University of Southern California | MathWorks

July 11, 2023

Introduction

The current methods of resume screening are outdated, involving time-consuming and cumbersome processes that often incur high costs for industries. Finding the right candidate requires significant effort. While the prevailing trend involves resume screening and application tracking systems (ATS) as a standardized process, there is now an opportunity to harness the true potential of AI for headhunting.

When discussing AI and its impact on jobs, there is often a negative perception, as people fear job loss due to AI advancements (which, to some extent, is true). However, the focus of this article is not on the speed at which we will reach that point, as there are speculations suggesting exponential progress. Instead, it presents an alternative perspective.

The article explores the possibility of utilizing AI for headhunting, highlighting the potential benefits and opportunities it presents.

Drawbacks

Let's walk through what's wrong with the traditional hiring process.

Time-consuming

The average time it takes to hire a new employee is 42 days.

Limited candidate pool

In addition to the limited candidate pool, the use of ATS further restricts the selection process: According to JobScan's survey reports, over 98.8% of Fortune 500 companies utilize ATS, with 66% of large companies and 35% of small organizations relying on these systems. The current approach involves passive searching based on candidate applications, which may not always identify the most suitable candidates for the job. However, there is potential for alternative methods to proactively find candidates with greater capabilities for the position.

Inefficient assessment of skills

Traditional processes often rely on interviews and assessments conducted at later stages of the hiring process to evaluate a candidate's skills and abilities. However, these assessments may not always provide a comprehensive understanding of a candidate's true capabilities or potential for success in the role.

High cost

Recruitment efforts consume approximately 15% of Human Resources expenses, with an average cost per hire exceeding $4,000. In 2022, the cost per application (CPA) increased by 43%, contributing to the average cost per hire, which surpasses $4,000.

Lack of real-world performance evaluation

Ineffective cultural fit assessment

It is important to acknowledge that there are additional challenges involved in assessing a candidate's personality and cultural compatibility with the company, which we will briefly discuss in the following section.

Finding a good fit

The criteria for finding a good candidate broadly fall into 2 categories.

Qualitative

The qualitative assessment encompasses several human factors, such as likability, cultural fit, personality, work ethic, attitude, and emotional intelligence. These aspects are crucial for building a harmonious team, as when starting a company, one would naturally want to hire people they enjoy working with. Teamwork has the potential to yield significantly more powerful results.

However, evaluating these qualitative attributes during the hiring and interview process can be challenging. It is only after an individual has worked with a team for a substantial period that their fit within the team becomes apparent. This means that while the hiring process may capture some elements of a candidate's qualitative attributes, it is only over time that the team truly gets to know how well the candidate fits within their dynamic.

Quantitative

Conversely, when it comes to quantitative attributes, traditional hiring processes provide a reasonable understanding, albeit with some challenges, as mentioned earlier. The evaluation of quantitative aspects already incorporates a considerable degree of automation.

While utilizing AI for assessing qualitative attributes is a difficult endeavor, even in the realm of quantitative criteria, the current methods are becoming outdated with the emergence of well-trained AIs.

By leveraging AI to gauge the quantitative attributes of candidates, we can overcome the obstacles encountered in the traditional hiring process and enhance its effectiveness.

Leveraging AI

How can AI facilitate this process?

Similar to how LeetCode is utilized to enhance developers' coding skills and rank their abilities, it can also be employed as a means to identify promising candidates based on their LeetCode rankings. In a way, it becomes a hiring agency.

Now, let's consider extending this concept to encompass all fields. Throughout their lives, individuals engage in various activities and tasks, which can be assessed in terms of their performance and alignment with specific objectives. By mapping individuals' actions to task-specific key performance indicators (KPIs) using AI, it becomes possible to determine how they fare compared to others who have undertaken the same tasks. This mapping facilitated by AI would aid in identifying the most talented individuals across a broad spectrum of skills and tasks.

Practically, this approach relies on the concept of performance as the primary criterion. The AI system possesses knowledge of what constitutes typical good performance for each specific job, and these performance benchmarks serve as key performance indicators (KPIs).

To implement this approach, a central hiring agency opens job opportunities on behalf of parent companies and hires individuals based on their submissions, including written proposals, presentations, and research. The hiring agency then returns these submissions to the parent company, which evaluates the job itself rather than the individual applicant. The combination of the parent company's assessment and the AI's review results in the generation of a user index, providing an overall evaluation of the candidate's suitability for the job.

How will it save the costs?

Implementation of this AI-based approach can lead to cost savings in several ways:

1. Time-saving: The system provides real-time data on how candidates perform across various fields, eliminating the need for lengthy and time-consuming evaluation processes.
2. Expanded candidate pool: As everyone is mapped and assessed through this system, the candidate pool becomes much larger, providing a broader range of potential hires.
3. Improved skills assessment: Skills are evaluated based on extensive experiences and measured against established KPIs, enhancing the accuracy and efficiency of skill assessment.
4. Reduced costs: The costs associated with finding suitable candidates can be significantly reduced as the AI system streamlines the hiring process, minimizing manual efforts and associated expenses.
5. Real-world performance evaluation: By evaluating individuals based on their real-world projects and experiences, the challenge of assessing candidates purely based on theoretical qualifications can be overcome.

However, it's important to note that while this approach addresses quantitative metrics, it does not fully account for qualitative attributes, which also play a significant role in the hiring process.

Pay for work instead of people?

The concept of paying for work instead of solely focusing on individuals has the potential to reshape traditional hiring methods. Many student developers actively contribute to GitHub and open-source projects, often driven by academic purposes or to enhance their professional credibility for future job opportunities. What if these developers were compensated for their work on GitHub?

Imagine bypassing conventional approaches and directly initiating projects similar to those on GitHub. Businesses could raise tickets for specific tasks, attach a price tag, and integrate them into their private repositories. When a developer's code is accepted into the repository, they would be paid through a smart contract.

This is precisely what we aim to accomplish using Dandelion! It provides a platform where work is valued and rewarded, shifting the focus from traditional hiring methods to a more direct and project-based approach.

To learn more about Dandelion:

Conclusion

In conclusion, the traditional methods of resume screening and hiring are burdened by time-consuming processes, limited candidate pools, inefficient skills assessment, high costs, and a lack of real-world performance evaluation. However, the emergence of AI presents an opportunity to revolutionize the hiring landscape.

Works Cited

B., Cherri. “What percentage of the revenue/operating budget of large hourly employers is dedicated to recruitment annually? | Wonder.” Ask Wonder, 23 March 2017, https://askwonder.com/research/percentage-revenue-operating-budget-large-hourly-employers-dedicated-recruitment-f644iqa21. Accessed 23 June 2023.

Baes, Hannah. “How to Optimize Your Cover Letter to Beat the ATS - ATS Cover Letter.” Jobscan, 27 September 2022, https://www.jobscan.co/blog/cover-letter-robot-approved/. Accessed 9 July 2023.

“The Cost of Hiring a New Employee.” Investopedia, https://www.investopedia.com/financial-edge/0711/the-cost-of-hiring-a-new-employee.aspx. Accessed 23 June 2023.

“Recruiting Costs: Budget and Cost per Hire | Recruiting Metrics FAQ.” Workable resources, https://resources.workable.com/tutorial/faq-recruitment-budget-metrics. Accessed 7 July 2023.

“What is the average time it takes to hire a new employee?” Zippia, 28 June 2022, https://www.zippia.com/answers/what-is-the-average-time-it-takes-to-hire-a-new-employee/. Accessed 7 July 2023.