Session Chair: Kiyota Hashimoto Session Theme: Online Discussion and Cooperation Session Number: 2 Paper No: 28 Session and Talk No: TS2-2 Type: Short Co-authors: Shun Shiramatsu and Yasunobu Igarashi Title: A Preliminary Consideration toward Evidence-based Consensus Building through Human-Agent Collaboration on Semantic Authoring Platform

1. A Preliminary Consideration toward
Evidence-based Consensus Building
through Human-Agent Collaboration
on Semantic Authoring Platform
Shun Shiramatsu (Nagoya Institute of Technology, Japan)
Yasunobu Igarashi (E2D3.org, Japan)
KICSS 2020, 2020-11-25

2. Background and Motivation
• Addressing sustainability problems needs citizen
participatory debate for public collaboration
– Global society: Climate change, COVID-19, etc.
– Japanese local society: Low birth rate and aging population
• Repeating irrational decisions may lead catastrophic
situations due to the sustainability problems
• To avoid catastrophic situations, we aim to develop
systems for supporting rational consensus building
– with structuring evidence information and visualizing it
detail

3. Approach: Agent-Human Collaboration
on Semantic Authoring Platform
• We assume that Semantic Authoring Platform [1] is
suitable for structuring consensus-building process
– because it has a functionality for collaborative authoring
through graph-like visualization of discourse
• We aim to develop software agents to support
consensus-building on this platform
– because we assume that this platform can be used not only
for collaboration among people but also for collaboration
among people and software agents
[1] K. Hasida, “Decentralized, collaborative, and diagrammatic authoring,” in the 3rd International Workshop
on Argument for Agreement and Assurance, 2017.

4. Required three software agents
1. Agent for exploring evidence
– aims to find appropriate evidence information (e.g., data,
news articles, and scientific papers) on the web.
2. Agent for structuring evidence
– aims to arrange background knowledge such as evidence
and context behind the social issues.
3. Agent for ensuring accountability
– aims to enable people to understand the decision-making
process. It is required also for ensuring legitimacy of the
decision making.
To confirm the output form of these agents,
we tried manual structuring of past consensus building
as a case study of an irrational decision

5. Case study of irrational decision
Manual structuring of
Japan’s decision in 1941

6. Case study of irrational decision

7. Case study of irrational decision

8. Case study of irrational decision
• Use of evidence does not ensure rational decision
• Irrational inference can be structured and
visualized
– Contradicting relations
need to be detected by
our agents

9. Required three software agents
1. Agent for exploring evidence
– aims to find appropriate evidence information (e.g., data,
news articles, and scientific papers) on the web.
2. Agent for structuring evidence
– aims to arrange background knowledge such as evidence
and context behind the social issues.
3. Agent for ensuring accountability
– aims to enable people to understand the decision-making
process. It is required also for ensuring legitimacy of the
decision making.
It is difficult to check whether the found information is appropriate
for the evidence or not (e.g., hypotheses on COVID-19)

10. Difficulty of fact check
• For example, many hypotheses on COVID-19 are still
not clearly verified
– However, making rational decision needs such knowledges
• We are planning to use Semantic Authoring Platform
for discussion about such hypotheses
– Automated fact check systems like SciFact [2] can be used
for connecting the experts’ opinions on this platform
– We also need to consider how to build a training corpus
[2] D. Wadden, K. Lo, L. L. Wang, S. Lin, M. van Zuylen, A. Cohan, and H. Hajishirzi,
“Fact or fiction: Verifying scientific claims,” arXiv preprint arXiv:2004.14974, 2020.

11. Conclusion and future perspective
• We aim to develop agents collaborating with people
– e.g., citizens, government officers, and experts
– to support the structuring of consensus-building process
– We are planning to use Semantic Authoring Platform
• We tried manual structuring of a historical example
– It indicated that visualizing irrational inference is important
• Sometimes making rational decision requires to grasp
experts’ knowledges (e.g., hypotheses on COVID-19)
– Semantic Authoring can be used
for discussion on such knowledge
• As a future work, we need to
build a corpus of structure of
recent policy making
– We will integrate Semantic Authoring
and our data schema of decision-making
to deal with contextual information