Ensuring Accountability

Principle: Legal accountability has to be ensured when human agency is replaced by decisions of AI agents. Recommendations: Ensure legal certainty: Governments should ensure legal certainty on how existing laws and policies apply to algorithmic decision making and the use of autonomous systems to ensure a predictable legal environment. This includes working with experts from all disciplines to identify potential gaps and run legal scenarios. Similarly, those designing and using AI should be in compliance with existing legal frameworks. Put users first: Policymakers need to ensure that any laws applicable to AI systems and their use put users’ interests at the center. This must include the ability for users to challenge autonomous decisions that adversely affect their interests. Assign liability up front: Governments working with all stakeholders need to make some difficult decisions now about who will be liable in the event that something goes wrong with an AI system, and how any harm suffered will be remedied.
Principle: Guiding Principles and Recommendations, Apr 18, 2017

Published by Internet Society

Related Principles

Fairness

Throughout their lifecycle, AI systems should be inclusive and accessible, and should not involve or result in unfair discrimination against individuals, communities or groups. This principle aims to ensure that AI systems are fair and that they enable inclusion throughout their entire lifecycle. AI systems should be user centric and designed in a way that allows all people interacting with it to access the related products or services. This includes both appropriate consultation with stakeholders, who may be affected by the AI system throughout its lifecycle, and ensuring people receive equitable access and treatment. This is particularly important given concerns about the potential for AI to perpetuate societal injustices and have a disparate impact on vulnerable and underrepresented groups including, but not limited to, groups relating to age, disability, race, sex, intersex status, gender identity and sexual orientation. Measures should be taken to ensure the AI produced decisions are compliant with anti‐discrimination laws.

Published by Department of Industry, Innovation and Science, Australian Government in AI Ethics Principles, Nov 7, 2019

Ensure “Interpretability” of AI systems

Principle: Decisions made by an AI agent should be possible to understand, especially if those decisions have implications for public safety, or result in discriminatory practices. Recommendations: Ensure Human Interpretability of Algorithmic Decisions: AI systems must be designed with the minimum requirement that the designer can account for an AI agent’s behaviors. Some systems with potentially severe implications for public safety should also have the functionality to provide information in the event of an accident. Empower Users: Providers of services that utilize AI need to incorporate the ability for the user to request and receive basic explanations as to why a decision was made.

Published by Internet Society in Guiding Principles and Recommendations, Apr 18, 2017

Responsible Deployment

Principle: The capacity of an AI agent to act autonomously, and to adapt its behavior over time without human direction, calls for significant safety checks before deployment, and ongoing monitoring. Recommendations: Humans must be in control: Any autonomous system must allow for a human to interrupt an activity or shutdown the system (an “off switch”). There may also be a need to incorporate human checks on new decision making strategies in AI system design, especially where the risk to human life and safety is great. Make safety a priority: Any deployment of an autonomous system should be extensively tested beforehand to ensure the AI agent’s safe interaction with its environment (digital or physical) and that it functions as intended. Autonomous systems should be monitored while in operation, and updated or corrected as needed. Privacy is key: AI systems must be data responsible. They should use only what they need and delete it when it is no longer needed (“data minimization”). They should encrypt data in transit and at rest, and restrict access to authorized persons (“access control”). AI systems should only collect, use, share and store data in accordance with privacy and personal data laws and best practices. Think before you act: Careful thought should be given to the instructions and data provided to AI systems. AI systems should not be trained with data that is biased, inaccurate, incomplete or misleading. If they are connected, they must be secured: AI systems that are connected to the Internet should be secured not only for their protection, but also to protect the Internet from malfunctioning or malware infected AI systems that could become the next generation of botnets. High standards of device, system and network security should be applied. Responsible disclosure: Security researchers acting in good faith should be able to responsibly test the security of AI systems without fear of prosecution or other legal action. At the same time, researchers and others who discover security vulnerabilities or other design flaws should responsibly disclose their findings to those who are in the best position to fix the problem.

Published by Internet Society in Guiding Principles and Recommendations, Apr 18, 2017

5 DEMOCRATIC PARTICIPATION PRINCIPLE

AIS must meet intelligibility, justifiability, and accessibility criteria, and must be subjected to democratic scrutiny, debate, and control. 1) AIS processes that make decisions affecting a person’s life, quality of life, or reputation must be intelligible to their creators. 2) The decisions made by AIS affecting a person’s life, quality of life, or reputation should always be justifiable in a language that is understood by the people who use them or who are subjected to the consequences of their use. Justification consists in making transparent the most important factors and parameters shaping the decision, and should take the same form as the justification we would demand of a human making the same kind of decision. 3) The code for algorithms, whether public or private, must always be accessible to the relevant public authorities and stakeholders for verification and control purposes. 4) The discovery of AIS operating errors, unexpected or undesirable effects, security breaches, and data leaks must imperatively be reported to the relevant public authorities, stakeholders, and those affected by the situation. 5) In accordance with the transparency requirement for public decisions, the code for decision making algorithms used by public authorities must be accessible to all, with the exception of algorithms that present a high risk of serious danger if misused. 6) For public AIS that have a significant impact on the life of citizens, citizens should have the opportunity and skills to deliberate on the social parameters of these AIS, their objectives, and the limits of their use. 7) We must at all times be able to verify that AIS are doing what they were programmed for and what they are used for. 8) Any person using a service should know if a decision concerning them or affecting them was made by an AIS. 9) Any user of a service employing chatbots should be able to easily identify whether they are interacting with an AIS or a real person. 10) Artificial intelligence research should remain open and accessible to all.

Published by University of Montreal in The Montreal Declaration for a Responsible Development of Artificial Intelligence, Dec 4, 2018

(Preamble)

New developments in Artificial Intelligence are transforming the world, from science and industry to government administration and finance. The rise of AI decision making also implicates fundamental rights of fairness, accountability, and transparency. Modern data analysis produces significant outcomes that have real life consequences for people in employment, housing, credit, commerce, and criminal sentencing. Many of these techniques are entirely opaque, leaving individuals unaware whether the decisions were accurate, fair, or even about them. We propose these Universal Guidelines to inform and improve the design and use of AI. The Guidelines are intended to maximize the benefits of AI, to minimize the risk, and to ensure the protection of human rights. These Guidelines should be incorporated into ethical standards, adopted in national law and international agreements, and built into the design of systems. We state clearly that the primary responsibility for AI systems must reside with those institutions that fund, develop, and deploy these systems.

Published by The Public Voice coalition, established by Electronic Privacy Information Center (EPIC) in Universal Guidelines for Artificial Intelligence, Oct 23, 2018