How to approach AI on national and regional levels
This article delves into the recommendations for the national and regional approaches to AI. Leading experts in AI shared their thoughts on crafting better strategies.
Creating legal frameworks and strategies for AI that address local concerns and needs is the main topic of AI implementation. Customized regulations ensure that AI development aligns with national interests and regional development goals, facilitating a more focused and relevant approach to AI governance.
Regional Strategies for AI
Understand the Focus Areas
First of all, it is very important to consider regional specifics. AI isn’t just about technology but about real benefits for the community, as regions differ a lot in terms of their diverse business and cultural conditions, possibilities, challenges, and needs. Thus politicians should start crafting strategies with all these in mind and implement technology where the result is archivable and creates real value for citizens. Having tailored solutions to local problems is the goal of any tech in the public service.
GTF Insights experts who participated in the survey about AI in public services agreed. “Focus on identifying specific areas where AI can make a significant impact, such as improving local public services or optimizing transportation.” - comments Mathias Lindbro, AI Advisor, AI Strategist at Nextevo, and Founder at Strategic 9 AB.
Improving public service and citizens' lives is the point of having this technology. For example, under the California State University Transportation Consortium (CSUTC), researchers recently finished working on applying AI to the state’s established general transportation priorities and developing a project to save the lives of cyclists and pedestrians.
Engage Local Stakeholders
Knowledge exchange between the local stakeholders is essential for building the collective expertise and experience needed to accelerate the public sector. Regions have a unique ecosystem of government agencies, research institutions, and local communities, each capable of offering insights and capabilities. By establishing cross-sectoral collaboration, regions can encourage innovation clusters, and accelerate technology diffusion. Some governments already had such experience. For example, a citizen science project that uses AI to analyze air quality data collected by locals was deployed in Pittsburgh in 2016. The AI helps identify patterns in the data and reveals local air pollution issues for public scrutiny and advocacy to this day.
Boosting AI education and training
Adding AI to the learning system will give future generations the advantage of understanding this complex technology early on and learning how to utilize it. There are some case studies already. For example, the nonprofit organization Michigan Virtual has released a sample K-12 AI Guidance document. Statewide, this is the first group to come together and establish an AI direction for schools. It includes 13 organizations like the Michigan Association of Secondary School Principals and Michigan Elementary & Middle School Principals, directly linking it to the active schools in the state that can implement the guidance.
Run Pilot Projects
“Utilize regional areas as testing grounds for innovative AI solutions. Successful projects can be scaled for implementation at the national level.” –
Liam Sapsford, Senior Enterprise Account Executive at 2021.AI.
Experts agree that successful implementation of projects with AI components is only possible by running experiments and launching such projects.
“Utilize regional areas as testing grounds for innovative AI solutions. Successful projects can be scaled for implementation at the national level.” – Liam Sapsford, Senior Enterprise Account Executive at 2021.AI.
A great example would be a regional project going national in the UK. Network Rail, the UK’s railway infrastructure management organization, has extended its collaboration with artificial intelligence firm CrossTech to test camera-based AI on UK trains. So far the system has saved as much as £3m for taxpayers, and the project has moved forward. Now, cameras will be installed on the East Coast Main Line. With future testing, it may be implemented across the country.
Create Innovation Centers
“Establish regional innovation hubs and technology incubators to support startups and SMEs in developing and scaling AI technologies.” –
Silvia Vianello, founder of Silvia Vianello Academy, Executive Coach, and visionary.
“Establish regional innovation hubs and technology incubators to support startups and SMEs in developing and scaling AI technologies.” – Silvia Vianello, founder of Silvia Vianello Academy, Executive Coach, and visionary.
Initiatives such as regional innovation centers, technology transfer programs, and industry partnerships promote collaboration and knowledge exchange, helping the government’s competitiveness in the AI era. We see great cases of this happening now – In late 2023, Berlin established the AI Innovation Hub that’s designed to support startups focusing on AI technologies in healthcare and urban planning.
Build up workforce development programs
“AI training initiatives, apprenticeships, and reskilling programs ensure that the regional workforce possesses the necessary skills and competencies to harness AI technologies effectively.”
Michael Charles Borrelli, Director of AI & Partners.
“AI training initiatives, apprenticeships, and reskilling programs ensure that the regional workforce possesses the necessary skills and competencies to harness AI technologies effectively.” – Michael Charles Borrelli, Director of AI & Partners.
By investing in infrastructure development, governments can ensure that the regional workforce possesses the necessary skills and competencies to harness AI technologies effectively. Wisconsin’s “Governor’s Task Force on Workforce and Artificial Intelligence” examined how AI’s workforce impacts may affect the state’s key industries, occupations, and foundational skillsets. They released an action plan, proposing the expansion of digital lliteracy, flexible training, and AI tools, opening more jobs for people with the AI skillset.
National Strategies for AI
National approach to policy development requires a comprehensive understanding of the diverse needs and interests of the entire country. This process involves careful consideration and strategic planning to ensure that policies are not only effective but also equitable and inclusive. Governments need to be protective but not take away freedom and prioritize public and national interests over anything else. It’s a hard line to walk, and AI is a dangerous enough thing to require good decision-making and clear strategy.
Some of the more prominent strategies on this level could be:
Establish Clear Regulatory Frameworks
“Develop comprehensive regulations that address ethical, legal, and societal concerns. Ensure these frameworks are adaptable to evolving technologies and international standards.” - Bruno Silva, Head of R&D at Muvu Technologies, Professor, PhD Candidate in AI.
“Develop comprehensive regulations that address ethical, legal, and societal concerns. Ensure these frameworks are adaptable to evolving technologies and international standards. '
- Bruno Silva, Head of R&D at Muvu Technologies, Professor, PhD Candidate in AI.
GDPR, the U.S. “Privacy Rights Act”, and the “Artificial Intelligence and Data Act” – all good examples of active or potential policies that protect citizens from harm. They are designed to safeguard individual privacy and data rights, mitigating misuse of personal information. These frameworks establish clear guidelines for data handling, consent, and individual rights, which are crucial in maintaining trust in digital interactions
It's also important to tailor regulations to the regions. For example, some areas may prioritize AI applications for industrial automation and supply chain optimization, and some focus on healthcare and may emphasize AI-driven diagnostics and personalized medicine. Tailored policies ensure that AI initiatives align with regional development goals, stimulate innovation, and foster inclusive growth.
Ensure Ethics and Privacy
Establish clear ethical guidelines and privacy protection standards. Ensure AI systems are designed to uphold societal values and individual rights. legal frameworks that address local ethical concerns, economic priorities, and social values.
In January 2024, the WHO released AI ethics and governance guidance for large multi-modal models. The guidance outlines over 40 recommendations for governments, tech companies, and healthcare providers to ensure the safe and ethical use of AI in the health sector.
Oversight and Guidance
“Form advisory bodies to oversee AI development, ensuring it aligns with national values and strategic priorities. For instance, Sweden’s AI Sweden serves as a model for guiding AI advancements.” - Mathias Lindbro, AI Advisor, AI Strategist at Nextevo and Founder at Strategic 9 AB.
The organization pushes public sector leaders to adopt AI technologies. Their strategy serves as a guide for decision-makers, promoting collaboration and resource sharing between the public and private sectors to accelerate AI application and development in Sweden. Advisory bodies guide governments towards successful AI implementation and safe adoption.
“Form advisory bodies to oversee AI development, ensuring it aligns with national values and strategic priorities. For instance, Sweden’s AI Sweden serves as a model for guiding AI advancements.” -
Mathias Lindbro, AI Advisor, AI Strategist at Nextevo and Founder at Strategic 9 AB.
Public and Private Sector Partnerships
Foster collaboration between government, industry, academia, and international organizations. This collective approach can enhance resource sharing, innovation, and the alignment of AI developments with national goals.
UK’s National AI Strategy, this initiative promotes collaboration between the public and private sectors to drive AI innovation. It includes funding for AI research and development, as well as partnerships with universities and industry leaders to ensure that AI advancements fit with national direction.
Standardization
Create national AI strategies and roadmaps to promote consistency and avoid fragmented approaches. This helps in creating a unified direction for AI deployment and research.
In December 2023, the International Organization for Standardization (ISO) released new guidelines for AI systems, promoting consistency and best practices across countries. This effort aims to prevent fragmented approaches to AI regulation and ensure that AI technologies are developed and deployed responsibly.
Combined National and Regional Approach
On both levels, it’s important to align regional initiatives with national strategies, facilitate data sharing and governance, engage the public, and support continuous learning and adaptation. And, in the end, it’s pivotal to combine the efforts for successful integration.
By harmonizing national strategies with regional initiatives, governments can effectively address the challenges of AI while still letting it be innovative and progressive. This localized yet collaborative approach ensures consistency and alignment with national and regional goals while allowing for localized customization and experimentation. National and regional governments can create a dynamic and responsible AI ecosystem that serves the public good.
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