Artificial intelligence (AI) will transform our world. As a global leader in AI, IBM continues to push cognitive computing to the edge of possibility, from Watson agricultural insights informing planting season to incident reporting insights helping to fight human trafficking. But leadership means more than creating the world’s most advanced technologies — it also requires responsible stewardship of these powerful new tools.

Responsibility has been a hallmark of IBM’s culture for over 100 years. Our commitment to responsible stewardship is grounded in long-held Principles of Trust and Transparency.

IBM offers these 10 AI policy priorities for governments and public policy makers around the world in order to advance trusted AI.

1. Recognize and promote how AI is being applied to solve some of humanity’s most pervasive problems and expand economic opportunity for all.
2. Establish national public-private bodies where stakeholders can work together to advance AI responsibly.
3. Increase research funding for AI and prioritize effective methods for human-AI collaboration.
4. Advance AI testbeds, multi-disciplinary, inclusive approaches that bring together diverse stakeholders including impacted communities, government, industry and academia to test new AI innovations in controlled environments.
5. Award grants to encourage researchers and developers of AI solutions to create diverse and inclusive developer teams, who are trained to identify and mitigate possible sources of bias in data or models.
6. Support building digital skills for tomorrow’s workforce, empowering and enabling students and mid-career professionals to realize the economic opportunity AI represents.
7. Implement open government data, while respecting privacy rules, to train responsible AI systems by requiring all non-sensitive government data to be in machine-readable format and to be under standardized data sharing and licensing models, e.g., the open source Community Data License Agreement.
8. Support and advance global, consensus-based, industry-led standards for AI explainability, fairness, accountability, and security, and provide incentives to companies that apply them and conform accordingly.
9. Promote open source for AI, especially tools – such as IBM’s AI Fairness 360 – that can help developers and users assess and mitigate bias, and demonstrate explainability.
10. Increase government’s use of AI to expand access to and familiarity with the technology among government and the citizens they serve.

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