AI & DATA IN ACTION - Day 2

 

 

Creating for humans: diversity, bias and imagination in the age of generative AI

A session to explore how to design more inclusive and responsible generative AI. Through concrete, creative examples, we will discuss cultural biases, the diversity of datasets, and the human impact of AI-generated content at scale.

Giovanna Graziosi Casmiro (French Institute of Fashion)

AI, a lever for sustainable performance: what you need to know to make the adoption of AI in your company a success

Artificial intelligence is now a major driver of sustainable performance for businesses, provided it is deployed methodically and thoughtfully. To ensure successful adoption, it is essential to start with actual business needs, not the technology itself. AI must serve a specific purpose: to increase productivity, improve the customer experience, or automate low-value-added tasks.

Elie Bensoussan (GETTIA)

Deploying humanoids: risks, regulations and potential

As humanoid robots move out of the laboratory and into industrial, logistics, medical and public environments, their integration raises critical new questions about safety, compliance, socio-economic impact and corporate responsibility.

Virginie Cuvilliez (ISACA France), David Ofer (French Cybersecurity Federation), Simon Bunel (École Normale Supérieure)

From data to people: inclusive AI for healthcare, finance and the public sector

How can we design AI systems that truly serve all populations? This panel will bring together leaders from the healthcare, finance, and public sectors to discuss concrete projects where technological inclusivity has transformed outcomes—from personalized preventive care to streamlined administrative processes. A session focused on the real impact of team diversity on the quality and equity of AI systems.

Adia DANSO (Tech with Women), Angela Naser (WOMEN IN TECH), Jacqueline Tejeda Carnot (Roche), Gloria Fataki (UN Women France), Frédérique Deschamps (Bpifrance)

 

 

 

AI Fresco Workshop: Understanding AI, its business uses and impacts for responsible integration

Workshop to raise awareness of the impacts of AI by identifying business use cases and establishing conditions for success to ensure the successful integration of AI and effective risk management.

What AI says about us: Data and industrialization at source

AI is everywhere. But before we talk about industrialization, we need to ask ourselves what drives it: data. Like us, AI learns from what we feed it. Feed it false information, and it will repeat the error. Feed it bias, and it will amplify that bias. Give it quality data, and it will be a powerful tool. In this talk, we’ll explore the human-machine relationship as it relates to data, intelligence, and decision-making. Between technophile fantasies and technophobic fears, the most important thing is to realize one thing: before we industrialize AI, let’s industrialize the quality of our data.