Will Robots Take Our Jobs?
It is estimated that within the next 35 years, 50% of the world’s jobs will be taken from the people and carried out by a machine. This figure is direct from Moshe Vardi, of Rice University Houston when speaking to the American Association for the Advancement of Science.
It is estimated that within the next 35 years, 50% of the world’s jobs will be taken from the people and carried out by a machine. This figure is direct from Moshe Vardi, of Rice University Houston when speaking to the American Association for the Advancement of Science. His lasting question surrounds what will humans do if machines are going to do all of the work.
He believed middle-class jobs will be the first to go, and the rolls robots would take initially would be surrounding driving and sex. This could leave humans worth a few hours work and week and an immense amount of leisure time. He believes humans will suffer as they have a deep lying belief that work is needed to keep humans healthy.
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Voluntary work would be one thing to do, and charities could benefit, but, whatever happens, there are going to be changes and artificial intelligence is on the rise. It is hard to determine the exact consequences, but they will be strong.
Vardi is not the first person to come to this conclusion, as previous research has led to the view that the UK will lose 35% of the jobs to robots within 20 years, and lower paid workers who will be most affected ones from this change.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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