AI sexting can also be integrated with consent mechanisms, where NLP (Natural Language Processing) and sentiment analysis is used to identify boundaries of users. Collectively, these systems work with ~90% accuracy at recognizing affirmatives or hesitating language to trigger the AI into asking for more direct explicit CS while escalating intimate interactions. Consent algorithms often incorporate different pre-programmed checks which can sometimes take the form of AIs asking a bunch clarifying questions, testing their stated preference against what other things they are doing and all to reassure itself it has asked permission correctly from its own perspective because that illusion is important for giving users more control.
This process of consent is made more nuanced with the advent of affective computing, that enables AI to read emotional cues and respond when picked up on non-verbal signs from participants for eg. pauses or language prompting hesitation. Even this adaptive technology has a few constraints of its own. Dr. Sonia Patel, PhD Digital Ethics expert said from her own experience: “AI can imitate the impression that consent is being respected but it comes nowhere near one of our most divine intuitions in life; this further reduces AI to misunderstanding human intention due to lack of subtlety when simulating humanness.” Still these platforms arguably spend on reviews of consent agreements and sentiment analysis (up to $250K a year) in order to avoid the unsavory smudge that can come from only accidentally crossing boundary lines.
They are using real-time feedback loops in their AI network so that if they received a certain type of response for consent at one time, the next text is adjusted…based on prior interactions. This iterated learning model actually instructs the AI to develop a “sense” of when it is pushing boundaries based on how well or poorly its decision go over with users, which should result in fewer future breaches. Although this system keeps increase the accuracy of consent knowning to about 10, it still depends on users action; in that case this is affected by designed user activity therefore adjustable with AI based on individual rather than general all-user propos.
To enhance their systems, certain AI platforms offer keyword-based content filters that recognize potentially persuasive language and pause the conversation unless there is explicit consent provided again. Yet, identifying universal consent recognition is difficult — how people say yes or no (i.e. express their agreement) changes from one culture to another which affects the way AI understands affirmations and hesitations across diverse groups of users. The 2022 Digital Interaction Report reveals as much, with nearly one in six users (15%) noting that AI struggles to parse the nuances of these cues — a trend which becomes even more pronounced when delving into less explicit or culturally bound signifiers.
Though the complexity of human communication is not fully represented, ai sexting manages to integrate consent protocols through NLP and affective computing; as demonstrated above, it cannot easily be adapted but might prove useful with more sophistication.