Recruiting & Job Board News You Can Use
You’re either hyper-aware of GDPR or you feel like you vaguely recollect hearing it but don’t have a clue what it’s about. GDPR is a new set of privacy laws set to roll out across the European Union, but will also affect anyone doing business in the EU as well.
Generally speaking, GDPR (General Data Protection Regulation) is designed to “give citizens back control over of their personal data, and to simplify the regulatory environment for business”.
Striving to be compliant with GDPR is a complex process for some companies. Facebook, for example, has had to dedicate resources to creating a new privacy control centre for users. Algorithms used to power Facebook’s advertising publishing have been subject to much scrutiny in recent months and years, and the company has been taking steps to try and prevent political interference. There have also been concerns about whether Facebook’s tools allow or encourage discrimination in recruitment advertising.
For Facebook, GDPR is a big deal. Changes Facebook makes to its platform to accommodate the European regulations will also impact how it operates in America and the rest of the world.
For smaller companies with simpler businesses and digital footprints that are smaller and less complex, GDPR still matters. Even if you don’t do business in Europe or have European Union citizens as users or customers, it’s still worth it to be aware of GDPR, as other countries and jurisdictions may implement similar regulations in the future.
How to Use This News:
Read up on GDPR. While I am not a lawyer and cannot promise that my interpretation is accurate or comprehensive, I would say the basic factors are:
- Getting and recording consent
- Knowing what data you have, where it’s stored, and where it goes
- Being transparent about the data you collect, both in a broad sense and with individuals
- Having a process in place for dealing with a person’s request to know what data you have on them and/or to delete that data
If you’re not based in Europe, take stock of how many (if any) users or customers you do have in Europe. If you find you have gaps, chances are they may be solved by adding some text* and a checkbox to your registration page, or by outlining an internal policy or process for dealing with GDPR requests from users.
*The text must be clear and explicit when asking a user for consent to use their data. Lengthy and confusing legal language buried in fine print is not the catch-all way to avoid liability anymore.
Beware the Biased Algorithm:
One of the most interesting parts of GDPR might be the right to be informed when a major decision that can negatively impact one’s life is not made by a human, but an algorithm, artificial intelligence, machine learning, predictive analytics, or whatever the latest buzzword is today.
This TechCrunch article outlines it nicely:
“Article 22 of GDPR places certain restrictions on entirely automated decisions based on profiling individuals — but only in instances where these human-less acts have a legal or similarly significant effect on the people involved.
There are also some exemptions to the restrictions — where automated processing is necessary for entering into (or performance of) a contract between an organization and the individual; or where it’s authorized by law (e.g. for the purposes of detecting fraud or tax evasion); or where an individual has explicitly consented to the processing.
In its guidance, the ICO specifies that the restriction only applies where the decision has a “serious negative impact on an individual”.
Suggested examples of the types of AI-only decisions that will face restrictions are automatic refusal of an online credit application or an e-recruiting practices without human intervention.”
There has been a proliferation of recruiting and HR tools that market themselves as using machine learning or predictive analytics to screen and evaluate job candidates and current employees, make predictions or provide insights on their present or future performance.
Such tools promise to save time and remove human bias by using big data to objectively assess job applicants and make predictions about how well they will perform in a job at your company.
Whether they follow through on their marketing is another question. In some cases, such tools may make the job of hiring easier simply because they narrow down your list of candidates in some way. Without complete transparency about how algorithmic decision-making for such tasks actually works, it’s hard to say whether any given tool is helping or hindering a company’s goal to hire a diverse workforce in a fair and unbiased fashion.
When the criteria and underlying decision-making is out of your control with opaque and proprietary algorithms doing the heavy lifting, your shiny new neural network with machine learning may be using or picking up on common biases and even prejudices that can actually mess up your hiring in a big way. For example, if your data shows that 80% of your best employees when to the same school, it may decide your best bet is to hire someone else with that same background and screen out exceptional candidates who don’t fit your pre-established mold.
How to Use This News:
Job boards and recruiters should ask questions about tools that replace human decision-making. Humans are incredibly flawed and are perfectly capable of making bad decisions all on their own, but you should probably know what you’re getting into when you effectively outsource those jobs to a third party tool.
If you’re considering using machine learning/AI as a way to evaluate and hire candidates, it’s a good idea to ask some tough questions. Ask yourself whether or not you understand how decisions are made for you, and whether you would be able to explain it to a candidate and how comfortable you would feel about being on the receiving end of being rejected at the hands of an automated tool.
If whittling down your list of candidates is your top concern, you could try improving your job posts to better attract the right applicants and filter out the unqualified or inappropriate ones. If ridding your hiring process of bias is your goal, examining your current processes and evaluation criteria might be the place to start, as bias and discrimination can exist regardless of what tools you use. The same questions can still be asked about your old Applicant Tracking System that boots out candidates whose resumes lack a certain keyword density or some other arbitrary criteria. Is it actually helping you find the better candidates? Or is it just a way to shorten the list of applicants you have to review? Low-tech or high-tech, it’s important to put yourself in the candidate’s shoes and consider what their experience will be like, whether or not you would feel like you’d be evaluated fairly through the same system, and if it might exclude candidates of diverse backgrounds and abilities.
The rights of your users is a complex and fascinating topic, and it’s easy to get overwhelmed just thinking about the possibilities. Will we soon be living in a fantastic dystopia where runaway algorithms decide our futures? Or will we have complete choice and control over the fate of the data that represents our digital shelves? I suspect the reality may lie somewhere in the middle and we will all find a way to muddle through it!
Image credit:Matthew Henry