#hybridintelligence — Public Fediverse posts

Design's most distinctive cognitive contribution — abductive reasoning — remains largely confined to the studio, the workshop, the project timeline. We theorize it extensively (Kolko, Zingale, Dorst), we recognize it as the engine of design synthesis, the mechanism through which incomplete observations become structured hypotheses, through which uncertainty generates possibilities.
Yet when it comes to collective contexts — communities navigating complex territorial challenges — abduction stays trapped in episodic formats, limited by the well-known pathologies of participation: who gets to be in the room, for how long, with what resources, and whose complexity gets actually processed.

This is the gap we explored in the paper presented at the Italian Design Society last June with Michele Zannoni and Flaviano Celaschi. The Systemic Relational Insight (SRI) framework, born from my doctoral research at the University of Bologna, proposes a hybrid intelligence process — community and machine — designed to scale the abductive dimension of sensemaking across broader publics, longer timeframes, and thicker layers of data and knowledge.
The core idea: integrate qualitative knowledge from situated workshops with quantitative data and scientific references, generate candidate insights and submit them to community validation (bringing scale in the formula to reach who didn't attend). An insight here is never a single statement delivered by an algorithm. It's a cluster containing multiple versions, each traceable to its genealogy of sessions, voices, and contexts, each carrying different degrees of community consensus, data support, and scientific consistency.
That simple.

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#DesignResearch #AbductiveThinking #Sensemaking #SystemicDesign #CommunityIntelligence #HybridIntelligence #PluralDesign

Design's most distinctive cognitive contribution — abductive reasoning — remains largely confined to the studio, the workshop, the project timeline. We theorize it extensively (Kolko, Zingale, Dorst), we recognize it as the engine of design synthesis, the mechanism through which incomplete observations become structured hypotheses, through which uncertainty generates possibilities.
Yet when it comes to collective contexts — communities navigating complex territorial challenges — abduction stays trapped in episodic formats, limited by the well-known pathologies of participation: who gets to be in the room, for how long, with what resources, and whose complexity gets actually processed.

This is the gap we explored in the paper presented at the Italian Design Society last June with Michele Zannoni and Flaviano Celaschi. The Systemic Relational Insight (SRI) framework, born from my doctoral research at the University of Bologna, proposes a hybrid intelligence process — community and machine — designed to scale the abductive dimension of sensemaking across broader publics, longer timeframes, and thicker layers of data and knowledge.
The core idea: integrate qualitative knowledge from situated workshops with quantitative data and scientific references, generate candidate insights and submit them to community validation (bringing scale in the formula to reach who didn't attend). An insight here is never a single statement delivered by an algorithm. It's a cluster containing multiple versions, each traceable to its genealogy of sessions, voices, and contexts, each carrying different degrees of community consensus, data support, and scientific consistency.
That simple.

1/2

#DesignResearch #AbductiveThinking #Sensemaking #SystemicDesign #CommunityIntelligence #HybridIntelligence #PluralDesign

Design's most distinctive cognitive contribution — abductive reasoning — remains largely confined to the studio, the workshop, the project timeline. We theorize it extensively (Kolko, Zingale, Dorst), we recognize it as the engine of design synthesis, the mechanism through which incomplete observations become structured hypotheses, through which uncertainty generates possibilities.
Yet when it comes to collective contexts — communities navigating complex territorial challenges — abduction stays trapped in episodic formats, limited by the well-known pathologies of participation: who gets to be in the room, for how long, with what resources, and whose complexity gets actually processed.

This is the gap we explored in the paper presented at the Italian Design Society last June with Michele Zannoni and Flaviano Celaschi. The Systemic Relational Insight (SRI) framework, born from my doctoral research at the University of Bologna, proposes a hybrid intelligence process — community and machine — designed to scale the abductive dimension of sensemaking across broader publics, longer timeframes, and thicker layers of data and knowledge.
The core idea: integrate qualitative knowledge from situated workshops with quantitative data and scientific references, generate candidate insights and submit them to community validation (bringing scale in the formula to reach who didn't attend). An insight here is never a single statement delivered by an algorithm. It's a cluster containing multiple versions, each traceable to its genealogy of sessions, voices, and contexts, each carrying different degrees of community consensus, data support, and scientific consistency.
That simple.

1/2

#DesignResearch #AbductiveThinking #Sensemaking #SystemicDesign #CommunityIntelligence #HybridIntelligence #PluralDesign

Design's most distinctive cognitive contribution — abductive reasoning — remains largely confined to the studio, the workshop, the project timeline. We theorize it extensively (Kolko, Zingale, Dorst), we recognize it as the engine of design synthesis, the mechanism through which incomplete observations become structured hypotheses, through which uncertainty generates possibilities.
Yet when it comes to collective contexts — communities navigating complex territorial challenges — abduction stays trapped in episodic formats, limited by the well-known pathologies of participation: who gets to be in the room, for how long, with what resources, and whose complexity gets actually processed.

This is the gap we explored in the paper presented at the Italian Design Society last June with Michele Zannoni and Flaviano Celaschi. The Systemic Relational Insight (SRI) framework, born from my doctoral research at the University of Bologna, proposes a hybrid intelligence process — community and machine — designed to scale the abductive dimension of sensemaking across broader publics, longer timeframes, and thicker layers of data and knowledge.
The core idea: integrate qualitative knowledge from situated workshops with quantitative data and scientific references, generate candidate insights and submit them to community validation (bringing scale in the formula to reach who didn't attend). An insight here is never a single statement delivered by an algorithm. It's a cluster containing multiple versions, each traceable to its genealogy of sessions, voices, and contexts, each carrying different degrees of community consensus, data support, and scientific consistency.
That simple.

1/2

#DesignResearch #AbductiveThinking #Sensemaking #SystemicDesign #CommunityIntelligence #HybridIntelligence #PluralDesign

Design's most distinctive cognitive contribution — abductive reasoning — remains largely confined to the studio, the workshop, the project timeline. We theorize it extensively (Kolko, Zingale, Dorst), we recognize it as the engine of design synthesis, the mechanism through which incomplete observations become structured hypotheses, through which uncertainty generates possibilities.
Yet when it comes to collective contexts — communities navigating complex territorial challenges — abduction stays trapped in episodic formats, limited by the well-known pathologies of participation: who gets to be in the room, for how long, with what resources, and whose complexity gets actually processed.

This is the gap we explored in the paper presented at the Italian Design Society last June with Michele Zannoni and Flaviano Celaschi. The Systemic Relational Insight (SRI) framework, born from my doctoral research at the University of Bologna, proposes a hybrid intelligence process — community and machine — designed to scale the abductive dimension of sensemaking across broader publics, longer timeframes, and thicker layers of data and knowledge.
The core idea: integrate qualitative knowledge from situated workshops with quantitative data and scientific references, generate candidate insights and submit them to community validation (bringing scale in the formula to reach who didn't attend). An insight here is never a single statement delivered by an algorithm. It's a cluster containing multiple versions, each traceable to its genealogy of sessions, voices, and contexts, each carrying different degrees of community consensus, data support, and scientific consistency.
That simple.

1/2

#DesignResearch #AbductiveThinking #Sensemaking #SystemicDesign #CommunityIntelligence #HybridIntelligence #PluralDesign

Researchers created a global #planthealth indicator. 🌱 Using satellite images and #hybridintelligence, it delivers reliable weekly data – supporting science, #agriculture, and #climateplanning: http://go.tum.de/501520

📷iStock / wmaster890

Much of the conversation around AI lately is about #neuroSymbolic systems that combine neural-network tech like #LLMs and symbolic AI like #knowledgeGraphs.

Frank van Harmelen's puts his AI research in the larger context of how these technical systems can best support #people.

While some in the AI world seek to replace #humans with machines, Frank focuses on AI systems that collaborate with people to create #hybridIntelligence.

https://knowledgegraphinsights.com/frank-van-harmelen/

Much of the conversation around AI lately is about #neuroSymbolic systems that combine neural-network tech like #LLMs and symbolic AI like #knowledgeGraphs.

Frank van Harmelen's puts his AI research in the larger context of how these technical systems can best support #people.

While some in the AI world seek to replace #humans with machines, Frank focuses on AI systems that collaborate with people to create #hybridIntelligence.

https://knowledgegraphinsights.com/frank-van-harmelen/

Much of the conversation around AI lately is about #neuroSymbolic systems that combine neural-network tech like #LLMs and symbolic AI like #knowledgeGraphs.

Frank van Harmelen's puts his AI research in the larger context of how these technical systems can best support #people.

While some in the AI world seek to replace #humans with machines, Frank focuses on AI systems that collaborate with people to create #hybridIntelligence.

https://knowledgegraphinsights.com/frank-van-harmelen/

Much of the conversation around AI lately is about #neuroSymbolic systems that combine neural-network tech like #LLMs and symbolic AI like #knowledgeGraphs.

Frank van Harmelen's puts his AI research in the larger context of how these technical systems can best support #people.

While some in the AI world seek to replace #humans with machines, Frank focuses on AI systems that collaborate with people to create #hybridIntelligence.

https://knowledgegraphinsights.com/frank-van-harmelen/

Much of the conversation around AI lately is about #neuroSymbolic systems that combine neural-network tech like #LLMs and symbolic AI like #knowledgeGraphs.

Frank van Harmelen's puts his AI research in the larger context of how these technical systems can best support #people.

While some in the AI world seek to replace #humans with machines, Frank focuses on AI systems that collaborate with people to create #hybridIntelligence.

https://knowledgegraphinsights.com/frank-van-harmelen/

Researchers from our university and @unihohenheim show that #HybridIntelligence could help preserve #biodiversity while maintaining #AgriculturalProductivity: http://go.tum.de/333807 🌾

#Agriculture #Sustainability #AI #HumanJudgement

📷iStock/A. Nijssen

Can Hybrid Intelligence Opens Up New Opportunities In Healthcare - Over the last decade, we have made groundbreaking achievements like artificial org... - https://readwrite.com/can-hybrid-intelligence-opens-up-new-opportunities-in-healthcare/ #hybridintelligence #aiinhealthcare #healthcare #ai

New publication 🚨

"Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation" co-authored by Mohammad H. Jarrahi (UNC), Gemma Newlands (OII) and me has been published in the open access journal Big Data & Society.

Explore the concept of hybrid intelligence and its potential benefits in this exciting new paper: https://journals.sagepub.com/doi/full/10.1177/20539517221142824

#hybridintelligence #AI

😲 This post was written by #openAI #ChatGPT and only slightly modified.