Ironically, algorithms are telling us that machines will soon be able to do most of our jobs, but those conclusions perfectly illustrate what's non-scientific about turning human reasoning over to computers. Barely a month passes without a news story about how robots and artificial intelligence (AI) are going to devastate a significant number of the jobs in the workplace, sweeping away solid salary paying employment for factory workers and white-collar clerks alike. Just this month, the UK Parliament reported on the future of work in the face of automation, declaring that over 70% of jobs were at medium to high risk of displacement. While the report draws on a "more optimistic" study by the ONS to arrive at this prediction, the ONS used methods inspired by the even-more-frightening results in a 2013 paper by Oxford economist Carl Frey and machine learning expert Michael Osbourne, which found that almost half of jobs were at high risk, and two-thirds at medium risk. The paper was so important that in addition to shaping the methodologies of later reports (like those of the ONS, the OECD, and others), it informed a speech of the Bank of England's Chief Economist to the Trades Union Congress in 2015, prompted the "Fourth Industrial Revolution" theme of the 2016 Davos Forum, provided the basis of the WEF "Future of Jobs" report, and generated a subsequent sea of articles by journalists who rarely questioned the numbers.