In June of this year, CNBC hosted the Talent@Work summit, the first event in its @Work series.

The event took place in New York City with what CNBC called an all-star lineup of speakers.

On the Competitive Edge Panel, Tara AI’s CEO joined the founder of Pymetrics and Jon Fort in a discussion on the power of artificial intelligence in HR and the talent acquisition process.

If you missed the chance to attend this exciting event, below are key takeaways from the Competitive (Machine) Edge Panel!

🚀 We’d love to learn more about your team and the challenges in your current workflow. Let’s chat!

1. Bias is a real and concerning challenge in talent sourcing.

Humans are inherently biased. This is the overarching challenge in talent acquisition.

According to the CEO of Pymetrics, women and minorities are at a 50-60% disadvantage when it comes to recruiting. Many of them never hear back after the resume screening round.

There’s also a massive pool of untapped talent constantly overlooked by recruiters for reasons such as not holding a degree from a prestigious university.

Is AI the solution to this problem?

2. Artificial intelligence in HR can be the key to a bias-free recruiting process.

Human recruiters may omit the right talent. Data won’t.

We can rely on artificial intelligence to make judgment based on technical competencies and experience, not age, race, gender, etc.

Tara AI’s machine learning model is capable of looking into open source repositories on Github and gathering information on candidates’ past projects, thereby evaluating the technical competency of an applicant for a particular project or position.

This successfully eliminates human biases while accurately determining the aptitude of a candidate.

3. Artificial Intelligence is the new talent-sourcing rockstar.

Screening, reviewing, interviewing… then more interviewing. Traditional recruiting is a time-intensive process with lots of tedious procedures.

This is a nightmare for companies that need talent quickly but can’t afford to sacrifice candidate quality.

Artificial intelligence can take the pain out of the recruiting process. By examining candidates’ technical background and matching them with the project’s requirements, AI can quickly find the developer with the right skills in a reduced amount of time.

It makes screening and searching for talent a breeze.

According to the CEO of Tara AI, Cisco has a five-month recruiting process. This is reduced to 24 hours with the help of Tara AI’s platform.

Less time recruiting, more time building. Isn’t this the dream of all project managers?

4. Artificial intelligence does have blind spots.

By default, machines don’t have biases. Humans do – and they’re building machine learning algorithms.

An AI model is created based on dataset training. How it interprets a set of data is shaped by the developer’s own interpretation.

False assumptions create false algorithms.

The CEO of Tara AI called artificial intelligence “the mirror of a society,” and at the end of the day our society is flawed.

Artificial intelligence in HR will either be free of human biases or it’ll amplify them.

5. Another challenge of developing AI: constant updating.

The need of a business changes and so do its recruiting standards.

For an AI platform to function effectively, it’s important for training datasets to be updated constantly in order to match with new requirements.

This is a challenging task since it requires humans to manually update the data or develop API integrations to social profiles for example, which is usually resource-intensive and has its own limitations.

Wrapping Up

Artificial intelligence is a game changer in the talent acquisition and innovation landscapes.

It delivers new opportunities to marginalized segments of the society.

Tara AI’s project management platform and Pymetrics’ AI evaluation tool are examples of the endless power of AI in talent sourcing.

It’s important to remember that artificial intelligence, after all, is a creation of human intelligence. It is inherently neutral, but humans aren’t.

Will AI eliminate or reinforce human biases?

The answer lies in our hands.