While we are optimistic about the potential of AI, we recognize that advanced technologies can raise important challenges that must be addressed clearly, thoughtfully, and affirmatively. These AI Principles describe our commitment to developing technology responsibly and work to establish specific application areas we will not pursue.
Created by Khyati Trehan as part of the Visualising AI project launched by Google DeepMind, this image depicts AI safety research to prevent its misuse and encourage beneficial uses.
We are using artificial intelligence to help clinical experts detect breast cancer in mammograms.
The expanded reach of new technologies increasingly touches society as a whole
Advances in AI will have transformative impacts in a wide range of fields, including healthcare, security, energy, transportation, manufacturing, and entertainment. As we consider potential development and uses of AI technologies, we will take into account a broad range of social and economic factors, and will proceed where we believe that the overall likely benefits substantially exceed the foreseeable risks and downsides.
AI also enhances our ability to understand the meaning of content at scale. We will strive to make high-quality and accurate information readily available using AI, while continuing to respect cultural, social, and legal norms in the countries where we operate. And we will continue to thoughtfully evaluate when to make our technologies available on a non-commercial basis.
Using machine learning developed in partnership with Google, the Geena Davis Inclusion Quotient (GD-IQ) helps identify gender bias onscreen by identifying a character’s gender, as well as how long each actor spoke and were on-screen.
AI algorithms and datasets can reflect, reinforce, or reduce unfair biases
We recognize that distinguishing fair from unfair biases is not always simple, and differs across cultures and societies. We will seek to avoid unjust impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and political or religious belief.
How Google keeps you safe online with AI that is secure by default.
We will continue to develop and apply strong safety and security practices to avoid unintended results that create risks of harm
We will design our AI systems to be appropriately cautious, and seek to develop them in accordance with best practices in AI safety research. In appropriate cases, we will test AI technologies in constrained environments and monitor their operation after deployment.
Project Vaani involves working with speakers of many different languages across hundreds of districts in India to build an inclusive dataset.
Our AI technologies will be subject to appropriate human direction and control
We will design AI systems that provide appropriate opportunities for feedback, relevant explanations, and appeal.
SynthID helps identify AI-generated content by embedding an imperceptible watermark on text, images, audio, and video content generated by our models.
We will incorporate our privacy principles in the development and use of our AI technologies
We will give the opportunity for notice and consent, encourage architectures with privacy safeguards, and provide appropriate transparency and control over the use of data.
AlphaFold is accelerating breakthroughs in biology with AI, and has revealed millions of intricate 3D protein structures, helping scientists understand how life’s molecules interact.
Technological innovation is rooted in the scientific method and a commitment to open inquiry, intellectual rigor, integrity, and collaboration
AI tools have the potential to unlock new realms of scientific research and knowledge in critical domains like biology, chemistry, medicine, and environmental sciences. We aspire to high standards of scientific excellence as we work to progress AI development.
We will work with a range of stakeholders to promote thoughtful leadership in this area, drawing on scientifically rigorous and multidisciplinary approaches. And we will responsibly share AI knowledge by publishing educational materials, best practices, and research that enable more people to develop useful AI applications.
A woman uses Lookout, an AI powered Pixel feature designed to help people who are blind or low vision identify information about their surroundings, in a flower market.
Many technologies have multiple uses. We will work to limit potentially harmful or abusive applications
As we develop and deploy AI technologies, we will evaluate likely uses in light of the following factors:
Primary purpose and use: the primary purpose and likely use of a technology and application, including how closely the solution is related to or adaptable to a harmful use
Nature and uniqueness: whether we are making available technology that is unique or more generally available
Scale: whether the use of this technology will have significant impact
Nature of Google’s involvement: whether we are providing general-purpose tools, integrating tools for customers, or developing custom solutions
In addition to the above objectives, we will not design or deploy AI in the following application areas:
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Technologies that cause or are likely to cause overall harm. Where there is a material risk of harm, we will proceed only where we believe that the benefits substantially outweigh the risks, and will incorporate appropriate safety constraints.
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Weapons or other technologies whose principal purpose or implementation is to cause or directly facilitate injury to people.
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Technologies that gather or use information for surveillance violating internationally accepted norms.
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Technologies whose purpose contravenes widely accepted principles of international law and human rights.
As our experience in this space deepens, this list may evolve.
Building on our AI Principles, we have developed recommended practices for developers and researchers to use when designing AI systems. This includes using a human-centered design approach to address challenges throughout the AI responsibility lifecycle: understanding unique limitations of datasets and models through research; building fairness, interpretability, privacy and safety into the systems; conducting ongoing assessments and testing; and sharing helpful information, tools and educational resources.
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UPDATES ON OUR AI PRINCIPLES
