Building Employee Trust in the Age of AI Advancement

Building Employee Trust in the Age of AI Advancement

Managers are under more pressure to drive productivity, and ironically ⁢efficiencies created by‍ generative artificial ​intelligence (AI) tools are a big part of why⁣ expectations are growing.

At the same time, ‍organizations face⁣ a crisis of trust from⁣ employees who see⁢ AI as a threat to their jobs.

In fact, generative AI is expected ‍to replace some part of the workforce in the years ahead. As much ‍as 29% ⁤of computer-related tasks could be automated ​by AI, as well as 28% of work by healthcare practitioners and technical tasks in that field, according to a study by Goldman Sachs.

Most experts agree,⁤ however, that newer AI tools are less about replacing people‌ and more about eliminating mundane, manual,‍ or number-crunching tasks ​that most employees already hate. In fact, the technology will mostly help free up⁢ workers to tackle ⁣more⁣ important ⁢tasks such‍ as project management, data ⁢science research and, perhaps most importantly, creative thinking​ and‌ problem solving.

“There⁢ is no ‍example today of an AI system that can perform data science totally independent ​of people,”⁤ said Erick Brethenoux, a⁣ distinguished vice ⁣president⁣ analyst at research firm Gartner.

A lot of the uncertainty and fear workers feel about generative AI tools is based on ignorance, experts say.‌ AI, in its many forms, has been around for more than 50 years, but many people simply don’t recognize it’s been beside them all this time.

“People have always been afraid of AI because the vision they have of it is science fiction; it’s a Hollywood ‍vision of it,” Brethenoux said. “There’s a lot of hype around it.”

AI, for example, has been used to automate credit card ​approvals and transactions — and anyone who’s used a GPS system has used AI to determine their ⁤routes. But in⁣ the past six or so months, new generative​ AI platforms such as ChatGPT have placed a spotlight on the technology and added a plethora of new use cases.

Generative ​AI, for instance, has been and can be used in ⁤decision support, decision⁤ augmentation, and decision automation.

“Decision‍ augmentation, that’s what’s interesting; it’s the collaboration of humans and machines working together.” Brethenoux ​said. “I cannot analyze⁤ 7,000 dimensions at once.‌ Machines can do​ that.‍ So, ‍then, great — ⁣let them analyze the data ⁢and find the patterns. Then how to ‌apply ⁣those ⁣patterns ​can be at my discretion and could also be helped by a​ machine.”

For ⁢example, Brethenoux said ‍his brother works in real estate and⁣ has five agents⁢ working for him. He has ⁤been using ChatGPT to analyze multiple⁤ property profiles, a task that would ‍typically take up to six weeks if done manually.⁣ ChatGPT, ​Brethenoux said, can do‍ that same task in an hour and a ⁢half. ​Instead of using the efficiencies of ChatGPT to reduce his workforce, his‌ brother said the technology has freed up agents to⁣ be more hands-on and discover more prospective buyers.

“Right away,‍ he thought, ‘What can my people do that…

2023-08-15 12:00:04
Source from www.computerworld.com rnrn

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