Marta Turek-Olearczyk on Tackling Conformity and AI Bias in Hiring for Data Roles

In a recent episode of the Objective Hiring podcast, Marta Turek-Olearczyk, a Marketing Intelligence & Data Science Expert, joined host Tim Freestone to explore the growing challenges in hiring for data roles. Marta shared her insights on the increasing conformity in applications and the complications brought about by AI-generated content, offering practical solutions to improve hiring processes.

As companies continue to rely on technology in recruitment, the hiring landscape has shifted dramatically. While AI offers efficiencies, it also introduces new obstacles. Marta, with her vast experience in data science, provided a clear perspective on how hiring managers can balance innovation with fairness and effectiveness.

The Problem of Conformity in Applications

One of the key challenges Marta highlighted is the "conformity of applications," especially in technical fields like data science. With a high degree of jargon inherent to these roles, applicants often present CVs that sound nearly identical. This conformity becomes more pronounced when candidates use AI tools like ChatGPT to generate their applications.

"When you are receiving a large number of applications that all sound the same, then none of them appear to be viable candidates, even though they might be," Marta explained. The overuse of technical keywords, library names, and buzzwords creates a homogenised pool of candidates, making it challenging for hiring managers to identify truly qualified individuals.

The conformity issue, she added, is compounded by the current job market dynamics, where applicants focus on quantity over quality. "Because there’s such a high volume of applications, it feels like applicants are putting more weight on quantity versus quality," Marta noted. This flood of similar applications overwhelms hiring teams and raises the risk of overlooking strong candidates.

Distinguishing Human vs. Machine-Generated Content

The rise of AI-generated applications adds another layer of complexity. Marta pointed out that AI tools often produce responses in a highly formalised and generic style, which can be easy to spot. "ChatGPT has a very particular style of writing, which is quite easy to pick out," she observed.

To address this, Marta advocates for incorporating filtering mechanisms into the hiring process, such as open-ended questions. These allow hiring managers to evaluate not just the technical skills listed on a CV but also the thought process and creativity of the applicant.

"I actually find myself now focusing more on the answers to the questions than I do on the resume itself," Marta shared. By assessing the specificity and originality of answers, hiring teams can gauge whether a response is genuinely human or AI-generated. "The more specificity, the better," she added, noting that vague or generic responses often indicate a lack of real experience or the use of AI.

This approach not only helps filter out machine-generated applications but also identifies candidates who are genuinely engaged and interested in the role. Open-ended questions can reveal problem-solving skills, creativity, and depth of experience—qualities that are often hidden behind standardised CV formats.

The Role of Technical Assessments

Another strategy Marta emphasised is the use of technical assessments to objectively evaluate candidates. Reflecting on her own experiences, she admitted, "In the past, I hired without doing a technical assessment… and it became really clear that some people are just really good at talking." Without assessments, there is a risk of hiring candidates who lack the practical skills required for the job.

Marta underscored the importance of aligning assessments with the technical requirements of the role. "Whether it is technical or for data or otherwise, assessments are critical in any interview," she stated. For data roles, this becomes even more essential as technical skills are non-negotiable.

She also discussed the shift from live assessments to take-home assignments in the remote work era. While live assessments can make candidates nervous, take-home assignments allow applicants to demonstrate their skills in a less pressured environment. However, Marta cautioned against cookie-cutter assessments, encouraging hiring managers to design tasks that require creativity and contextual understanding.

"You need assessments that go beyond basic technical skills," Marta explained. "Candidates should demonstrate their ability to think critically and apply their knowledge to real-world problems." This ensures that the hiring process is not only fair but also effective in identifying the best talent.

Addressing Bias in the Hiring Process

A recurring theme in the conversation was the potential for bias in traditional hiring practices. Marta and Tim discussed how CVs often reveal irrelevant personal details, such as gender, ethnicity, or even religion, depending on the region. These details can inadvertently influence hiring decisions.

"When the hiring process starts with a human and a CV, it’s just rife with bias," Tim commented. Marta agreed, adding that cultural norms often dictate what information is included in applications, which can further complicate the process.

AI has the potential to mitigate some of this bias by anonymising applications, but it also introduces its own challenges. For instance, Marta pointed out how AI can perpetuate conformity and hinder creativity. Balancing these factors requires hiring managers to critically evaluate their tools and processes.

"Anonymising applications can be a double-edged sword," Marta noted. "While it reduces bias, it also removes context that might be crucial for certain roles." This underscores the need for hiring teams to strike a balance between fairness and practicality.

The Need for Quality Over Quantity

Throughout the conversation, Marta stressed the importance of shifting the focus from volume to quality in the hiring process. She recounted a recent experience where her team received 250 applications for a data analyst role within just 72 hours. "It has really increased the workload… to manually review such a large number of applications," she said.

This volume of applications not only strains resources but also risks diminishing the candidate’s experience. Marta highlighted the need for candidates to invest time in crafting thoughtful and personalised applications. "A job application is an opportunity to show a potential employer what you can do, what you’re capable of," she noted. Effort and attention to detail can set candidates apart in a crowded field.

Employers also have a role to play in encouraging quality over quantity. Marta suggested streamlining application processes and setting clear expectations for candidates. "When companies provide clarity and transparency, it creates a better experience for everyone involved," she said.

Looking Forward: Practical Steps for Hiring Managers

To navigate these challenges, Marta and Tim outlined several actionable strategies for hiring managers:

1. Implement Open-Ended Questions: Use free-form questions to assess candidates’ problem-solving skills and creativity.
2. Introduce Technical Assessments: Ensure every candidate’s skills are objectively evaluated early in the hiring process.
3. Anonymise Applications Where Possible: Remove identifying details from CVs to minimise unconscious bias.
4. Focus on Quality Over Quantity: Encourage candidates to invest in fewer, more thoughtful applications.
5. Adapt to AI Tools: Leverage AI for efficiency but remain vigilant about its limitations and biases.
6. Provide Clear Application Guidelines: Help candidates understand what is expected, reducing confusion and increasing effort.

By adopting these measures, companies can make their hiring processes fairer and more effective, ensuring they identify the best talent in a competitive market.

Final Thoughts

As Marta Turek-Olearczyk eloquently articulated, hiring for data roles is fraught with challenges, from conformity in applications to the growing influence of AI. However, with the right strategies, these obstacles can be overcome. Her emphasis on objectivity, creativity, and quality provides a roadmap for hiring managers looking to refine their processes.

For more insights from Marta and other experts, listen to the full episode of the Objective Hiring podcast. If you’re ready to transform your hiring process, explore the solutions offered by Alooba and sign up today.