What’s The Real I.Q. Of Your Artificial Intelligence Platform?

After decades of development, Artificial Intelligence has certainly come a long way.  Cautious decision-makers within school systems, governments and other high-level industries all over the world now rely on various AI-driven tools on a daily basis.  IntelliMetric’s automated essay-scoring capabilities, for example, are currently being utilized by the United Nations to enhance the efficiency of their hiring practices.  

If you are looking to dedicate time, money and trust into all that AI has to offer, you should proceed with caution.  There is a wide divide between leading tools like IntelliMetric and other automated essay scoring options that don’t offer the same level of unbiased expert feedback. 

Choose wisely because a long-term commitment to the perfect product could be beneficial for years to come, while selecting a poor fit could be detrimental for even longer. Let’s dive deeper into this issue.

Do Your Homework

Finding the right AI is challenging, as with shopping for any solution. From mobile apps to electronic devices, we’ve all seen the good, the bad and the downright unusable offerings that crop up whenever a group of products are branded with a common label. The responsibility lies with the client or consumer to do their homework and find the product that truly fits their needs.

Like other forms of technology, Artificial Intelligence platforms offer a wide range of options. Handpicking the best tool for your needs is a challenging, yet necessary task, and failure could lead to a scoring system fraught with inconsistencies.  Below is an all-too-realistic example of what could happen when you trust the wrong technology.

Biased Hiring Practices = Bad News

The fictional XYZ Corporation has been in business for years. While sales growth has been solid, allegations persist that the company is fraught with gender and racial bias, both in hiring practices and career advancement opportunities.  A quick review of the upper-management staff and sales team illustrates an extreme lack of diversity, thus reinforcing these claims.

In order to salvage their reputation and make a fresh start, the XYZ Corporation decided to replace their hiring process with a machine-learning algorithm. The tool was programmed to evaluate job candidates’ writing samples against twenty years of saved job applications, narrowed down to employees who stayed with the company for at least five years, and received at least one promotion.

The idea was to search for potentially successful employees by comparing them to proven success stories, and it seemed like a surefire success story on the surface. After all, employees who fit this criteria displayed enough company loyalty to stay with XYZ for five years while overachieving enough to earn promotions within the company.

Limiting referencing of past applications to those who achieved longevity and upward mobility with the company seemed like the perfect way to cherry-pick similarly-minded candidates for the company’s future.

Unfortunately, this tactic was destined to fail for one very important reason: the hiring process that led to all of those past success stories was flawed from the start. Due to the company’s biased hiring practices, barely any minorities or women had been added to the team in many years. Therefore, the algorithm utilized for this new hiring procedure blindly replicated the same biases. Nothing had changed.

The More Things Stay The Same

In her 2017 Ted Talk, Investigative Journalist Cathy O’ Neill discussed a similar situation that she’d researched. She summed up the same faulty logic exhibited by XYZ with a simple statement:

“Algorithms don't make things fair if you just blithely, blindly apply algorithms.  They repeat our past practices, our patterns. They automate the status quo. That would be great if we had a perfect world, but we don't.”

XYZ’s unfortunate choices, while fictional, are reminiscent of many real-life tales of technological woes and million-dollar misfires.  It’s easy to see why these issues occur. By buying into solutions that carry the “Artificial Intelligence” designation, corporate decision makers are easily compelled to blindly trust this technology without truly understanding its capabilities… or limitations.

The story you just read is imaginary, but there is a very real solution: IntelliMetric.

IntelliMetric: Your Best-Case Scenario

With accuracy, consistency, and reliability greater than human expert scoring, IntelliMetric is the most capable automated essay-scoring and job candidate evaluation platform on the market.  Accessible any time or place, the web-based tool is capable of scoring long and short answer responses with efficiency, precision and fairness, thanks in part to the tool’s Natural Language Processing (NLP) and Natural Language Understanding (NLU) capabilities.

Best of all, IntelliMetric’s advanced capabilities allow it to identify and eliminate any biases found in reference data. Unlike the flawed algorithm used by XYZ News, the use of IntelliMetric in hiring practices paves the way for true diversity. This is why IntelliMetric is used to score hundreds of thousands of business school candidates, scholarship candidates and job applicants for leading universities and corporations. 

To learn more about why IntelliMetric is a superior tool for your hiring needs, visit IntelliMetric.com.

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