Training for data literacy and AI literacy: Data literacy in an AI context

This sub-guideline is part of the guideline Training for data literacy and AI literacy. Refer to the main guideline for context and an overview.

Data literacy is the ability to read, understand, create and communicate data as information. It involves understanding how to effectively collect, analyse, interpret and present data in meaningful ways. Data literacy includes knowing where data comes from, and grasping basic statistical concepts and data presentation and visualization techniques. Data literacy is vital for critically evaluating data-driven arguments and conclusions.

In parliaments, data has emerged as a critical asset across all business domains. As parliaments increasingly rely on data-driven insights to fulfil their mandate, the importance of robust data management practices cannot be overstated. Becoming data-literate empowers parliaments to harness the full potential of their data assets, driving informed decision-making, enhancing transparency, fostering public trust and strengthening the foundations of democratic governance. This is fundamental to the adoption of AI.

Users are important actors in a data culture, since they add data into many systems and are often the people who come face-to-face with the data. It is important for them to understand basic data principles and to be attuned to possible errors or problems that can arise.

Increasingly, too, users are extracting, combining and otherwise repurposing data, often into top-line reports or business dashboards. In all cases, this requires quality assurance, as well as an understanding of where the data comes from and what it means. 

AI can be a powerful tool for analysing and understanding data and trends. But it can also be unreliable, which is why data literacy is especially important in this context.

Parliaments could develop or source training programmes on the following topics in order to achieve a good level of data literacy across MPs and a wide range of non-technical staff:

• Introduction to data literacy
• Data collection and management
• Data analysis fundamentals
• Data visualization and presentation
• Ethical data usage and privacy
• Data-driven decision-making
• Introduction to AI and machine learning
• Critical thinking with data

These courses could be offered at different levels (basic, intermediate or advanced) to cater to learners in different roles and with varying levels of exposure to AI-based systems within parliament.

AI-related data literacy is crucial for senior leaders and decision makers in parliaments, as it enables informed decision-making, effective risk management and strategic planning for AI adoption. Data-literate leaders are able to exercise oversight over AI projects, optimize resource allocation and foster innovation, while ensuring that AI is used ethically.

By equipping decision makers with these skills, parliaments can ensure that AI adoption is guided by informed leadership, aligning with institutional goals while adhering to ethical standards and best practices.

A targeted data literacy training programme for senior leaders and decision makers could include the following:

• Dedicated workshop: This session covers the importance of data-driven initiatives, AI readiness and associated risks. Participants gain an overview of foundational data management concepts tailored to their level, reaching a comprehensive understanding of the AI landscape in a parliamentary context.
• Just-in-time learning and self-paced resources: Additional learning resources allow senior leaders and decision makers to embed their knowledge and understanding of AI. 

Data literacy training is of paramount importance for technical staff, as these individuals are at the forefront of implementing and managing AI systems in parliaments. Their expertise directly impacts the effectiveness, ethical use and security of AI applications in parliamentary operations.

A data literacy training programme for this population could be structured as follows, depending on the needs of parliament:

• Data management foundations: The programme begins with an overview of the fundamental concepts of data management, ensuring participants have a solid understanding of data types, integrity, governance and life-cycle management. This foundational knowledge is critical, since the quality and management of data directly affect the performance and reliability of AI systems.
• Practical skills: The programme then progresses through practical skills in data collection, cleansing and storage. These skills are essential for preparing and maintaining the high-quality data sets that AI systems rely on. Advanced topics such as database management, cloud storage solutions and data visualization techniques could be included to ensure technical staff can effectively handle and communicate insights from large, complex data sets.
• Non-technical aspects: Importantly, the programme also addresses key non-technical topics including data ethics, legal compliance and the application of data in parliamentary contexts. This training ensures that technical staff not only have the skills to implement AI systems, but also understand the broader implications and responsibilities of using AI in a parliamentary setting.

By providing comprehensive training in this way, parliaments can ensure that their technical staff are well-equipped to lead the responsible and effective implementation of AI technologies, ultimately enhancing the efficiency and effectiveness of parliamentary operations.

The Guidelines for AI in parliaments are published by the IPU in collaboration with the Parliamentary Data Science Hub in the IPU’s Centre for Innovation in Parliament. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International licence. It may be freely shared and reused with acknowledgement of the IPU. For more information about the IPU’s work on artificial intelligence, please visit www.ipu.org/AI or contact [email protected].