Maximising the Benefits of AI While Managing the Disruption of its Implementation

Vodafone is a responsible employer and is determined to become a leading, human centric, digital business.
Principle: Vodafone's AI Framework, Jun 11, 2019

Published by Vodafone Group

Related Principles

· 5. The Principle of Explicability: “Operate transparently”

Transparency is key to building and maintaining citizen’s trust in the developers of AI systems and AI systems themselves. Both technological and business model transparency matter from an ethical standpoint. Technological transparency implies that AI systems be auditable, comprehensible and intelligible by human beings at varying levels of comprehension and expertise. Business model transparency means that human beings are knowingly informed of the intention of developers and technology implementers of AI systems. Explicability is a precondition for achieving informed consent from individuals interacting with AI systems and in order to ensure that the principle of explicability and non maleficence are achieved the requirement of informed consent should be sought. Explicability also requires accountability measures be put in place. Individuals and groups may request evidence of the baseline parameters and instructions given as inputs for AI decision making (the discovery or prediction sought by an AI system or the factors involved in the discovery or prediction made) by the organisations and developers of an AI system, the technology implementers, or another party in the supply chain.

Published by The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI, Dec 18, 2018


The Internet Society has developed the following principles and recommendations in reference to what we believe are the core “abilities” that underpin the value the Internet provides. While the deployment of AI in Internet based services is not new, the current trend points to AI as an increasingly important factor in the Internet’s future development and use. As such, these guiding principles and recommendations are a first attempt to guide the debate going forward. Furthermore, while this paper is focused on the specific challenges surrounding AI, the strong interdependence between its development and the expansion of the Internet of Things (IoT) demands a closer look at interoperability and security of IoT devices.

Published by Internet Society, "Artificial Intelligence and Machine Learning: Policy Paper" in Guiding Principles and Recommendations, Apr 18, 2017


1.1. Human centered and humanistic approach. Human rights and freedoms and the human as such must be treated as the greatest value in the process of AI technologies development. AI technologies developed by Actors should promote or not hinder the full realization of all human capabilities to achieve harmony in social, economic and spiritual spheres, as well as the highest self fulfillment of human beings. AI Actors should regard core values such as the preservation and development of human cognitive abilities and creative potential; the preservation of moral, spiritual and cultural values; the promotion of cultural and linguistic diversity and identity; and the preservation of traditions and the foundations of nations, peoples, ethnic and social groups. A human centered and humanistic approach is the basic ethical principle and central criterion for assessing the ethical behavior of AI Actors listed in Section 2 of this Code. 1.2. Recognition of autonomy and free will of human. AI Actors should take necessary measures to preserve the autonomy and free will of human in the process of decision making, their right to choose, as well as preserve human intellectual abilities in general as an intrinsic value and a system forming factor of modern civilization. AI Actors should forecast possible negative consequences for the development of human cognitive abilities at the earliest stages of AI systems creation and refrain from the development of AI systems that purposefully cause such consequences. 1.3. Compliance with the law. AI Actors must know and comply with the provisions of the national legislation in all areas of their activities and at all stages of creation, integration and use of AI technologies, i.a. in the sphere of legal responsibility of AI Actors. 1.4. Non discrimination. To ensure fairness and non discrimination, AI Actors should take measures to verify that the algorithms, datasets and processing methods for machine learning that are used to group and or classify data that concern individuals or groups do not entail intentional discrimination. AI Actors are encouraged to create and apply methods and software solutions that identify and prevent discrimination manifestations based on race, nationality, gender, political views, religious beliefs, age, social and economic status, or information about private life (at the same time, the rules of functioning or application of AI systems for different groups of users wherein such factors are taken into account for user segmentation, which are explicitly declared by an AI Actor, cannot be defined as discrimination). 1.5. Assessment of risks and humanitarian impact. AI Actors are encouraged to: • assess the potential risks of the use of an AI system, including social consequences for individuals, society and the state, as well as the humanitarian impact of an AI system on human rights and freedoms at different stages of its life cycle, i.a. during the formation and use of datasets; • monitor the manifestations of such risks in the long term; • take into account the complexity of AI systems’ actions, including interconnection and interdependence of processes in the AI systems’ life cycle, during risk assessment. In special cases concerning critical applications of an AI system it is encouraged that risk assessment be conducted with the involvement of a neutral third party or authorized official body given that it does not harm the performance and information security of the AI system and ensures the protection of the intellectual property and trade secrets of the developer.

Published by AI Alliance Russia in AI Ethics Code (revised version), Oct 21, 2022 (unconfirmed)

3. Human centric AI

AI should be at the service of society and generate tangible benefits for people. AI systems should always stay under human control and be driven by value based considerations. Telefónica is conscious of the fact that the implementation of AI in our products and services should in no way lead to a negative impact on human rights or the achievement of the UN’s Sustainable Development Goals. We are concerned about the potential use of AI for the creation or spreading of fake news, technology addiction, and the potential reinforcement of societal bias in algorithms in general. We commit to working towards avoiding these tendencies to the extent it is within our realm of control.

Published by Telefónica in AI Principles of Telefónica, Oct 30, 2018

6 Promote artificial intelligence that is responsive and sustainable

Responsiveness requires that designers, developers and users continuously, systematically and transparently examine an AI technology to determine whether it is responding adequately, appropriately and according to communicated expectations and requirements in the context in which it is used. Thus, identification of a health need requires that institutions and governments respond to that need and its context with appropriate technologies with the aim of achieving the public interest in health protection and promotion. When an AI technology is ineffective or engenders dissatisfaction, the duty to be responsive requires an institutional process to resolve the problem, which may include terminating use of the technology. Responsiveness also requires that AI technologies be consistent with wider efforts to promote health systems and environmental and workplace sustainability. AI technologies should be introduced only if they can be fully integrated and sustained in the health care system. Too often, especially in under resourced health systems, new technologies are not used or are not repaired or updated, thereby wasting scare resources that could have been invested in proven interventions. Furthermore, AI systems should be designed to minimize their ecological footprints and increase energy efficiency, so that use of AI is consistent with society’s efforts to reduce the impact of human beings on the earth’s environment, ecosystems and climate. Sustainability also requires governments and companies to address anticipated disruptions to the workplace, including training of health care workers to adapt to use of AI and potential job losses due to the use of automated systems for routine health care functions and administrative tasks.

Published by World Health Organization (WHO) in Key ethical principles for use of artificial intelligence for health, Jun 28, 2021