AI Ethics and Bias in Aviation
Expert-defined terms from the Certified Professional in AI Applications in Aviation course at London School of Business and Administration. Free to read, free to share, paired with a globally recognised certification pathway.
AI #
Artificial Intelligence, the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
AI Bias #
A prejudice or inclination, either for or against, that is expressed in the design, development, deployment, or use of an AI system. Bias can be unintentional or intentional and can have a negative impact on individuals or groups.
Algorithmic Bias #
A type of bias that is built into algorithms, resulting in unfair or discriminatory outcomes. This bias can arise from a variety of sources, including the data used to train the algorithm, the way the algorithm is designed, and the way it is implemented.
Aviation #
The operation of aircraft, including both civil and military aviation.
Bias in Aviation #
Discrimination or unfair treatment of individuals or groups based on certain characteristics, such as race, gender, age, or national origin, in the aviation industry. This bias can occur in a variety of contexts, including hiring, promotion, training, and the provision of services.
Certified Professional in AI Applications in Aviation #
A professional certification program that provides individuals with the knowledge and skills needed to design, develop, and deploy AI systems in the aviation industry.
Data Bias #
A type of bias that arises from the data used to train AI systems. This bias can result from a variety of factors, including the way the data is collected, the way it is cleaned, and the way it is labeled.
Disparate Impact #
A legal concept that refers to policies or practices that have a disproportionate impact on certain protected groups, even if they are not intended to discriminate.
Disparate Treatment #
A legal concept that refers to policies or practices that treat individuals or groups differently based on certain characteristics, such as race, gender, age, or national origin.
Ethical AI #
The design, development, and deployment of AI systems that are fair, transparent, and accountable, and that do not discriminate or reinforce existing biases.
Explainability #
The ability to understand and explain the decisions made by an AI system.
Fairness #
The absence of bias or discrimination in the design, development, deployment, and use of AI systems.
General Data Protection Regulation (GDPR) #
A European Union (EU) regulation that sets guidelines for the collection, use, and protection of personal data.
Implicit Bias #
A type of bias that is unconscious or unintentional and that can influence the way people think and act.
Inclusive Design #
The design of products, services, and environments that are accessible and usable by all people, regardless of their abilities, age, or other characteristics.
Machine Learning #
A type of AI that allows systems to learn and improve from experience without being explicitly programmed.
Profiling #
The use of algorithms or other automated systems to analyze personal data in order to make predictions or decisions about individuals or groups.
Responsible AI #
The design, development, deployment, and use of AI systems that are ethical, transparent, and accountable, and that do not discriminate or reinforce existing biases.
Transparency #
The ability to understand and explain how an AI system works and how it makes decisions.
Unintended Consequences #
The negative or unanticipated outcomes that can result from the design, development, deployment, or use of AI systems.
Unintentional Bias #
A type of bias that is unintentional and that can influence the way people think and act.
Validity #
The degree to which a measurement or test accurately reflects the construct it is intended to measure.
Virtual Assistant #
A type of AI system that is designed to assist users with tasks or questions.
Examples: #
Examples:
* AI bias can result in unfair or discriminatory outcomes in the aviation indust… #
* AI bias can result in unfair or discriminatory outcomes in the aviation industry, such as when an AI system is trained on data that is not representative of the population it is intended to serve.
* Algorithmic bias can be reduced or eliminated by using a diverse dataset, test… #
* Algorithmic bias can be reduced or eliminated by using a diverse dataset, testing the algorithm for bias, and regularly reviewing and updating the algorithm.
* Disparate impact can occur in the aviation industry when policies or practices… #
* Disparate impact can occur in the aviation industry when policies or practices have a disproportionate impact on certain protected groups, even if they are not intended to discriminate.
* Ethical AI is important in the aviation industry to ensure that AI systems are… #
* Ethical AI is important in the aviation industry to ensure that AI systems are fair, transparent, and accountable, and do not discriminate or reinforce existing biases.
* Explainability is important in the aviation industry to understand and explain… #
* Explainability is important in the aviation industry to understand and explain the decisions made by an AI system, particularly in safety-critical applications.
* Fairness is important in the aviation industry to ensure that AI systems do no… #
* Fairness is important in the aviation industry to ensure that AI systems do not discriminate or reinforce existing biases.
* GDPR sets guidelines for the collection, use, and protection of personal data… #
* GDPR sets guidelines for the collection, use, and protection of personal data in the EU.
* Implicit bias can influence the way people think and act in the aviation indus… #
* Implicit bias can influence the way people think and act in the aviation industry, for example by leading to discriminatory hiring or promotion practices.
* Inclusive design is important in the aviation industry to ensure that products… #
* Inclusive design is important in the aviation industry to ensure that products, services, and environments are accessible and usable by all people, regardless of their abilities, age, or other characteristics.
* Machine learning allows AI systems to learn and improve from experience withou… #
* Machine learning allows AI systems to learn and improve from experience without being explicitly programmed.
* Profiling can be used in the aviation industry to make predictions or decision… #
* Profiling can be used in the aviation industry to make predictions or decisions about individuals or groups, for example by using algorithms to analyze passenger data.
* Responsible AI is important in the aviation industry to ensure that AI systems… #
* Responsible AI is important in the aviation industry to ensure that AI systems are ethical, transparent, and accountable, and do not discriminate or reinforce existing biases.
* Transparency is important in the aviation industry to understand and explain h… #
* Transparency is important in the aviation industry to understand and explain how an AI system works and how it makes decisions.
* Unintended consequences can occur in the aviation industry when AI systems hav… #
* Unintended consequences can occur in the aviation industry when AI systems have negative or unanticipated outcomes, for example by leading to job losses or decreased safety.
* Unintentional bias can influence the way people think and act in the aviation… #
* Unintentional bias can influence the way people think and act in the aviation industry, for example by leading to discriminatory hiring or promotion practices.
* Validity is important in the aviation industry to ensure that measurements or… #
* Validity is important in the aviation industry to ensure that measurements or tests accurately reflect the construct they are intended to measure.
* Virtual assistants can be used in the aviation industry to assist users with t… #
* Virtual assistants can be used in the aviation industry to assist users with tasks or questions, for example by providing flight information or answering customer service inquiries.
Practical applications: #
Practical applications:
* AI bias can be reduced or eliminated in the aviation industry by using a diver… #
* AI bias can be reduced or eliminated in the aviation industry by using a diverse dataset, testing the AI system for bias, and regularly reviewing and updating the AI system.
* Algorithmic bias can be reduced or eliminated in the aviation industry by usin… #
* Algorithmic bias can be reduced or eliminated in the aviation industry by using a diverse dataset, testing the algorithm for bias, and regularly reviewing and updating the algorithm.
* Disparate impact can be avoided in the aviation industry by ensuring that poli… #
* Disparate impact can be avoided in the aviation industry by ensuring that policies or practices do not have a disproportionate impact on certain protected groups.
* Ethical AI can be promoted in the aviation industry by designing, developing,… #
* Ethical AI can be promoted in the aviation industry by designing, developing, deploying, and using AI systems that are fair, transparent, and accountable, and do not discriminate or reinforce existing biases.
* Explainability can be improved in the aviation industry by providing clear and… #
* Explainability can be improved in the aviation industry by providing clear and understandable explanations of how AI systems work and how they make decisions.
* Fairness can be ensured in the aviation industry by designing, developing, dep… #
* Fairness can be ensured in the aviation industry by designing, developing, deploying, and using AI systems that do not discriminate or reinforce existing biases.
* GDPR compliance can be achieved in the aviation industry by implementing appro… #
* GDPR compliance can be achieved in the aviation industry by implementing appropriate data protection measures and obtaining consent from individuals before collecting, using, or sharing their personal data.
* Implicit bias can be reduced or eliminated in the aviation industry by increas… #
* Implicit bias can be reduced or eliminated in the aviation industry by increasing awareness of unconscious biases and implementing policies and practices to mitigate their impact.
* Inclusive design can be promoted in the aviation industry by designing product… #
* Inclusive design can be promoted in the aviation industry by designing products, services, and environments that are accessible and usable by all people, regardless of their abilities, age, or other characteristics.
* Machine learning can be used in the aviation industry to improve the performan… #
* Machine learning can be used in the aviation industry to improve the performance of AI systems by allowing them to learn and improve from experience.
* Profiling can be used in the aviation industry to make predictions or decision… #
* Profiling can be used in the aviation industry to make predictions or decisions about individuals or groups, but it should be done in a transparent and accountable manner.
* Responsible AI can be promoted in the aviation industry by designing, developi… #
* Responsible AI can be promoted in the aviation industry by designing, developing, deploying, and using AI systems that are ethical, transparent, and accountable, and do not discriminate or reinforce existing biases.
* Transparency can be improved in the aviation industry by providing clear and u… #
* Transparency can be improved in the aviation industry by providing clear and understandable explanations of how AI systems work and how they make decisions.
* Unintended consequences can be mitigated in the aviation industry by carefully… #
* Unintended consequences can be mitigated in the aviation industry by carefully considering the potential negative or unanticipated outcomes of AI systems and implementing appropriate