Responsible AI

AI Principles

A guiding framework for our responsible development and use of AI, alongside transparency and accountability in our AI development process.

Responsible AI Principles and Approach | Microsoft AI

Discover Microsoft AI tools, industry-specific governance solutions, and responsible AI practices to make smarter, more informed decisions about AI implementation.

Using Amazon Augmented AI for Human Review - Amazon SageMaker AI

Use SageMaker AI to build, train, and host machine learning models in AWS.

Amazon Is Using Specialized AI Agents for Deep Bug Hunting

Born out of an internal hackathon, Amazon’s Autonomous Threat Analysis system uses a variety of specialized AI agents to detect weaknesses and propose fixes to the company’s platforms.

Irresponsible AI: big tech's influence on AI research and associated impacts

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.

Irresponsible AI: big tech's influence on AI research and associated impacts

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.

Irresponsible AI: big tech’s influence on AI research and associated impacts

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech’s influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech’s influence. Third, we discuss the underlying economic forces driving big tech’s actions. Finally, as a call to action, we invite AI researchers to counter big tech’s influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.

Using the Amazon Mechanical Turk Workforce - Amazon SageMaker AI

Use SageMaker AI to build, train, and host machine learning models in AWS.

Americans for Responsible Innovation on Twitter / X

NEW: Today ARI released a blueprint for federal AI governance, including three pillars that promote safe frontier AI development: ✅ Standards set by the government ✅ Independent assurance they are met ✅ Transparency into frontier AI development https://t.co/s2mlUP27Wm pic.twitter.com/X6IhBS9jKF— Americans for Responsible Innovation (@americans4ri) August 10, 2026

AI agents pose untold risk to humanity. We must act to prevent that future | David Krueger

The pieces are falling into place for autonomous artificial intelligence. We must stop unregulated development

Responsible Innovation at the Frontier - Americans for Responsible Innovation

ARI’s blueprint for federal AI governance is designed to promote safe frontier AI development in America. The blueprint is built around three governance functions any federal proposal should incorporate.

Human-Centered Artificial Intelligence: Three Fresh Ideas

Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation. These human aspirations also encourage consideration of privacy, security, environmental protection, social justice, and human rights. This commentary reverses the current emphasis on algorithms and AI methods, by putting humans at the center of systems design thinking, in effect, a second Copernican Revolution. It offers three ideas: (1) a two-dimensional HCAI framework, which shows how it is possible to have both high levels of human control AND high levels of automation, (2) a shift from emulating humans to empowering people with a plea to shift language, imagery, and metaphors away from portrayals of intelligent autonomous teammates towards descriptions of powerful tool-like appliances and tele-operated devices, and (3) a three-level governance structure that describes how software engineering teams can develop more reliable systems, how managers can emphasize a safety culture across an organization, and how industry-wide certification can promote trustworthy HCAI systems. These ideas will be challenged by some, refined by others, extended to accommodate new technologies, and validated with quantitative and qualitative research. They offer a reframe -- a chance to restart design discussions for products and services -- which could bring greater benefits to individuals, families, communities, businesses, and society.

Agentic AI Governance: Securing Autonomous AI Agents in Enterprise

When AI agents start making decisions, calling tools, and coordinating with other agents without waiting for human approval, the governance playbook most...

How Shifting Responsibility for AI Harms Undermines Democratic Accountability | TechPolicy.Press

The moralization of individual AI use deflects responsibility away from powerful actors like corporations and governments, Suvradip Maitra and others write.