Human Guidance in AI Development
- Design and Objectives: Humans decide AI systems’ goals, purposes, and ethical boundaries. This includes choosing the problems to solve and defining what successful AI development looks like.
- Algorithm and Architecture Choices: Engineers and data scientists determine the structure and algorithms used, directly influencing how the AI processes information.
- Data Selection and Preparation: Creators of AI systems make decisions about the quality, type, and bias of the data used to train AI systems, which in turn affect the system’s behavior.
Impact of Creators’ Decisions on Societal Outcomes
- Bias and Fairness: Decisions on dataset curation and algorithmic design can introduce or mitigate biases. These choices directly affect fairness in applications like hiring, law enforcement, financial services, and many more.
- Transparency and Accountability: The way creators document and explain the workings of an AI system affects public trust and accountability. Clear guidelines and open processes help society understand and regulate AI.
- Ethical Considerations: From privacy to job displacement, the ethical frameworks that guide AI development are the result of deliberate human choices. Responsible innovation requires weighing societal impacts against technological benefits.
It is very important that we keep an oversight of AI after its development and deployment, that it does not work in anyway that can harm humans and human societies. This is becoming increasingly true as AI agents – AI’s that can make decisions and take action without human – are widely developed and adopted.
