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AI, hiring and the need for humans in the loop

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Manage episode 400558227 series 3493557
Content provided by Informa TechTarget. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Informa TechTarget or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

The fear of AI technology eliminating thousands of jobs or affecting the hiring process continues to prevail in the age of generative AI.

While many believe that AI technology will augment workers, some are already seeing the effect of AI in the job market. Indeed, tech companies and other large enterprises have laid off thousands of workers in recent months, though staffing levels are mostly still higher than before the COVID-19 pandemic.

ResumeBuilder.com found in a November 2023 survey that of 750 business leaders, 44% reported AI technology would cause layoffs in 2024. The presence of AI in the hiring process has also led to laws like New York's Local Law 144. It prevents employers from using an automated employment decision tool unless they prove they performed a bias audit beforehand.

This law and others are among the ways of proving accountability in the hiring process, said Cliff Jurkiewicz, vice president of global strategy at Phenom, an AI recruiting vendor.

"We must be accountable for the use of artificial intelligence, and the recommendations that it may be making in our decision-making," Jurkiewicz said on TechTarget Editorial's Targeting AI podcast.

While accountability is needed, removing all bias in hiring and recruiting is almost certainly unattainable, Jurkiewicz said.

"It is impossible to do that," he said. "It requires humans in the loop ... to be examining how these tools are functioning and being used in organizations."

Esther Ajao is a TechTarget Editorial news writer covering artificial intelligence software and systems. Shaun Sutner is a journalist with 35 years of experience, including 25 years as a reporter for daily newspapers. He is a senior news director for TechTarget Editorial's information management team, covering AI, unified communications software, analytics and data management technology. Together, they host the Targeting AI podcast.

  continue reading

48 episodes

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Manage episode 400558227 series 3493557
Content provided by Informa TechTarget. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Informa TechTarget or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

The fear of AI technology eliminating thousands of jobs or affecting the hiring process continues to prevail in the age of generative AI.

While many believe that AI technology will augment workers, some are already seeing the effect of AI in the job market. Indeed, tech companies and other large enterprises have laid off thousands of workers in recent months, though staffing levels are mostly still higher than before the COVID-19 pandemic.

ResumeBuilder.com found in a November 2023 survey that of 750 business leaders, 44% reported AI technology would cause layoffs in 2024. The presence of AI in the hiring process has also led to laws like New York's Local Law 144. It prevents employers from using an automated employment decision tool unless they prove they performed a bias audit beforehand.

This law and others are among the ways of proving accountability in the hiring process, said Cliff Jurkiewicz, vice president of global strategy at Phenom, an AI recruiting vendor.

"We must be accountable for the use of artificial intelligence, and the recommendations that it may be making in our decision-making," Jurkiewicz said on TechTarget Editorial's Targeting AI podcast.

While accountability is needed, removing all bias in hiring and recruiting is almost certainly unattainable, Jurkiewicz said.

"It is impossible to do that," he said. "It requires humans in the loop ... to be examining how these tools are functioning and being used in organizations."

Esther Ajao is a TechTarget Editorial news writer covering artificial intelligence software and systems. Shaun Sutner is a journalist with 35 years of experience, including 25 years as a reporter for daily newspapers. He is a senior news director for TechTarget Editorial's information management team, covering AI, unified communications software, analytics and data management technology. Together, they host the Targeting AI podcast.

  continue reading

48 episodes

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