Amazon has just revealed the proposed design for its second headquarters, in Arlington, Virginia, just outside of Washington, D.C. Designed by NBBJ, the project “creates an environment that prioritizes healthy work, celebrates nature and engages the community across multiple scales.” Encompassing 2.8 million square feet of offices, public gathering areas and street-front retail, the intervention aims to create a healthier workforce and community.
This article was originally published by Common Edge as "A Seattleite Reflects on the City in the Age of Amazon."
At first, it was just a crane or two, a little urban renewal down on Westlake, a rumor that Paul Allen was cleaning things up, wanted a huge park with bike trails. I thought that might be nice and didn’t think about it again for a while.
No park happened, but one day I went down to the new Whole Foods below where I work and noticed that a whole habitat had sprung up on Westlake, an expensive Mexican chain restaurant and an expensive Italian place and an expensive Thai place, and some expensive after-work bars. I also noticed small groups of men, all white or Indian and all wearing lanyards. These groups moved around the streets, talking animatedly, freshly out of their cubicles and going to lunch, oblivious to whomever else was on the street.
Amazon’s open call for bids for its new headquarters, HQ2, closed last month, but in the months leading up to the final decision in 2018, analysts will continue to flood the internet with detailed studies evaluating who they believe should be the winner. In other words, the mirror-mirror-on-the-wall game for cities is just starting to warm up.
Earlier, ArchDaily reported on the data-driven approach adopted by Moody’s Analytics which projected Austin, TX as the winner. But another study by IT education company Thinkful now points towards Washington DC as the city most likely to make the cut. So what makes Washington DC the fairest of them all? Read on to see how data science techniques helped analysts at Thinkful with this prediction, what kind of approach they adopted, and how it differed from that of Moody’s Analytics.
