issues with AI?
data protection
privacy
transparency
accountability
biases
What is the issue with privacy?
Privacy: appropriate ethical level of data privacy collected; privacy input (data for training) + privacy output (predictions about people). The extent to which people have knowledge and control over their data without undue pressure.
What is the issue with explainability?
Explainability: the space between the inputs and the outputs, the extent you can precisely assess what has been going on
What is the issue with biases?
Bias: coming from real-world discriminations, under- sampling, benchmark bias, wrong metrics, etc.
What is the goal of using AI for good?
The goal is to leverage powerful AI tools to achieve a desirable social impact, focusing on responsible business practices and sustainable AI development.
How can ethical risks posed by AI be avoided?
Ethical risk mitigation involves a comprehensive and all-encompassing approach, focusing on understanding the risks and operationalizing ethical risk mitigation strategies.
What are the five basic ethical AI principles?
The principles are:
Beneficence
Non-maleficence
Autonomy, Justice
Explicability
They focus on promoting well-being, preventing risks, balancing decision power, ensuring fairness, and maintaining transparency and accountability.
How does AI contribute to human flourishing? (florieren)
AI contributes by enabling self-realization without devaluing human abilities, enhancing human agency without removing responsibility, increasing societal capabilities without reducing human control, and cultivating societal cohesion without eroding self-determination.
What are the main ethical considerations in deploying AI technologies?
Considerations include biases and fairness, privacy and cybersecurity, impacts on jobs and work nature, compliance with legal frameworks, misuse of AI, and environmental impacts.
What is the alignment problem in AI?
The alignment problem involves embedding human values in machines and ensuring that machines are developed and used according to organizational values.
What are the key components of an AI ethical risk program?
Key components include governance structure, ethical content, clear values, cross-organizational awareness, product development standards, internal accountability, tracking standards adherence, and control mechanisms.
What is the 5-step model for adopting AI technologies based on the precautionary principle?
The model involves understanding AI tech workings, assessing reliability levels, transparency about risks, complementing AI to increase reliability, and continuous control and improvement processes.
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