Academic vs Commercial Uses of AI Humanization
There's a growing effort to make AI sound more human, but the reasons behind it vary. Academic scholars and commercial organizations personify AI, although their motives, approaches, and priorities tend to diverge in opposite directions.
This difference makes it easy to realize how AI is gradually finding its way into the daily routine.
What is AI Humanization?
AI Humanization refers to the process of designing artificial intelligence systems to appear or behave more like humans. This may include emotive voice, conversational skills, or adjusting to changes.
But the reason for humanizing AI depends entirely on the context.
But the reason for humanizing AI depends entirely on the context.
Academic Use: Learning from Human Behavior
In academic environments, AI is humanized to explore questions, not sell products. It is a method of testing, of gaining insight into user behavior and of building longer-term knowledge.
- Understanding interaction: The ways people interact with AI presented as more human are analyzed by researchers, including responses and levels of trust.
- Ethical evaluation: The academic projects work with privacy, manipulation, fairness, and long-term societal impacts.
- Theoretical development: Academic teams develop models and ideas that can be used to drive development in the future, as opposed to the construction of final products.
Commercial Use: Driving Results and Engagement
In contrast, commercial AI humanization is tied to performance. It's used to enhance experiences, reflect brand personality, and increase retention.
- Enhancement of customer service: Emotions and clarity in the AI enhance the satisfaction of its use and eliminate friction.
- Creating brand consistency: Businesses make AI sound human in their tone: informal, formal, or lighthearted.
- Scaling efficiently: Humanized AI handles large volumes of queries while maintaining a personal feel, especially in support or sales.
Ethics and Transparency
Ethics is where the gap widens. In academia, the ethical review of a project before launch is common and aims at establishing possible risks and providing protection measures.
Commercial systems, in turn, are more likely to focus on speed, user/market interactions, and market disruption, which often is at the cost of transparency. Moral issues such as emotional control or data of the users may become of secondary concern.
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