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

· We will make AI systems fair

1. Data ingested should, where possible, be representative of the affected population 2. Algorithms should avoid non operational bias 3. Steps should be taken to mitigate and disclose the biases inherent in datasets 4. Significant decisions should be provably fair

Principle: Dubai's AI Principles, Jan 08, 2019

Published by Smart Dubai

Related Principles

2. Fairness and Equity

Deployers should have safeguards in place to ensure that algorithmic decisions do not further exacerbate or amplify existing discriminatory or unjust impacts across different demographics and the design, development, and deployment of AI systems should not result in unfair biasness or discrimination. An example of such safeguards would include human interventions and checks on the algorithms and its outputs. Deployers of AI systems should conduct regular testing of such systems to confirm if there is bias and where bias is confirmed, make the necessary adjustments to rectify imbalances to ensure equity. With the rapid developments in the AI space, AI systems are increasingly used to aid decision making. For example, AI systems are currently used to screen resumes in job application processes, predict the credit worthiness of consumers and provide agronomic advice to farmers. If not properly managed, an AI system’s outputs used to make decisions with significant impact on individuals could perpetuate existing discriminatory or unjust impacts to specific demographics. To mitigate discrimination, it is important that the design, development, and deployment of AI systems align with fairness and equity principles. In addition, the datasets used to train the AI systems should be diverse and representative. Appropriate measures should be taken to mitigate potential biases during data collection and pre processing, training, and inference. For example, thetraining and test dataset for an AI system used in the education sector should be adequately representative of the student population by including students of different genders and ethnicities.

Published by ASEAN in ASEAN Guide on AI Governance and Ethics, 2021

· Plan and Design:

1 At the initial stages of setting out the purpose of the AI system, the design team shallcollaborate to pinpoint the objectives and how to reach them in an efficient and optimizedmanner. Planning the design of the AI system is an essential stage to translate the system’sintended goals and outcomes. During this phase, it is important to implement a fairness awaredesign that takes appropriate precautions across the AI system algorithm, processes, andmechanisms to prevent biases from having a discriminatory effect or lead to skewed andunwanted results or outcomes. 2 Fairness aware design should start at the beginning of the AI System Lifecycle with a collaborative effort from technical and non technical members to identify potential harm andbenefits, affected individuals and vulnerable groups and evaluate how they are impacted bythe results and whether the impact is justifiable given the general purpose of the AI system. 3 A fairness assessment of the AI system is crucial, and the metrics should be selected at this stage of the AI System Lifecycle. The metrics should be chosen based on the algorithm type (rule based, classification, regression, etc.), the effect of the decision (punitive, selective, etc.), and the harm and benefit on correctly and incorrectly predicted samples. 4 Sensitive personal data attributes relating to persons or groups which are systematically or historically disadvantaged should be identified and defined at this stage. The allowed threshold which makes the assessment fair or unfair should be defined. The fairness assessment metrics to be applied to sensitive features should be measured during future steps.

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

· We will make AI systems as explainable as technically possible

1. Decisions and methodologies of AI systems which have a significant effect on individuals should be explainable to them, to the extent permitted by available technology 2. It should be possible to ascertain the key factors leading to any specific decision that could have a significant effect on an individual 3. In the above situation we will provide channels through which people can request such explanations

Published by Smart Dubai in Dubai's AI Principles, Jan 08, 2019

· We will make AI systems transparent

1. Developers should build systems whose failures can be traced and diagnosed 2. People should be told when significant decisions about them are being made by AI 3. Within the limits of privacy and the preservation of intellectual property, those who deploy AI systems should be transparent about the data and algorithms they use

Published by Smart Dubai in Dubai's AI Principles, Jan 08, 2019

· AI systems will be safe, secure and controllable by humans

1. Safety and security of the people, be they operators, end users or other parties, will be of paramount concern in the design of any AI system 2. AI systems should be verifiably secure and controllable throughout their operational lifetime, to the extent permitted by technology 3. The continued security and privacy of users should be considered when decommissioning AI systems 4. AI systems that may directly impact people’s lives in a significant way should receive commensurate care in their designs, and; 5. Such systems should be able to be overridden or their decisions reversed by designated people

Published by Smart Dubai in Dubai's AI Principles, Jan 08, 2019