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How to use AI to prepare for a job interview

1 Reply Christopher Roberts

AI isn’t just for big organisations, there are many ways you can use AI tools to help improve your speed and effectiveness at completing everyday tasks too.

One example is to help you prepare for a job interview. It can be difficult to know how to spend your time effectively, so why not enlist the help of an AI chatbot like Bard or ChatGPT to come up with ideas, and better still, get it to do some of the work for you?

Job Spec

Where to start? First, try feeding ChatGPT the job description you’ve been given, and ask it to suggest how you should approach interview prep. Here are a few examples of prompts to try:

Prompt 1

I've got an interview for the attached role, could you give me a 50 word summary of how you'd advise I prepare?

If you can’t upload documents, just copy the text after the prompt instead.

Prompt 2

I need to prep for an interview tomorrow. I only have 20 mins. Please read the background info doc (attached) and give me a list of 5-10 bullet points walking me through how to use the 20 minutes to get ready. The list should take me no more than 3 minutes to read.

The more specific you are on your requirements, the better the answer will be. For example, you could ask for it to answer in a numbered list, or to display it in a table. You could ask for it to be no more than 50 words, or for it to be written so that it could be easily understood by a five year old.

Prompt 3

Help! I've got an interview and I'm really out of practice. Could you read the job spec and give me some pointers on what I should be doing?

Sometimes being more creative with your prompt can lead to a more interesting response from the AI.

An example conversation you could have with ChatGPT

Gather More Info

Don’t forget, if you don’t get the response you want, or you need more information, try using follow-up prompts. For example, if it tells you to check out the organisation’s website, ask it to do the legwork for you, here are some examples of how you can ask that.

Follow-up prompt 1

That's great, thanks. Here's the library's website, could you read it and provide me a consise summary that I can use to quickly get up to speed before my interview? www.example-library.org/about

Follow-up prompt 2

I don't know if they have a website actually. Could you search the web and see if you can find one? If they don't, how would you suggest I research the libary more, in the most time effective way, given I've only got 20 minutes to prepair?

Most AI chatbots are designed to understand natural language, so write back as though you were talking to a person. Good spelling and grammar will help you get a better response the first time around, but don’t be afraid to be creative with the instructions you use.

Caution: be mindful not to share personal information with an AI chatbot. If you wouldn’t tell something to a random stranger, don’t type (or paste) it into a chatbot either.

Questions

In any interview, you’re going to be asked questions, so why not practice with the help of AI?

Question prompt 1

I haven't interviewed for this sort of position before, could you give me a list of 5 questions that you think I could be asked, based on the job description?

Question prompt 2

Let's role play the interview, you ask me a question the interviewer is likely to ask, and I'll type my reply. You can then give me feedback on my answer and tips to improve.

Question prompt 3

Could you provide a list of the 5 most common interview questions and 2-3 bullets on how to answer them?

It’s also a good idea to turn up with a few questions of your own. You can ask the AI to help you format these, or if you’re running short of ideas, ask it to give you some suggestions!

Follow-up questions prompt

What questions could I ask the interviewer to help them see I'm interested in the role and want to work for this organisation?

Sharing Ideas

Do you have any tips on how to use ChatGPT to prepare for an interview? Why not help others too, by sharing your prompt ideas below.

If you’re early to this post and the comments section is a little empty, why not ask Bard to come up with some ideas for you instead!

Asking Bard how to prompt ChatGPT to get ready for a job interview

The Future of Work: Preparing for AI

2 Replies Christopher Roberts

This is the first in a new series on AI – Artificial Intelligence.

Artificial intelligence is rapidly changing the way we work, bringing about new opportunities and challenges. In this article, we’ll explore how we can prepare for the changes ahead.

Efficiency

AI is being increasingly used to automate tasks and processes in the workplace. By taking on mundane and repetitive tasks, AI can free up employees to focus on more complex and creative work. For example, AI can automate data entry and analysis, freeing up time for employees to focus on strategy and decision-making. This can lead to increased efficiency, productivity, and profitability for organisations.

An AI future - an image generated by DALL·E

AI can also support decision-making processes by providing real-time data and insights. This can help businesses to make better decisions faster and more accurately, improving their competitive edge. AI can also help to identify patterns and trends in large datasets, providing valuable insights that can be used to inform strategy and decision-making.

Ethics

While AI can bring about many benefits in the workplace, it’s important to consider the ethical implications of its use. One key concern is the potential impact on employment. As AI becomes more advanced, it’s likely that it will replace some jobs that are currently done by humans. This could lead to job losses, particularly in industries that rely heavily on manual labor or routine tasks.

Another concern is bias. AI systems are only as unbiased as the data they are trained on. If this data is biased, the AI system will be biased too. This can lead to discrimination and inequality in the workplace. It’s important to ensure that AI systems are trained on diverse and representative data to avoid bias.

Preparing for the Future

To prepare for the future of work in the age of AI, it’s important to focus on skills that cannot be automated. These include creativity, problem-solving, and emotional intelligence. By focusing on developing these skills, employees can enhance their value in the workplace and prepare for the changes ahead.

An AI minimalist future - an image generated by DALL·E

It’s also important to consider the ethical implications of AI use. Organisations should prioritise diversity and representation in their data and AI systems to avoid bias. They should also provide training and support to employees who may be affected by the introduction of AI.

Conclusion

AI is going to take bloggers jobs!!! The content of this post was written entirely by the AI ChatGPT, based on a few prompts I gave it. All I’ve done is add this conclusion and the opening lines. Oh, and the images were generated by DALL·E – completely new images, generated specifically for this post.

How?

I’ll share that and more in future posts.

Some Thoughts on Bias

3 Replies Jonny Hankins

A Little story of bias

A father was driving his two children to watch a football match when they were involved in a terrible accident. The driver was killed immediately, as was one of the boys. The youngest child was sitting in the back on his car seat, survived the accident but was seriously injured.

The young child was taken to hospital where he was rushed into an operating theatre where they hoped they could save his life.

The doctor entered the room and looked at the patient, froze and said “I cannot operate on this boy, he is my son!’

Bias within Data

If you asked the question of how the boy could be the doctor’s son you are falling in a trap of bias. The doctor in the story is the child’s mother (obviously), but that may not be the first solution that comes to mind. In many societies we are brought up to see doctors as male, and nurses as female. This has really big implications if we are using computers to search for information though, as a search machine that uses content generated by humans will reproduce the bias that unintendedly sits within the content.

The source of the bias could be from how the system works. For example, if a company offers a face recognition service and uses photos posted on the internet (for example categorized in some way by GOOGLE), there will be a lot more white males than girls of Asian background. The results will be more accurate for the category with the largest presence in the database.

If a banking system takes the case of a couple who declare an income together, it will presume that the man’s income is higher then that of the woman’s and treat the individuals accordingly, because from experience the data shows that men’s income is higher then that of women and this generalization will become part of the structure.

The problem with language is also easy to see. If the example above of the doctor problem can be in some way ‘seen’ in the vast amount of text analyzed and used for an algorithm, then proposals and offers will differ according to gender.

Let’s take how we describe ourselves for a moment. A male manager will use a set of descriptive terms to describe himself that will differ from those used by a woman, he might be assertive, but she is more likely to be understanding and supportive. A system that unwittingly uses a dataset based upon (or even referring to) language used in job adverts and profiles of successful candidates will replicate a gender bias, because more proposals will be sent to people who use the language that reflects the current make-up of the employment situation.

In short: More men will be using the language that the system picks up on, because more men (than women) in powerful positions use that type of language. The bias will be recreated and reinforced.

In 2018 the State of New York proposed a law related to accountability within algorithms, Take a look at this short description, and the European Commission released a white paper on Artificial Intelligence – A European approach to excellence and trust in 2020. It might be more important an argument than it first appears.

There is lots of literature about this problem if you are interested, a quick online search will offer you plenty of food for thought.