Job Huntress’s Secrets: Forget the Boss, go for the Bots!

Have you ever been hunted by robots? What about trying to get past their nets? If you are like me, looking for your new job, it happens to you more often than you think! Here we are, navigating the tides of the job market, these thrilling moments of being at the crossroads that will determine your life for a few years to come. You venture into the ocean ready for the battle, your colors flying high, your resume in its full shine. In the Old World, it is called curriculum vitae (CV), which means the course of life. The New World is pragmatic and prefers a resume: a brief bullet-pointed skeleton of your qualifications, skills, and previous work experience. I notice that hiring departments have now turned into fancy Talent Acquisition Teams. I feel flattered to be referred to as such and take it that every event in my future acquisition should feel like a talent show. The 2020 era has even popularized video conference job interviews, and one of the talent judges has eventually to press the promote-to-next-stage button! Still, to get to that exciting show moment, you need to pass the modern sieve, Artificial Intelligence (AI).

One of the wonders promised by companies offering AI-based resume parsers (aka Applicant Tracking Systems) is that they will free the Talent Acquisition Teams from the mundane work of digging through thousands of resumes and bring just the right applicants to the stage. Thus, 75% of resumes never get to a human. There is a lot of articles on how to style your resume to get past the AI gatekeepers. But we, huntresses, are still at a noticeable disadvantage. AI is not a fairy godmother who will push you to rule the kingdom, my dear Cinderellas. The ugly truth is that those fascinating AI sieves are inherently biased as they are trained on real-world data, in which women still have to fight for equal employment in many sectors. As shown in the research by Bolukbasi et al., 2016, “man” is to “computer programmer” as “woman” is to “homemaker”.

Since April 2020, I have taken courses on various aspects of Machine Learning (ML) and Artificial Intelligence from Accenture, AWS, Azure, and Google, and found out that the AI bias is a growing concern. Your resume gets a “to be or not to be” from a computer algorithm based on its training data. If this data is biased, the decisions continue the same trend, as it happened in the widely-cited Amazon example: their AI-based recruiting tool developed a preference for male candidates and penalized resumes that included gender keywords such as “women’s volleyball” or “women’s golf club member”. Removing gender-related fields from the analyzed data did not help much, as the bias stayed through proxy features, such as being a graduate of a women’s college.

But even training on the English-language Wikipedia teaches the model the gender bias. The course Machine Learning for Business Professionals on Coursera demonstrates the gender bias “learned” by a model from Wikipedia articles. The Tensorflow Embedding Projector can perform neighborhood analysis for understanding dependencies between different words: the smaller the distance between words, the stronger is the association. They defined “male” and “female” as data points and checked the nearest neighbors. The words closer to “female” were from the artistic domain (art, dance, and sculpture), while a whole cluster of math-related words (equations, computation, algebra, calculus, geometry, and math) was near the “male” side.

Remember, the words we use in our resumes can help us or become traps: ML perceives the agentic descriptions as masculine-sounding and communal as feminine-sounding. The moment you use the categories like collaborative, dedicated, committed, supportive, responsible, conscientious, understanding, or sociable gets you on the female side of the classification. And such agentic descriptions as achiever, aggressive, lead, dominant, “executed or captured something” are still considered as male candidate characteristics by ML.

Takeaways

Knowing all the above, get your salvation in your own hands! How are you going to get those bots? Here are my suggestions:

  1. Use strong and assertive expressions. Fit in the agentic characteristics, such as ambitious, aggressive, analytical, assertive, confident, decisive, independent, and self-reliant. Point out that you thrive in a competitive atmosphere.
  2. Bravely go after those companies that describe themselves as “dominant engineering firms that boast many clients”. In real life, they may turn out to be “communities of engineers who have effective relationships with many satisfied clients”.
  3. If applicable, enhance your engineering, math, programming, or cloud computing sides.
  4. If you are into extreme sports, wrestling, bodybuilding, bikes, 3d-printers, golf, or chess, make them shine in the Hobbys and Interests section of your resume.

--

--

--

I am a [technical] writer, poet, and engineer. My domains are IT, Cryptography, Data Science, Artificial Intelligence, Machine Learning, and Cloud Computing.

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Handling emotions in business

The Social Contract:

Why a sales career is not what you think it is

Compensation systems: Is it easy to maintain job fairness and equity at work?

Preparing For The Future Of Work: Kelly Mackin of Motives Met On The Top Five Trends To Watch In…

More Remote Work Means Greater Opportunity and Competition

Gemstone Lights Appointment

Gemstone Lights Appointment

6 Entry-level Jobs in Tech to Get Your Tech Career Started

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Tali de York

Tali de York

I am a [technical] writer, poet, and engineer. My domains are IT, Cryptography, Data Science, Artificial Intelligence, Machine Learning, and Cloud Computing.

More from Medium

How going back to market after long break

How to Answer the Question “What Is Your Greatest Weakness” in an Interview

How to pivot at the height of your career

Landing Your First Job After CorrelationOne — Pt 2. Leveraging Your Past Experiences