Four Work and Life ‘Rules’ Technology Is Making Obsolete

Four Work and Life ‘Rules’ Technology Is Making Obsolete

No day goes by without the announcement of some new and amazing technological advancement. Flexible robots, bionic humans, crime detecting streetlights, to name a few. But we’re still stuck in the paradigms of a culture created by, and based on, the old rules of industrialization that led to the occupational restructuring in the 1950s-60s.

Four books I’ve read in the last few weeks?—?including ‘Throwing Rocks At The Google Bus’ and ‘The End of Average‘?—?have made me question a few things about the current nature of ‘work’. Thankfully, our technology is enabling us to rewrite these rules.

Throwing Rocks at The Google Bus’ and ‘End of Average’.
  1. There is no ‘Average’: I’ve never been a standardized test taker. I can comfortably say that because my perceptions of my own abilities have never been based on my test scores. But the US and most of the world’s education system (and the healthcare system, and job market etc) are based on this embedded rule of individual performance compared to a group average. There are two archaic rules we assume about averages and society: Quetelet’s law of average man (individual traits are deviations from ‘proper’ dimensions) and Galton’s law of rank (eminence is consistent, people who are superior in one thing are superior in all things). Deviation from the average suggests that the person being measured is ‘not normal’ in their physical, mental or health conditions. The impact is negative and huge; our jobs, our credit scores, our social interactions have all been defined by this average. Intuitively we know that is not quite right. And now, technology is allowing us to manage our lives to the individual. Todd Rose, in ‘The End of Average’, suggests that ‘jaggedness’?—?the multidimensional nature of skill, aptitude, and health in all individuals?—?makes it impossible to capture anything average in a world where our unique experiences, personal quirks and environmental conditions impact our ‘score’. Thankfully, with technology allowing us to personalize learning and focus on competence testing and accreditation (and whatever area of interest the individual has!), we are moving to a system that doesn’t draw conclusions about capabilities based on just averages. We all know or have read of the implicit biases that exist in these tests anyway, it’s about time technology helps us break these rules that disenfranchise people. People like me, a poor test taker.
  2. How creatives are paid for their work: I couldn’t agree more with the premise of Jon Westenberg’s blog post on how we, and the system, have screwed creatives. The pervasive rule (unfortunately still true in some circles) is that, for art to be true, the creative/artist needs to be poor while doing it. This rule of the starving artist has been immutable for a while. But that rule should no longer apply in a world where the internet allows creatives to do the work and have thousands (even millions) of people enjoy and benefit from it. Jason Lerneir has an approach that’s worth considering in a world where technology allows a creative to benefit from their art. Using Medium for example, according to Lernier, all the content creators/writers on Medium should be paid a cut of whatever revenues Medium makes. But this is not the case. The problem isn’t our ability to measure the value a content creator provides to Medium – every writer on Medium gets analytics on the number of views/recommends/engagement on every article written?—?and neither is the problem an issue of tracking, with Blockchain (for example) every unique view or recommend can trigger a micropayment that can be credited to the account of the writer instantaneously. The real problem is that the old rule says that the platform helping to promote the creative work (record companies for music, publishing houses for books, Galleries for art) is the value provider that captures the returns in the equation and this is false. Technology enables us to change this rule. Now.
  3. The 40 Hour Work Week: Clocking in at 9am and clocking out at 5pm, with a lunch break in-between, is a remnant of a different time. Crazy as it may sound now, the typical work day was 10–16hrs in an age when most employees were factory and shift workers. Henry Ford moved the workday to 8hrs, after the work of folk like Robert Owen, when he realized that employees needed rest to work efficiently. Factory work was an exchange of time for money. It was not based on productivity or value created by the individual. But modern day technology changes that. Our technology (rightly or wrongly) makes us productive wherever we are. Think about it, when was the last time you actually spent eight hours at work, actively doing work all day? Research by Juliet Schor in her book ‘The Overworked American’ provides some food for thought and suggests that not much more productivity is obtained from having employees sit in an office for 8 hrs a day/5 days a week. While telecommuting hasn’t solved the problem (it actually makes people work more), it did prove that there is a different way. And we all know that hanging around in your PJs at home doing work amounts to just about 3–4hrs of real productive work, anyway. Modern technology allows us to have bursts of creativity and productivity that are totally disconnected from the regular 9–5. My best work is done in 2 hour chunks of time, sometimes at 2am in the morning. This level of flexibility due to technological tools at everyone’s disposal is the new rule.
  4. Years of Experience as a metric for hiring: We are living in an age where the tools we are using for our work are brand new. Microsoft released a Creator’s update that allows you to draw 3D objects as you would a regular image, capability that is new. Take machine learning software development or augmented reality operations headsets for linesmen, I dare you to find people with experience/skills of over 20 years using these tools. It might be folly to expect anyone to have more than 10 years experience in building the operating system for AI implanted in brains to prevent epilepsy. What is now required, in the place of work experience, is the number of cycles of experimentation an applicant has had implementing a skill. An example from Creative Confidence; a 30 yr old 10 yr veteran of the auto industry has less experience in mapping software deployment for cars than a 30 yr old who has shipped 20 software updates for Tesla, working at Tesla for just 2yrs. Who would you hire for your driverless car company? The one with more test cycles/mileage? Or the one with 10 years of experience? Years of experience is a rule of hiring that needs to get stress tested for how much value it still provides. It’s one of the issues with hiring new great talent for the utility industry. The industry is looking for years of expertise when it should be looking for the number of rapid innovation cycles a person has been through regardless of their age. It’s the only way the industry will get itself out of this ticking bomb of the retirement of over a third of the workforce in the next 5 years

 

originally published here

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