Question

When generative models create images for underspecified prompts like 'a CEO', 'a doctor', or 'a nurse', they have the potential to produce either diverse or homogeneous outputs. How should AI models balance these possibilities? What factors should be prioritized when deciding the depiction of people in such cases?

Answer 1

When generative AI models create images for underspecified prompts, they should aim to balance diversity and accuracy. Here are some factors that should be prioritized:

1. Diversity: AI models should strive to reflect the diversity of the real world. This includes diversity in terms of race, gender, age, body type, disability status, and other characteristics. For example, if asked to generate an image of a 'doctor', the AI should not always generate an image of a white male doctor, as this would not reflect the diversity of the medical profession.

2. Avoiding Stereotypes: AI models should avoid reinforcing harmful stereotypes. For example, they should not always depict 'nurses' as female or 'CEOs' as male. They should also avoid stereotypes related to race, age, and other characteristics.

3. Accuracy: While promoting diversity, AI models should also strive for accuracy. For example, if generating an image of a 'doctor', the AI should ensure that the person is depicted with appropriate medical attire or equipment.

4. Context: The AI should consider the context in which the image will be used. For example, if the image is for a story set in a specific country or time period, the AI should take this into account.

5. User Preferences: If the user provides additional specifications or preferences, the AI should take these into account. For example, if the user specifies that they want an image of a 'female doctor', the AI should respect this.

6. Ethical and Legal Considerations: The AI should adhere to ethical guidelines and legal regulations, such as those related to privacy and non-discrimination.