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Tips on running a bias-free, early-talent hiring process

Tips on running a bias-free, early-talent hiring process

Author
Soumya Chittigala
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September 7, 2020
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4 min read
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The generation of early-talent is comprised mostly of Gen Z (those born after 1996). This group comprises students who are recent graduates or about to graduate. They are known to be entrepreneurial, tech-savvy, and are true digital natives.

With the unemployment rate hitting the lowest of lows and several Baby Boomers (those born between 1946 and 1964) entering retirement, the need to hire early-talent is more significant than ever. The early-talent you recruit will help define your company culture for years to come. Therefore, it is important to prioritize a diverse pool of candidates with the right skill sets throughout your hiring process. To effectively engage with this sought-after group of job-seekers and run a bias-free hiring process, organizations need to evolve their recruitment methods to be more authentic, digital, and proactive.

What bias means in recruitment

As humans, we are bound to make quick decisions. Every day we make a multitude of choices: your most recent one was whether to read this article or not. Similarly, in the hiring process, bias happens when you prefer one candidate over another based solely on first impressions. Or, be inclined toward a candidate who seems similar to you. Sometimes, a candidate’s name, pictures on their resume, or hometown could influence your opinion more than you think. In short, bias (conscious or unconscious) affects your decision—whether positively or negatively, using criteria irrelevant to the job.

How to avoid bias in early-talent hiring?

Does your company have a program for hiring early-talent as interns, co-ops, and for entry-level roles? If yes, great! However, it may be wise to revisit your hiring strategy. That’s because Gen Z represents the first generation of true digital natives. This generation is equipped with the most in-demand skills, such as leadership, communication, problem-solving, data analysis, and tech. Hence, it would be best if you had a solid understanding of the profile of this generation and how to recruit them while cutting from the entire process.
Read more on the 7 Types of hiring bias and how to avoid them.
Here are 3 proven ways to avoid bias in early-talent recruitment.

Use a pre-employment assessment tool

Gen Z were the first to be born into a completely digital world. They are extremely tech-savvy because they grew up immersed in a digital culture.

Hence, you must speak their language and digitize your hiring process, leaving no room for bias. Consider using coding assessment tools or recruitment software solutions. These tools have many benefits that can help you eliminate bias from the interview process:
  1. First of all, these tools will allow you to conduct structured interviews. You will also be able to use evaluation parameters or scorecards to test candidates on the go. Conducting structured interviews and having pre-defined evaluation parameters are excellent ways to interview candidates in an unbiased and standardized manner. Asking a set of questions in a structured interview format helps the hiring team collect useful information from each interviewee that they can use to make informed hiring decisions and compare with other candidates in the funnel.
  2. These tools foster collaboration between two or more recruiters and hiring managers. Hence, every hiring decision is a team effort, which helps you avoid recruitment bias.
  3. These tools hide all personally identifiable information of candidates such as gender, name, email address, etc. Hence, the chances of unconscious bias are reduced drastically.

Rework your job descriptions

It’s no surprise that Gen Z uses mobile phones with lightning dexterity—as if the features of their phones and their minds were one and the same. But that also means that this generation is quick to swipe left at lackluster or poor job descriptions. Hence, employers and recruiters need to be on their toes.

Gen Z doesn’t want to be gender-stereotyped and is acutely aware of bias. According to a New York Times poll, this generation believes that they can change their sexual preferences and gender identities more than any other generation.

In early-talent hiring job descriptions play an important role as they provide the first impression of a company's culture. Look at the language in your tech job descriptions. Chances are, the wording is more biased toward one gender than you realize. Always avoid pronouns and potentially gender-charged terms in your job-descriptions. The idea is to make them gender-fluid.

Furthermore, you can emphasize both in your job descriptions and in your company brand that your company is committed to inclusion and diversity. This results in a richer, expanded candidate pool of Gen Z.

Shift your focus from pedigree to potential

Every student dreams of getting into one of the Ivy League universities around the world. However, the competition for getting into elite colleges seems to be getting more and more intense. According to research, elite colleges and universities enroll fewer than 6 percent of U.S. college students.

This brings us to a fundamental question: what should be more critical to an organization when hiring early-talent – the educational pedigree or potential of candidates? When organizations begin searching for early-talent, elite universities are likely to be the first to attract their attention. However, by doing so, they are limiting their candidate pool.

Google helped start this trend when they spoke of hiring for “Intellectual Humanity” and a push toward a focus on skills more than credentials. We are not saying that you should ditch the Ivy League cohort altogether. But it is important to remember that students from the lesser privileged section of the society can have the required skills that you’re looking for even without going to an Ivy League school. By shifting your focus from pedigree to potential, you will have a clear insight into a candidates’ performance and problem-solving skills in a real-world scenario. This method has proven to be accurate, delivering actionable results, and leaving no room for bias whatsoever.
Assess a candidate's potential with accurate coding assessments

Gen Z are on their way and it’s time to get ready for them…

Gen Z are hot on their heels in the job market today, and now is the time to get ready for them. This generation is known for being open-minded and deeply invested in diversity and inclusivity. A study found that 70% of this generation strongly believes that public spaces should provide gender-neutral bathrooms, compared to 57% of Millennials.

What does this mean for you? You must shine a spotlight on your diversity and inclusion efforts by eliminating bias from the recruitment process!

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Author
Soumya Chittigala
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September 7, 2020
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4 min read
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Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today,...

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing code.

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.​

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.​
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.​

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

  • Develop an understanding of basics of system design and architecture
  • Familiarize yourself with commonly asked systems design interview questions
  • Read about system design case studies for popular applications
  • Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

  • Plan the extent of the topics and scope of discussion in advance
  • Clearly define the evaluation criteria and communicate expectations
  • Quantify constraints, inputs, boundaries and assumptions
  • Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

  • Ask follow-up questions to challenge a solution
  • Probe candidates to gauge real-time logical reasoning skills
  • Make it a conversation and take notes of important pointers and outcomes
  • Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

  • Encourage candidates to explore and consider alternative solutions
  • Work with the candidate to drill the problem into smaller tasks
  • Provide context and supporting details to help candidates stay on track
  • Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.
  • Secure, sealed-off testing environment
  • AI-enabled live test monitoring
  • Enterprise-grade, industry leading compliance
  • Built-in features to track, detect and flag cheating attempts
Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.
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