Knitting (Artificial Intelligence) vs. Crocheting (Human Writing) a Resume

The hottest trend lately is using Artificial Intelligence (AI) for anything related to creating content for stories, blogs, books, illustrations – and resume writing. Clients submit their resumes (designed by AI), thinking they can ‘beat’ the filter. They don’t understand why they are not getting any responses or calls for employment. 

Here is the secret.

Artificial Intelligence uses a compendium of resumes’ out there’ on the web to ‘learn’ how to create new resumes. Unfortunately, AI often cannot distinguish between ‘bad’ and ‘good’ resumes. The AI algorithm groups both types to create an ‘artificial’ resume. In addition, AI may add elements that gum up the Automatic Tracking Systems (ATS), e.g., tables, icons, and columns, making the resume look like a mess on the other side of the firewall after it gets parsed into the SQL database.

Recruiters and ATS are getting savvy to the practice of using AI to build resumes and are incorporating ‘AI identification’ applications. These applications identify an applicant’s resume created by AI and automatically reject that resume. Some websites advertise services to help your resume ‘get noticed’ by recruiters – and these websites use AI to develop suggestions and wording. And the AI suggestions still come from both bad and good resume examples. Recruiters prefer resumes rich in objective wording, rich achievement descriptions, and documentation proven by metrics. An AI system can’t do that.  

The method of assimilation and creation in AI is similar to needle crafting. One can build a knitting machine, and the stitches will be uniformly consistent. Knitting is a thread craft using two needles that can be machine-engineered. One can quickly create a machine-generated blanket or sweater, and that machine can make the same item repeatedly. Crochet is a thread craft using only one needle, but one cannot build a crochet machine per se. The manipulation of the needle, ‘catching’ of threads on either side of a stitch, or the complication of the stitch (twists, double, or triple stitches, or catching of threads 1-2 rows down and up again) in crocheting are just too complicated for a machine to imitate.

The same goes for AI-built resumes and hand-crafted (human-written) resumes. Artificial Intelligence written resumes use injections of subjective and vague terminology. Because the resume owner has not contributed specifics (e.g., metrics), the result is a boring conversation of vague and broad terms that don’t showcase the applicant’s career achievements. Job seekers are not professional job applicants or resume writers, so they write what they can, and with most automation processes, their efforts result in – garbage in and garbage out. Artificial Intelligence will not improve a bad resume; it may worsen it. 

Recently, in the news, AI users have discovered that biases have been built into AI engines and algorithms, creating artificial ‘prejudicial influences’ on AI-generated results. While the news focuses on images being produced, don’t for a minute believe that AI’ prejudicial influences’ are not built into generating word content. When writing a resume – focus on objectively worded, unbiased, documentable facts about career achievements. 

Most resumes that get through the ATS filters are read and analyzed by recruiters. It’s somewhat easy to tell a HW resume from an AI resume. Artificial Intelligence-based resumes concentrate on using ‘fancy’ and ‘impressive’ wording to write the resume. Human-written resumes concentrate on using easy-to-understand layperson’s terms to richly describe what the applicant physically did and what resulted from those actions (e.g., revenue or productivity increases and cost or labor savings).   

Scientists working on AI-generated content applications are creating significant technology improvements. But, more advances need to be achieved before AI can be trusted to generate an attention-grabbing, practical resume for job seekers. It is acceptable to consider reviewing an AI-generated resume to get ideas for content in an HW resume.

I am not discounting using AI (I used an AI program to check my grammar in this story). While some job seekers pursue AI-generated resumes, thinking the AI resume will get their resume through the firewall, they may gain more momentum and hits on HW-generated resumes in the ATS platforms. Users should be careful about the weight they emphasize while relying on the process. Artificial Intelligence is not perfect. The final AI result still needs to pass the ‘human’ test for recruiters to provide serious consideration to job applicants’ qualifications.

Dawn Boyer, Ph.D., owner of D. Boyer Consulting – provides resume writing, editing, publishing, and print-on-demand consulting. Reach her at Dawn.Boyer@me.com or visit her website at www.dboyerconsulting.com.

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Knitting (Artificial Intelligence) vs. Crocheting (Human Writing) a Resume

The hottest trend lately is using Artificial Intelligence (AI) for anything related to creating content for stories, blogs, books, illustrations – and resume writing. Clients submit their resumes (designed by AI), thinking they can ‘beat’ the filter. They don’t understand why they are not getting any responses or calls for employment. 

Here is the secret.

Artificial Intelligence uses a compendium of resumes’ out there’ on the web to ‘learn’ how to create new resumes. Unfortunately, AI often cannot distinguish between ‘bad’ and ‘good’ resumes. The AI algorithm groups both types to create an ‘artificial’ resume. In addition, AI may add elements that gum up the Automatic Tracking Systems (ATS), e.g., tables, icons, and columns, making the resume look like a mess on the other side of the firewall after it gets parsed into the SQL database.

Recruiters and ATS are getting savvy to the practice of using AI to build resumes and are incorporating ‘AI identification’ applications. These applications identify an applicant’s resume created by AI and automatically reject that resume. Some websites advertise services to help your resume ‘get noticed’ by recruiters – and these websites use AI to develop suggestions and wording. And the AI suggestions still come from both bad and good resume examples. Recruiters prefer resumes rich in objective wording, rich achievement descriptions, and documentation proven by metrics. An AI system can’t do that.  

The method of assimilation and creation in AI is similar to needle crafting. One can build a knitting machine, and the stitches will be uniformly consistent. Knitting is a thread craft using two needles that can be machine-engineered. One can quickly create a machine-generated blanket or sweater, and that machine can make the same item repeatedly. Crochet is a thread craft using only one needle, but one cannot build a crochet machine per se. The manipulation of the needle, ‘catching’ of threads on either side of a stitch, or the complication of the stitch (twists, double, or triple stitches, or catching of threads 1-2 rows down and up again) in crocheting are just too complicated for a machine to imitate.

The same goes for AI-built resumes and hand-crafted (human-written) resumes. Artificial Intelligence written resumes use injections of subjective and vague terminology. Because the resume owner has not contributed specifics (e.g., metrics), the result is a boring conversation of vague and broad terms that don’t showcase the applicant’s career achievements. Job seekers are not professional job applicants or resume writers, so they write what they can, and with most automation processes, their efforts result in – garbage in and garbage out. Artificial Intelligence will not improve a bad resume; it may worsen it. 

Recently, in the news, AI users have discovered that biases have been built into AI engines and algorithms, creating artificial ‘prejudicial influences’ on AI-generated results. While the news focuses on images being produced, don’t for a minute believe that AI’ prejudicial influences’ are not built into generating word content. When writing a resume – focus on objectively worded, unbiased, documentable facts about career achievements. 

Most resumes that get through the ATS filters are read and analyzed by recruiters. It’s somewhat easy to tell a HW resume from an AI resume. Artificial Intelligence-based resumes concentrate on using ‘fancy’ and ‘impressive’ wording to write the resume. Human-written resumes concentrate on using easy-to-understand layperson’s terms to richly describe what the applicant physically did and what resulted from those actions (e.g., revenue or productivity increases and cost or labor savings).   

Scientists working on AI-generated content applications are creating significant technology improvements. But, more advances need to be achieved before AI can be trusted to generate an attention-grabbing, practical resume for job seekers. It is acceptable to consider reviewing an AI-generated resume to get ideas for content in an HW resume.

I am not discounting using AI (I used an AI program to check my grammar in this story). While some job seekers pursue AI-generated resumes, thinking the AI resume will get their resume through the firewall, they may gain more momentum and hits on HW-generated resumes in the ATS platforms. Users should be careful about the weight they emphasize while relying on the process. Artificial Intelligence is not perfect. The final AI result still needs to pass the ‘human’ test for recruiters to provide serious consideration to job applicants’ qualifications.

Dawn Boyer, Ph.D., owner of D. Boyer Consulting – provides resume writing, editing, publishing, and print-on-demand consulting. Reach her at Dawn.Boyer@me.com or visit her website at www.dboyerconsulting.com.



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