How AI Helps Tech Giants


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Artificial intelligence (AI) and its related technologies — machine learning and the metaverse — represent a watershed in the evolution of the global economy. Like other such shifts, its emergence is likely to favor certain interests, notably a handful of technology giants, the media and a small cadre of highly skilled programmers. Everyone else faces economic danger, certain to roil domestic and international politics in coming years.

Eighty-two percent of millennials fear AI will reduce their earning ability — and they are right to be worried. The first group to lose will be the usual suspects: factory and warehouse workers as well as professionals with largely routinized occupations suited to automation. Service jobs are particularly vulnerable, especially such positions as executive assistants and office managers, long dominated by women.

The most politically disruptive development may derive from the loss of sizable numbers of skilled professionals. Tech firms such as Salesforce, Meta, Amazon and Lyft have announced major cutbacks in their white-collar workforce and have warned that these positions are unlikely to return. IBM has put hiring on hold while assessing how many mid-level jobs can be replaced by AI. Google has recently laid off 12,000 workers, a number that is expected to grow to 30,000. The damage may be even greater at the grassroots level. Within months of AI’s emergence, freelance work in software declined markedly, along with pay for the jobs that remained.

Yet artificial intelligence presents a great opportunity for the economy as a whole. PricewaterhouseCoopers estimates artificial intelligence technologies will add $15.7 trillion to the global economy by 2030. But this boom will likely be more feudal and stratified than earlier tech waves. The “early digital idealists,” notes technology analyst Jaron Lanier, envisioned a “sharing” web that functioned “free from the constraints of the commercial order.”

In contrast, the AI revolution is fostering dependent small satrapies that serve the existing giants of the industry. This new configuration helps those who can tap enormous financial interests such as pension and sovereign wealth funds, who have provided upwards of $7 trillion in capital for new high-end chips and the development of ever more complex and sophisticated algorithms, even as global cash for startups is at the lowest ebb in five years.

AI likely will accelerate the shift towards corporate giantism. Already, Google and Apple account for nearly 84 percent of all mobile browsers worldwide and Microsoft and Apple operating systems control 89 percent across all desktops and laptops. A relative handful of large digital platforms also dominate the $421 billion digital advertising market. Meta, Google, Amazon, X (formerly Twitter), TikTok and Alibaba being the major players globally. Perhaps more ominously, two-thirds of the world’s cloud services — essential for AI and the operation of most digital servers — are controlled by Amazon, Microsoft and Google.

The very logic behind AI, its reliance on existing records and databases, is not ideal for startups; its “primary value,” notes venture capitalist Martin Casado, is “to improve existing operations for incumbents who have the resources to invest at the required levels.” AI may spark improvements in education, medicine and even infrastructure design and maintenance, but the odds that smaller companies will play large developmental roles are slim. Big-tech executives such as LinkedIn and Inflection co-founder Reid Hoffman promise that AI will serve the cause of “elevating humanity,” reflecting the “techno-optimism” embraced by venture capitalist Marc Andreessen. Yet the impact on employment may not be so utopian. Some projections have AI wiping out hundreds of millions of jobs worldwide. In the US, according to McKinsey, at least 12 million will be forced to find new work by 2030.

It’s obvious that AI and enhanced machine learning will accelerate the loss of blue-collar jobs. Warehouse workers will be among the most prominent losers. This extends also to people taking digital orders; Walmart expects to automate its systems with new software and lay off 2,000 workers by 2026. The push for AI-driven automation will be critical in the future, particularly in countries such as Japan and Germany, with their rapidly aging workforces.

AI could also threaten the social and medical services which have experienced huge growth in recent decades. Tech firms are looking to develop “something like your personal AI”; others are developing new robotic nannies. There are already bots that duplicate the work of professionals: by harvesting his total oeuvre into cutting-edge AI software, students of prominent psychologist Martin Seligman came up with a prototype chatbot that Seligman agrees gives much the same advice he would. Less intellectually demanding services may get the AI treatment too, if the need for human sex workers is outsourced to bots. Will the world’s oldest profession disappear?

AI might be most disruptive to the very professional classes that once benefited most from digitization. A recent survey suggests that two-thirds of business leaders agree that ChatGPT will soon lead to large layoffs of white-collar workers, including coders and symbolic analysts. “We may be at the peak of the need for knowledge workers,” Atif Rafiq, a former chief digital officer at McDonald’s and Volvo, told the Wall Street Journal last year. “We just need fewer people to do the same thing.”

Read the rest of this piece at The Spectator.


Joel Kotkin is the author of The Coming of Neo-Feudalism: A Warning to the Global Middle Class. He is the Roger Hobbs Presidential Fellow in Urban Futures at Chapman University and and directs the Center for Demographics and Policy there. Learn more at joelkotkin.com and follow him on Twitter @joelkotkin.

Marshall Toplansky is a widely published and award-winning marketing professional and successful entrepreneur. He co-founded KPMG’s data & analytics center of excellence and now teaches and consults corporations on their analytics strategies.





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