The Latest News, Views, and Insights from Kairos

Much to even the Microsoft software engineers' surprise, their How Old Do I Look website suddenly became a viral phenomenon a couple of weeks ago. At the time of writing this post, the Microsoft age recognition site had 2.1 million Facebook shares, and many internet and media commentators have written articles about it. Much of the discussion centered around the success, or otherwise, of its algorithms in accurately detecting the photo subjects' actual ages.

If nothing else, this flurry of attention has brought to the fore the topic of determining a best-guess of someone's age using facial detection software.

You are watching TV when suddenly an advertisement comes on. Screeching! Bombastic! Exhorting you, yet again, to go to a particular shop to spend your hard-earned cash on some low-quality plastic trinket. It seems like the millionth time that you have seen and heard, this cacophony of cheapness!

How do you feel? Does this advertisement impel you leave your comfortable chair and drive down to the store in question? Or does it bring a scowl to your face as your eyes glaze over from boredom?

The next advertisement comes on. It is part of a series. It continues a story. You know you've seen it before, but you don't care. You're secretly hoping that it would be the next instalment, but hey, this one's still entertaining. You watch. It reminds you that you've run out of the product being promoted. Better get some on the way home from work!

The thing is your emotions have totally driven your reactions to the two advertisements. The two promotions have drawn completely different responses from you. The products themselves are irrelevant. Two decidedly different types of ads have resulted in two entirely different reactions.

In today’s world many marketers fear not evoking any reaction at all and consider any emotion valuable. Is any reaction truly better than no reaction?

A great media scare story of late has been horror at the potential misuse of facial recognition. Tales of possible privacy invasion have become common in mass media, as well as on the internet.

Of course, much of the speculation is simply hype, designed to play on the public's emotions and fears of a Big Brother power.

However, there are some genuine privacy concerns that do need to be thought through.

When it comes down to it, a photograph is merely a collection of tiny dots that combine to make a recognizable image.

A facial detection system attempts to find patterns in these small dots. There are a number of criteria a face detection app utilizes as it searches for faces, but one aspect it looks for which impacts on this is areas of intensity and darkness.

Extremes in lighting conditions can have an enormous effect on success in detecting faces. An area that is shadowy and dark, or an area bleached out in lightness, may include a face. However from a computer's point of view, the visible shade it sees in the image is outside its programmed accepted range of facial hues. The computer will not detect a face in this situation.

When we talk about facial detection or facial recognition, we generally think about detecting one or more faces that are looking square at the camera. Sometimes, however, it is the situations when people are not looking at the camera that interest us most. There is often a real wish to detect glances away from the camera.