How can you ensure AI algorithms are safe in aviation applications?

1 Define clear objectives and boundaries

One of the first steps to ensure AI safety is to define the objectives and boundaries of the AI algorithms, such as what tasks they are supposed to perform, what data they are allowed to access and process, and what constraints and rules they have to follow. This helps to avoid ambiguity, confusion, and misuse of the AI algorithms, as well as to align them with the ethical and legal standards of the aviation industry.

2 Implement rigorous testing and validation

Another essential step to ensure AI safety is to implement rigorous testing and validation processes for the AI algorithms, both before and after deployment. Testing and validation should cover different scenarios, inputs, outputs, and performance indicators, as well as potential failures, errors, and anomalies. Testing and validation should also involve human experts, stakeholders, and end-users, who can provide feedback, insights, and verification.

3 Monitor and update regularly

A third important step to ensure AI safety is to monitor and update the AI algorithms regularly, especially when they are based on machine learning or adaptive techniques. Monitoring and updating help to detect and correct any issues, bugs, or biases that may arise over time, as well as to improve the accuracy, efficiency, and robustness of the AI algorithms. Monitoring and updating should also include auditing and reporting mechanisms, which can provide transparency, accountability, and traceability.

4 Ensure human oversight and intervention

A fourth crucial step to ensure AI safety is to ensure human oversight and intervention capabilities for the AI algorithms, especially when they involve high-stakes or complex decisions. Human oversight and intervention help to prevent and mitigate any harmful or undesirable outcomes, as well as to preserve human dignity, autonomy, and responsibility. Human oversight and intervention should also include training and education, which can enhance the skills, knowledge, and trust of the human operators and users.

5 Collaborate and share best practices

A fifth beneficial step to ensure AI safety is to collaborate and share best practices with other stakeholders in the aviation industry, such as regulators, manufacturers, airlines, researchers, and customers. Collaboration and sharing help to foster a common understanding, vision, and framework for AI safety, as well as to exchange information, experiences, and solutions. Collaboration and sharing should also promote innovation and diversity, which can enrich the potential and value of AI in aviation.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?