AI for leaders in the public sector
The training aims to effectively and inspiringly educate leaders in the public sector, bringing Sweden closer to the goal of becoming the best in the world at realizing the possibilities of artificial intelligence.
At AI Innovation of Sweden, we see significant needs regarding AI competence throughout society. Knowledge about technical solutions, data quality, legal and ethical aspects, and so on is especially important when discussing, piloting, or adopting AI solutions in the public sector. In this project, aimed at politicians and leaders in the public sector, we work together with The Swedish Association of Local Authorities and Regions (SKR) and management consultant firm Governo.
AI for leaders in the public sector is a joint effort where SKR, AI Sweden, and Governo have been working closely together to raise knowledge and awareness.
Different types of skills needed
Over just a few years, AI has gone from a relatively unknown subject for most people to being singled out as a solution for significant efficiencies, increased quality, and completely new ways of working and ways of delivering services for the public sector. But for the changes to become a reality, both in-depth specialist knowledge and increased general knowledge are required. And since solutions are usually not developed internally among individual public actors, it is vital to strengthen their ability to define and evaluate requirements.
The training, divided into a self-study tutorial part and a workshop part, comprising one day each, is adapted to be conducted digitally.
The workshop will be offered as a physical event around Sweden when circumstances allow. Until then, digital workshops are being conducted, with very positive feedback. In the workshop, people from different organizations meet with the focus on what leveraging AI brings for leadership, organization, and decision-making.
The self-study part deals with what AI is and how AI solutions work. Possible use cases for the public sector are brought up, as well as how digitization/digitalization is related to AI. Furthermore, the role of accessible data, necessary technical choices, ethical and legal issues are also highlighted.