Thanks! It’s a great point about use of forecasting, which is the case here. Offenders who are put into the ‘moderate’ category are admitted to the Checkpoint program which takes them through things including rehabilitation and civil service. They are given this as an alternative to prosecution, potentially ending in a jail sentence. So it is indirect, but the machine is informing a decision which leads to some people avoiding jail – that for me is the ethical grey area.
There was a big team from my group at KPMG who were on that same program with WMP, small world!
This is probably one of the coolest things that anyone on earth is trying to do right now. If they are able to figure out the technology for 3D printing a rocket that can get to Mars, could they put a remotely operated 3D printer on Mars as well? A large part of the problem with humans living off-planet is the impossible difficulty in building a habitat fit for humans – if we could have robots build it for us first, the future may have officially arrived.
AI in health is a fascinating area – the potential benefits are enormous, and as Babylon are showing in the UK, automated diagnosis is rapidly becoming a reality. A big concern here though is the lack of an ethical framework – where do we draw the line between human and machine decision making? To take it from the obvious to a little further down the road – how about when machine learning algorithms have developed to the point where they are consistently, provably more accurate than even the best human doctors. At that point, should humans have the right tot over-ride the machine’s decision? We need some philosophers in here alongside the doctors…
With sales per square foot of $2,700 Amazon Go’s store is outselling the average Walmart store by over 600%, given Walmart’s average of $437 (https://retail-index.emarketer.com/company/data/5374f24d4d4afd2bb4446614/5374f3094d4afd2bb444a93c/lfy/false/wal-mart-stores-inc-walmart-us).
Albeit this is Walmart’s average across the US in comparison to the Amazon HQ, but the potential for increasing store sales is clearly huge – could Amazon license its technology to Walmart rather than building its own stores?
Timely article! You do a good job of elucidating the potential cost advantages to Nike of moving to more use of additive manufacturing rather than traditional injection molding, but I wonder about the time impact. From my limited understanding I would expect 3D printing to be slower than traditional injection mold manufacturing, and so the big question is – does the unit cost differential adequately compensate for the loss in output volume?
Interesting post. I am sceptical though of the extent to which content can be crowdsourced in the sense of input across a wide group of people – in part because a majority of people do not possess the requisite creative skills, but primarily because it is impossible to maintain a narrative thread across a population: here is one person’s take on their attempt to crowdsource a novel: https://www.cnet.com/news/4-lessons-i-learned-crowdsourcing-a-science-fiction-novel/.
Bringing crowdsourcing into a government context is an intriguing idea – both for the potential cost / innovation advantages, and the fundamental precept of opening up access to government more widely to the governed.
The example cited in the post about the Department for Education’s app seems to be an opening up of the traditional request for proposal (RFP) process as opposed to necessarily a classic crowdsourcing approach to content. That is to say, presumably the agency is going to pick a single app to run with and pay the creator accordingly. If that is the case, once development companies discover this area then it is logical to assume that app development shops will begin pitching in to these competitions; it is also presumably likely that established businesses (who would respond to a classic RFP in the normal course of events) will win due to its superior resources and understanding of government requirements vs an individual citizen. Therefore, it feels like there is a risk here that the ultimate outcome is simply an additional layer of cost for government procurement.