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AI & Data Best Practices

Top 10 Ethical Considerations for AI Projects

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Artificial Intelligence is seen by many as a great transformative technology. However, as with any transformative technology the impacts on society can be tremendous. As such,if your organization is going to be using AI and ML technologies, it makes sense to spend time considering what you want these systems to do and make sure to address ethical considerations now so that you build these systems with the common good of humanity in mind. But what are the top 10 Ethical Considerations for AI Projects?

In the context of technology, the concept of ethics applies to how technology is used by humans to accomplish goals, and also the way in which technology systems operate in relation to humanity. In this light, ethics primarily relates to human-to-human, human-to-machine, and machine-to-human interactions, and only casually applies to machine-to-machine interactions in which there is some human component, impact, or aspect.

Below are ten considerations you should take into account when building and using AI systems.

  1. Fairness and bias: One of the most important ethical considerations for AI is ensuring that the technology is fair and unbiased. This means taking steps to prevent discrimination based on factors such as race, gender, and socioeconomic status as well as paying attention to data the system is trained on.
  2. Transparency: Another key ethical consideration is transparency. This means being upfront about how AI systems work and providing users as much visibility into overall system behavior as possible. It also means making sure that users understand how their data is being used and protected including addressing appropriate disclosure and user consent.
  3. Privacy: Privacy is a critical consideration for ethical AI. This means taking steps to protect user data and ensure that it is not misused or mishandled.
  4. Safety: Ensuring the safety of users is another important ethical consideration for AI. This means taking steps to prevent accidents or harm caused by AI systems. It can also mean safety and respect of the environment as well and  not use resources to the extent that it becomes a significant net negative impact on the environment.
  5. Explainability: Explainability is an important ethical consideration for AI. This means making sure that users understand how AI systems make decisions and providing them with explanations when requested. In the case that AI systems can’t use fully explainable AI algorithms, AI systems should provide a means to interpret AI results so that cause and effect can be understood.
  6. Human oversight: Another ethical consideration for AI is the need for human oversight. This means having humans in the loop to ensure that AI systems are behaving as expected and are making decisions that align with human values, as well as any laws, regulations, or company policies.
  7. Trustworthiness: Trustworthiness is also important. This means taking steps to build trust with users by being transparent about how AI systems work and being accountable for any errors or problems.
  8. Human-centered design: Human-centered design is an ethical consideration for AI. This means designing AI systems with the needs and wants of users in mind, rather than just focusing on technical capabilities.
  9. Responsibility: Responsibility is also important. This means taking responsibility for the actions of AI systems and being accountable for any negative impacts they may have.
  10. Long-term impacts: Long-term impacts are an ethical consideration for AI as well. This means considering the long-term effects of AI systems on society and the planet, and taking steps to mitigate any negative impacts.

Listen to our AI Today Ethical & Responsible AI series for even more insight into the specific areas of making AI more trustworthy, ethical, and responsible.

AI is a powerful technology that has the potential to greatly benefit society, but it’s also critically important to consider the ethical implications of its use. By taking steps to ensure fairness, transparency, privacy, safety, explainability, human oversight, trustworthiness, and long-term impacts, AI can be intentionally created to align with human values and follow ethical standards.

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