The principle of responsibility must be fundamental to AI research and application. ‘Autonomous’ systems should only be developed and used in ways that serve the global social and environmental good, as determined by outcomes of deliberative democratic processes. This implies that they should be designed so that their effects align with a plurality of fundamental human values and rights. As the potential misuse of ‘autonomous’ technologies poses a major challenge, risk awareness and a precautionary approach are crucial. Applications of AI and robotics should not pose unacceptable risks of harm to human beings, and not compromise human freedom and autonomy by illegitimately and surreptitiously reducing options for and knowledge of citizens. They should be geared instead in their development and use towards augmenting access to knowledge and access to opportunities for individuals.
Research, design and development of AI, robotics and ‘autonomous’ systems should be guided by an authentic concern for research ethics, social accountability of developers, and global academic cooperation to protect fundamental rights and values and aim at designing technologies that support these, and not detract from them.
(d) Justice, equity, and solidarity
AI should contribute to global justice and equal access to the benefits and advantages that AI, robotics and ‘autonomous’ systems can bring. Discriminatory biases in data sets used to train and run AI systems should be prevented or detected, reported and neutralised at the earliest stage possible.
We need a concerted global effort towards equal access to ‘autonomous’ technologies and fair distribution of benefits and equal opportunities across and within societies. This includes the formulating of new models of fair distribution and benefit sharing apt to respond to the economic transformations caused by automation, digitalisation and AI, ensuring accessibility to core AI technologies, and facilitating training in STEM and digital disciplines, particularly with respect to disadvantaged regions and societal groups. Vigilance is required with respect to the downside of the detailed and massive data on individuals that accumulates and that will put pressure on the idea of solidarity, e.g. systems of mutual assistance such as in social insurance and healthcare. These processes may undermine social cohesion and give rise to radical individualism.
4. The Principle of Justice: “Be Fair”
Published by: The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI
For the purposes of these Guidelines, the principle of justice imparts that the development, use, and regulation of AI systems must be fair. Developers and implementers need to ensure that individuals and minority groups maintain freedom from bias, stigmatisation and discrimination. Additionally, the positives and negatives resulting from AI should be evenly distributed, avoiding to place vulnerable demographics in a position of greater vulnerability and striving for equal opportunity in terms of access to education, goods, services and technology amongst human beings, without discrimination. Justice also means that AI systems must provide users with effective redress if harm occurs, or effective remedy if data practices are no longer aligned with human beings’ individual or collective preferences. Lastly, the principle of justice also commands those developing or implementing AI to be held to high standards of accountability. Humans might benefit from procedures enabling the benchmarking of AI performance with (ethical) expectations.
6 EQUITY PRINCIPLE
The development and use of AIS must contribute to the creation of a just and equitable society.
1) AIS must be designed and trained so as not to create, reinforce, or reproduce discrimination based on — among other things — social, sexual, ethnic, cultural, or religious differences.
2) AIS development must help eliminate relationships of domination between groups and people based on differences of power, wealth, or knowledge.
3) AIS development must produce social and economic beneﬁts for all by reducing social inequalities and vulnerabilities.
4) Industrial AIS development must be compatible with acceptable working conditions at every step of their life cycle, from natural resources extraction to recycling, and including data processing.
5) The digital activity of users of AIS and digital services should be recognized as labor that contributes to the functioning of algorithms and creates value.
6) Access to fundamental resources, knowledge and digital tools must be guaranteed for all.
7) We should support the development of commons algorithms — and of open data needed to train them — and expand their use, as a socially equitable objective.
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.