AI holds tremendous promise for many industries. It can improve accuracy, speed, scalability, personalization, consistency, and clarity in so many business functions.
But many businesses still hesitate to move forward with AI projects. Why? On the one hand, they know that they need to embrace AI to remain competitive. On the other hand, they fear the consequences of getting it wrong after hearing stories of high profile companies making mistakes with AI that have damaged their reputations.
In our white paper, AI Ethics, we take a deeper dive into why these fears are unfounded. We look at how to overcome common blockers to ensure that you build AI that is trustworthy and remains true to your business rules and core values.
Specifically, we dive into the four principles of AI Ethics that help people trust your AI:
- Principle 1: Ethical Purpose -- How to make sure your AI’s actions have a net good to society.
- Principle 2: Fairness -- Ensuring your AI’s actions avoid entrenching historical disadvantage and avoid discriminating on sensitive features.
- Principle 3: Disclosure -- Disclosing sufficient information to an AI’s stakeholders so that they can make informed decisions.
- Principle 4: Governance -- Where there is risk, apply high standards of governance over the design, training, deployment, and operation of AIs.
The DataRobot Team