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

Computers can’t tell if you’re happy when you smile


Anne says: Facial recognition is becoming ubiquitous – slowly but surely – as more and more images are used for identifying people through their unique facial structures. For anyone that uses facial recognition on their phone, you may already know it’s not an exact science! (My phone really doesn’t like me first thing in the morning!). Extending facial recognition there is now the emerging market of emotion recognition – particularly in robots that might be deployed in customer service or carer roles. This market is predicted to be worth US$23 billion by 2023. But… as this article in MIT Technology Review explains – they just don’t have enough data and computers are worse at it than people. (And people aren’t very good either – if you’d like to have a shot – try the Spot the Fake Smile activity below!). 

So what’s going wrong? Apparently, they’ve based the data on “reading faces”. However, emotion is expressed in more than just our faces and has cultural and behavioural contexts as well. To date, the research is insufficient and the amount of data inadequate. The article also highlights the current processes for developing the algorithms – again, flawed by the use of stereotypes or using actors to pose for an emotion, such as surprise. Another approach for data collection is using real people in context and asking them to self-report on their emotions. From our experience of user research, people may not provide accurate reports – in many cases, they’ll tell you what they think you’re looking for.

The recommendations for developing accuracy in reading emotions is going to take a lot of work – it will need to include context, voice, posture and physiological information for several occasions, not a single event. Clearly, emotion recognition is complicated but with the size of the industry and the demand for products with emotion recognition, watch how quickly this will evolve. And of course, watch the number of bloopers along the way!


Now – it’s your turn – if you’re up for the challenge – here’s a short test.

Spot the Fake Smile

Most people think they are fairly good at reading facial expressions – in particular, spotting fake smiles.

The Fake Smile Test was first published by the BBC on their Human Body show and based on the research by Professor Paul Ekman from the University of California and Dr Wallace V. Friesen from the University of Kentucky.

An average individual typically scores 13 or 14 out of 20 smiles correctly. How well do you think you can do?

The test will take about 10 minutes to complete – there are 20 questions – or smiles to evaluate. You have to figure out if the person is smiling because they have genuinely seen something amusing, or if they are smiling because they were told to! Select Genuine or Fake and click next. You’ll then be shown the correct answer.

NB: Keep track of your score on a piece of paper – the site doesn’t total these up at the end. And you only get one shot at each video, you can’t keep replaying it!

Good luck and happy smiling!

Click the link below to start. On the second page, it asks you to fill in details – you don’t need to, just click next and start the challenge!

Take the test

Woolworths to roll out mini robots to process online shopping orders


Joel says: Woolworths has announced that it will be taking a larger leap into the technology world to help assist in the processing of customer’s online orders. They have partnered with US company, Takeoff Technologies to help them build automated packing centres that will be located at the back of supermarket chains that will handle the picking of shopping orders placed online.

Due to the growing demand for online orders and their customers urging same-day delivery, Woolworths CEO Brad Banducci has mentioned that the partnership with Takeoff will allow them to enhance the overall shopping experience with faster order picking and delivery. The trial sites for automated picking are planned to be up and running within a year.

This isn’t the only advancement Woolworths has been making to the customer’s shopping experience though. Earlier this year they announced that they would be expanding their drive-through shopping service to other areas. Allowing you to pick up your groceries without having to park or leave the car.

I found this piece interesting because it’s another case of a big retailer expanding it’s sales and customer experience through the use of modern technology. Amazon has implemented similar kinds of robots in their fulfilment centres to meet customer demand, and reminded me how pizza giant Dominos no longer consider themselves a pizza company, but as a technology company whose end product is pizza. All of their recent advancements into better products come from technology that can keep your pizza fresher longer, live tracked, quality scanned etc and I think we’ll be seeing more tech-focused advancements from Woolworths and other large chains constantly thanks to the technology-driven world we live in today.


Emoji Don’t Mean What They Used To


Helen says: I came across an article about Ford celebrating the approval of a pickup truck emoji. I had never really considered a formal submission process, in the context of creating emojis, so I started googling. To my fascination, an entire emoji world unfolded before me. I came across an emoji conference, found an emoji dictionary, discovered that 17 July is World Emoji Day (the date on the calendar emoji), checked out the 2019 World Emoji Award winners and even uncovered a musical, Emojiland, performed in 2018 to sell-out crowds in New York. By the way, I did find a helpful video on how emojis are made and submission is not for the faint-hearted! 

Completely distracted from the original article I found myself reading about the emoji evolution. I like to think of myself as an early adopter – from about the age of 10, back when writing letters was not a novelty, my signature always ended with a smiley face. Fast forward a few decades and emojis have become a big part of popular culture playing an important role in online communications. However, as the emoji library – now 3000 plus – continues to expand and images become more explicit, they are losing their flexibility. Rather than having an abstract meaning they are becoming more specific which, may appeal to diversity, but it could also be making it harder, not easier, to find the right emoji. I enjoyed this article and the examples used to help demonstrate how the emoji as we knew it is changing.


Meet Generation Alpha, the 9-year-olds shaping our future


Jakkii says: I am generally troubled by our use of ‘generations’ and the stereotypes and broad-stroke assumptions that often come with them. I have, on many occasions, been the naysayer tweeter at conferences, rejecting incorrect generational assertions such that all boomers are bad at technology, or, even worse, an ongoing obsession with talking about what to do about millennials in the workplace that conveniently ignores that the oldest millennials are now nearly 40, and quite possibly even your boss. Recently at conferences, we seem to have dropped the millennial talk to finally discuss Gen Z, the oldest of which are in their 20s and well into the workplace already, making it a little late to start discussing how to ‘prepare’!

When it comes to generational discussions, I think it’s fair to consider the changing nature of the world at large and, more specifically, the changing nature of education, work, and the workplace, and how different experiences of these can impact expectations. What I think we miss in these discussions, though, is remembering that each generational cohort is made up of a whole bunch of individuals who each have their own lived experiences, needs, wants and expectations, and that they aren’t the same across each individual. A generation is not a homogenous group of people who can’t be differentiated from one another. Similarly, we also neglect to discuss in much detail that previous generations don’t stop learning, growing, evolving and adapting to the world around them when a new generation comes on the scene, or when they come of age and enter the workforce. It feels, at times, like an extension of the myth that ‘you can’t teach an old dog new tricks’ – we are not incapable of learning and adapting, though some of us may struggle more than others, and some may resist more as well. 

All that said, from a sociological perspective I do find it interesting to consider the different global, local and social contexts in which each generation have grown up and the different notions of work and the workplace that existed when they came of age – or will exist, for the youngest amongst us. Which leads me to this week’s contribution, all about the youngest generation: Generation Alpha. (Not going to lie, that sounds super sci-fi to me, but then maybe I just watch too much TV  ). Gen Alpha were born starting in 2010 to now, and are generally children of millennials. The piece points out that they’ve been ‘wired all their lives’, but interestingly doesn’t really touch on that social media like Facebook, Twitter, and even Instagram have all been around since they were born, with Snapchat appearing in 2011.  

This is a short overview from Axios, so if you want to dive deeper you might like to check out this blog from McCrindle (the researchers Axios reference in their overview), read the article “Generation Alpha: The Children of the Millennial” on Interesting Engineering, and give this podcast with Hotwire’s Laura MacDonald a listen, where she discusses “how these technological inventions are changing kids’ minds and what that ultimately means for communications.” 


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