Among tech CEOs touting AI's potential to empower workers, IBM CEO Arvind Krishna has been one of the most vocal about AI's ability to replace workers.
Last spring, the executive said up to 30 percent of IBM's back-office operations could be automated by AI. So it's no surprise that Big Blue will be one of the first companies to join a consortium of tech giants including Cisco, Google, Microsoft, Intel, SAP, and more to address the impact of AI on the workforce. It becomes. The group will also include advisors from the American Federation of Labor, Digital Europe, Khan Academy and others.
The group's stated goal, clearly inspired by the US-EU Joint Trade and Technology Council, is to explore the impact of AI on information and communications technology (ICT) jobs. In the initial phase, the consortium will first consider 56 roles that could be eliminated by AI. According to IBM, these roles include 80% of the top 45 ICT occupations.
Based on these findings, the group said it recommends and supports training programs aimed at helping students, career changers, and existing IT employees prepare for and transition into roles that cannot be filled by AI models. I am.
And the Biden administration seems happy to let tech companies developing artificial intelligence alternatives take the lead on this.
“We recognize that economic security and national security are inextricably linked,” said U.S. Secretary of Commerce Gina Raimondo. She added, “Thank you to the members of the consortium for joining us in this effort to address the new workforce needs created by the rapid development of AI.”
AI products aimed at improving productivity, such as Microsoft's Copilot for Office 365 and Github, Google's Gemini for Workspaces, and SAP's Coding Assistant, to name just a few, have seen positive, if not necessarily positive, growth over the past year. , has attracted considerable attention.
At the same time, companies like Nvidia, IBM, and others are selling tools that help enterprises build, fine-tune, and customize large-scale language models (LLMs) for internal workloads and processes. IBM debuted its Watson-X platform last spring, while Nvidia launched NIM, a containerization model designed to make it easier to build AI apps and integrate efforts.
All of this is based on the idea that AI can make employees more efficient, allowing them to do more work faster with fewer resources.
This concept may be attractive to industries already facing talent shortages. But the real concern is the potential for AI to reduce headcount, so the announcement emphasizes retraining.
“Consortium members broadly recognize the urgency and importance of a concerted effort to accelerate AI in all aspects of business and the need to build an inclusive workforce with opportunities to provide for their families. '' IBM said in the announcement.
Among the consortium members, the group aims to retrain and transition more than 95 million IT workers over the next 10 years.
Many of these employees will no doubt fill so-called “prompt engineering” roles, or as comedian John Steward put it in his recent skit “Type Question Guy,” where they are responsible for creating instructions to direct the AI. You will have to bear the burden. . But as researchers recently discovered, AI is good at creating prompts for it.
On the surface, the idea of retraining workers for a world automated by AI sounds like the responsible thing to do. But the same data used to assess the impact of AI on the workforce can be used to determine which positions to eliminate first and how quickly those roles can be eliminated without looking too sinister. Note that it can just as easily be used to make a decision.
IBM doesn't have a track record of questionable human resources practices. Oh, wait a minute.
it is [disproved] The boiled frog problem. If you put a frog in boiling water, it will jump out, but if you slowly raise the temperature, it will eventually boil away alive. In this case, acting too quickly risks a corporate backlash and, worse, destabilizing the economy. However, there is an argument that introducing AI in stages would give workers time to adapt. ®
