Emotion Technology Year in Review: Affectiva in 2016

It’s an exciting time to be in the artificial intelligence space. AI is becoming more pervasive and a lot more mainstream. The work we do at Affectiva brings a unique perspective to AI, with our mission of humanizing technology with artificial emotional intelligence.

Beyond the scope of Affectiva, interest in Emotion AI is heating up, with Apple acquiring Emotient earlier this year and other large tech companies investing in the space.

Personally, it was quite an exciting and busy year. I became Affectiva’s CEO and focused on our culture of openness, innovation and flexibility (in fact we were listed as one of the best rated places for parents to work). We raised additional capital for the company and positioned Affectiva at the center of artificial intelligence. Throughout the year, we evangelized how Emotion AI is transformative across various industries. We spoke at events such as TechCrunch and WebSummit showing audiences how they can apply emotion analytics in their own line of work.

Here are some of my top Affectiva highlights of 2016:

1. Defining the Category of “Emotion AI” the next frontier of artificial intelligence.

In 2010, shortly after we spun Affectiva out of MIT Media Lab, I had the opportunity to meet with Todd Dagres of Spark Capital. “The best companies”, he said, “are those that define a new category, name it, seed it and lead it”. Advice I never forgot.

Affectiva has always been a thought leader within the new and emerging emotion technology space, yet the category was still unnamed.

Earlier this year, we were brainstorming this category’s name. Our top contenders were emotion recognition, emotion analytics, and emotion sensing. All were true to the category but did not fully capture the transformative implications of our technology. So we came up with Emotion AI and used #EmotionAI in a tweet the same day.

Emotion AI, short for artificial emotional intelligence, underscores that machines, like humans, need emotional intelligence to be most effective. This is especially true today in a world where technology is becoming more and more conversational, perceptual and relational.

Ever since then, Emotion AI has taken a life of its own. It has been referenced thousands of times, and has become synonymous for this class of technology. My favorite example was when months later a VC called and said “We’re looking to invest in the Emotion AI space”, I remember thinking to myself “Wow, so it’s a thing now!”.

Read more about EmotionAI

2. Leading in Emotion AI Innovation with deep learning and on-device emotion sensing

We strive to provide comprehensive facial expression and emotion classifiers. This year we added multiple-face tracking in photos as well as video streams. We also added gender, age and ethnicity detectors, 13 new emojis and 6 new facial expression classifiers including nuanced ones such as a cheek raise, lip stretch and jaw drop.

We continue to experiment with deep learning, leveraging the massive dataset of emotions we have and our video labeling infrastructure. As I write this, we have collected and analyzed over 4.8 million face videos from 75 countries. This year we also focused on expanding the various contexts represented in our data to include data of people viewing online content, playing video games, driving cars and conversing with other humans and robots.

Read more about our work with emotion recognition

3. Applying Emotion AI Across Multiple Industries

Our vision for Emotion AI is one that cuts across many markets, humanizing the way in which we interact with technology while enabling businesses to get emotion insights in a way never possible before. This year we invested in seeding Emotion AI in several verticals:

• In advertising research, we continue to grow our footprint with global partners such as Millward Brown and Unruly, through which over a third of the Global Fortune 100 and over 1,400 brands use our technology to optimize their advertising content and media placement.
• In gaming, we announced our Unity SDK and partnered with game studios to build emotion-aware games. For example, Flying Mollusk developed Nevermind, a psychological thriller that adapts gameplay based on the player’s emotional state.
• Through iMotions and their human behavioral research platform, our technology is in use by many research labs including Texas A&M, GSK, Deloitte, McGill University, NYU, and Mindshare.
• In social robotics, the healthcare companion robot Mabu uses our tech to most effectively engage with patients and encourage adherence to treatment plans.
• We partnered with Giphy to analyze and encode emotions in all their content – making it possible to search for GIFs by emotion, and even use your own emotions to search online with our emotion recognition technology.

Read more about Industries leveraging EmotionAI

Final thoughts:

I just finished reading Shoe Dog, Phil Knight's fascinating memoir of how he started Nike--and was struck by this line "With thanks for taking a chance on me".

So as we end 2016, I want to thank my team, our investors, our clients, partners and developers for taking a chance on Affectiva, for believing in our mission and for championing it. We are grateful for that support. Together, we are building a bigger and better future for Emotion AI, and have some new developments in store for the industry in 2017. We hope you’ll join us for the ride.

Best, Rana

PS - you can read more of my highlights from this year at Affectiva at the full article here.