AI Ethics Principles for DoD

 

AI Ethics Principles for DoD

 

October, 2019 – DIB

 

AI Ethics Principles for DoD

 

The following principles represent the means to ensure ethical behavior as the Department develops and deploys AI. To that end, the Department should set the goal that its use of AI systems is:

1. Responsible. Human beings should exercise appropriate levels of judgment and remain responsible for the development, deployment, use, and outcomes of AI systems.

2. Equitable. DoD should take deliberate steps to avoid unintended bias in the development and deployment of combat or non-combat AI systems that would inadvertently cause harm to persons.

3. Traceable. DoD’s AI engineering discipline should be sufficiently advanced such that technical experts possess an appropriate understanding of the technology, development processes, and operational methods of its AI systems, including transparent and auditable methodologies, data sources, and design procedure and documentation.

4. Reliable. AI systems should have an explicit, well-defined domain of use, and the safety, security, and robustness of such systems should be tested and assured across their entire life cycle within that domain of use.

5. Governable. DoD AI systems should be designed and engineered to fulfill their intended function while possessing the ability to detect and avoid unintended harm or disruption, and disengage or deactivate deployed systems that demonstrate unintended escalatory or other behavior.

This White Paper is organized into five chapters. Chapter One outlines the stated needs for a set of AI Ethics Principles and ethics guidance from existing strategic documents and law. It also addresses definitional approaches associated with AI and autonomy to clearly frame how the DIB approaches key issues for DoD and its development and use of AI. Chapter Two provides the necessary grounding for a set of DoD AI Ethics Principles to ensure that they are coherently and consistently derived for DoD. We explain DoD’s existing ethics framework that applies to all of DoD’s technologies, AI included. In Chapter Three, we offer substantive and evidence-driven explanations of each of the five AI Ethics Principles. These principles are normative; they are intended to inform and guide action. However, we are mindful that depending upon context, some principles may override others, and for various AI use cases, these will apply differently. Chapter Four outlines our recommendations to the Department, while Chapter Five provides conclusions. We also provide a set of Appendices to aid readers by providing transparency and clarity about our process in developing these principles and providing high-level content about existing DoD processes.

You can reach the White Paper from the link below:

https://admin.govexec.com/media/dib_ai_principles_-_supporting_document_-_embargoed_copy_(oct_2019).pdf

AI at Google: Our Principles

AI at Google: Our Principles

Related image

Sundar Pichai

 

Sundar Pichai

CEO

June 7, 2018

 

 

 

At its heart, AI is computer programming that learns and adapts. It can’t solve every problem, but its potential to improve our lives is profound. At Google, we use AI to make products more useful—from email that’s spam-free and easier to compose, to a digital assistant you can speak to naturally, to photos that pop the fun stuff out for you to enjoy.

Beyond our products, we’re using AI to help people tackle urgent problems. A pair of high school students are building AI-powered sensors to predict the risk of wildfires. Farmers are using it to monitor the health of their herds. Doctors are starting to use AI to help diagnose cancer and prevent blindness. These clear benefits are why Google invests heavily in AI research and development, and makes AI technologies widely available to others via our tools and open-source code.

We recognize that such powerful technology raises equally powerful questions about its use. How AI is developed and used will have a significant impact on society for many years to come. As a leader in AI, we feel a deep responsibility to get this right. So today, we’re announcing seven principles to guide our work going forward. These are not theoretical concepts; they are concrete standards that will actively govern our research and product development and will impact our business decisions.

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.

Objectives for AI applications

We will assess AI applications in view of the following objectives. We believe that AI should:

  1. Be socially beneficial. 

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.

  1. Avoid creating or reinforcing unfair bias.

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.

  1. Be built and tested for safety.

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.

  1. Be accountable to people.

We will design AI systems that provide appropriate opportunities for feedback, relevant explanations, and appeal. Our AI technologies will be subject to appropriate human direction and control.

  1. Incorporate privacy design principles.

We will incorporate our privacy principles in the development and use of our AI technologies. We will give opportunity for notice and consent, encourage architectures with privacy safeguards, and provide appropriate transparency and control over the use of data.

  1. Uphold high standards of scientific excellence.

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.

  1. Be made available for uses that accord with these principles.  

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

AI applications we will not pursue

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.

 

We want to be clear that while we are not developing AI for use in weapons, we will continue our work with governments and the military in many other areas. These include cybersecurity, training, military recruitment, veterans’ healthcare, and search and rescue. These collaborations are important and we’ll actively look for more ways to augment the critical work of these organizations and keep service members and civilians safe.

AI for the long term

While this is how we’re choosing to approach AI, we understand there is room for many voices in this conversation. As AI technologies progress, we’ll work with a range of stakeholders to promote thoughtful leadership in this area, drawing on scientifically rigorous and multidisciplinary approaches. And we will continue to share what we’ve learned to improve AI technologies and practices.

We believe these principles are the right foundation for our company and the future development of AI. This approach is consistent with the values laid out in our original Founders’ Letter back in 2004. There we made clear our intention to take a long-term perspective, even if it means making short-term tradeoffs. We said it then, and we believe it now.

 

You can reach the original text below:

https://blog.google/topics/ai/ai-principles/

The Ethics Of Artificial Intelligence

The Ethics Of Artificial Intelligence

 

Nick Bostrom
Eliezer Yudkowsky

Cambridge University Press, 2011

 

 

 

Abstract

“The possibility of creating thinking machines raises a host of ethical issues.  These questions relate both to ensuring that such machines do not harm humans and other morally relevant beings, and to the moral status of the machines themselves.  The first section discusses issues that may arise in the near future of AI. The second section outlines challenges for ensuring that AI operates safely as it approaches humans in its intelligence.  The third section outlines how we might assess whether, and in what circumstances, AIs themselves have moral status.  In the fourth section, we consider how AIs might differ from humans in certain basic respects relevant to our ethical assessment of them.  The final section addresses the issues of creating AIs more intelligent than human, and ensuring that they use their advanced intelligence for good rather than ill.”

 

You can reach the article from the link below:

https://nickbostrom.com/ethics/artificial-intelligence.pdf


For Citation :

Selin Cetin
"The Ethics Of Artificial Intelligence"
Hukuk & Robotik, Friday October 13th, 2017
https://robotic.legal/en/the-ethics-of-artificial-intelligence/- 07/03/2021