Tech titans assemble to decide which jobs AI should cut first

But don't worry, if tech takes your job, we'll retrain you

Of all the tech CEOs touting AI's potential to empower workers, IBM CEO Arvind Krishna has been among the most vocal about its ability to replace them.

Last spring, the exec opined that as many as 30 percent of IBM's back-office jobs could be automated by AI. So, naturally, Big Blue is among the first to join a consortium of tech heavy weights, including Cisco, Google, Microsoft, Intel, SAP, among others to address AI's impact on workers. The group will also include advisors from the likes of the American Federation of Labor, DigitalEurope, Khan Academy.

The group's stated goal, apparently inspired by the US and EU's joint Trade and Technology Council, is to explore AI's impact on information and communication technology (ICT) jobs. In the initial phase, the consortium will look at 56 roles likely to be eliminated by AI first. According to IBM these roles include 80 percent of the top 45 ICT job titles.

Based on these findings, the group says it'll recommend and support training programs aimed at helping students, career changers, and existing IT workers prepare and transition to roles that AI models are less capable of filling.

And it appears that the Biden administration is more than happy to let the very tech companies developing your AI replacement take the lead on this one.

"We recognize that economic security and national security are inextricably linked," US Secretary of Commerce Gina Raimondo saidt. "I'm grateful to the consortium members for joining in this effort to confront the new workforce needs arising in the wake of AI's rapid development."

AI products aimed at boosting productivity, like Microsoft's Copilot for Office 365 and Github, Google's Gemini for Workspaces, and SAP's coding assistant, to name just a few, have garnered considerable attention, though not always positive, over the past year.

At the same time, companies like Nvidia, IBM, and others have been peddling tools to help enterprises build, fine tune, and customize large language models (LLMs) for internal workloads and processes. IBM debuted its Watson-X platform last spring, while Nvidia launched NIMs, containerized models designed to make it easier to build AI apps and consolidate efforts.

All of these are predicated on the idea that AI will make workers more efficient, enabling them to get more work done faster and with fewer resources.

This concept might be appealing for those in industries already facing staff shortages. However the real concern is AI's potential to cut staff, hence the emphasis in the announcement on retraining.

"Consortium members universally recognize the urgency and importance of their combined efforts with the acceleration of AI in all facets of business and the need to build an inclusive workforce with family-sustaining opportunities," IBM wrote in its announcement.

Between the consortium members the group aims to retrain and transition more than 95 million IT workers over the next 10 years.

Many of these workers will no doubt find themselves in so-called "prompt engineering" roles — or as comedian John Steward put it in a recent skit "types question guy" — where they'll be responsible for crafting instructions used to direct the AI. But as researchers recently discovered, AI is better at writing prompts for AI.

On the surface, the idea of retraining workers for a world automated by AI sounds like the responsible thing to do. But, we'll note that the same data used to assess the impact of AI on the workforce could just as easily be used to determine which positions to cut first and how quickly those roles can be eliminated without appearing too evil.

It's not like IBM has a track record of problematic human resource practices. oh wait.

It's the [disproved] boiling frog problem. Drop the frog into hot water and it'll jump out, but if you slowly raise the temperature, it'll eventually boil alive. In this case, move too quickly and enterprises at best risk backlash and worse destabilize the economy. But, introducing AI gradually, the argument goes that workers will have time to adjust. ®

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