Ethics and Responsible AI

2019 was the year of the ethical considerations in the AI industry, and we need to continue prioritizing this conversation as we move forward and scale the technology further.

Many different companies have used keynotes and other outlets to promote the importance of responsible AI and aligning with established ethical practices.

The idea is to have an AI system we can trust. That means ensuring fairness, robustness, explainability, transparency, just to name a few.

Considering the quick pace of advancement for deep learning solutions and their effects on society, the biggest attention is drawn to making models’ predictions explainable.

The major philosophical foundations can be divided into 4 principles:

In addition to those, we could also consider the Pareto Improvements principle that strives to improve at least one person without making anyone else worse off. All of these are perfectly valid principles, but it can be difficult to choose one to apply in all practical situations.

The challenge for AI technologists and strategists will be to build systems that are able to take different points of view into account, weigh the pros and cons based on specific criteria (e.g. population size, or cost-benefit analysis), transparently communicate and collaborate with all of the involved actors, and react in a timely manner to accommodate changes of the society needs (governments, companies, and people).

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