off the rails, required to have human employee. Which sounded AS INTERESTING AS HUMANLY POSSIBLE; In a paper for a recent University of Edinburgh Business School/Stanford University conference Dr Ewa Luger and Dr David Murray-Rust set out futuristic scenarios to highlight the challenges presented by artificial intelligence and other leading edge technologies. Is this a glimpse into the future?
KEVIN was tired of being interesting. He's been 20-years-old in 2017, surfing the tech explosion, opening up new areas of AI-supported work, glorying in the new possibilities. The new jobs that came up suited his 'hyper-focused but only for 10 minutes' way of working: he was a bot wrangler, a decision tree surgeon, a scrum herder - all unheard of ten or even years before.
He'd watched the rules of work being rewritten, the gig economy taking the slack out, perfectly matching people to work, turning free capacity into value. He'd built his career in predictive employment algorithms, creating the hypercompetitive systems that delivered people to just the right place to do a task before the clients even knew they were needed - or 'zero click person shopping' as they called it in the team.
He was so deep in adversarial modelling of human labour networks - understanding what employers would need and when - that he wasn't entirely surprised when he was algo-sized in the 2020s, replaced by a next generation, sub-sentient AI. Expecting it didn't make it any easier to be burped out into a wild and empty job market that even his insider knowledge couldn't navigate.
Truth was, there wasn't much left in the way of work that people were better at. Doctors had gone surprisingly early, helped by rising healthcare costs and precision medicine. Lawyers too, replaced by smart contracts and generalised judgements.
The creative industries held out for a while longer, but the semantic AI boom meant that that concept generation, story writing, music were all just processes, with a 'creativity' dial to tweak. In the economically reduced times, even wedding photographers lost out to fleets of intelligent microdrones, with cinematic kinematics and real-life reconstructions to make the full HD, panoramic, authentic, simple high production weeding videos of people's dreams.
For a while, Kevin was part of the primitivist collective - making things by human coordination and human hands. They had a great line in ceramic tiles, each one slightly different. But those didn't last long - the AI had already figured out the interesting parts of artisanal production, they could 'model the variance', and make every piece bespoke, unique and still ISO compliant. Even in the collective, humans felt inefficient and wasteful, and eventually, chastened, Kevin handed over his rile in the production process to an embarrassingly expert system - about as clever as a dog, but with an amazing knack for resource allocation.
So he'd found himself, two weeks ago, applying for one of the only jobs left, Through a strange combination of Sarbanes-Oxley and a public outcry as the first wave of Decentralised Autonomous Organisations went off the rails, corporations were now required to have at least one single human employee.
Which sounded easy, except that each organisation had to prove that that had a human in the loop. The AIs had spent the last 20 years pretending to be people - tricking lonely men out of credit card numbers, acting in auto-generated content, providing satisfying customer facing interactions - and they were really, really good at it. So Kevin's job as a 'proof of human presence' was harder than it sounds - he had to continually be new and interesting. Anything that a computational model of him could do no longer counted as proof of humanity.
It was exhausting. He'd run through his entire emotional range within the first two days, until the corporation's AIs could trivially model his rants and giggling fits. He tried babbling and nursery rhymes, telling childhood stories that no one else knew and made it to the end of the week while still just being too implausible to simulate. He got through the next few days with dancing - unskilled human movement still had some quirks that were hard to simulate.
But now he was stuck. His only job was to be convincingly human, to pass the inverted Turing test. And he wasn't sure he was up to it any more. |
Below: Dr Ewa Luger
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|Article Type:||Conference news|
|Date:||Mar 9, 2018|
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