# Public Outreach and Science Communication

**Last updated**: 2025-10-31

Stefan Szeider engages the public through educational initiatives, policy lectures, and creative visualizations that make algorithms and computer science accessible to non-experts.

## ADA: Algorithms Think Differently

**ADA** is an educational initiative bringing algorithmic thinking to children and young people.

- **Founding Member**: Co-created the program with colleagues from Vienna's CS community
- **Philosophy**: Algorithms represent a fundamentally different way of thinking that should be accessible to everyone, not just computer scientists
- **Activities**: Workshops, interactive demonstrations, and educational materials for K-12 students
- **Website**: https://www.ada.wien/

ADA has reached thousands of students across Austria, introducing concepts like sorting, graph algorithms, and computational thinking through hands-on activities.

## Lecture to Austrian Parliament

In 2021, Stefan Szeider delivered a lecture on algorithms to members of the Austrian Parliament.

**Topic**: How algorithmic decision-making impacts public policy, privacy, and democratic processes.

**Key Message**: Policymakers need foundational understanding of algorithms to effectively regulate AI systems and protect citizens' interests.

**Impact**: Contributed to ongoing discussions about AI regulation in Austria and the European Union.

**Coverage**: http://www.vcla.at/2021/06/a-lecture-on-algorithms-at-the-austrian-parliament/

## World Record Human Sorting Network

Stefan Szeider organized a **world record attempt** for the largest human sorting network, demonstrating parallel sorting algorithms at scale.

- **Participants**: Hundreds of people forming a physical sorting network
- **Concept**: Each person represents a "comparator" in a sorting network, physically moving to demonstrate how parallel sorting works
- **Educational Value**: Makes abstract algorithmic concepts tangible and memorable
- **Video**: https://youtu.be/4yAeLkrcXGc

This visualization shows how parallel algorithms differ from sequential ones, which helps explain modern computing.

## Shannon Linguistic Playground

An interactive web tool demonstrating Claude Shannon's information theory applied to natural language.

**Features**:
- Real-time text generation based on n-gram models
- Visualization of entropy and predictability in language
- Educational explanations of information-theoretic concepts

**Educational Goal**: Show how mathematical concepts from the 1940s directly enabled modern natural language processing and LLMs.

**Access**: https://www.ac.tuwien.ac.at/people/szeider/shannon/

Students and educators worldwide use this tool to understand the foundations of language modeling.

## OBDD Visualizations of U.S. Presidential Elections

Stefan Szeider created **Ordered Binary Decision Diagram (OBDD)** representations of the U.S. Electoral College for the 2020 and 2024 presidential elections.

**2024 Election OBDD**: https://www.ac.tuwien.ac.at/people/szeider/us2024/
**2020 Election OBDD**: https://www.ac.tuwien.ac.at/people/szeider/2020-us-presidential-election-as-an-obdd/

**Concept**: OBDDs are data structures from computer science that compactly represent Boolean functions. Applied to elections, they show all possible paths to victory.

**Insights**: The visualizations reveal:
- Critical "swing states" whose outcomes determine the election
- The exponential complexity of electoral combinations
- How algorithmic thinking illuminates political processes

These visualizations were widely shared during election cycles, making data structures accessible to the general public.

## Algorithms in 60 Seconds Video Competition

Stefan Szeider initiated a **video competition** challenging researchers and students to explain algorithms in 60 seconds or less.

**Website**: http://www.vcla.at/activities/algorithmen-wettbewerb-in-60-sekunden/

**Goal**: Break down communication barriers between computer scientists and the public by forcing concise, creative explanations.

**Impact**: Generated dozens of accessible algorithm explanations, many used in classrooms worldwide.

## Contemporary Garey-Johnson Cartoon

Stefan Szeider created a **modernized version** of the famous Garey & Johnson cartoon illustrating computational complexity classes.

**Original Context**: Michael Garey and David Johnson's 1979 book "Computers and Intractability" included a cartoon showing relationships between P, NP, NP-complete, and other complexity classes.

**Szeider's Update**: Reflects modern understanding of complexity theory, including parameterized complexity, approximation, and quantum computing.

**Access**: https://www.ac.tuwien.ac.at/people/szeider/cartoon/

Used in complexity theory courses worldwide as a teaching tool.

## Communications of the ACM Article

Stefan Szeider co-authored a survey article in **Communications of the ACM** that has been **downloaded over 45,000 times**.

**Topic**: Advanced algorithms made accessible to broad computer science audience.

**Impact**: One of the most-read articles in Communications of the ACM, demonstrating effective science communication.

The article's success shows how technical depth and accessibility can coexist when communication is thoughtfully designed.

## Media Coverage

Stefan Szeider regularly engages with journalists and media outlets to explain algorithms, AI, and computational thinking.

**Recent Coverage**: https://www.ac.tuwien.ac.at/people/szeider/media/

Topics include:
- AI and large language models
- Algorithm transparency and accountability
- The future of automated reasoning
- Ethics of algorithmic decision-making

## Philosophy: Making Algorithms Legible

Stefan Szeider's outreach work reflects a core belief: **algorithms are too important to remain in the exclusive domain of computer scientists**.

As algorithmic systems increasingly shape society—from social media feeds to hiring decisions to climate modeling—public understanding becomes essential for democratic governance.

His outreach activities aim to:
1. **Demystify** computational thinking for non-experts
2. **Empower** citizens to engage critically with algorithmic systems
3. **Inspire** young people to pursue computer science
4. **Inform** policymakers about technical realities of AI and algorithms

**Contact**: sz@ac.tuwien.ac.at