Safe and Ethical AI (SEA) Platform Network · Linking Artificial Intelligence Principles (LAIP)

L Learning

To maximise the potential of AI, people need to learn how it works and what are the most efficient and effective ways to use it. Employees and other stakeholders need to be empowered to take personal responsibility for the consequences of their use of AI and they need to be provided with the skills to do so.

Principle: IBE interactive framework of fundamental values and principles for the use of Artificial Intelligence (AI) in business, Jan 11, 2018

Published by Institute of Business Ethics (IBE)

Related Principles

4. Human centricity

AI systems should respect human centred values and pursue benefits for human society, including human beings’ well being, nutrition, happiness, etc. It is key to ensure that people benefit from AI design, development, and deployment while being protected from potential harms. AI systems should be used to promote human well being and ensure benefit for all. Especially in instances where AI systems are used to make decisions about humans or aid them, it is imperative that these systems are designed with human benefit in mind and do not take advantage of vulnerable individuals. Human centricity should be incorporated throughout the AI system lifecycle, starting from the design to development and deployment. Actions must be taken to understand the way users interact with the AI system, how it is perceived, and if there are any negative outcomes arising from its outputs. One example of how deployers can do this is to test the AI system with a small group of internal users from varied backgrounds and demographics and incorporate their feedback in the AI system. AI systems should not be used for malicious purposes or to sway or deceive users into making decisions that are not beneficial to them or society. In this regard, developers and deployers (if developing or designing inhouse) should also ensure that dark patterns are avoided. Dark patterns refer to the use of certain design techniques to manipulate users and trick them into making decisions that they would otherwise not have made. An example of a dark pattern is employing the use of default options that do not consider the end user’s interests, such as for data sharing and tracking of the user’s other online activities. As an extension of human centricity as a principle, it is also important to ensure that the adoption of AI systems and their deployment at scale do not unduly disrupt labour and job prospects without proper assessment. Deployers are encouraged to take up impact assessments to ensure a systematic and stakeholder based review and consider how jobs can be redesigned to incorporate use of AI. Personal Data Protection Commission of Singapore’s (PDPC) Guide on Job Redesign in the Age of AI6 provides useful guidance to assist organisations in considering the impact of AI on its employees, and how work tasks can be redesigned to help employees embrace AI and move towards higher value tasks.

Published by ASEAN in ASEAN Guide on AI Governance and Ethics, 2024

Preamble

Two of Deutsche Telekom’s most important goals are to keep being a trusted companion and to enhance customer experience. We see it as our responsibility as one of the leading ICT companies in Europe to foster the development of “intelligent technologies”. At least either important, these technologies, such as AI, must follow predefined ethical rules. To define a corresponding ethical framework, firstly it needs a common understanding on what AI means. Today there are several definitions of AI, like the very first one of John McCarthy (1956) “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” In line with other companies and main players in the field of AI we at DT think of AI as the imitation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self correction. After several decades, Artificial Intelligence has become one of the most intriguing topics of today – and the future. It has become widespread available and is discussed not only among experts but also more and more in public, politics, etc.. AI has started to influence business (new market opportunities as well as efficiency driver), society (e.g. broad discussion about autonomously driving vehicles or AI as “job machine” vs. “job killer”) and the life of each individual (AI already found its way into the living room, e.g. with voice steered digital assistants like smart speakers). But the use of AI and its possibilities confront us not only with fast developing technologies but as well as with the fact that our ethical roadmaps, based on human human interactions, might not be sufficient in this new era of technological influence. New questions arise and situations that were not imaginable in our daily lives then emerge. We as DT also want to develop and make use of AI. This technology can bring many benefits based on improving customer experience or simplicity. We are already in the game, e.g having several AI related projects running. With these comes an increase of digital responsibility on our side to ensure that AI is utilized in an ethical manner. So we as DT have to give answers to our customers, shareholders and stakeholders. The following Digital Ethics guidelines state how we as Deutsche Telekom want to build the future with AI. For us, technology serves one main purpose: It must act supportingly. Thus AI is in any case supposed to extend and complement human abilities rather than lessen them. Remark: The impact of AI on DT jobs – may it as a benefit and for value creation in the sense of job enrichment and enlargement or may it in the sense of efficiency is however not focus of these guidelines.

Published by Deutsche Telekom in Deutsche Telekom’s guidelines for artificial intelligence, May 11, 2018

· 2) Research Funding

Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as: How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked? How can we grow our prosperity through automation while maintaining people’s resources and purpose? How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI? What set of values should AI be aligned with, and what legal and ethical status should it have?

Published by Future of Life Institute (FLI), Beneficial AI 2017 in Asilomar AI Principles, Jan 3-8, 2017

3. New technology, including AI systems, must be transparent and explainable

For the public to trust AI, it must be transparent. Technology companies must be clear about who trains their AI systems, what data was used in that training and, most importantly, what went into their algorithm’s recommendations. If we are to use AI to help make important decisions, it must be explainable.

Published by IBM in Principles for Trust and Transparency, May 30, 2018

1. Transparent and explainable

There must be transparent use and responsible disclosure around data enhanced technology like AI, automated decisions and machine learning systems to ensure that people understand outcomes and can discuss, challenge and improve them. This includes being open about how and why these technologies are being used. When automation has been used to make or assist with decisions, a meaningful explanation should be made available. The explanation should be meaningful to the person requesting it. It should include relevant information about what the decision was, how the decision was made, and the consequences. Why it matters Transparent use is the key principle that helps enable other principles while building trust and confidence in government use of data enhanced technologies. It also encourages a dialogue between those using the technology and those who are affected by it. Meaningful explanations are important because they help people understand and potentially challenge outcomes. This helps ensure decisions are rendered fairly. It also helps identify and reverse adverse impacts on historically disadvantaged groups. For more on this, please consult the Transparency Guidelines.

Published by Government of Ontario, Canada in Principles for Ethical Use of AI [Beta], Sept 14, 2023