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This is the final blog post to our 5 Part Series on Empathy and its relation to artificial intelligence, machine learning, and where we are headed in the future with technology. Read up on the series and follow the Kairos team as we explore empathy in the tech field and ways to implement it.


The future of empathetic AI is taking place every minute ahead of you. The future is being shaped now. We already looked at several companies integrating empathetic code into their AI and each day there are more developers innovating with emotional AI in the fields of education, healthcare, retail, marketing, and even gaming.

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"...every tool ever invented is a mixed blessing. How things will balance out is a matter of vigilance, moral courage, and the distribution of power.” - The Cult of Information, by Theodore Roszak, Author and Professor


At Kairos our vision is clear, we want to make the world a better place by serving humanity with our Human Analytics software. And that isn’t just hollow marketing talk - this is a deeply rooted belief that Kairos can have a lasting, positive impact on people's lives. It’s a daily mission to listen, support and empower our customers to create experiences that go beyond the nuts and bolts of a product. Together we are creating the future. And with that comes a great responsibility.

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Illustration of two heads, one human and the other a robot or machine.


This is part 4 to our 5 Part Series on Empathy and its relation to artificial intelligence, machine learning, and where we are headed in the future with technology. Follow the Kairos team as we explore empathy in the tech field and ways to implement it.


In our earlier posts we've discussed, and proven, empathys' growing importance in artificial intelligence. The next questions to ask are, "How do we make AI empathetic?", "How do we build emotion into our AIs?" and "Can we ever make AI feel?"

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We’re announcing our new developer product, the Kairos Human Analytics SDK, to allow any business to create more personal experiences for their users.


This new SDK lets you measure and use data about the human face in your camera enabled apps and products. Its state-of-the-art face analysis and machine learning algorithms deliver fast and accurate real-time results. You can analyze any image, video or stream from most embedded, USB or IP cameras.

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Illustration of two hands shaking, one human hand the other a robot or machine hand


This is part 2 to our 5 Part Series on Empathy and its relation to artificial intelligence, machine learning, and where we are headed in the future with technology. Follow the Kairos team as we explore empathy in the tech field and ways to implement it.


The debate over machines and their role in our society is not new, people have been fearing machines, or robots, will replace us in the workforce and slowly take over the world since machines came into the workplace during the Industrial Revolution, via the 1800s. However, we were wrong to be afraid.

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This is a 5 Part Series on Empathy and its relation to artificial intelligence, machine learning, and where we are headed in the future with technology. Follow the Kairos team as we explore empathy in the tech field and ways to implement it.


I recently expressed to someone about a time in my life that left me upset, changed, and almost broken. Their response was "I'm sorry, but every one goes through tough times. It sucks, but it's normal". I have thick skin, it's hard to offend me or upset me, but that statement made me roll my eyes and shake my head.

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Photos of different human faces with the words 'private' and 'public' overlaid.


A database of faces is a key element that is needed when working with any facial recognition technology. Without it, an algorithm can not ensure accuracy when comparing or recognizing unknown images to older identified images just like without a battery, your computer won’t turn on.

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Technology is changing and evolving every day at an increasing rate. It seems like every week we hear about a new tool we can use, a new software that will soon be part of our lives, and sometimes it can seem overwhelming. With all this new information out there how can we be sure that the technology we are developing is being used for good?

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1984, George Orwell said it best “BIG BROTHER IS WATCHING YOU”, a line that seems to be repeated in different ways in different mediums over the course of human history. Big brother is usually a reference to the government, but it’s any authoritative power, who uses force, power, and technology to mindlessly control the majority of the population.

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Photo of happy young girl with text explaining the micro expressions of the emotion 'Joy'


Imagine you are watching a political debate where Candidate A is passionately going on about a topic and Candidate B is listening attentively. The camera zooms in on Candidate A whose eyes are wide open and hands are gesticulating. As the camera pans to candidate B you see it, a smirk, and a quick eyebrow raise. It only takes a fraction of a section but through this small group of facial movements you have learned that Candidate B does not agree with Candidate A. Candidate B didn’t have to say a word, the distaste was shown through a micro expression, which will gain or lose voters’ sway just like that.

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Whatever your opinion about facial recognition software, it’s clear it’s becoming an integral part of everyday life. Whether it’s preventing and eliminating crime, identifying lost children, ensuring deliveries, or just bringing some much needed humanity to the tech revolution. Afterall, in the not too distant future, every ‘thing’, we are told, will be connected to the Internet. It’s only a matter of time before those ‘things’ are able to recognize and understand us.

Now to some this may feel like an Orwellian prophecy come true, yet, on closer inspection, this simply isn’t the case. Companies, both big and small, are thinking deeply about how to make our lives easier with this technology.

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Illustration of Robert Plutchik's 'Wheel of Emotions'


“How are you?” What a simple question with so many complex answers yet most of us answer with “Good”. Besides our culture, why do we default to a one-word expression to explain our feelings? We feel a range of emotions but to use them we must learn what they are and express them correctly.

We’ve already discussed the 6 universal emotions; joy, surprise, sadness, anger, disgust, fear, and sometimes contempt, but there are many other emotions that stem off of them.

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Image of the 'Kairos Human Analytics' logo and 'IBM Watson Ecosystem Partnership' logo


As an IBM Watson Ecosystem Partner we work with IBM Watson™ to transform how businesses understand people through unique human analytics. Kairos’ face analysis algorithms are able to recognize and understand how people feel in video, photos and the real-world. Watson is a cognitive computing platform that uses machine learning to reveal insights from large amounts of unstructured data.

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A young, smiling brunette woman with the words 'Project Look by Kairos' overlaid.


Project Look is a market research tool that uses best-in-class emotion detection algorithms to measure people's reactions to video content. Within minutes you can be testing your videos with your audience and get real-time, actionable insights. All in the cloud. No coding required.

Why we created Project Look

Imagining how to use a technology like face analysis is often the easy part. Applying it in the real world - that’s a whole different ball game.

Yet, this is what motivates us over at Kairos HQ. We love seeing our customers solve real business problems by using the tools we have designed. But when we spoke to early customers, we realized these tools weren’t the only part of their journey.

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A line graph and text describing emotions overlayed on the face of an attractive, brunette young woman who looks surprised.


People used to think the earth was flat. That theory was disproved by many famous mathematicians, but before those discoveries, humans perceived the universe in two dimensions. Fast forward to today, while the earth is still round, business, an integral part of modern-day society, is still only running on engines of two dimensional data.

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The research of facial recognition has been a fascinating journey. It began in the 1960s with Woody Bledsoe, Helen Chan Wolf, and Charles Bisson who created programs to assist with basic face recognition. They were not fully automated back then, requiring the administrator to locate the key facial features such as the eyes, ears, nose, and mouth on the image being examined. The programs calculated distances and ratios to a common reference point which was then compared to set reference data.

Since those early days, many facial recognition research groups have examined various aspects of facial detections and recognition. By the 1970s Goldstein, Harmon, and Lesk were able to automate the recognition process by using 21 specific subjective markers, such as hair color and lip thickness.

Kirby and Sirovich's research in the late 1980s gave another leap forward to the nascent technology, by determining that less than one hundred values were required to accurately code a suitable aligned and normalized face.

I have found 56 locations where facial recognition research groups have been the vanguard of 21st-century research into facial analysis. Some of this research is now historic, although still freely available on the internet. In other cases, the research is ongoing, with capabilities and techniques being improved on all the time. Some of the research is very clearly focused on facial research. Some of the other studies have only a peripheral connection to the subject.

I have tried to include all facial recognition research groups whose work appears on the internet. If you know of a group that is missing from this article feel free to contact us at Kairos and I am happy to update this post.

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Who's talking about facial recognition privacy?


The biggest news in the facial recognition industry this month has been the walkout from the ongoing facial recognition privacy talks by the nine consumer/privacy representatives. While the media has widely reported the walkout, as in this New York Times article, often quoting from the privacy advocates' press statements, there has been little public comment from members of the facial recognition industry. As a strong supporter of these talks, we at Kairos would like to share our viewpoint.

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It may surprise people to know that although Kairos is still a relatively young company, it has not always focused on providing facial recognition software. In its early days, Kairos was best known for its flagship app, TimeClock.

As its name suggests, Kairos designed TimeClock to clock employees in, who are paid on an hourly basis. The TimeClock app used facial recognition technology to enable employees to clock in, to eliminate the risk of “buddy punching", which is when people clock in on for their coworkers for time when they did not actually work.

Now, TimeClock was an excellent product - make no mistake about that. However, it did not take long for the team at Kairos to discover there was far more interest in the facial recognition technology itself. There was more potential uses for facial recognition technology than just underpinning the time clock itself.

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You prick up your ears at the word "analytics".

It's something of a buzzword at the moment. Google Analytics, Moz Analytics, Pinterest Analytics, Twitter Analytics... the lists of data that analyze our online lives goes on.

If you are a marketer, I am sure that you regularly use a wide selection of valuable analytics reports to determine the successes and failures of your online campaigns.

And the developers among you, just about to click away from this post, at the mere mention of the word “marketing”, do you know analytics can help you too? Imagine the potential you have to create apps that collect and provide valuable analytics reports that your users truly love.

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Icons symbolizing different face recognition use cases mentioned in the article


All too often we read doom and gloom stories in the media decrying the uses of facial recognition in society. Stories abound of "Big Brother" looming over you, watching your every move. We disagree. If you look at the facts, there are many inspiring uses of facial recognition in practice. Facial recognition technology has a real potential to help people, whether it be finding missing loved ones, keeping you safe or helping you to relive some of your happiest memories.

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