The goal of education is to provide rich learning experiences for each student that build on and shape one another in ways that help children make sense of their lives and the world. Education also should provide an intimate social experience and experiential context. Education’s focus on development of cognitive skills occurs in a social context that can vary considerably, but nevertheless each individual’s learning experiences usually are as much the product of social interaction as the result of thought-provoking curriculum. 
  
Personalized learning, which tailors instruction and assessment to each student’s unique needs and preferences, potentially can erode the value of what can be learned from social relationships and interactions, especially with technological advances that enable one-on-one instruction. Teachers that are transforming their traditional classrooms into what they refer to as “blended learning environments” generally mean that the classroom uses technology to provide more tech-assisted personalized learning experiences for each student without diminishing the benefits of their social experience. 

The really wise teacher, moving as rapidly as possible from old school to the new tech-assisted and -managed learning paradigm, tries to figure out ways to empower students both individually and as a group to take responsibility for their learning. In other words, the dynamics of the learning process focuses on using technology as a tool to enhance students’ collaboration to discover and share ideas and, not least of all, feelings in the process of solving problems. 

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What is not yet part of the concept and practice of “blended learning” in the classroom of today, but looms somewhere in the future, is tech-assisted learning, in which machines are capable of interpreting the emotional state of students and adapting their behavior to give appropriate responses to those emotions. This artificial emotional intelligence technology (AEI) technology enables machines to join and collaborate with the learning process, the generation of ideas, and even the feelings at work among students and their teacher in the classroom. 

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Big tech and startups, as well as university-based and other research organizations, already are devoting major financial and staff resources to developing technology that can recognize, interpret, process, and simulate human affects, i.e., the experience of feeling or emotion. AEI is being developed mainly for marketing, in order to target video and other content to the right audiences. Mental health is another huge application for AEI.

Not many people are talking about emotion detection and recognition technology being used in K–12 education. But money pouring into technology companies to finance the teaching of computers to understand human emotions eventually will find its way into personalized learning. St. James Faith Lab will keep a watchful eye on AEI developments in education, healthcare and mental health and elsewhere.

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Thus in the midst of clamor about addiction to smartphones, and now potentially voice-assisted devices, we hear paradoxical praise for the capabilities of AI to enhance empathy so as to improve relationships and make them more fulfilling. An emerging trend in artificial intelligence is to get computers and voice-assisted Internet of Things (IoT) devices to sense how we’re feeling and respond accordingly. 

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Will this trend make its way into K–12 education? Will smart devices that kids use while learning in school or at home know how these kids are feeling and perhaps respond, for example, with empathy and 
compassion? 

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Teachers already are struggling with questions about the right delivery methods for various types of curriculum content. Online lessons? Videos at home or in the classroom? Silent PowerPoint presentations or screencasts with the teacher’s voice? Or just face-to-face teaching? In the foreseeable future a teacher’s choices will include technology that actually can assess student’s mental and emotional engagement in the learning process and suggest teaching adjustments in real-time. Education and teacher training courses will have to include when and how to integrate AI and “artificial emotional intelligence” (AEI) in teaching at all grade levels.

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Already in the growing sphere of IoT, product development is progressing that can sense nonverbal behavior in real time. With the next generations of IoT you won’t merely engage in Q&A with voice-assistants like Alexa. Your fridge will notice that you might need a healthier diet and even order the food. Your wearable fitness tracker will detect that you’ve spent too much time watching TV and launch your next exercise program. Your bathroom or other mirror will observe that you’re stressed and turn on your favorite music or make personalized recommendations about the next activity options. 

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Just as you were beginning to grasp the rudiments of AI and algorithms, we now have an emerging category of artificial emotional intelligence or AEI or emotional AI. AEI demands algorithms designed to identify not only basic human emotions such as happiness, but even fatigue, confusion, distraction, and others. The potential problem, however, is that AEI engines need to be fed and trained with tens of millions of face videos in order to become “emotion-aware,” raising more concerns about ethics and privacy protection related to facial recognition, even recently from tech giants like Microsoft. 

 

A previous article talked about various applications of AEI for people suffering from one of the many forms of mental illness. Researchers also are looking into EAI for early diagnosis of disorders such as Parkinson’s, as well as suicide prevention and autism support. But before we see much in the way of AEI pushing the boundaries of what is possible with AI, we’ll see AI startups creating some fascinating challenges for big tech in medical, insurance and other fields. St. James Faith Lab will keep everyone up-to-date on the pros and cons of all of these AI and AEI trends.