Comparison with other recent disruptive trends One such indirect way would consist in finding individual estimates for each and every type of DiDIY practice that we can think of (DiDIY design, manufacturing, free and open source software, etc.), and then adding up the numbers to get a global estimate of the expected impact of DiDIY. The problem with such a solution is that such individual, more specific estimates are also, for the most part, lacking. While we have seen that some raise a general concern about the greater role of amateur designers potentially destroying jobs, those who express that concern rarely offer quantitative estimates of the net result. While Xxxxx ventures an estimate of 90% of current engineering jobs being under threat, and Xxxxx worries about the jobs of 50 million women in fashion manufacturing and retail, neither of them suggests a timeline for such losses, nor do they estimate how many new jobs might get created in parallel (and as we have said, it seems implausible to assume that XxXXX might solely destroy jobs without generating any new ones). Offering a quantitative estimate of the net impact of DiDIY on employment over the next decade or two is therefore an interesting avenue for future research on the topic. It is worth noting here that even when it comes to other disruptive trends, the anticipated impact of which has been estimated by various experts, we often find wide variance between different estimates. The best illustration of this might be machine intelligence, robotics, and the process of automation that they allow. A widely cited 2013 study by Oxford researchers Xxxx Xxxxxxxx Xxxx and Xxxxxxx Xxxxxxx thus estimated the probability of computerisation for 702 different occupations, and concluded that 47% of US workers had jobs that were at high risk of becoming automated over the next decade or two (Xxxx and Xxxxxxx, 2013). This would correspond to the astounding figure of around 60 million American jobs being at risk from automation – Xxxx and Xxxxxxx highlight, as most likely to be substituted for by computerization, “most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations” together with “office and administrative support occupations” (ibid., p. 38).
