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Responsible AI, Quantified

Government Can Lead AI Adoption, Responsibly

As the adoption of AI grows throughout government, there has never been more awareness of the need to build and maintain AI systems with a clear understanding of their ethical risk. Every day, these systems shape human experience, bringing issues of , equity, autonomy, data integrity, and regulatory compliance into focus. But how do agencies turn a commitment to abstract ethical AI principles into a fully operational responsible AI strategy—one that that delivers not just transparency and reduced risk but also innovation that improves mission performance?

Consider the many frameworks, principles, and policies that define the field of responsible AI—such as the Department of Defense’s (DOD) AI Ethical Principles, the Principles of Artificial Intelligence Ethics for the Intelligence Community, and the Blueprint for an AI Bill of Rights. These frameworks provide agencies with overarching guidelines essential for defining an ethical vision. But they offer few tangible tools and little practical guidance to operationalize responsible AI.

As the trusted AI leader to the nation, ĢƵ Allen partners with clients to address this void with a rigorous, risk-based method for assessing the ethical risk of AI systems—and a corresponding roadmap for taking continuous and concrete action to ensure these systems operate fully and responsibly in line with mission objectives.

AI Governance, Risk, and Compliance Management Services

ĢƵ Allen offers complementary services backed by sector-leading expertise and best practices addressing the end-to-end responsible AI lifecycle:

Strategy

Develop an integrated strategy encompassing defined objectives, established administrative processes, and supporting governance, risk, and compliance infrastructure.

Assessment

Audit and assess existing and planned AI systems for potential ethical, legal, compliance, or other responsible AI risks.

Testing, Monitoring and Compliance

Establish and maintain systems and processes for sustaining and verifying trusted, responsible operations.  

Workforce Readiness

Develop and implement training programs to educate employees about responsible AI risks and their responsibilities.

A Call to Action for AI Leaders

Hear from Geoff Schaefer on the state of responsible AI and things AI ethicists should make central to their work to improve outcomes:

Geoff Schaefer leads ĢƵ Allen's responsible AI practice.

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What does it mean to live a good life? How can AI help us flourish? These are questions that AI ethicists should make central to their work. We should consider an AI system’s potential benefits and risks in concert with one another. In fact, a more robust—and historically accurate—ethical calculus will focus on the net good that an AI system will generate over its lifespan. As we think about the future of AI ethics, the field should emphasize three questions: First, what is the maximal good an AI system can do? Second, what are the potential risks in its design? And third, how can we mitigate those risks to achieve the maximal good? The order of these questions is intentional, as they shift our focus from harms to happiness and from failure to flourishing. This will help us open up new missions and needs for AI ethics to support. After all, ethics was never about compliance. Nor was it simply about the difference between right and wrong. Instead, it provided the overriding question of philosophy in ancient times: How can we be happy and flourish? Revisiting this ancient question will ensure that the future of AI ethics is bright, useful, and critical to the advancement of society. In other words, AI ethics can help us live lives that are, indeed, well-lived. The field is just getting started. 

A Practical, Quantitative Approach to Responsible AI

One key to realizing this modern approach to responsible AI is enabling decision makers to measure the ethical risk of their AI systems systematically. With a quantitative scorecard of their systems’ “ethical surface area,” they can more effectively capitalize on proven strategies to de-risk and recalibrate those systems. This will not only ensure their AI ecosystem is measurably responsible but will enhance the overall mission performance of their individual AI systems.

Our practical and quantitative approach to responsible AI accelerates agency progress from theoretical principles to concrete models and actions, enabling the design and deployment of AI systems for any mission in any sector.

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Industry-first ethical risk framework and criteria for ethical test and evaluation
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Ethical X-ray of an AI system’s architecture
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Deployment-focused evaluation to increase mission success
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Actionable recommendations to reduce ethical risk
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Different assessment types and timelines for unique mission needs
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Validation that an AI system is safe to operate ethically

Proven Solutions to Accelerate Responsible AI Adoption

ĢƵ Allen offers turnkey solutions to help define, implement, and sustain an enterprise responsible AI strategy:

Responsible AI QuickStart

A turnkey serving offering for establishing an enterprise responsible AI program in line with best practices and sector regulatory requirements  

ETHICAL ATO: Risk + Impact Assessment

A quantitative analysis of both an AI system’s ethical risk and the Office of Management and Budget’s rights and safety-impacting categories

Credo.AI for AI Governance

Streamlined governance of your AI portfolio—from a comprehensive AI registry to dedicated policy packs enabling regulatory compliance—through our exclusive partnership with Credo.AI

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