What is ethics in AI (AI ethics)?

Need to discuss ethics in AI

Artificial intelligence, especially in its advanced forms (e.g., machine learning, generative AI), has the potential to have a huge impact on society, the economy and the lives of individuals. AI systems make decisions that can affect people’s health, finances, employment, justice or safety. Therefore, it is critical to have an informed discussion and develop ethical principles to guide the development and use of this powerful technology.

Key ethical issues in AI

The discussion of ethics in AI revolves around several key issues:

• Bias (prejudice) and fairness (equity): AI algorithms learn from data that often reflect existing biases in society (e.g., racial, gender). This can lead to discriminatory or unfair decisions by AI systems (e.g., in recruitment processes, credit risk assessment, facial recognition systems). It is crucial to develop methods to detect and mitigate biases and ensure algorithmic fairness.
• Transparency and explainability (transparency and explainability): Many advanced AI models (especially deep learning) act as “black boxes,” making it difficult to understand why they made a particular decision. The lack of transparency and explainability (XAI – Explainable AI) raises concerns about accountability, auditability and trust in AI systems, especially in critical applications.
• Liability (accountability): Who is liable for damage caused by an autonomous AI system? Is it the algorithm developer, the company implementing the system, or perhaps the system itself? Establishing a clear framework for legal and ethical accountability is a key challenge.
• Privacy: AI systems often require access to huge amounts of data, including personal data. Adequate mechanisms must be in place to protect privacy, anonymize data, and control users over their data, in accordance with regulations such as the Personal Data Protection Regulation (PDPA).
• Safety (safety and security): Ensuring that AI systems operate reliably, resist attacks (e.g., adversarial attacks) and do not cause unintended harm.
• Labor market impact: AI’s automation of tasks raises concerns about mass unemployment and the need to retrain workers. Ethical issues relate to the equitable transformation of the labor market and support for those affected by the changes.
• Autonomy and human control: How do we ensure an appropriate level of human control over decisions made by increasingly autonomous AI systems? Where does the limit of autonomy lie?
• AI Values and Goals: How do we ensure that the goals pursued by AI systems are consistent with human values and social good?

Initiatives and regulations

In response to these challenges, numerous initiatives, ethical guidelines (e.g., published by technology companies, international organizations) and regulatory proposals (e.g., the AI Act in the European Union) are being developed around the world to create a framework for the responsible development and use of artificial intelligence.

Summary

Ethics in AI is an indispensable part of the responsible development of this technology. Addressing key issues such as bias, transparency, accountability, privacy and security is essential for AI to benefit society while minimizing potential risks and negative impacts. This requires an ongoing dialogue between technologists, ethicists, lawyers, policymakers and the public.