AI that scans a construction site can spot when things are falling behind
technologyreview.com
technologyreview.com
I think people will have no idea what the AI evaluates but they will make myths about it and adhere to those (which effectively triggers Goodhart's law). IMO a big chunk of SEO and content marketing is already based on myths around PageRank/YouTube/…
Everyone lives in fear of something with more wrath than a god. Liability.
Because of this they are not willing to do anything even slightly outside of code, and any decision that needs making is a phone call to the engineer rather than making the call on the job.
This slows everyone down as nobody is keen to actually be the one with responsibility. The engineeer who feels the same way also make sure that everything is overspecced to all hell to make extra cirtain that they won’t be liable for anything failing.
You can't imagine it because those bridges and cathedrals collapsed (and were probably rebuilt).
https://www.reconstructinc.com/
Their software is pretty cool, came out of a research group I was working in. Originally, we were using drones to scan the site every day and building a point cloud. I know much of the research team went to the company (I was only working on the scanning system).
Pretty sweet stuff and honestly one of the best uses for a drone I’ve seen.
function isConstructionRunningBehind(project){ return true; }
It would be like an automated inspector that is up to date on the latest building codes at all time and is available 24/7
Yes, this is hugely informative in a $million cost space, but it is also basically "work harder: we said you could"
Estimation is hard. I only do peripheral work in s/w estimation but my life-long experience is that its just hard, and even on million dollar projects, cost blowouts are common. I'm amazed how the london tube expansion, or the new sewerage went, all things considered.
Brisbane's cross-river rail project is 2x price and late btw.
I've had the good fortune to participate in projects where stuff really had to get done and cash was flowing. So a mixture of well-defined scopes, significant performance bonuses and non-performance penalties were implemented, and somehow the downstream contractors were magically able to respond to the unexpected.
The article is quick to say people won't lose their job, but that's not the only fear about automation. Employees hated taylorism because of the reduced autonomy, unrealistic expectations of consistency, pseudo-scientific increased workloads and sometimes mind-numbing boredom.
Problem is, this can sometimes be a little tricky and the supervisors often fudge the numbers to smooth out how their works look. Ie, they may have done 50% of the work, but will only claim 20% because they know that the last 50% worth of the claim card will actually take way longer. They don't want to look bad at the end of each week cause the estimators did a shit job. So they'll take their gains and average them out.
A system that was more automatic and had way more compliance built in would be cool to see. I doubt however, that an algorithm could solve what is predominately an issue of people and estimation.
If a subcontractor were to report, "hey boss, we've gotten 8/10 items done this week, but the remaining two are going to take two weeks because $REASONS. The estimates appear to be flawed, perhaps because $X and $Y.", I suspect the entire project's management would benefit.
The goal is to get the work done on time and with the resources at hand. Micromanagement is often a hindrance to the goal, so good managers avoid it.
They're interested in surviving this project. There seems to be fuck all continuity out there.
Here's my prediction: the AI is going to see a lot of jobs that progress linearly to completion and then stop dead at 90%. That having been said, it'll still be useful if metrics can be sampled out to guesstimate how much padding is needed to account for the 90% dead-stop time.
Image scanning is a stepping stone to true project tracking which I am hoping to work on next! Wish I could say more.
If someone has only half (or less) of the data to forge his lies out of the creative book keeping window is almost gone. Employees with 10-20 years of experience generate lies of undetectable mind blowing quality. I've seen people negotiate their way out of 100% of their job arguing they didn't have time for it.
You want it geo-referenced? Good luck.. so you end up putting a bunch of people on the team working for them to get decent data which bloats your budget and then you look bad to client.
On the other side, an easier to implement and more worrisome idea (for me): AI that monitors your git repo to report you when you aren't getting things done quickly...
Sure, they may not be technically hired, but it comes with the same life devastating effect!
I find it hard to believe AI knowing what's happening on a complex construction site and offer constructive ideas. Just a human looking at a daily photo should do.
McDonald's is 40,000 stores, all similar, 360 days of the year, multiple shifts.
It's just time until the DOM Pizza Checker gets lifted 2 meters and gets an update.
Fact or fiction?