These technologies are engaging you--a human driving a car--in human terms. Myriad technologies that detect physical states such as alertness are increasingly being used to infer emotional states such as happiness or sadness. Unlike their machine forebears that set rigid rules of engagement, these systems will follow rules, reading your mood, intuiting your needs, and responding in contextually and emotionally appropriate ways. Welcome to the next stage of human-machine interaction, in which a growing class of AI-powered solutions--referred to as "affective computing" or "emotion AI"--is redefining the way we experience technology. These experiences are hardly confined to automobiles. Retailers are integrating AI-powered bots with customer segmentation and CRM systems to personalize customer interactions while at the same time capturing valuable lead-nurturing data.2 Apps are designing custom drinks and fragrances for fashion-show attendees based on emotional quotient (EQ) inputs.3 A global restaurant chain is tailoring its drive-through experiences based on changes in the weather.4

Those deemed in the higher class may be envied for their luxurious cars, large homes and stylish clothes, but there is one thing they do not have – the ability to read people's emotions. A study used a cognitive empathy test called'the Reading the mind in the eyes,' which participants from higher and lower social classes were asked to determine emotional states from images of eyes. The results showed those in the lower class were better at understanding other people's minds compared to their counterparts. Experts suggest the reason is because lower social classes tend to prioritize the needs and preferences of others, and are ultimately more empathetic. A study used a cognitive empathy test called'the Reading the mind in the eyes,' which participants from higher and lower social classes were asked to determine emotional states from images of eyes - and the team calculated the scores The study was conducted by a team at the University of California, Irvine who questioned – 'How does access to resources (e.g., money, education) influence the way we process information about other human beings,' PsyPost reported.

Several years ago, I packed up my life in Cairo, Egypt, and moved to the UK to pursue my PhD – thousands of miles away from everyone I knew and loved. As I settled into my new life, I found myself spending more hours with my laptop than with any other human being. I felt isolated and incredibly homesick. Chatting online with my family back home, I was often in tears, but they had no idea how I was feeling behind my screen (with the exception of a sad face emoticon that I would send). I realised then that our technology and devices – which we consider to be "smart", and helpful in many aspects of our lives – are emotion blind.

Researchers from Skoltech, INRIA and the RIKEN Advanced Intelligence Project have considered several state-of-the-art machine learning algorithms for the challenging tasks of determining the mental workload and affective states of a human brain. Their software can help design smarter brain-computer interfaces for applications in medicine and beyond. The paper was published in the IEEE Systems, Man, and Cybernetics Magazine. A brain-computer interface, or BCI, is a link between a human brain and a machine that can allow users to control various devices, such as robot arms or a wheelchair, by brain activity only (these are called active BCIs) or can monitor the mental state or emotions of a user and categorize them (these are passive BCIs). Brain signals in a BCI are usually measured by electroencephalography, a typically noninvasive method of recording electrical activity of the brain.

The experimental use of AI spread across sectors and moved beyond the internet into the physical world. Stores used AI perceptions of shoppers' moods and interest to display personalized public ads. Schools used AI to quantify student joy and engagement in the classroom. Employers used AI to evaluate job applicants' moods and emotional reactions in automated video interviews and to monitor employees' facial expressions in customer service positions. It was a year notable for increasing criticism and governance of AI related to emotion and affect.

Perhaps you've heard of AI conducting interviews. Or maybe you've been interviewed by one yourself. Companies like HireVue claim their software can analyze video interviews to figure out a candidate's "employability score." The algorithms don't just evaluate face and body posture for appearance; they also tell employers whether the interviewee is tenacious, or good at working on a team. These assessments could have a big effect on a candidate's future.

Imagine you're on your daily commute to work, driving along a crowded highway while trying to resist looking at your phone. You're already a little stressed out because you didn't sleep well, woke up late, and have an important meeting in a couple hours, but you just don't feel like your best self. Suddenly another car cuts you off, coming way too close to your front bumper as it changes lanes. Your already-simmering emotions leap into overdrive, and you lay on the horn and shout curses no one can hear. Except someone--or, rather, something--can hear: your car.

Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. What is facial emotion recognition?

A British company has developed an artificial voice that can speak with'deep human emotion' -- and even cry -- with complete realism. The digital helpers that we are used to -- like Alexa and Google Assistant -- tend to speak in close-to monotones, without real inflection to convey emotion. While this may suffice for voice assistants, such flat computer-generated voices are unsuitable for applications like producing dialogue for video games or film. However, technology developed by the ten-person team at the London-based firm Sonantic allows the creation of authentic-sounding lines of speech in minutes. A British company has developed an artificial voice that can speak with'deep human emotion' -- and even cry -- with complete realism (stock image) 'We create hyper-realistic artificial voices.

Forbes catches up with Element Human to discuss how they're implementing AI technology to hone a brand's ability to predict the way a product will be received emotionally by the public.