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Always fun to read; most are no surprise.


As one year ends and another comes into life, it’s a time of both reflection and prediction. People tend to reflect on the past year – what’s gone right and what’s gone wrong, and also predict how things are going to go for the next 12 months. In terms of technological advancements, 2016 bought us quite a few, but according some of the biggest names in science, 2017 will be even better. Keep reading to see what they had to say:

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A future in which human workers are replaced by machines is about to become a reality at an insurance firm in Japan, where more than 30 employees are being laid off and replaced with an artificial intelligence system that can calculate payouts to policyholders.


Insurance firm Fukoku Mutual Life Insurance is making 34 employees redundant and replacing them with IBM’s Watson Explorer AI.

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A very seductive hypothesis: did Cambridge Analytica use its psychographics profiles to find the audience for our post-truth world? Did they target gullible voters on behalf of Trump’s campaign? Why is a Cambridge Analytica employee reading about the Need for Cognition Scale?

In a remarkable paper (summarised here), Fording and Schram analysed some survey results from January 2016 and highlighted the disproportionate support for Trump among “low-information voters”. They define those as voters who either score low in political knowledge or low on the so-called Need for Cognition Scale. The latter criterion means that they tend to make decisions based on heuristics rather than by thinking through the issue methodically. Of course, the two factors correlate: if you don’t think much about politics, you are unlikely to know a lot about it and vice-versa.[1]

Fording and Schram went on to assess the preference for Trump or Clinton segmented through those criteria. Because the data was collected in January, this is not expressed as a vote preference, but as a “warmth index” (or a difference of warmth), in the Y-axis.

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