Strategic Integration of Artificial Intelligence in Parliamentary Processes

Paper presentation at the Wroxton Workshop 16th edition on 27 July 2024.

1. July 27-27, 2024
Strategic Integration of
Artificial Intelligence in
Parliamentary Processes
Fotios Fitsilis, George Mikros, and Jörn von Lucke

Wroxton Workshop 2024

2. ●Introduction
●Core AI technologies
●Case studies
●Five-point approach to AI integration
●Quick wins
●Challenges
●Conclusion and future steps
Structure
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3. Introduction
to AI in Parliaments
●Trend of AI in e-government systems
●Potential of AI in parliamentary processes
●Several types of AI
●AI applications in law-making, data analysis,
policy-making, and administrative tasks
●Global adoption and calls for regulation
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4. Core AI technologies
Natural Language
Generation
Utilizes algorithms to understand the
meaning and context of language,
enabling the correlation of legal
documents and the detection of
latent semantic relationships.
Semantic Similarity Named Entity Recognition
Identifies specific entities within legal
texts, allowing for accurate extraction
and categorization of legal references,
citations, and stakeholders.
Generates coherent legal texts based
on specific inputs, facilitating tasks
such as drafting amendments and
creating reports
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Legal Ontology and
Terminology
Management
Automatically extracts structured
information from unstructured and/or
semi-structured machine-readable
documents.
Information Extraction
Advanced Language Editing
and Correction
Applies computational linguistics and
machine learning techniques to detect
and correct errors in written text.
Involves the systematic handling of
legal terms and their definitions. It
ensures that legal terminology is
consistent, accurate, and aligned
across various legal documents and
contexts.

5. Brazil implements the
Ulysses project to classify
web pages and distribute
bill requests using NLP,
identity similar bills and
studies, perform speech
recognition and citizen
opinion analysis, It also
uses facial recognition for
authentication.

Canada uses
voice-to-text captioning,
translation and speech
recognition, cognitive AI
for security and
cybersecurity, NLP for
text analysis, and facial
recognition for e-voting.
Various European Union
parliaments have
adopted AI tools for
document automation
and data visualization,
streamlining legislative
processes and improving
transparency.
Brazilian Congress Canadian Parliament EU parliamentsSelected case
studies of AI
Integration
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6. Develop a clear vision and
specific strategic goals for
AI integration that align
with the parliamentary
objectives, ensuring that
the strategy encompasses
digital and AI dimensions.
Strategy
Employ methodologies to
evaluate and rank AI usage
scenarios through
interactive workshops,
creating a ranked list of
priorities for
implementation based on
stakeholder feedback.
Prioritization
Adopt an agile
development process for
implementing prioritized AI
solutions, ensuring that
specifications and
requirements are met while
introducing quick wins to
demonstrate feasibility.
Implementation
Establish a parliamentary
body for oversight and
governance of AI integration,
defining its composition,
responsibilities, and ensuring
balanced representation
across political and technical
expertise.
Governance
Organize training sessions
tailored for various
parliamentary stakeholders
to enhance their
understanding of AI
concepts, ethical
considerations, and
potential applications in
legislative processes.
Training
Five-point
approach
to AI
Integration
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7. Speech-to-Text
solutions
Sentiment analysis tools
Implement multilingual speech
recognition systems can
automate transcription of
parliamentary sessions,
enhancing accessibility and
transparency.
Utilize sentiment analysis for
public consultations enables
parliaments to gauge public
opinion effectively and identify
key areas of concern.
Quick Wins in AI
Implementation
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8. Challenges
Regulatory and
ethical challenges
⦿Ensure compliance with data protection laws,
such as GDPR, to safeguard personal data.
⦿Address ethical concerns surrounding
AI decision-making and the potential for discrimination.
⦿Establish clear guidelines for accountability
in AI-generated outputs and actions.
⦿Promote transparency in AI processes
to strengthen public trust and understanding.
⦿Develop robust ICT infrastructure
to support AI applications in parliaments.
⦿Mitigate biases in AI models
to ensure fair and equitable outcomes in legislative processes.
⦿Ensure the reliability and accuracy of AI outputs
in critical decision-making scenarios.
⦿Manage large volumes of data securely
and effectively to prevent breaches and misuse.
Technical
Challenges
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9. Collaboration for AI integration
●Government bodies establish regulations,
fund AI initiatives, and ensure alignment
with national digital strategies and policies.
●The private sector offers technical expertise,
innovative solutions, and resources
for AI development and deployment.
●Academia provides research, evaluates AI
applications, and ensures implementations
are scientifically sound and ethical.
●Collaboration among parliaments
enhances knowledge sharing, resource allocation,
and transparency for effective AI integration.
●Joint efforts help develop tailored AI solutions
to address challenges and
strengthen parliamentary functions.
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10. 10
New publication - AI guidelines for parliaments
⦿Structure: 40 guidelines grouped in 6 sections.
⦿Publisher: Westminster Foundation for Democracy.
⦿Creators: Hellenic OCR Team, partner institutions and experts.
⦿Author team: 22 parliamentary experts from 16 countries.
⦿Dissemination: Translations in multiple languages underway.
⦿Download: https://www.wfd.org/ai-guidelines-parliaments

11. Conclusion
and future
steps
●AI in parliamentary processes can boost efficiency,
transparency, and public engagement.
●A strategic framework is needed for research, prioritization,
training, implementation, and governance.
●AI tools like speech-to-text, sentiment analysis, and chatbots
can show immediate value in legislative functions.
●Collaboration among government, private sector, and
academia is essential for effective AI implementation.
●Ethical considerations and transparency are crucial for
maintaining public trust in AI technologies.
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12. Thank
you!
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The information and views set out in this presentation are only
those of the authors and do not necessarily reflect the official
opinion of their institutions.
https://hellenicOCRteam.gr
[email protected]