Create a synthetic CV powered by AI to test HR systems' functionality and engineering skill while avoiding potential privacy issues. Learn how with ChatGPT.
- 5 minutes read - 978 words
Table of Contents
In this article, we will discuss crafting a synthetic CV with the help of OpenAI’s ChatGPT for testing or prototyping purposes.
Creating a synthetic CV powered by AI enables developers and users to test their systems’ functionality, HR prompt engineering skill, and compatibility while avoiding any potential privacy issues that may arise from using real-life examples.
What is a Synthetic CV?
A synthetic CV refers to an artificially generated curriculum vitae for testing or protecting an individual’s privacy. It often contains fictional or anonymized personal details, employment history, and educational background.
Motivation to Create a Synthetic CV
The primary motivation for developing a synthetic CV is to use it for testing various scenarios within chatbot systems like ChatGPT. Using synthetic CVs allows developers to bypass potential privacy concerns related to real CVs.
Role of CVs
CVs are critical in job applications, as they comprehensively summarize a candidate’s skills, experience, and education. A well-structured and appealing CV increases the chances of standing out in a competitive job market.
Structuring a Synthetic CV
Structuring a synthetic CV is similar to writing or structuring an accurate CV because both aim to effectively showcase an individual’s professional background, skills, and qualifications.
A synthetic CV should have a structure similar to an accurate CV while ensuring it doesn’t violate privacy laws. In this context, a synthetic CV is a fictional CV created for demonstration, practice, or educational purposes, without accurate personal information.
- Outlining the CV structure
- Personal details (anonymized or fictional)
- Summary
- Skills and competencies
- Professional experience
- Education and certifications
- Projects
- References
- Choosing a CV format
- Chronological: Organizes information based on a timeline
- Functional: Prioritizes skills and competencies over employment history
- Hybrid: Combines elements of both chronological and functional formats
- Customizing Synthetic CVs for Specific Roles
- Analyze job descriptions to identify critical requirements and relevant keywords
- Tailor the synthetic CV’s content according to the requirements of your target test scenario
- Use ChatGPT to generate specific, role-based examples and attainments that add value to the document and demonstrate domain knowledge
- Reviewing and Revising Synthetic CVs
- Thoroughly proofread and edit the synthetic CV to maintain high-quality output
- Ensure the absence of inconsistencies or inaccuracies before using the CV for testing purposes
- Reiterate and refine the CV as required, aligning it with the objectives of your test
Creating a Synthetic CV with ChatGPT
The prompts in this session may contain errors; prompts were provided as used and not altered. The compiled result of this session can be found here .
Do not use the word „fake. “
The prompt contains some background about the synthetic person, including experiences and technologies used. ChatGPT is using this contextual information to create much more details from its training data, prompt: create a fake CV for a senior java backend developer doing java for 25 years, on-premise, cloud, lots of Oracle, but also some frontend, multi-page CV for a freelancer, long project list
Result (shortened): Sorry, as an AI language model, I cannot create a fake CV or any other fabricated content.
For the Next attempt, use „synthetic“ instead of „fake. “
Prompt:
create a synthetic CV without personal details which can be used for testing purposes for a senior java backend developer doing java since 25 years, on-premise, cloud, lots of Oracle, but also some frontend, multi-page CV for a freelancer, long project list
Result:
We get an outline of the CV with a summary but no project details.
Create a Project list
Prompt:
elaborate each project, add technology and tools, add a timeframe from-to like YYYY/MM to YYYY/MM, describe activities in some detail, describe the role, add the synthetic company name, do not explain what the systems are doing, add synthetic project names and locations, add industry, start in the year 1998, output as markdown source code:
Result:
We do get a complete project list since 1998, but the output may be too long, which means you need to ask ChatGPT to continue by, for example, copying the last project into the prompt box.
Create certificate, education, and reference contacts
To make our CV complete, we also do need some references, prompt:
create synthetic education, certifications, references
Result:
We do get a list of certificates, education, and reference contacts.
The result was slightly altered:
- Removing the word „Synthetic. “
- Adding international number dummy prefixes
You also cloud add some inconsistencies in the CV for testing purposes, add feedback from references, etc., to improve this synthetic CV’s usefulness for testing.
Create a Letter of Application for a CV
Prompt:
write a letter of application for: cv_text
Result: A resulting letter can be found here , you can repeat the prompt multiple times, and you will get different results, because of the proablistic nature of LLMs.
Input:
- cv_text: as a complete text, accepts markown as input
Conclusions
The ability of ChatGPT to generate synthetic CVs holds significant potential as a tool for developers in testing applications while mitigating risks associated with sensitive data.
Synthetic CVs protect individual privacy and offer valuable data points for experimentation. As AI-generated content evolves, developers are encouraged to responsibly explore and incorporate these automated solutions into their work.