The intensification of feeling According to recent PitchBook research, AI is becoming a major trend in commercial software.
The effectiveness of emotion AI technology and its ethical ramifications are still hotly contested, despite supporters’ views that it can make AI assistants more human-like and sympathetic in their interactions.
The Expanding Emotion AI Trend
In order to provide a more thorough knowledge of human emotions, emotion AI goes beyond typical sentiment analysis by combining data inputs ranging from visual, auditory, and psychological.
This technology, which offers more complex interpretations of human behavior, has the potential to completely transform AI interactions, as noted in PitchBook’s latest Enterprise SaaS Emerging Tech Research study.
Businesses are depending more and more on AI to handle consumer interactions; therefore, it’s clear that these systems need to be able to distinguish between different emotional states, like happiness, perplexity, and wrath.
Emotion AI is now more widely available to developers and companies across the globe thanks to the integration of this technology by well-known tech companies like Google and Amazon.
Derek Hernandez, a senior analyst at PitchBook, highlights the growing importance of emotion AI in the context of AI assistants and automated human-machine interactions.
Hernandez notes that wearable technologies, cameras, and microphones are all used by the technology to gather the information required for emotion recognition.
Emotion AI has great promise, but there are a lot of obstacles in the way.
The primary tenet of technology, according to critics, is that body language, tone of voice, and facial expressions can all be used to accurately detect human emotions.
The effectiveness of emotion AI is called into question by a meta-review of research published in July 2020, which found that facial movements alone are not a reliable indicator of human emotions. The ethical and regulatory environment also presents difficulties.
For instance, the AI Act of the European Union imposes stringent restrictions on the application of emotion detection technologies in specific settings, such as the classroom.
Laws such as Illinois’ Biometric Information Privacy Act (BIPA) make it more difficult to gather and use biometric data—including emotional cues—without express agreement in the United States.
Additional Consequences and Industry Reaction
Concerns around the use of AI in the workplace going forward are reflected in the discussion around emotion AI.
On the one hand, by personalizing and empathizing with interactions, this technology might greatly improve sales, customer service, and human resources. However, there are serious concerns regarding its long-term sustainability and ethical implications due to the possibility of misuse, privacy infringement, and false readings.
Notwithstanding these obstacles, there is still a significant push for emotion AI, especially in Silicon Valley, where there is a strong desire to use more technology to address technological problems.
Significant venture cash is being attracted to startups like Uniphore, which has raised $610 million, in order to build emotion AI solutions. Significant investments are also being made in other businesses to progress this subject, such as MorphCast, Voicesense, Superceed, and Siena AI.
Notably, there has been prior interest in emotion AI before now. In 2019, the idea of emotion AI became more popular, even though the majority of the AI/ML sector was still centered on computer vision.
