By Amy Do

Artificial intelligence is becoming more and more integrated with our daily lives, both at home and at work. According to Harvard Business Review, “…most business functions and more than 40% of all U.S. work activity can be augmented, automated, or reinvented with gen (generative) AI.” 

ChatGPT and other genAI are changing the landscape of content generation and prompting new questions surrounding sustainability and integrity. Learn more about this exciting new world and stay ahead of the curve.  

What is Generative AI?

Generative AI is “artificial intelligence (AI) that can create original content—such as text, images, video, audio or software code—in response to a user’s prompt or request. (IBM).” You’ve probably seen ChatGPT and Midjourney (or used it yourself)! 

The most common way to use genAI is to  ‘prompt’ it by typing a specific request into a chat box. There are a huge range of requests from ‘What can I make for dinner if I have 30 minutes and this list of ingredients?’ to, “Could you please generate a photorealistic image of Santa riding a dragon into battle?” Generative AI works for text-to-text, text-to-image, text-to-video, and text-to-audio outputs. 

As you can imagine, this technology has huge implications. Governments are still considering how to regulate use of this technology, and it’s not infallible—there are lots of examples of ChatGPT providing inaccurate information or full-on fabricating fictional information. Because of the black box nature of AI algorithms, not even the engineers know exactly how Language Learning Models (LLM’s) arrive at the conclusions they do. This has brought up concerns about algorithmic bias and copyright concerns, especially around artist IP.  

Interesting. How is it being implemented in the workplace?

You might have already noticed generative AI integrations into common workplace tools like Zoom’s note taking AI secretary, Canva’s Magic Studio tool, and Microsoft’s Copilot. Best practices for using each tool are provided along with training workshops and tutorials easily accessible online.  

Additionally, open access to ChatGPT and Midjourney means that working with genAI can be an extremely marketable skill to add to your professional toolkit.  

What do you mean, skill? Don’t I just tell it what I want and it makes it? 

Yes and no. For simple tasks like drafting replies to emails or generating tables out of existing data, a simple conversational query will work fine (ex.”Please generate a table for me of the to 10 most populous countries in the world with the populations in one column and the name of the country in the second column. Sort the table so the highest population is at the top and the lowest is on the bottom”). 

For higher order tasks such as project management or multi-step prompts, learning how to work with the program to get the desired result is a challenge.

Additionally, Language Learning Models often get stuff wrong. For example, ChatGPT can “hallucinate”, citing articles that have never been written, and occasionally malfunction. This is devastating to those who rely on it heavily as their sole source of information and can lead to disastrous consequences, especially when using it to complete tasks like plan a trip itinerary, learn a new skill, or do research into a new topic. Protect yourself from misinformation by fact checking regularly and asking LLMs to cite their sources. 

Harvard Business Review recommends asking LLMs to “think step by step” which creates a traceable chain of reasoning that allows users to check its work. This process of learning how to construct queries is called intelligent interrogation and is a sought-after skill in many industries. There are even jobs titled ‘prompt engineer’ – the entire position is oriented around query construction and iteration to achieve a target result. 

Judgment interrogation and reciprocal apprenticing are also best practices in embracing the use of generative artificial intelligence at work. I recommend reading the HBR article if you’re interested. For the sake of this article, I’m going to focus back on job searching.  

I hear that people are using it to write their resumes and cover letters. Is that ok? 

Language Learning Models supports content generation and copywriting. Chris Lavigne, head of production at Wistia said, “ChatGPT gives you an incredible starting point to get you from zero to one, so that you have something to poke at.” This can be especially useful if you have challenges working from scratch. 

However, strong prompt engineering is key. Telling ChatGPT, “Please write me a resume” will produce a coherent but extremely vague document that’s unlikely to lead to an interview. It’s important to know exactly what kind of resume you’re looking for, and what specific keywords, skills, or experience you want to emphasize within your prompt. For example, if you want feedback on the way that you’re describing your past internship, a prompt might look like this: 

“Hello. Here is the job description for the job that I am applying for: (paste entirety of job description). Here is the job description for my current internship: (paste entirety of internship description). Please:

• Come up with a list of key transferable skills from my current internship to the job description
• Explain step by step why those skills are transferable
• Provide examples of bullet points I could include in my resume that highlight those transferable skills using the STAR method. 
• Please also generate a list of keywords.”

As you can see, specific and thorough prompt engineering scaffolds content generation and upskilling. The response from this prompt is more likely to provide the necessary tailored copy that iterates on what you already have, and produces a copy that’s more appealing to employers. 

The same process can be utilized when it comes to cover letters: “Write me a cover letter for a front desk position” will provide a vague, likely outdated, overwrought document that doesn’t speak to your specific skills and qualifications. A better prompt might be: 

“Hello! Please help me write a cover letter! Here’s the job description: (paste entire job description). Here’s my resume (paste text of updated resume). Here’s my current cover letter (paste draft of cover letter). 

Please edit the above draft of my cover letter to emphasize (insert short list of relevant skills here). Address it to (department name) at (company)’s team, and keep it shorter than 500 words. The writing style should be conversational and positive. Explain step by step why you made the edits you made.”

Giving genAI the correct data from which to work off of is incredibly important to maintain integrity in the job search process. Do not fabricate qualifications or work experience in a resume, or submit an AI-generated document without careful edits. 

GenAI is a super powerful tool for many purposes. There’s lots of data and discourse around implications for the climate and the future of the job market. Job seekers can seize this opportunity to upskill on this frontier of consumer-facing technology. If you’re confused on how to utilize generative AI in your job search, book a coaching session to discuss best practices.

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