The NeoMundi team is pleased to take part in an educational initiative designed to help students better understand AI Weather and the reliability issues associated with generative artificial intelligence systems.
This initiative is exclusively educational. Its purpose is to help students become better-informed users of artificial intelligence: to understand that model behavior can vary, learn how to verify AI-generated responses, and recognize situations in which human judgment remains essential.
An awareness campaign at Champlain College
As part of this initiative, an AI reliability awareness campaign will be displayed on digital screens throughout Champlain College Saint-Lambert, a publicly funded English-language higher education institution located on Montreal’s South Shore.
Through short and accessible messages, students will be invited to discover some of the risks associated with generative AI and to think critically about the situations in which they can rely on AI-generated information, as well as the degree of confidence they should place in it.
The campaign will also introduce students to NeoMundi AI Weather, a public resource that observes daily variations in the behavior of different artificial intelligence systems.
Like a conventional weather forecast, this resource does not make decisions on behalf of the user. It provides additional information to help people exercise their own judgment.
NeoMundi warmly thanks Mohamed Lhamidi, founder of Visual Impact, for initiating and contributing to this awareness campaign.
A collaboration initiated by Thomas Hormaza Dow
This collaboration was initiated by Thomas Hormaza Dow, a professor at Champlain College Saint-Lambert and founder of the Business Physics AI Lab.
Together with Morris Nassi, Thomas Hormaza Dow also developed the REACT framework, an educational framework designed to move the discussion about using artificial intelligence toward a more fundamental question: that of human judgment.
REACT is a structured framework built around five pillars: Reason, Evidence, Accountability, Constraints, and Trade-offs. These pillars are operationalized through seven reflection questions that invite users to examine their decisions before, during, and after AI-assisted work.
The framework is designed to make human reasoning, verification, and responsibility more visible. In particular, it encourages students to:
- determine whether using AI is appropriate in light of the intended objective and expected benefits;
- consider how their prompts and input data are constructed;
- define a method for accepting and verifying the outputs produced;
- clarify who remains accountable for decisions, deliverables, and their consequences;
- identify the value contributed by the student;
- govern the use of AI through principles relating to ethics, privacy, integrity, copyright, and compliance;
- make explicit the trade-offs between speed, quality, learning, and the exercise of human judgment.
This approach directly aligns with the philosophy behind AI Weather: a measurement can provide useful information, but it cannot interpret a situation on its own or make a decision on behalf of the user.
NeoMundi invited to meet with students
The initiative will extend beyond the awareness campaign displayed on the College’s screens.
NeoMundi has also been invited to Champlain College Saint-Lambert to present its approach directly to students and engage with them in the classroom.
On this occasion, Sébastien Favre-Lecca, founder and Research Director of NeoMundi, will meet with students enrolled in the Business Administration with AI program, as well as computer science students taking the Business Fundamentals course.
The Business Administration with AI program combines a strong foundation in management, finance, accounting, and marketing with the applied use of AI in decision-making, data analysis, operations, and innovation.
It prepares students to use artificial intelligence tools in professional contexts while integrating ethical reasoning, data protection, privacy, and governance considerations.
During the session, students will have the opportunity to explore several practical issues related to generative artificial intelligence:
- understand why a model’s behavior can vary;
- discover what measurement signals can – and cannot -indicate;
- recognize situations that require greater caution;
- learn how to verify important claims;
- identify potential limitations, biases, and uncertainties;
- reflect on the user’s responsibility when working with an AI-generated response.
The objective is not to tell students whether they should or should not use artificial intelligence. It is to provide them with additional reference points so they can make their own decisions, question the outputs they receive, and exercise critical thinking.
Putting measurement at the service of judgment
In the industrial and cognitive revolution driven by artificial intelligence, the ability to produce an answer quickly is not enough. We must also know how to evaluate it, verify it, and decide what can responsibly be done with it.
This is precisely the complementarity explored through this collaboration: AI Weather makes certain variations in model behavior more visible, while the REACT framework helps structure students’ reflection and decision-making.
Measurement comes first, shedding light on the observed conditions.
Human judgment follows.
Measurement can inform a decision. It cannot make that decision on behalf of the user.
Understand AI Weather. Recognize the risks. Exercise judgment.