, but now we are dramatically realizing that we are part of the same global network of social, economic, cultural and environmental connections. Now we know that ignoring our fundamental condition of interconnection has led us to design institutions that completely fail at times like this.

The pandemic has shown us that the challenges of our time cannot be understood in isolation, but are interconnected, requiring a radical change in our ways of thinking, perceiving and acting; in a world of increasing interdependence, doing good is not easy. Creating sustainable solutions that can change over time implies considering the systemic impacts of these possible solutions before giving life to innovation processes, solutions and decisions that could do more harm than good. A review of the literature indicates that many of the AI initiatives in the public sector are generally focused on highly domain specific solutions. There has not been widespread adoption of systemic solutions proposed.

AI and Epistemic Capacity of the State

As part of the agenda of challenges and opportunities for an innovative research agenda on AI, Nishanta, Kennedy and Corbetta highlight that the true value of AI will be how it facilitates and fosters governance. They also point out that future studies on AI should incorporate, among other aspects, multilevel points of view, a systems approach, design thinking and considerations of economic value, to show how AI can offer immediate solutions without introducing long-term threats.

In this order of ideas, based on this form of systemic knowledge, the use of AI can improve the capacity of the state to move towards a more comprehensive and holistic vision that allows capturing interdependencies and interactions. In other words, improve thinking and acting systemically.

Systemic Knowledge and Artificial Intelligence

According to Geoff Mulgan, professor of Collective Intelligence, Public Policy and Social Innovation at University College London, one of the main challenges is to make systems visible and understandable and, above all, to implement processes for learning and developing systems skills. He also points out that although many of these ideas are already familiar to some—maybe even common sense—they are quite unknown to many others, and are still very rare in general practice. Without better systems knowledge, the kind of systems change we need in the coming decades is likely to fall short.

Culture is another critical component. For systems thinking to flourish, organizations must value stakeholder engagement and diverse perspectives, willingly question the status quo and encourage and empower people to look beyond their part of the system. For public servants, the systemic thinking approach allows them to understand the place of AI as a component within solutions to real-world problems, which makes it critical learning. While branches of AI, such as machine learning, often bring critical new elements to these solutions, they typically function as part of a larger system involving hardware, software, data, people and procedures.


Author: Mauricio Covarrubias is Professor at the National Institute of Public Administration in Mexico.  He is co-founder of the International Academy of Political-Administrative Sciences (IAPAS).  He is the founder and Editor of the International Journal of Studies on Educational Systems (RIESED). Coordinator in Mexico of the TOGIVE Project: Transatlantic Open Government Virtual Education, of the ERASMUS + Program of the European Union. Member of the National System of Researchers of CONACYT.  He received his Ph.D. from the National Autonomous University of Mexico.  He can be reached at [email protected] and followed on Twitter @OMCovarrubias and LinkedIn @ http://linkedin.com/in/mauricio-covarrubias-2b49bb5

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