AI Transparency Notice
Digital Skills Compass™
Visit: ai4sp.org/transparency for details.
This notice provides transparent information about the AI system you are using, outlining the system’s capabilities, limitations, biases, data usage practices, and safety measures. We want to empower you with the knowledge needed to understand how this AI works, what it can and cannot do, and how your data is handled.
By providing this transparency, we enable you to make informed decisions about your interactions with our AI technology.
Intended Use and AI Features
The Digital Skills Compass™, created and maintained by AI4SP, uses Artificial Intelligence (AI) to generate personalized reports with recommendations to help individuals assess their gaps in digital skills. The Digital Skills Compass is based on 20 targeted questions across seven dimensions. These questions are designed to evaluate digital, problem-solving, AI, and collaborative skills, identify areas needing improvement, and set personal benchmarks for growth.
AI Used
- Baseline Model: We use GPT-5.2 from OpenAI, Gemini 3 Pro from Google, and Claude Opus 4.5 from Anthropic.
- Our Application: We’ve built upon these base models to create the Digital Skills Compass™.
How the AI is Trained
Baseline Model
GPT-5.2, Gemini 3 Pro, and Claude Opus 4.5 are trained on large amounts of publicly available data from the Internet. For detailed information on how these models were created, please visit the official websites of OpenAI, Google, and Anthropic. It’s important to note that there are ongoing discussions about data-sourcing practices and the potential copyright implications of using publicly accessible data to train large language models.
Our Application
We evaluated accepted methodologies to assess digital skills, analyzed thousands of job posts, and gathered insights from our proprietary knowledge base of more than 18,000 AI tools. The goal was to identify the minimum skills needed to participate in the new digital economy AI is reshaping.
Over 350,000 individuals have completed the assessment (you can see the up-to-date count at skills.ai4sp.org), and we have calculated the average by industry. Individuals can then compare their results with their sector’s average. This average is not a goal per se but a reflection of the population’s level of digital skills.
Our AI modules use all this data to suggest personal development plans, practical tips, and next steps.
We never use Personally Identifiable Information (PII) to train our AI modules.
Data Usage
| Aspect | Details |
|---|---|
| Use of Personal Identifiable Information (PII) | None |
| PII security | Not Applicable (not collected) |
| Data used for AI Training of our models | YES (aggregated data, non-PII) |
| Data shared with AI providers and used by them for training their models | NO |
Notes:
- No personally identifiable information (PII) is collected or used. Our app uses only drop-down menus and sliders, preventing accidental PII input.
- We collect sector, employee count, and self-assessment responses; responses are used for report generation and cannot be tied to individuals.
Known Biases
Potentially Inherited Biases
Our solution may inherit the following biases from its baseline models:
- Language bias favoring English-language content and Western perspectives.
- Demographic bias reflects the data available on the internet.
- Temporal bias due to the knowledge cutoff date of the baseline models.
- Representation bias in business practices, potentially favoring larger or tech-centric companies.
- Geographic bias, possibly overrepresenting practices from regions with high internet usage.
- Industry-specific bias, potentially favoring sectors with more online presence or documentation.
Inherited Biases Mitigation Efforts
We have taken steps to mitigate many of these biases:
- Our proprietary dataset includes information from 150,000 organizations and an analysis of 10,000 AI tools from global innovators.
- We have tuned our models based on input from over 350,000 individuals who have taken the assessment, and we work across over 15 industries in the private sector and 17 in the nonprofit and government sectors.
- As we evolve, our geographic coverage includes data from 70 countries.
Known Biases Specific to Our Application
- Potential bias towards common AI adoption patterns in surveyed organizations.
- Possible recency bias in AI technology recommendations.
We continuously work to identify and further mitigate these biases in our application.
Limitations
Our AI has some constraints:
- Scope: This tool is designed to generate recommendations related to improving digital skills. By design, it cannot offer any other type of advice.
- Knowledge cutoff: The model’s knowledge is continuously updated.
- Context: It may not fully capture the unique nuances of your specific situation, as the model relies only on industry and answers to 20 questions as references to personalized advice.
The Digital Skills Compass™ provides general guidance and should be a starting point for your personal and professional development related to digital skills, not a definitive plan.
Information Reliability and Accuracy
While generally reliable, our AI can sometimes produce incorrect or inconsistent information, a phenomenon often called “hallucinations” in AI:
- It might generate plausible-sounding but inaccurate recommendations.
- Outputs may not always reflect current AI technologies or business practices.
- Recommendations may be influenced by common practices from large organizations and academia.
We have mitigated inaccurate responses with our proprietary and patent-pending methodology.
Human Oversight
Our team regularly reviews and updates the AI’s recommendations based on real-world feedback and new developments in AI technology. We conduct regular focus groups and gather input at workshops, keynotes, and events where we collect direct feedback from users of our tool. This continuous engagement with our user community ensures that our AI system remains relevant, accurate, and aligned with the evolving needs of businesses across various sectors.
User Actions
- Interpreting Biases: Consider that recommendations may be influenced by common practices in large organizations and academic institutions and may not perfectly fit your unique situation.
- Seeking Human Review: For critical decisions about your career plan and personal development, we recommend consulting with trusted adults, counselors, coaches, professors, teachers, or managers, as well as local schools, community colleges, universities, and organizations focused on education and adult education.
Continuous Improvement
Our AI model is regularly updated to enhance performance and address issues. We update this notice when significant changes occur.
User Feedback
To provide feedback, click on the following link: ai4sp.org/#contacto