iWorld
OTT video services dominate US network traffic
MUMBAI: The latest internet traffic trend report from Sandvine has reported that the network traffic in the US is dominated by over the top (OTT) video services.
Tracking of the fixed and mobile networks across the globe shows that peer-to-peer file sharing has fallen below 10 per cent of the total traffic in North America. This is starkly different from the 60 per cent share it consumed 11 years ago in the heyday of Napster and other P2P services. Even five years ago, it accounted for over 31 per cent. The figure was reported in the six-monthly survey conducted by the broadband network solutions provider, Global Internet Phenomena Report 2H2013.
The report has also found that the OTT leader Netflix (31.6 per cent) held its ground as the leading downstream application in North America, and together with YouTube (18.6 per cent) accounts for over 50 per cent of downstream traffic on fixed networks.
Average monthly mobile usage in Asia-Pacific now exceeds 1GB, driven by video, which accounts for 50 per cent of peak downstream traffic, more than double the 443MB monthly average in North America.
eNews
AI could replace half of entry-level white-collar work: Anthropic study
Hiring in AI-exposed occupations fell 14 per cent post-ChatGPT
SAN FRANCISCO: From lamplighters to elevator operators, waves of technology have repeatedly erased once-common jobs. Now artificial intelligence may be poised to do the same for large swathes of professional work.
A new study by Anthropic suggests that while AI tools are technically capable of performing many knowledge-economy tasks, real-world adoption lags far behind that potential, at least for now.
The report, Labor market impacts of AI: A new measure and early evidence, by Maxim Massenkoff and Peter McCrory, introduces a new metric called “observed exposure,” which compares what AI systems could theoretically perform with what they are actually doing in workplaces.
Using professional interaction data from Anthropic’s Claude model, the researchers found that AI could theoretically cover a wide share of tasks in business, finance, management, computing, mathematics, legal services and office administration. Yet current adoption represents only a small fraction of those capabilities.
That gap between potential and reality reflects a mix of legal barriers, technical limitations and the continued need for human oversight, the study said. But the authors suggest those constraints may prove temporary as the technology matures.
Warnings about AI’s impact on white-collar employment have been growing. CEO Dario Amodei has previously argued that AI could disrupt as much as half of entry-level professional work, while Microsoft AI CEO Mustafa Suleyman has suggested that most professional tasks could eventually be automated within 12 to 18 months.
Highly educated workers most exposed
Contrary to common assumptions, the study finds that workers most exposed to AI are not those in manual labour but highly educated professionals. The most exposed group is 16 percentage points more likely to be female, earns on average 47 per cent more than the least exposed group and is nearly four times as likely to hold a graduate degree.
Occupations including computer programmers, customer service representatives and data entry clerks are among the most vulnerable to automation.
Yet even in highly exposed fields, AI is not yet replacing jobs at scale. The researchers cite routine medical tasks, such as authorising prescription refills, as examples that AI could technically perform but is not widely observed doing in practice.
In the report’s visual framework, actual AI usage (the “red area”) remains far smaller than the theoretical “blue area” of possible tasks. Over time, the researchers expect the red area to expand as adoption deepens.
At the other end of the labour market, roughly 30 per cent of occupations show virtually no AI exposure. Roles such as cooks, mechanics, bartenders and dishwashers still depend heavily on physical presence and manual work that large language models cannot replicate.
Hiring slowdown rather than layoffs
So far the clearest labour-market signal is not mass layoffs but a slowdown in hiring within AI-exposed occupations.
According to the study, job-finding rates in those sectors have fallen about 14 per cent since the arrival of generative AI tools such as ChatGPT compared with 2022 levels. A separate study cited by the authors found a 16 per cent drop in employment among workers aged 22 to 25 in AI-exposed roles.
Recent labour data from the US Bureau of Labor Statistics also point to softer hiring conditions, with employers shedding 92,000 jobs in February and unemployment rising to 4.4 per cent.
Some companies have already linked layoffs to automation. Jack Dorsey said his payments firm Block recently cut nearly half its workforce in part because AI tools allow smaller teams to operate more efficiently.
Not everyone is convinced the technology is solely responsible. Critics such as Marc Benioff have accused some firms of “AI washing”, using automation as a convenient explanation for cost-cutting measures.
Still, the researchers warn that the longer-term risk is a potential “white-collar recession”. If unemployment in the most AI-exposed occupations were to double, from about 3 per cent to 6 per cent, it would mirror the scale of labour-market disruption seen during the Global Financial Crisis.
For now, the shift may simply mean fewer entry-level openings. Some young workers are staying longer in existing roles, switching sectors or returning to education rather than entering AI-exposed fields.
