Handshake AI is looking for improv actors to train AI models to understand and reproduce human emotions. The company, which has surpassed $150 million in annual revenue, is seeing a threefold increase in requests for specialized data annotation in the field of emotional AI.
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Handshake AI ’s job posting highlights the need for individuals with strong creative instincts and the ability to authentically portray emotion. The role involves training an AI model for a leading AI company, focusing on helping the model understand and reproduce human emotions and tones. Professionals from a variety of fields, including chemists, doctors, lawyers, and screenwriters, are being hired to provide specialized training data.
The demand for training data has increased dramatically as AI labs seek to improve their models. They are now looking for performers like sketch comedians and improv actors. The job description calls for these individuals to participate in a paid collaborative improv project, where they will work with other performers to explore scenarios and prompts via video.
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Technical specifications and requirements for actors
Handshake AI ’s ad specifies a preference for candidates with a background in acting, improvisation, sketch or theatre, aiming to push the boundaries of AI’s understanding. Emotional awareness is highlighted as a key requirement, highlighting the need for participants to recognize, express and move through emotions authentically. The goal is to create interactions that feel grounded, human and enjoyable.
According to MIT 's Javier Hernandez , emotional AI is essential for natural human-machine interaction, similar to reading faces and body language in human conversations. MIT Sloan 's Erik Brynjolfsson points to the advantage of machines in processing vast data on micro-expressions and vocal variations faster than humans.
The affective AI market is driven by demand for multimodal systems (text, audio, video) in applications such as virtual assistants, mental health chatbots , and user experience research. Key players include MIT 's Affective Computing Group , MorphCast for modern solutions, and data companies such as Handshake AI .
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Challenges and future prospects
Challenges include reliance on data from artificial versus natural sources, according to affective computing researchers. RIWI analysts note that AI outperforms humans in detecting emotions through subtle cues, but requires a combination of contextual research, avoiding over-reliance on incomplete signals like tone.
For users, emotional AI enables empathetic interactions in chatbots and assistants, improving mental health support and providing real-time feedback in research. Studies on AI chatbots show effectiveness in reducing symptoms of depression and anxiety through emotion analysis.
