About this Video

• Video Title: Introduction to Responsible AI
• Channel: Google Cloud
• Speakers: Manny (Google Security Engineer)
• Duration: 00:09:38

Introduction

This Google Cloud video introduces the concept of responsible AI and explains why Google has implemented AI principles. The video emphasizes the importance of responsible AI practices in all stages of a project and across various organizations, highlighting the impact of human decisions in AI development and deployment.

Key Takeaways

• AI's pervasiveness: AI is increasingly integrated into daily life, impacting various aspects from traffic predictions to entertainment recommendations.
• AI's limitations: Despite advancements, AI is not infallible and can reflect or amplify existing societal biases if not developed responsibly.
• Organizational AI Principles: Organizations develop unique AI principles reflecting their mission and values, but common themes include transparency, fairness, accountability, and privacy.
• Google's AI Principles: Google's approach to responsible AI is rooted in building AI that is beneficial, accountable, safe, respects privacy, and is driven by scientific excellence. They have seven core principles and four application areas they will not pursue.
• Human role in AI: Human decisions are crucial throughout the AI lifecycle, from data collection and model training to deployment and application, influencing the values embedded within AI systems. Responsible AI requires careful consideration and evaluation at every decision point.

According to the transcript, Google will not design or deploy AI in these four application areas:

1. Technologies that cause or are likely to cause overall harm.
2. Weapons or other technologies whose principle purpose or implementation is to cause or directly facilitate injury to people.
3. Technologies that gather or use information for surveillance that violates internationally accepted norms.
4. Technologies whose purpose contravenes widely accepted principles of international law and human rights.

Google's seven AI principles, announced in June 2018, are:

1. AI should be socially beneficial.
2. AI should avoid creating or reinforcing unfair bias.
3. AI should be built and tested for safety.
4. AI should be accountable to people.
5. AI should incorporate privacy design principles.
6. AI should uphold high standards of scientific excellence.
7. AI should be made available for uses that accord with these principles.

Google incorporates responsibility into its AI products and organization by using its AI principles as a framework to guide responsible decision-making. They've incorporated responsibility by design into their products and, more importantly, their organization. They use assessments and reviews to ensure projects align with their AI principles, establishing rigor and consistency across product areas and geographies. They also build responsibility into AI deployment to create better models and build trust with customers. They acknowledge that a robust process, even if not every decision is agreed upon, builds trust.

The common misconception is that machines play the central decision-making role in artificial intelligence. The reality is that people design and build the machines and decide how they are used. Human decisions are threaded throughout AI development, from data collection and model training to deployment and application. Every decision made by a person introduces their own set of values into the AI system.