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

6. Pursuit of Transparency

During the planning and design stages for its products and services that utilize AI, Sony will strive to introduce methods of capturing the reasoning behind the decisions made by AI utilized in said products and services. Additionally, it will endeavor to provide intelligible explanations and information to customers about the possible impact of using these products and services.

Principle: Sony Group AI Ethics Guidelines, Sep 25, 2018

Published by Sony Group

Related Principles

2. Transparency

For cognitive systems to fulfill their world changing potential, it is vital that people have confidence in their recommendations, judgments and uses. Therefore, the IBM company will make clear: When and for what purposes AI is being applied in the cognitive solutions we develop and deploy. The major sources of data and expertise that inform the insights of cognitive solutions, as well as the methods used to train those systems and solutions. The principle that clients own their own business models and intellectual property and that they can use AI and cognitive systems to enhance the advantages they have built, often through years of experience. We will work with our clients to protect their data and insights, and will encourage our clients, partners and industry colleagues to adopt similar practices.

Published by IBM in Principles for the Cognitive Era, Jan 17, 2017

9. Principle of accountability

Developers should make efforts to fulfill their accountability to stakeholders, including AI systems’ users. [Comment] Developers are expected to fulfill their accountability for AI systems they have developed to gain users’ trust in AI systems. Specifically, it is encouraged that developers make efforts to provide users with the information that can help their choice and utilization of AI systems. In addition, in order to improve the acceptance of AI systems by the society including users, it is also encouraged that, taking into account the R&D principles (1) to (8) set forth in the Guidelines, developers make efforts: (a) to provide users et al. with both information and explanations about the technical characteristics of the AI systems they have developed; and (b) to gain active involvement of stakeholders (such as their feedback) in such manners as to hear various views through dialogues with diverse stakeholders. Moreover, it is advisable that developers make efforts to share the information and cooperate with providers et al. who offer services with the AI systems they have developed on their own.

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan in AI R&D Principles, Jul 28, 2017

10.Principle of accountability

AI service providers and business users should make efforts to fulfill their accountability to the stakeholders including consumer users and indirect users. [Main points to discuss] A) Efforts to fulfill accountability In light of the characteristics of AI to be used and its purpose, etc., AI service providers and business users may be expected to make efforts to establish appropriate accountability to consumer users, indirect users, and third parties affected by the use of AI, to gain enough trust in AI from people and society. B) Notification and publication of usage policy on AI systems or AI services AI service providers and business users may be expected to notify or announce the usage policy on AI (the fact that they provide AI services, the scope and manner of proper AI utilization, the risks associated with the utilization, and the establishment of a consultation desk) in order to enable consumer users and indirect users to recognize properly the usage of AI. In light of the characteristics of the technologies to be used and their usage, we have to focus on which cases will lead to the usage policy is expected to be notified or announced as well as what content is expected to be included in the usage policy.

Published by Ministry of Internal Affairs and Communications (MIC), the Government of Japan in Draft AI Utilization Principles, Jul 17, 2018

3. Provision of Trusted Products and Services

Sony understands the need for safety when dealing with products and services utilizing AI and will continue to respond to security risks such as unauthorized access. AI systems may utilize statistical or probabilistic methods to achieve results. In the interest of Sony’s customers and to maintain their trust, Sony will design whole systems with an awareness of the responsibility associated with the characteristics of such methods.

Published by Sony Group in Sony Group AI Ethics Guidelines, Sep 25, 2018

3 Ensure transparency, explainability and intelligibility

AI should be intelligible or understandable to developers, users and regulators. Two broad approaches to ensuring intelligibility are improving the transparency and explainability of AI technology. Transparency requires that sufficient information (described below) be published or documented before the design and deployment of an AI technology. Such information should facilitate meaningful public consultation and debate on how the AI technology is designed and how it should be used. Such information should continue to be published and documented regularly and in a timely manner after an AI technology is approved for use. Transparency will improve system quality and protect patient and public health safety. For instance, system evaluators require transparency in order to identify errors, and government regulators rely on transparency to conduct proper, effective oversight. It must be possible to audit an AI technology, including if something goes wrong. Transparency should include accurate information about the assumptions and limitations of the technology, operating protocols, the properties of the data (including methods of data collection, processing and labelling) and development of the algorithmic model. AI technologies should be explainable to the extent possible and according to the capacity of those to whom the explanation is directed. Data protection laws already create specific obligations of explainability for automated decision making. Those who might request or require an explanation should be well informed, and the educational information must be tailored to each population, including, for example, marginalized populations. Many AI technologies are complex, and the complexity might frustrate both the explainer and the person receiving the explanation. There is a possible trade off between full explainability of an algorithm (at the cost of accuracy) and improved accuracy (at the cost of explainability). All algorithms should be tested rigorously in the settings in which the technology will be used in order to ensure that it meets standards of safety and efficacy. The examination and validation should include the assumptions, operational protocols, data properties and output decisions of the AI technology. Tests and evaluations should be regular, transparent and of sufficient breadth to cover differences in the performance of the algorithm according to race, ethnicity, gender, age and other relevant human characteristics. There should be robust, independent oversight of such tests and evaluation to ensure that they are conducted safely and effectively. Health care institutions, health systems and public health agencies should regularly publish information about how decisions have been made for adoption of an AI technology and how the technology will be evaluated periodically, its uses, its known limitations and the role of decision making, which can facilitate external auditing and oversight.

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