AI: Telemarketers, History and Language Teachers At Risk

Besides teachers, telemarketers, legal services and securities, commodities, and investments are among the top industries at risk of AI advancements

AI: Telemarketers, History and Language Teachers At Risk
AI is currently bad at teaching history, but it is fast learning to correct its mistakes - Photo by Andrea De Santis / Unsplash

A new paper by professors from New York University, Princeton, and the University of Pennsylvania has revealed that language-modeling artificial intelligence (AI) like ChatGPT could threaten the job security of telemarketers and post-secondary teachers such as English language, literature, foreign language, literature, and history teachers.

Legal services and securities, commodities, and investments are among the top industries at risk of AI advancements. Using a methodology they developed back in 2018, the researchers estimated which occupational descriptions had changed the most due to advances in AI between 2010 and 2015.

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The results suggest that even educators are at risk of losing their jobs to AI, as the technology may change the way teachers assign work, detect cheating, or develop teaching materials.

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Furthermore, AI is currently bad at teaching history, which is one of the top-ranked teaching jobs likely to go the way of the machines.

The paper argues that the potential for language modeling to augment or substitute for human telemarketers' work highlights one aspect of the AI Occupational Exposure measure: it measures exposure to AI, but whether that exposure leads to augmentation or substitution depends on the specifics of any given occupation.

Moreover, as per the Daily Mail, school psychologists and judges are also put at risk by these technological advancements.

Mastercard, Spotify, Fandago, and Lyft are just a few companies that use chatbots to answer customer questions.

The ability of language modelling to replace human telemarketers demonstrates an aspect of AIOE: exposure, according to the researchers. The score assesses a person's exposure to AI. However, whether this exposure results in substitution or augmentation is dependent on the occupation.

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