Friday Faves – What We’re Reading This Week

Friday Faves is our weekly blog series highlighting a few select pieces from the REG team’s reading lists. You can catch up on past Friday Faves on the archive.

Is the war on for digital talent working for you?

Disclaimer: The title for my Friday Fave is not the title from the article.

Anne says: This article from MITSloan Management Review attracted my attention this week for a number of reasons. Firstly, it was co-authored by Kristine Dery, a colleague from the Digital Disruption Research Group (DDRG) and long time friend of the Ripple Effect Group. And secondly, the topic of digital talent is a current research focus that relates to my work on digital capabilities.

The official title: The four ways to manage digital talent and why two of them don’t work, reports on recent research from MITSloan that is exploring the digital workplace and digital transformation strategies being employed by organisations. Immediately you’re drawn to the marketplace war on talent – up until recently, this was relatively straightforward –  how to attract and retain the best people. But the changes brought on by digital workplaces has created 3 key shifts: shortage of talent; need for flexibility; and patterns of work.

In response to these shifts, the researchers have identified four distinct approaches to managing talent: Aligning, Orchestrating, Architecting, and Curating. Each of these approaches attempts to combine the mix of FTEs and freelancers/contractors with the organisations’ needs. The model (image below) highlights the challenges of traditional organisations and their associated processes and structures – the Transactional approach to talent. In contrast, the Relational approach was identified as being used by organisations that are either digitally born or further progressed in their digital transformation.

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So what doesn’t work?

The study identified that organisations with the transactional approach are challenged to adapt their traditional FTE processes and systems to include the type of flexibility digital workers are demanding. At this stage, the research indicated 64% of companies are using the transactional approach. Contrast this against what digital workers are attracted to: companies that offer the relational approach.

The article concludes with what feels like an epitaph: “Adapting to the expectations of the digital marketplace is critical to attracting and building a relationship…”

In this current environment, the digital talent will be the ones who decide – not the organisations and their approaches. Adapt or… not – at your own peril!

Read: http://sloanreview.mit.edu/article/the-four-ways-to-manage-digital-talent-and-why-two-of-them-dont-work/

Machines Taught by Photos Learn a Sexist View of Women

Jakkii says: Bias. There are many types, and we all have those we fall prey to from time to time – some more frequently than others. It should come as little surprise then to see yet another example of demonstrable evidence showing how algorithms are influenced by human biases.

In this instance, researchers noticed a pattern emerging from image-recognition software they were building:

“It would see a picture of a kitchen and more often than not associate it with women, not men,”

This prompted them to test for this (gender stereotyping) bias using large image collections. What they discovered was not only did the bias exist, but machine learning amplified the bias. The resulting software was even more likely to label an image of a person in a kitchen as a ‘woman’ than the training data fed into it showed.

That machine learning is derived from human input making it vulnerable to our biases is a topic we’ve touched on in previous Friday Faves. However what is interesting here is noting how we are working to identify and correct for bias in algorithms underpinning machine learning. Yet even this remains open to debate: as the piece touches on, there is disagreement as to whether we are correcting for bias, or “correcting reality” towards a perceived ideal state. Not only does this have implications within machine learning, but in how we ourselves approach our own biases – when aware of and actively attempting to address our biases, are we merely identifying and counteracting them, or are we overreaching, going too far the other way? How do we manage bias without ignoring our reality in favour of a utopian state?

Readhttps://www.wired.com/story/machines-taught-by-photos-learn-a-sexist-view-of-women/

Inside one of the world’s largest bitcoin mines

Nat says: Humanity has reached its peak in terms of our obsession with money. Imagine living onsite at your workplace for which your profession is to mine for bitcoin – encrypted currency in which one bitcoin is currently worth $4000. This is what workers at SanShangLiang industrial park are doing in inner Mongolia. The workers mine, so to speak, for hidden online gold, and the cost of such mining is huge. The SanShangLian park consumes a daily electricity bill of $39,000 in order to power its 250,000 machines which perform mining calculations 24 hours a day. The electricity cost, however, is nothing compared to the potential millions that can be found through mining.

Bitcoin is virtual, encrypted money and is similar to the mining of physical gold as not all bitcoins have been discovered. This is the extent of my knowledge on the subject matter, but a great overview and video about bitcoin, blockchain and bitcoin mining can be found via The Conversation. Instead, I’ll leave you with a quote by Alan Watts from his book ‘Does it Matter’:

Money is a way of measuring wealth but is not wealth in itself. A chest of gold coins or a fat wallet of bills is of no use whatsoever to a wrecked sailor alone on a raft. He needs real wealth, in the form of a fishing rod, a compass, an outboard motor with gas. But this ingrained and archaic confusion of money with wealth is now the main reason we are not going ahead full tilt with the development of our technological genius for the production of more than adequate food, clothing, housing, and utilities for every person on earth.

Readhttps://qz.com/1055126/photos-china-has-one-of-worlds-largest-bitcoin-mines/

KFC is Using A Fried Chicken Cooking VR Simulator to Train Staff (Apparently)

Joel says: Before you get too excited, I’m going to preface this article with the fact that this is could be a massive publicity stunt for KFC. If not we may be seeing what could become one of the biggest uses for VR outside of gaming. This is a gamified training experience for the KFC workplace in the form of a VR escape room.

The KFC training game (running on Oculus Rift) portrays Colonel Sanders as an AI overload who has trapped the player in a kitchen, where they must successfully inspect, rinse, bread, rack and pressure-fry chicken.

They must complete this task in order to get out of an escape room. The press release states that this VR process is much faster at training staff, taking them through the process in 10 minutes (as opposed to the 25 minutes it’d take in real life).

You can check out a video of the demo here. Be warned, it’s not like any KFC store you’ve ever seen. And hopefully never have to.

Readhttps://press-start.com.au/news/2017/08/24/kfc-using-fried-chicken-cooking-vr-simulator-train-staff-apparently/

The hashtag is 10 years old. Here are the surprising ways it’s changed modern culture.

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“…the hashtag (has been able) to unite the internet…and take over real life”.

Emilio says: It’s a decade old. The simple yet social media indispensable invention of the hashtag, that is.

Created by web developer, ex-Googler and early Twitter adopter, Chris Messina, the hashtag has come a long way since Chris first annexed the pound sign to a word in the hopes of making it easier to create groups on Twitter. And it surely has caught on.

Today, the hashtag is ubiquitous on social media and has been adopted by nearly every major social network besides Twitter including Instagram, Tumblr, Pinterest, Facebook and recently LinkedIn.

Today’s hashtags aren’t just a means of collating social posts around a specific theme or topic; they have become campaigns by themselves. Whether commercial or promotional in nature, or one that inspires action through a cause or movement, the hashtag anchors posts, ideas, sentiments, images, people, objects, places and events.

To celebrate the hashtag’s 10th birthday, here are a few hashtag trivia:

  • The origin of the hashtag is believed to trace back to the Medieval Age in what was known as the ‘Octothorpe’ or eight fields in a square. In later times, the symbol was used to measure weight (‘pound’) and for the number sign (‘hash’).
  • The first ever hashtag was #barcamp, conceived by Chris.
  • One of the first uses of the hashtag was in citizen journalism, by early Twitter users, who aggregated tweets to collate information.
  • 125 million hashtags are shared daily on Twitter alone.
  • Some of the most popular hashtags ever used include #FF (Follow Friday), #BlackLivesMatter, #IceBucketChallenge.
  • Conversely, there were some pretty spectacular hashtag #fails – hashtags whose use backfired because they were not carefully thought through or poorly constructed – #WTFF (What the French Fry) by Burger King, #RIMjobs (Research in Motion jobs) by Blackberry and so many more too dreadful to list here.

It’s a great thing Chris deliberately chose not to patent his invention because imagine how restrictive and pricey that would have been every time we shared a post and hashtagged!

Readhttps://www.vox.com/culture/2017/8/23/16188868/hashtag-cultural-influence-twitter-demthrones-rap