In June, Google became the latest tech company to publish a guide of principles designed to govern its work in artificial intelligence (AI). Following the likes of Microsoft, Mountain View detailed the following seven AI principles:
- be socially beneficial
- avoid creating or reinforcing bias
- be built and tested for safety
- be accountable to people
- incorporate privacy design principles
- uphold high standards of scientific excellence
- be made available for uses that accord with all principles
This week, Google has checked in on its principles with a progress report. Specifically, the company is detailing how it has fared in implementing the guidelines into its AI efforts. Kent Walker, senior vice president of global affairs at Google, discussed in a blog post that a review structure has been created.
Review Process
So far, Google has completed 100 reviews of its AI technology. The company confirms some have led to modifications in visual speech recognition research.
“Thoughtful decisions require careful and nuanced consideration of how the AI principles … should apply, how to make tradeoffs when principles come into conflict, and how to mitigate risks for a given circumstance,” Walker said. “Most of these cases … have aligned with the principles.”
AI reviews are conducted by a team of ethicists, human rights experts, researchers, social scientists, legal advisors, and leaders in privacy matters. Google has developed the review teams based on three core goals:
- A responsible innovation team that handles day-to-day operations and initial assessments. This group includes user researchers, social scientists, ethicists, human rights specialists, policy and privacy advisors, and legal experts on both a full- and part-time basis, which allows for diversity and inclusion of perspectives and disciplines.
- Senior experts from a range of disciplines across Alphabet who provide technological, functional, and application expertise.
- A council of senior executives to handle the most complex and difficult issues, including decisions that affect multiple products and technologies.