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  • Agustin Chevez

“How are my feet?” and “What did I learn”?


Since I finished my walk (has it really been 5 weeks already?), I’ve really appreciated people’s interest in my journey, and the conversation topics that have arisen. I hope they have been as valuable to others as they have been to me. Talking to people keeps shaping my learnings.


Just as, “Why?” and, “For which charity?” were the most Frequently Asked Questions during the walk, “How are your feet?” and, “What did you learn?” have become the top-rated FAQs post-walk.


To my surprise, I didn’t get a single blister on my feet! I strongly recommend the combination of SmartWool Socks and Inov8 shoes.


The second FAQ is a bit tougher. Unfortunately, what I learnt is not that straightforward. And at times, the look on people’s faces when I try to explain this highlights the difference between my learnings and the expectations of what I should have learnt.


I did, however learn one dazzling fact – and I can even make money out of it:

A bag of horse poo in Victoria sells for $2, whereas in New South Wales $3 is the going rate.


Not only did I learn that there is a horse poo market, I realised that I could become a millionaire! Of course, there are some technicalities to resolve. Preliminary calculations suggest it would take me just over 3,000 years to carry one million bags of horse poo across NSW.


Other learnings have arguably bigger markets than those in need of poo, but their commercialisation is not as clear or profitable. Nonetheless, here are a few of them.


Learning #27: Embrace absurdity, it might be all we have. Once Artificial Intelligence has modelled every possible rational scenario, absurdity might surface as our last standing trait. And by absurdity I mean the quirky mix of randomness with purpose. Not just randomness, not just purpose. Something like walking to Sydney.


Learning #33 (we can talk about numbers 28-32 another time) suggests that the above might happen faster than expected. And this has nothing to do with technology developments like AI, but more with us striving to become like machines.


As early as the 1800s Jevons warned us about the paradox of efficiency, in which the more efficient a resource is, the more it is used; thus becoming inefficient. From what I see, that doesn’t seem to matter in our pursuit of transient human-to-human competitive advantage. We continue to reward, if not demand, efficiency, reliability, consistency and other twentieth century machine-like behaviours in people. I hope we can save a record of what it meant to be human (at least half of the story) into an AI faster than we become an obsolete machine.


A very tangible wake-up call was seeing a cement truck, arguably the slowest of vehicles, passing me at 10 times my walking speed as I struggled to catch my breath walking up a hill. It served as the backdrop of Learning #22: The topography of AI roads, in which we won’t be able to compete even with the slowest of AIs.


Then came Learning #42: Humans are meaning-making machines. Beyond keeping me alive by flagging threats like rubbish snakes, my brain also found subtler, socially constructed meaning in rubbish. All of a sudden, the shadow of the random combination of a discarded roadside circular wire resting on a v-section drain can convey a highly complex humanly constructed message.


Another paradox, if not a cruelty, might be our craving for meaning in an increasingly preposterous future. So absurd it is deliciously human!


I would like to exchange these and other absurdities, like Learning #15: The radius of empathy, #51: Resilience eats motivation for breakfast and one of my favourites: #18 Blood plum jam, an octopus and the shape of memory. Let’s discuss all of these in an attempt to discover what makes us, us. And hopefully when combined, can help to shape the work environments in the future.


In the meantime, please contact me if you live in NSW and want to know more about the benefits of competitively-priced horse poo.

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About Me

As an Architect and academic I have dedicated my career to understand the notion of work and the environments that support it.

 

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© 2018 by Agustin Chevez