Digital MATSUMOTO's AI Business Guidelines Explanation Series Part 6 - Part 2 Common Guidelines '3. Fairness' -

The Japanese government is creating AI business guidelines.
Please explain, in an easy-to-understand manner within 2000 characters, how to implement the principles described in the following text using concrete AI examples.
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{**Part 2 C. Common Guidelines '3. Fairness'**}

Ensuring 'fairness' in the development, provision, and use of AI systems is an important issue directly linked to social trust and acceptance. Here, I will explain how to implement the principle of fairness using concrete AI examples.

3-1. Consideration for bias included in each constituent technology of AI models (e.g., recruitment AI)
When conducting a recruitment process using AI, a model trained based on past data may produce results biased toward attributes such as gender or alma mater.To solve this problem, the following steps are necessary.
- Data auditing: detect biases included in training data and balance them as necessary.
- Algorithm transparency: Disclose the learning process and clarify the criteria by which the AI makes judgments.
- Fairness evaluation: Define metrics to evaluate whether the AI model makes fair judgments and check them periodically.3-2. Intervention of human judgment (e.g., medical diagnosis support system)

AI in the medical field demonstrates high accuracy in diagnosing diseases, but
it does not exclude the professional judgment of doctors. It is essential to ensure an appropriate human-in-the-loop as follows.- Interactive process:
Doctors review the AI's inference results and share the logic leading to the final diagnosis.- Education and training:
Provide continuous education for doctors to interpret and appropriately utilize AI judgments.- Ensuring diversity: Consider the patient's cultural background and characteristics, and avoid bias by incorporating the opinions of diverse doctors.
Through these concrete efforts, it is important to enhance the fairness of AI while simultaneously evaluating and adjusting unavoidable biases so that they are permissible within the scope of respecting human rights and diversity. Furthermore, through dialogue with AI system users and stakeholders, we aim to reduce unconscious bias and improve fairness for society as a whole. Ethical operation of AI requires not only technological progress but also social consensus building and continuous monitoring.

[Referenced Memory]
1.2024-01-23 14:06:18.287419[ASSISTANT]: In order to practice the principle of 'Safety' in the AI Business Guidelines, human life, body, property, spirit, and enviro
2.2024-01-23 14:04:07.971522[USER]: The Japanese government has created AI Business Guidelines. To practice the principles described in the following text
3.2024-01-23 14:04:06.651135[ASSISTANT]: The 'Human-Centric' principle in the AI Business Guidelines proposed by the Japanese government means that AI systems and services are for humans
4.2024-01-23 14:01:06.261560[USER]: The Japanese government has created AI Business Guidelines. To practice the principles described in the following text
5.2024-01-23 14:01:03.588712[ASSISTANT]: Part 2 of the AI Business Guidelines being created by the Japanese government outlines the philosophy of the society we should aim for by utilizing AI, and the

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