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

4. Ownership

We will define owners for the principles guiding our operations and for the algorithms we have developed, and will ensure the ethics of AI throughout the lifecycle.

Principle: OP Financial Group’s ethical guidelines for artificial intelligence, 2018 (unconfirmed)

Published by OP Financial Group

Related Principles

6. We set the framework.

Our AI solutions are developed and enhanced on grounds of deep analysis and evaluation. They are transparent, auditable, fair, and fully documented. We consciously initiate the AI’s development for the best possible outcome. The essential paradigm for our AI systems’ impact analysis is “privacy und security by design”. This is accompanied e.g. by risks and chances scenarios or reliable disaster scenarios. We take great care in the initial algorithm of our own AI solutions to prevent so called “Black Boxes” and to make sure that our systems shall not unintentionally harm the users

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

9. We share and enlighten.

We acknowledge the transformative power of AI for our society. We will support people and society in preparing for this future world. We live our digital responsibility by sharing our knowledge, pointing out the opportunities of the new technology without neglecting its risks. We will engage with our customers, other companies, policy makers, education institutions and all other stakeholders to ensure we understand their concerns and needs and can setup the right safeguards. We will engage in AI and ethics education. Hereby preparing ourselves, our colleagues and our fellow human beings for the new tasks ahead. Many tasks that are being executed by humans now will be automated in the future. This leads to a shift in the demand of skills. Jobs will be reshaped, rather replaced by AI. While this seems certain, the minority knows what exactly AI technology is capable of achieving. Prejudice and sciolism lead to either demonization of progress or to blind acknowledgment, both calling for educational work. We as Deutsche Telekom feel responsible to enlighten people and help society to deal with the digital shift, so that new appropriate skills can be developed and new jobs can be taken over. And we start from within – by enabling our colleagues and employees. But we are aware that this task cannot be solved by one company alone. Therefore we will engage in partnerships with other companies, offer our know how to policy makers and education providers to jointly tackle the challenges ahead.

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

1. People first approach

We will use data and AI responsibly and for the good of our customers. We will define the objectives guiding our use of AI clearly and refine them if necessary based on changed data, technical possibilities and the working environment.

Published by OP Financial Group in OP Financial Group’s ethical guidelines for artificial intelligence, 2018 (unconfirmed)

1. We are driven by our values

We recognize that, like with any technology, there is scope for AI to be used in ways that are not aligned with these guiding principles and the operational guidelines we are developing. In developing AI software we will remain true to our Human Rights Commitment Statement, the UN Guiding Principles on Business and Human Rights, laws, and widely accepted international norms. Wherever necessary, our AI Ethics Steering Committee will serve to advise our teams on how specific use cases are affected by these guiding principles. Where there is a conflict with our principles, we will endeavor to prevent the inappropriate use of our technology.

Published by SAP in SAP's Guiding Principles for Artificial Intelligence, Sep 18, 2018

· Build and Validate:

1 Model development of the AI system and algorithm should consist of the selection of features, hyperparameter tuning and performance metric selection. To achieve this, the technical stakeholders who build and validate models should be responsible for these decisions. 2 Assigning the appropriate ownership and communicating responsibilities will set the tone for accountability that would aid in steering the development of the AI system on good reasons, solid interference, and will allow the intervention of human critical judgement and expertise. 3 The decisions should be supported with quantitative (performance measures on train test datasets, consistency of the performance on different sensitive groups, performance comparison for each set of hyperparameters, etc.) and qualitative indicators (decisions to mitigate and correct unintended risks from inaccurate predictions). 4 The appropriate stakeholders and owners of the AI technology should review and sign off the model after successful testing and validation of user acceptance testing rounds have been conducted and completed before the AI models can be productionized.

Published by SDAIA in AI Ethics Principles, Sept 14, 2022