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Scailable ML and AI Manifesto v0.1

Responsible ML/AI Manifesto

Scailable aspires to create and help create technologies that solve important problems and help people in their daily lives. We are optimistic about the potential for AI and other advanced technologies to empower people, widely benefit current and future generations, and work for the common good.

We believe that these technologies will promote innovation and further our mission to organize the world’s information and make it universally accessible and useful.

We recognize that these same technologies also raise important challenges that we need to address clearly, thoughtfully, and affirmatively. These principles set out our commitment to develop technology responsibly and establish specific application areas we will not pursue.

Many technologies have multiple uses. We will work to limit potentially harmful or abusive applications. As we develop and deploy ML/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 Scailable’s involvement: whether we are providing general-purpose tools, integrating tools for customers, or developing custom solutions

First Principles:

Inclusion

Maximize diversity, connectivity, and accessibility among projects, collaborators, and outputs.

Experimentation

Emphasize continuously iterative testing and analysis.

Accountability

Behave ethically and transparently, fix mistakes quickly, and hold ourselves and others accountable.

Impact

Prioritize projects with well-defined goals, and design them to achieve measurable, substantive outcomes.

Scailable aims to:

  1. Use technology to improve life for our users, customers, organizations, and communities.
  2. Create reproducible and extensible work.
  3. Build teams with diverse ideas, backgrounds, and strengths.
  4. Clearly identify the questions and objectives that drive each project and use to guide both planning and refinement.
  5. Be open to changing our methods and conclusions in response to new knowledge.
  6. Recognize and mitigate bias in ourselves and in the technologies we use.
  7. Present our work in ways that empower others to make better-informed decisions.
  8. Consider carefully the ethical implications of choices we make, and the impacts of our work on individuals and society.
  9. Respect and invite fair criticism while promoting the identification and open discussion of errors, risks, and unintended consequences of our work.
  10. Protect the privacy and security of individuals.
  11. Help others to understand the most useful and appropriate applications of technology to solve real-world problems.

In addition to the above objectives, we will not design or deploy AI in the following application areas:

  1. 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.
  2. Weapons or other technologies whose principal purpose or implementation is to cause or directly facilitate injury to people.
  3. Technologies that gather or use information for surveillance violating internationally accepted norms.
  4. Technologies whose purpose contravenes widely accepted principles of international law and human rights.

As our experience in this space deepens, this list will evolve.

We believe these principles are a first foundation for our company and our future development of ML/AI. We acknowledge that this area is dynamic and evolving, and we will approach our work with humility, a commitment to internal and external engagement, and a willingness to adapt our approach as we learn over time.