Over the past year, responsibly developed AI has transformed health screenings, supportedfact-checking to battle misinformation and save lives, predicted Covid-19 cases to support public health, and protected wildlife after bushfires. Developing AI in a way that gets it right for everyone requires openness, transparency, and a clear focus on understanding the societal implications. That is why we were among the first companies to develop and publish AI Principles and why, each year, we share updates on our progress.
Internal Education
In the last year, to ensure our teams have clarity from day one, we’ve added an introduction to our AI Principles for engineers and incoming hires in technical roles. The course presents each of the Principles as well as the applications we will not pursue.
Integrating our Principles into the work we do with enterprise customers is key, so we’ve continued to make our AI Principles in Practice training mandatory for customer-facing Cloud employees. A version of this training is available to all Googlers.
There is no single way to apply the AI Principles to specific features and product development. Training must consider not only the technology and data, but also where and how AI is used. To offer a more comprehensive approach to implementing the AI Principles, we’ve been developing opportunities for Googlers to share their points of view on the responsible development of future technologies, such as the AI Principles Ethics Fellowship for Google’s Employee Resource Groups. Fellows receive AI Principles training and craft hypothetical case studies to inform how Google prioritizes socially beneficial applications. This inaugural year, 27 fellows selected from 191 applicants from around the world wrote and presented case studies on topics such as genome datasets and a Covid-19 content moderation workflow.
Other programs include a bi-weekly Responsible AI Tech Talk Series featuring external experts, such as the Brookings Institution’s Dr. Nicol Turner Lee presenting on detecting and mitigating algorithmic bias.
Tools and Research
To bring together multiple teams working on technical tools and research, this year we formed the Responsible AI and Human-Centered Technology organization. The basic and applied researchers in the organization are devoted to developing technology and best practices for the technical realization of the AI Principles guidance.
As discussed in our December 2020 End-of-Year report, we regularly release these tools to the public. Currently, researchers are developing Know Your Data (in beta) to help developers understand datasets with the goal of improving data quality, helping to mitigate fairness and bias issues.
