Generative AI refers to a branch of artificial intelligence focused on creating systems that can produce content, data, or outputs that resemble human-created content. Unlike traditional AI systems that rely on explicit programming and predefined rules, generative AI employs advanced machine learning techniques to autonomously generate new and creative outputs based on patterns it learns from existing data. The above text in this introduction was written by generative AI, specifically, ChatGPT-3.
There has been a noticeable increase in the use of generative AI recently, particularly concerning career development and job application activities. In many ways, using generative AI is similar to using a template from the internet – it can increase efficiency by providing a template, but you will still need to ensure the content is appropriate, accurate and high quality so it is not enough to simply copy and paste from the answers to your prompts.
Below you will find information on the potential benefits and pitfalls of using generative AI as a careers tool, as well as some advice for best practice and further resources.
Please also check the College Generative AI Tools Guidancefor information about using generative AI for anything related to academic work.
Gen AI tabs
Ideas for using generative AI
It can be difficult to know where to begin, whether you are writing a CV for the first time, drafting a cover letter, or trying to plan answers for an interview.
Generative AI can help you develop your thoughts into words on the page – and because it is trying to replicate human communication, you can be conversational in your interactions, which can make the process seem less daunting.
Check over documents
Once you've completed your CV or cover letter, you could upload it to the AI tool with the opportunity/role description you have written it for and ask for feedback – ask it to look for errors and how closely you match the role requirements.
Identify your strengths for a particular role
Have you seen a role you're interested in, but don't know how your skills match up to what they're looking for?
One way generative AI could help with this would be to upload your CV and the text from the job advert and ask the interface where your skills match up. It might identify things you were unaware of, or it might help you identify where your skills aren't coming through enough in your CV.
Using a tool like this in conjunction with other information available to you, like the Imperial Guide to CVs and Cover Letters, could help to strengthen your application significantly.
Run a personal mock interview
Our section on interviews includes useful advice on how to identify generic job interview questions that you might face. To take your interview preparation further, you should also research interview questions that are specific to the role, industry and company you are applying to.
You can upload the job advert or job description to a generative AI tool and ask it to suggest potential interview questions based on the data.
You can also ask it to suggest potential interview questions for a certain job role and industry – for example, you might ask: "I am applying for a role as a Data Analyst in the drug discovery branch of the pharmaceutical industry. Please suggest some interview questions for this role and industry."
Once you have your list of questions, you can plan and practice your answers in advance. If you feed these back into the generative AI, it can even provide basic feedback on whether you are answering the question effectively. Please note though, that you should not be scripting your answers to memorise or read from in the interview because you will need to be adaptable and use active listening in the interview itself, so this exercise should be used with caution.
Research companies or industries
There are many resources available to help you research companies and industries as part of your career development, as a starting point, try our What can I do with my degree pages - that offer links to subject-specific resources.
It can however be difficult to know where to start with your research, and this is also something generative AI can help with. You can ask questions about how to get into a particular field with your degree, what the common routes into a role for a UK-educated graduate are, or what recent innovations are being discussed in the industry.
There is a caveat here, which we will discuss in the pitfalls section under "not all AI is equal".
Generic application documents
Whichever generative AI tool you use, it does not know you well enough to write an insightful, authentic and tailored application document. What it does produce is likely to be generic, and inauthentic and may also look very similar to a document written for someone else who asked the same thing of the AI tool. Employers, recruiters and opportunity providers are likely to be aware of this too – nothing is stopping a recruiter from using generative AI to mock up a cover letter and using that to compare it against the ones being sent in.
Make sure you check over any documents written using generative AI as a drafting tool. Ask yourself, does this sound like me? Is this accurate? Is there anything else I'd like to add?
Garbage in, garbage out
"Garbage in, garbage out" comes from computer science and roughly means that the quality of output from a computer system is directly related to the quality of input it receives.
This principle applies to writing prompts for generative AI, so if you're planning to use these tools it is important to learn how to interact with them effectively and be prepared to review and revise anything you produce with them.
When using generative AI models to generate text based on prompts, the quality, clarity, and specificity of the prompt strongly influence the quality of the AI's response. If the prompt is vague, ambiguous, or poorly constructed, it can lead to inaccurate or nonsensical outputs. Conversely, a well-crafted prompt that provides clear context, guidelines, and relevant information tends to yield more coherent and relevant generated content.
To get meaningful and accurate results from generative AI, it's important to put effort into constructing effective prompts that convey the desired context and expectations.
AI can "hallucinate"
If generative AI "hallucinates," it means that the AI system produces outputs that are not accurate representations of the input data. Hallucinations in the context of generative AI refer to instances where the AI generates content that is speculative beyond the information it has been trained on, sometimes leading to fictional outputs.
For example, if a language model is given an incomplete CV and is asked to write a cover letter, it could generate a detailed but incorrect statement about an internship or experience you haven't undertaken. This could be considered a form of hallucination.
Hallucinations can occur when the AI extrapolates from patterns it has learned and creates content that goes beyond the provided input.
Researchers and developers are working to reduce the chances of this happening in future products and updates, but in the meantime, it is crucial to ensure you thoroughly check any documents produced with generative AI to ensure it is accurate to your experience.
Not all AI is equal
ChatGPT is a hugely popular generative AI tool, and ChatGPT-3 is currently freely available to use. However, this model's knowledge and information are based on data and events available up until the year 2021.
As a result, ChatGPT-3 may not have information about events, developments, or changes that have occurred after 2021. If you ask questions about more recent events or information that has emerged post-2021, the model might not be able to provide accurate or up-to-date responses.
Different generative AI tools may also have limitations. It is important to do your research about any tool you might use to ensure it is helping you produce good-quality documents. This means you should not rely solely on generative AI to do research or to produce documents.
Use effective prompts
Generative AI can only generate content based on the information given to it, and therefore it is important to feed the programme prompts that will effectively generate content that meets your requirements. Tips on how to do this include:
Give the programme clear and specific tasks. Define your request clearly and be specific about what you want the AI to generate. Vague or ambiguous prompts can lead to unexpected outputs.
Vague: Generate some interview questions.
Clear: If I upload a role description, could you suggest some interview questions I could be asked at an interview for this opportunity?
Contextual information helps the AI generate more relevant content. For example, feed in your CV if you want to ask the programme to generate a tailored cover letter because otherwise, the AI has no context about your skills and experiences.
Desired tone: If you have a specific style, tone, or voice in mind, mention that in the prompt. This guides the AI's output to match your expectations. For example, "suggest a short opening of no more than three lines for a personal statement in a professional tone based on the CV and opportunity description I have uploaded."
Constraints: If there are any constraints, restrictions, or guidelines to follow, communicate them. For instance, if you want a response within a certain word limit or you want the AI to avoid certain topics, make sure this is part of your prompt.
For example, "I have uploaded information about an opportunity. Suggest some interview questions based on this role, but avoid highly technical questions and focus mostly on motivation questions."
Background information: If the topic is niche or specialised, provide some basic background information. This helps the AI understand the context and generate more accurate content.
This could be relevant if you are applying for an opportunity in a highly specialised area. There may be some text on the company's "about us" page that could provide this background information.
Prompt length: While being clear and specific is important, overly long prompts might confuse the AI. Keep the prompt as concise as you can while conveying all the necessary information – you might decide to refine the output by asking questions in stages if your prompt is getting too long – see "progressive prompts" in the Review and Revise tab for an example of this.
Review and revise
The content generated by the AI will likely need refining and editing before you can use it. Below are some tips to help with this:
Progressive prompts: If the initial response isn't what you're looking for, consider using progressive prompts, which means building upon the previous responses to guide the AI in the right direction. For example, once some content has been produced, you could ask the programme to "rewrite this in a formal tone," or "rewrite this and take out the academic grades."
Iterative refinement: Don't hesitate to refine your prompt if the initial output isn't satisfactory. Tweaking the prompt can often lead to better results. This is different to progressive prompts because you will change the initial prompt rather than asking follow-up questions.
Try both options and see what works best for you!
As well as refining the output directly in the AI programme, you should also edit any content produced to ensure it is accurate to you and your experience, and that it isn't generic and non-specific. Think of content produced by generative AI programmes as a first draft – you will still need to finalise the content and style to suit your purposes.
Examples of use
Below is an example of using generative AI to research a company and generate a draft of a cover letter for that company.
Step one: Ask the programme to help with your research. Make sure your prompt is appropriately detailed.
Example prompt: I am applying for a position at Company X as a Role Title. Please find information about Company X's values and mission as well as recent news about their work, avoiding news stories older than 2018.
Step two: Share your CV with the programme and ask it to identify where you match the role advert.
Step three: Based on this information, ask the system to generate a cover letter.
IMPORTANT NOTE – This is likely to be generic and will have only limited relevance to you as an individual. Remember to edit any content produced to ensure it is accurate to you and your experience, and that it isn't generic and non-specific.
Step four: Edit and tailor the resulting cover letter until you are confident it demonstrates your enthusiasm and skills relevant to the role.
In short, generative AI is one tool to help you during the application process and works best when used as a starting rather than finishing point for your documents.
- Imperial College statement on generative AI [webpage]
- Charlotte Whitehead – Can ChatGPT help your career? [LinkedIn blog post]
- Silei Cheng et al – Prompting GPT-3 to be reliable [links to PDF download]
- The Forage – We asked ChatGPT to write cover letters. Here's what it got right and wrong. [Article]
- Digital Waffle – The ultimate guide to using ChatGPT for CVs, cover letters and job interviews [Article]
- Raj Sidhu – What ChatGPT changes recruitment FOREVER [YouTube video]
- Forbes – Prompt engineering boosted via are-you-sure AI self-reflective self-improvement techniques that greatly improve generative AI answers [Article]