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An overview of AI in the Swiss Public Sector

In this article, we have looked at how AI is adopted in the Swiss Public Sector and how it is already today enabling public servants and citizens alike to benefit from increased effectiveness and efficiency, and thus optimized public spend and impact. We also highlight where we see room for further adoption and benefit to the Swiss public, especially drawing from AI applications that we have helped some of our global public clients realize. We have identified three main areas from which the Public Sector can benefit from an optimised adoption of AI.

In December 2022, the Federal Government published its first ever Federal Data Science Strategy which focuses on “human-centric and trustworthy data science” that fosters “understanding and trust by the administration and the general public in data driven decision making”. Next to building awareness and competence, the strategy also focuses on increasing “technical accessibility and availability”, with infrastructure initiatives such as e.g. Renku playing a key role here. As an open-source knowledge infrastructure for collaborative and reproducible data science, Renku is connecting people, data and insights.

On a Federal level, the Federal Office for statistics BFS is paving the way with its Data Science Competence Center and affiliated networks such as the Community of Practice for Data Science and AI for Public Good.
Also on a Cantonal level, there are a number of initiatives. Among these, the Canton of Zurich has recently launched an innovation sandbox where researchers, private and public partners can collaborate on AI cases and which provides access to data sets on regulation and public data.
Let’s zoom in on two use cases where AI is already today applied in the Swiss Public Sector and how it specifically adds value to citizens.

Where is the growth potential for AI in Swiss public administration?

With integration of AI solutions and large language models become increasingly simple, we are expecting a significant uptake in the usage of AI solutions across all sectors. The Public Sector is no exception to this, though there are some specific considerations.

In public administration in Switzerland, we see particular growth potential for the application of AI in the areas of healthcare, social security, and transportation, both because of its relevance to the Swiss system and in light of the global use cases Deloitte has helped governments in other countries implement.

While we see impressive growth in the digital health space, the pandemic has also shown us how many communication and interaction systems between care providers are still relying on outdated infrastructure, including even fax. Due to the Federal setup of the Swiss healthcare system and the complex interplay and governance between federal government, cantons and municipalities, there are additional challenges. For example, who decides which system to use, how do we set up data protection, given the highly sensitive nature of health data, etc.

An example from Deloitte global research illustrates the potential:

Global Inspiration 1: Patient Admission Prediction Tool

Queensland public hospitals use the Patient Admission Prediction Tool (PAPT) to predict patient admissions, injury type, their impact on bed availability, staff vacations, etc., hours, weeks, or even a decade in advance. Particularly regarding the nursing shortage and shortage of skilled workers, this also helps with improved deployment planning for staff. Predictions are made by identifying patterns in the records and tested by comparing predictions using historical data. As a result, Queensland hospitals are saving US$2.5 million a year, while the overall benefit to the state could be as high as US$80 million per year from improved patient outcomes. Around 50 hospitals in Queensland are using the tool, which has an accuracy rate of up to 95%

While there is already a number of initiatives in research and beyond where anonymized AHV / ALV data is used to better understand how economically vulnerable populations can be integrated in the labour market, international examples show that more can be done:

Global Inspiration 2: Decision-support Tool

In Estonia, a leading country in connected government, the Unemployment Insurance Fund’s decision-support tool stands out as particularly effective. The AI-based system—trained on more than 100,000 client records—is designed to predict the probabilities of various employment routes for clients, helping civil servants direct unemployed individuals to efficient job-seeking paths. The next step in the evolution of the unemployment office is an ML-powered tool to predict unemployment risk for workers currently in jobs, helping them plan ahead by offering training and skills to avoid losing their positions or reskilling for new opportunities.

Again, in the Swiss setting, we need to understand how to navigate the shared responsibilities between federal and cantonal authorities and the higher sensitivity when it comes to connecting and analysing personal data, especially those data points held by public authorities.

Computer vision opens up entire new possibilities to for example use image data (from e.g. surveillance / CCTV) to optimise and monitor traffic, be it for traffic jam prevention around rush hour or for security / surveillance purposes, e.g. for police and border control. Needless to say, there is questions around privacy to be addressed, e.g. can we use licence plate information. 2 examples from our global study can serve as inspiration here:

Global Inspiration 3: Digital Twin

Digital twin gives San Diego options in tackling traffic congestion: Seeking to clear clogged downtown streets and rush-hour commuter highways, the San Diego Association of Governments (SANDAG) looked to digital twin technology. The AI-powered tool has allowed the officials to consider and compare a comprehensive range of potential projects, from light rail systems to ridesharing and electric scooters, beyond the traditional solution of widening roads. The tool generates findings in hours or days and lets citizens visualize how a new city or proposed construction project might affect their travel.

US cities use analytics to deploy snowplows and garbage trucks efficiently: Keeping real-time tabs on where snowplows and street sweepers have been and where they’re going boosts efficiency. Cities are increasingly adding sensors to vehicles to collect information on location, road conditions, temperature, and effectiveness and transmit it to fleet managers and the public. With cloud-based technology combining data with social media feeds, traffic reports, and doppler radar, managers can make better, faster decisions about optimizing truck stationing and routing, and avoid redundant coverage of certain areas. Moreover, keeping citizens informed about service location and timing reduces unnecessary calls

Ethics and Governance

With the rise and increasing adoption of AI, there is increasing calls to address the ethical and legal implications, especially when public organizations and governments are involved. Ethical guidelines are required for both data sourcing but also in terms of model development standards to ensure unbiased, explainable results that ensure users can place trust in AI applications and to actively prevent abuse (e.g. misinformation / deepfakes). In the Swiss context, guidelines for practitioners and users in the Swiss public administration are key and ought to be in line with the Swiss Data Protection act, with GDPR and developed in close alignment with civil society. Also, the discussion about the European AI Act should be actively followed by the relevant actors in Switzerland, both at the legislative level and for implementing bodies / users in public administration.

In 2020, the Federal Council has provided guidelines for the use of AI in public administration, focusing on transparency, explainability, and robustness. The Federal Council further clearly stated that the responsibility and liability needs to be clarified and cannot be delegated.

Canton Zurich in February 2021 published a study on ethical and legal considerations of the use of AI in the public administration Künstliche Intelligenz in der Verwaltung braucht klare Leitlinien | Kanton Zürich (zh.ch)

Conclusion

To sum it up, it can be said that with the Federal Data Science Strategy and some impressive first use cases on the way, the Swiss Public sector – and Swiss taxpayers - are starting to reap the benefits of applying AI for the public good. However, the international examples show that more can be done, and hopefully can serve as inspiration for how AI can support to relieve the burden on public personnel, thereby allowing them to focus on essential tasks and, in particular, counteract the shortage of skilled workers. Needless to say, the big requirement will be to ensure AI is applied within clearly defined guidelines and with high ethical standards to ensure it is trustworthy.

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