V. Diversity, non discrimination and fairness
Data sets used by AI systems (both for training and operation) may suffer from the inclusion of inadvertent historic bias, incompleteness and bad governance models. The continuation of such biases could lead to (in)direct discrimination. Harm can also result from the intentional exploitation of (consumer) biases or by engaging in unfair competition. Moreover, the way in which AI systems are developed (e.g. the way in which the programming code of an algorithm is written) may also suffer from bias. Such concerns should be tackled from the beginning of the system’ development.
Establishing diverse design teams and setting up mechanisms ensuring participation, in particular of citizens, in AI development can also help to address these concerns. It is advisable to consult stakeholders who may directly or indirectly be affected by the system throughout its life cycle. AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility through a universal design approach to strive to achieve equal access for persons with disabilities.
(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.
3. Design for all
Published by: The European Commission’s High-Level Expert Group on Artificial Intelligence in Draft Ethics Guidelines for Trustworthy AI
Systems should be designed in a way that allows all citizens to use the products or services, regardless of their age, disability status or social status. It is particularly important to consider accessibility to AI products and services to people with disabilities, which are horizontal category of society, present in all societal groups independent from gender, age or nationality. AI applications should hence not have a one size fits all approach, but be user centric and consider the whole range of human abilities, skills and requirements. Design for all implies the accessibility and usability of technologies by anyone at any place and at any time, ensuring their inclusion in any living context, thus enabling equitable access and active participation of potentially all people in existing and emerging computer mediated human activities. This requirement links to the United Nations Convention on the Rights of Persons with Disabilities.
7 DIVERSITY INCLUSION PRINCIPLE
The development and use of AIS must be compatible with maintaining social and cultural diversity and must not restrict the scope of lifestyle choices or personal experiences.
1) AIS development and use must not lead to the homogenization of society through the standardization of behaviours and opinions.
2) From the moment algorithms are conceived, AIS development and deployment must take into consideration the multitude of expressions of social and cultural diversity present in the society.
3) AI development environments, whether in research or industry, must be inclusive and reﬂect the diversity of the individuals and groups of the society.
4) AIS must avoid using acquired data to lock individuals into a user proﬁle, ﬁx their personal identity, or conﬁne them to a ﬁltering bubble, which would restrict and conﬁne their possibilities for personal development — especially in ﬁelds such as education, justice, or business.
5) AIS must not be developed or used with the aim of limiting the free expression of ideas or the opportunity to hear diverse opinions, both of which being essential conditions of a democratic society.
6) For each service category, the AIS offering must be diversiﬁed to prevent de facto monopolies from forming and undermining individual freedoms.
2. Stakeholder Engagement
In order to solve the challenges arising from use of AI while striving for better AI utilization, Sony will seriously consider the interests and concerns of various stakeholders including its customers and creators, and proactively advance a dialogue with related industries, organizations, academic communities and more. For this purpose, Sony will construct the appropriate channels for ensuring that the content and results of these discussions are provided to officers and employees, including researchers and developers, who are involved in the corresponding businesses, as well as for ensuring further engagement with its various stakeholders.