Human-centred Values

AI systems should respect human rights, diversity, and the autonomy of individuals.

Faireness

AI systems should be inclusive and accessible, and should not involve or result in unfair discrimination against individuals, communities or groups.

Privacy protection and security

AI systems should respect and uphold privacy rights and data protection, and ensure the security of data.

Transparency and explainability

There should be transparency and responsible disclosure so people can understand when they are being significantly impacted by AI, and can find out when an AI system is engaging with them.

Human, Societal, and Environmental Wellbeing

AI systems should benefit individuals, society and the environment.

Contestability

 When an AI system significantly impacts a person, community, group or environment, there should be a timely process to allow people to challenge the use or outcomes of the AI system.

Accountability

People responsible for the different phases of the AI system lifecycle should be identifiable and accountable for the outcomes of the AI systems, and human oversight of AI systems should be enabled.

Reliability and safety

AI systems should reliably operate in accordance with their intended purpose.

Bias and Discrimination

One of the most significant concerns with AI is its potential to embed bias and discrimination in decision-making processes. Developers train AI algorithms on vast data sets that can be biased or incomplete, which often leads to discriminatory outcomes. For instance, studies have shown that facial recognition algorithms tend to have higher error rates for individuals with darker skin tones, potentially leading to false identifications and unfair treatment.

Lack of Transparency and Explainability

Another concern with AI is the lack of transparency and explainability in decision-making. Some AI algorithms are so complex that even their developers may not understand how they arrive at their decisions. This lack of transparency makes it difficult to identify potential biases and correct them.

Regulation and Governance

The rapid advancement of AI has outpaced the development of regulatory frameworks, raising concerns about ensuring AI development and usage align with societal values and principles. There is a pressing need for clear regulations and governance frameworks to ensure that AI is developed and used in a responsible and ethical manner.

Privacy and Security

AI requires vast amounts of data to operate, which can raise concerns about privacy and security. As AI becomes more prevalent in areas such as healthcare and finance, there is a risk that personal data could be misused or compromised. Additionally, AI systems themselves can be vulnerable to hacking, which could have significant consequences, particularly in critical infrastructure.

Define Ethical Principles

Organizations should establish clear ethical principles that guide the development and use of their AI systems. These principles should reflect societal values and principles, such as transparency, fairness, accountability, and human rights. The principles should be well-communicated and integrated into the organization’s decision-making processes.

Foster a Culture of Ethics

Creating a culture of ethics within an organization is essential for promoting ethical AI. This involves establishing a code of conduct that outlines ethical expectations for employees, providing training on ethical decision-making, and incentivizing ethical behavior.

Ensure Transparency and Explainability

Organizations should ensure that their AI systems are transparent and explainable. This means that the decision-making process of the AI system should be understandable and auditable by humans. This allows for the identification of potential biases or errors and promotes accountability.