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Comment by jsemrau | Hacker News Reader

I was hiring on LinkedIn and what really annoyed me the most are two UI dark patterns.

1. If there is someone that LinkedIn doesn't seem fit, there are three clicks necessary to make this person fit compared to one click for accepting the rejection. And it is visually made very clear that this person is not fit.

2. The fitness as calculated by LinkedIn it not working correctly by flagging too many people as being unfit.

As a result, inexperienced recruiters or HR staff would blanket disregard these applicants even though a lot of them are much more qualified than non-flagged applicants.

[edit] Here is the overview I created at the time. One might argue that the sample is small. But I think it should be possible to speak to applicants in this case. https://i.imgur.com/n7i5VtP.jpg

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> As a result, inexperienced recruiters or HR staff would blanket disregard these applicants even though a lot of them are much more qualified than non-flagged applicants.

Aren't you told as an applicant that you can improve on "x number of points, buy premium to see how you can become a better fit"?

E.g., it's an intentional upsell, to get not only the demand side of LinkedIn to pay for pro features, but also the supply side.

Not having much LinkedIn experience for applying, how could a candidate make sure that they fit a job spec? Is it just based on the skills you put in yourself?

Well, I put my spec into the Job Description (JD). If a person applies I can match this to what I expect from the role. The more an applicant has to offer the higher the score.

This is just an abbreviated example for an Accountant

Score 1. Bar Tender.

2. Accountant no experience.

3. Accountant experience small business.

4. Accountant with experience across several business lines.

Score 5. Accountant with experience across several business lines and the right companies on the CV.

The fit / not fit comes from LinkedIn and usually doesn't relate to the job posting.

What do the grades mean?

This is a grading where 1-worst and 5-best. Fit/Not Fit is the grading from LinkedIn

Oh, I see - makes sense. Thanks for the explanation and an interesting data point!

I wonder if this means that I should not spend too much energy on applying for jobs that LinkedIn thinks I am not a good match for, assuming most recruiters are not as motivated as you.

That's the lessons learned for me at least.

An algorithm that you don't know how it works decides that you are not fit for the role. Even though the algorithm is provably wrong.

Feels like Kafka's The Trial. Really Dystopian.

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