In the first episode of our Questioning Artificial Intelligence mini-series, Ian Sample explores some of the key hurdles for machine learning, including reasoning and social intelligence

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The media is full of stories of the hopes and fears over rapidly evolving artificial intelligence (AI) technology. But it’s not just pundits debating the pros and cons of what AI might one day achieve: among AI researchers themselves there is plenty of disagreement over what the future holds. Instead of trying to predict what will happen in decades to come, this mini-series will look at the here and now, and pose four questions to experts about AI in 2018. First up: what are the key challenges AI researchers are wrestling with today?

To help Ian Sample try to identify some of these hurdles we hear from Prof Manuela Veloso, head of machine learning at Carnegie Mellon University in Pittsburgh, who believes that the key to success is data, data, and more data. Joining them both is Arizona State University’s Prof Subbarao Kambhampati, who highlights the need for reasoning as well as recognition in machine learning systems.