Google and Uber are both developing self-driving cars to replace taxi drivers and truckers, thereby challenging jobs that are ‘below the API.’ This refers to jobs that require set responses to predictable inputs, which are increasingly being automated. Google’s self-driving cars, currently in prototype testing, are expected to launch within five years. Uber, on the other hand, is building its own fleet of self-driving cars, aiming to replace its 160,000 drivers.

The rise of automation could lead to significant job losses. For instance, there are 233,000 taxi drivers and chauffeurs in the US, and 1.7 million truckers. These jobs are at risk due to the development of self-driving cars.

Furthermore, automation is not confined to the transport sector. Jobs that involve predictable physical work, data collection, and data processing are also highly susceptible to automation. This includes jobs such as food preparation, retail sales, and office administration.

While automation can lead to job losses, it can also create new jobs. However, these new jobs often require higher skills and education. Consequently, the rise of automation could increase inequality by disproportionately affecting low-skilled workers.

In response to these challenges, society needs to rethink education and labour policies. This includes promoting lifelong learning and retraining, and considering policies such as a ‘robot tax.’

Go to source article: