Artificial Intelligence is a powerful tool that can be used to greatly benefit the world. However, like any tool, it must be used responsibly.
Fairness
AI
systems should treat all people fairly. For example, suppose you create a
machine learning model to support a loan approval application for a bank. The
model should make predictions of whether or not the loan should be approved
without incorporating any bias based on gender, ethnicity, or other factors
that might result in an unfair advantage or disadvantage to specific groups of
applicants.
Machine
Learning includes the capability to interpret models and quantify the extent to
which each feature of the data influences the model's prediction. This
capability helps data scientists and developers identify and mitigate bias in
the model.
Reliability and
safety
AI
systems should perform reliably and safely. For example, consider an AI-based
software system for an autonomous vehicle; or a machine learning model that
diagnoses patient symptoms and recommends prescriptions. Unreliability in these
kinds of system can result in substantial risk to human life.
AI-based
software application development must be subjected to rigorous testing and
deployment management processes to ensure that they work as expected before
release.
Privacy and
security
AI
systems should be secure and respect privacy. The machine learning models on
which AI systems are based rely on large volumes of data, which may contain
personal details that must be kept private. Even after the models are trained
and the system is in production, it uses new data to make predictions or take
action that may be subject to privacy or security concerns.
Inclusiveness
AI
systems should empower everyone and engage people. AI should bring benefits to
all parts of society, regardless of physical ability, gender, sexual
orientation, ethnicity, or other factors.
Transparency
AI
systems should be understandable. Users should be made fully aware of the
purpose of the system, how it works, and what limitations may be expected.
Accountability
People
should be accountable for AI systems. Designers and developers of AI-based
solution should work within a framework of governance and organizational
principles that ensure the solution meets ethical and legal standards that are
clearly defined.
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