The Invisible Power of DIGITAL FOOTPRINTS: How Stigmergy Shapes Our World

#Stigmergy #DigitalTransformation #SocialChange #LeadershipMindset #DataAnalytics

This video lecture by Dr. Marvin Starominski-Uehara delivered at Temple University Japan's Academic Conference in March 2025 explores the concept of "stigmergy," a process of indirect coordination through traces, and its application in understanding complex systems, particularly in the digital world. Starominski-Uehara uses examples from diverse fields like termite mounds, parkour, and social movements to illustrate how seemingly simple individual actions can lead to significant collective outcomes and social change.

Key Takeaways:

Human Stigmergy: The core concept is stigmergy – indirect coordination and communication through traces left by individuals. This applies to both physical (e.g., termite mounds) and digital (e.g., social media posts) environments.

Autonomous Actions, Reproducible Domains, Scalable Platforms: Starominski-Uehara proposes a framework encompassing autonomous actions (individuals' passionate, purposeful actions), reproducible domains (the shared interests and information-seeking behavior of like-minded individuals), and scalable platforms (the algorithms and systems enabling information spread). These three elements together create the conditions for stigmergic processes to unfold.

Information as Cues: Individuals often share incomplete information online, acting as cues or hints for others to interpret and build upon. The meaning-making process is crucial in stigmergy.

Case Studies: The lecture presents numerous case studies demonstrating stigmergy's impact, including: a near-fatal accident highlighting the importance of shared information, the neglect of a child highlighting the need for credible information sharing, and a flood event showing how early citizen warnings could have saved lives. Also, it uses examples from parkour and social activism, illustrating how individual actions can collectively lead to change.

Analytics & Data: The importance of data analysis and analytics in understanding and harnessing stigmergic processes is emphasized, particularly for businesses using digital platforms. This includes both intuitive (learning through experimentation) and statistical approaches (using data to identify patterns and optimize strategies). 

These slides show the progression of prompts for 'conversational search' and how to leverage large language models to learn better, faster and have more fun about a concept one has not prior knowledge of. 

Large language models are great tools for self-directed learners as they tailor knowledge acquisition based on users' pace, resources, and limitations. 

We investigated 'rapid prototyping' in this lecture I gave at Chaminade University, 'Inana Innovators Program. 

Powerful chatbots can help students learn faster, better, and have more fun (Cooper 2023; Alier et al. 2024; Pesovski et al. 2024). Some even argue that these tools are ‘skill levelers’ in a sense that now ‘everyone is above average’ (Mollick 2023). This session shares online educational practices that test the premises of this claim. Reverse engineering (Zhong & Li 2024) and collective excitation (Zheng et al. 2023) are two opposing, but complementary, methods that empower students to engage in an interactive process of building collective knowledge while further developing their analytical and critical skills by paying close attention to causality, assumptions, structures, and patterns on AI-generated outputs.

The guiding question of this session is:

‘How do reverse engineering and collective excitation help high school and college students leverage chatbots for the design of tailor-made educational experiences?’  

Learning outcomes:

. What are the assumptions of chatbots as a ‘skill leveler’ in education?

. How does ‘reverse engineering’ help students enhance their critical thinking skills?

. What is ‘collective excitation’ and what role it plays in creating valuable ‘collective knowledge’? 

URLs associated with this session:

https://www.youtube.com/watch?v=rXfDH3gMy-g

https://www.youtube.com/watch?v=Rf96bDPGNYQ

References

Alier, M., García-Peñalvo, F., & Camba, J. D. (2024). Generative Artificial Intelligence in Education: From Deceptive to Disruptive. 

Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452. 

Mollick, E. (2023, September 24). Everyone is above average. Retrieved from https://www.oneusefulthing.org/p/everyone-is-above-average 

Pesovski, I., Santos, R., Henriques, R., & Trajkovik, V. (2024). Generative AI for Customizable Learning Experiences. Sustainability, 16(7), 3034. 

Zheng, L., Mai, F., Yan, B., & Nickerson, J. V. (2023). Stigmergy in Open Collaboration: An Empirical Investigation Based on Wikipedia. Journal of Management Information Systems, 40(3), 983-1008.

 Zhong, B., Liu, X., & Li, X. (2024). Effects of reverse engineering pedagogy on students’ learning performance in STEM education: The bridge-design project as an example. Heliyon, 10(2).

AI Summary: This video presents a session on empowering students with generative AI, specifically large language models (LLMs) or chatbots, for enhanced learning. The speaker discusses student perspectives on the risks and benefits of using these tools, and shares two techniques—reverse engineering and collective excitation—for incorporating LLMs into online classes.

Key Takeaways

• Student Concerns about LLMs: Students are aware of potential negative impacts on cognitive development, independent thinking, and communication skills. They worry about fairness in assessment and the unequal access to these tools among classmates. Students also express concerns about potential laziness and procrastination resulting from over-reliance on AI.

• Reverse Engineering LLMs for Learning: This technique involves guiding students to craft effective prompts, analyze LLM outputs for keywords, and use these keywords to deepen their understanding of concepts. The process aims to personalize learning and enhance critical thinking by breaking down and analyzing the LLM’s responses.

• Collective Excitation for Collaborative Learning: This approach simulates Wikipedia's collaborative model in the classroom. Students collectively answer a question using Google Docs, fostering collaboration and building collective intelligence. Constructive feedback from the instructor is key to the success of this method.

• Instructor's Role: The instructor's role is crucial in guiding students on responsible and ethical LLM use, addressing their concerns, and adapting teaching methods to leverage the technology's benefits while mitigating its risks. The instructor needs to listen to student feedback and adapt teaching strategies accordingly.

• Embrace, Don't Fear: The presentation advocates for embracing the opportunities presented by generative AI while acknowledging its risks. It highlights that the technology is rapidly evolving and requires a flexible and adaptable approach to education.

This webinar, part of the Sustainable Action Dialogue series, focuses on generative sustainability and the significance of "baby steps" in achieving long-term sustainability goals. The speaker discusses the use of digital traces to align business actions with mission statements and the importance of transparent communication with stakeholders.

Key Takeaways

• Digital Traces and Mission Alignment: Using digital traces (online interactions and information) to connect business actions to the organization's mission statement. Consistent, regular actions ("baby steps") are crucial for long-term impact.

• Creating Kind Environments for Strategic Decisions: Strategic decision-making should involve understanding the online environment, identifying target audiences, and creating a welcoming atmosphere for engagement. This can involve pre-emptive research and confident exploration.

• Transparent Communication for Long-Term Goals: Openly communicating sustainability initiatives with all stakeholders builds trust and loyalty, leading to better brand recognition and market positioning.

• Generative Design for Sustainable Solutions: Leveraging generative design (using novel ideas to address complex issues) to find innovative solutions to sustainability challenges. This involves consistent, regular engagement with online platforms.

• Brand Positioning and Personality: Consistent digital presence builds brand identity and recognition, allowing algorithms to work in the company's favor. This should involve a long-term commitment and regular updates.

Explore the transformative power of digital communication in leadership and sustainability in our upcoming masterclass titled "Unlocking Digital Task Scaling: Strategic Management, Collaborative Communication, and Brand Positioning for Sustainability" led by Marvin Starominski-Uehara, a distinguished theorist in contemporary leadership at Temple University in Japan.

Dive into essential topics, including:

• Strategic use of digital traces for complex sustainability tasks

• Long-term decision-making in the digital sphere

• Mediated communication and its business transformation potential

• Scaling ideas through algorithms in uncharted territories

• Positive social changes driven by digital interactions

AI Summary: This masterclass focuses on unlocking digital task scaling, strategic management, collaborative communication, and brand positioning for sustainability. The speaker discusses his research on digital communication leadership and its three layers of analysis: autonomous acts, reproducible domains, and scalable platforms.

Key Takeaways

• Acting with Intent: Digital engagement should leverage opportunities and mitigate risks purposefully to achieve goals. The algorithm's suggestions are influenced by intent.

• Tracing Passion: Documenting one's passions online helps define purpose, fosters conscious engagement, and creates a sense of discovery. Examples show how individual actions, with purpose, consciousness, and a sense of discovery, are reproduced and scaled by algorithms.

• Connecting to Thrive: Online connections bring personal and organizational goals closer, fostering success. This is facilitated by indirect communication through digital traces.

• Embracing Uncertainty: Algorithms' exposure of information to users creates positive effects, and embracing uncertainty aids in achieving goals.

• Kindness Boomerang: Positive, constructive engagement online leads to positive feedback and improvement. Examples illustrate the interconnectedness of individuals, where actions influence others, creating a ripple effect.