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Ethical Scan

Completion requirements

The EKITIA association has developed this tool to facilitate the identification of ethical issues for any project based on data (personal, geolocated, measurements, images, videos, etc.) at any stage of the project's life cycle.
It is based on the EKITIA ethical charter, which formalises 21 principles for the ethical use of data and artificial intelligence around societal, individual, environmental and governance issues.
 
⚠️ Please note! The results obtained are partial and aim to highlight likely issues that require vigilance. This tool does not replace impact studies and other more precise or even mandatory assessments that must be carried out to ensure projects comply with regulations.

Ethical Scan
11 questions that helps identify whether a project raises potential ethical risks or issues

The EKITIA association has developed this tool to facilitate the identification of ethical issues for any project based on data (personal, geolocated, measurements, images, videos, etc.) at any stage of the project's life cycle.
It is based on the EKITIA ethical charter, which formalises 21 principles for the ethical use of data and artificial intelligence around societal, individual, environmental and governance issues.
 
⚠️ Please note! The results obtained are partial and aim to highlight likely issues that require vigilance. This tool does not replace impact studies and other more precise or even mandatory assessments that must be carried out to ensure projects comply with regulations.

Socio-environmental Impact
1

Does your project conflict with any of the Sustainable Development Goals (SDGs) or with your organization’s corporate social responsibility policy?

Example: Your project conflicts with SDG 3 — ensuring healthy lives and promoting well-being for all at all ages.

2

Will your project require significant energy consumption?

Example: Do you need large computing capacities for tasks such as training deep learning models or processing real-time data, as in the case of a generative AI for content creation?

3

Does your project involve processing large volumes of data?

Example: Are you using massive datasets, such as satellite images or real-time data streams from IoT sensors?

Discrimination risk
4

Will your tool assist in making important decisions about individuals or organizations?

Example: Could the solution you are developing influence critical decisions, such as job application evaluations or eligibility for social benefits?

5

Is there a risk, even if identified and manageable, that your project could reinforce discrimination or stigmatization against certain individuals or groups?

Example: Could your project unintentionally disadvantage certain groups? For instance, you are developing a credit scoring algorithm that penalizes some socio-economic categories due to bias in the training data.

Quality of results and robustness of algorithms
6

Does the quality of your datasets (completeness, representativeness, etc.) significantly impact the relevance of your results?

Example: If your data are incomplete or biased, could that distort your project’s outcomes, as might happen with a recommendation algorithm based on non-representative demographic data?

Sensitive or strategic data
7

Does your project involve processing confidential data (personal, sensitive, or strategic)?

Example: Are you handling information such as health records, financial data, or personally identifiable information? For instance, you are developing a healthcare app that stores electronic medical records.

Impact on end users
8

Will your project reach or affect the general public?

Example: Is the solution you are developing intended for use by a broad segment of the population, such as a consumer mobile app for managing urban transportation?

9

Will your digital solution transform daily professional life and significantly change how a job is performed?

Example: Are you developing a solution that automates repetitive accounting tasks, freeing up time for strategic consulting? Or could your AI application be a game-changer for radiologists by automatically detecting anomalies in scans, allowing them to focus on complex cases and improve diagnostic accuracy?

Regulatory compliance and AI-related risks
10

Does your project involve AI systems that may present risks under applicable regulations?

Example: Are you developing an AI system to be used in sensitive sectors such as healthcare for medical diagnosis, in defense, or using a general-purpose off-the-shelf AI system within your project?

Collaboration between different stakeholders
11

Does your project involve collaboration between multiple stakeholders?

Example: Are you working with other companies, institutions, or subcontractors to develop or deploy this project? For instance, you are developing an IoT project that requires integrating sensors manufactured by an external partner.