- All computer algorithms must follow rules and live within the realm of societal law, just like the humans who create them.
- Trustworthy AI is a term used to describe AI that is lawful, ethically adherent, and technically robust. It is based on the idea that AI will reach its full potential when trust can be established in each stage of its lifecycle, from design to development, deployment and use.
- AI governance involves establishing frameworks that promote transparency, accountability, fairness, and ethical use of AI. By implementing robust AI governance, organisations can ensure that AI technologies are developed and deployed in a responsible and trustworthy manner.
AI governance is a set of standards, principles, and frameworks that prescribe ethical, responsible, and safe development and deployment of AI technologies.
On one hand, it addresses potential challenges and risks of developing and using AI. On the other, it promotes the positive effects AI can have on society and ensures nobody uses the technology for unethical, illegal, or malicious purposes.
By delving into the nature of AI systems, AI governance plays a crucial role in fostering trust. It ensures AI technology is transparent, fair, and well-regulated, prioritising privacy and respecting human rights and freedoms.
What is ‘trustworthy AI’?
AI trustworthiness encompasses generative AI and conversational AI systems that are developed and deployed to prioritise ethics, reliability, fairness, transparency, and accountability. As the lines between human and AI capabilities become blurrier, trustworthy AI aims to keep these two worlds separate but harmonious — the robots aren’t here to take over, they’re here to help. Operating within a trustworthy framework means that AI technologies respect human values, uphold fundamental rights, and adhere to ethical standards while providing consistent and reliable outputs. Keeping processes fair and transparent fosters user confidence and societal well-being — so everybody wins when we stay honest.
There are several components needed to achieve trustworthy AI:
Privacy
Besides ensuring full privacy of the users as well as data privacy, there is also a need for data governance access control mechanisms. These need to take into account the whole system lifecycle, from production training which means personal data initially provided by the user, as well as the information generated about the user throughout their interaction with the system.
Robustness
AI systems should be resilient and secure. They must be accurate, able to handle exceptions, perform well over time and be reproducible. Another important aspect is safeguards against adversarial threats and attacks. An AI attack could target the data, the model or the underlying infrastructure. In such attacks the data as well as system behavior can be changed, leading the system to make different or erroneous decisions, and even shut down completely. For AI systems to be robust they need to be developed with a preventative approach to risks aiming to minimise and prevent harm.
Explainability
Understanding is an important aspect of developing trust. It is important to understand how AI systems make decisions and which features are important to the decision-making process for each decision. Explanations are necessary to enhance understanding and allow all involved stakeholders to make informed decisions.
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How does AI governance deliver trustworthy AI?
1. Clear ethical guidelines
One of the key ways in which AI governance delivers trustworthy AI is through the establishment of clear ethical guidelines. These guidelines help developers and users of AI systems understand the ethical implications of their work and provide a framework for addressing ethical concerns. By adhering to ethical guidelines, organisations can build trust with the public and demonstrate their commitment to responsible AI development.
2. Transparency
Transparency is another crucial aspect of AI governance that contributes to the development of trustworthy AI. Transparency in AI involves providing clear and understandable explanations of how AI systems work, including the data they use, the algorithms they employ, and the decisions they make. By promoting transparency, AI governance helps to hold AI systems accountable and enables stakeholders to better understand and trust the technology.
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3. Bias in AI
Furthermore, AI governance plays a vital role in ensuring fairness and preventing bias in AI systems. Bias in AI can arise from the use of biased training data, flawed algorithms, or inadequate testing. Through robust governance mechanisms, organisations can implement measures to identify and mitigate bias in AI systems, ultimately leading to fair and equitable outcomes.
4. Accountability
Accountability is another essential element of AI governance that contributes to the delivery of trustworthy AI. It involves clearly defining roles and responsibilities for the development, deployment, and use of AI systems. By holding individuals and organisations accountable for the outcomes of AI systems, governance frameworks can help ensure that AI technologies are used responsibly and ethically.
AI governance is essential for delivering trustworthy AI. By establishing ethical guidelines, promoting transparency, ensuring fairness, fostering accountability, and addressing various legal and societal implications, AI governance plays a crucial role in shaping the responsible development and use of AI technologies. As the field of AI continues to advance, effective governance will remain critical in building trust and confidence in AI systems and contributing to the realisation of their full potential for the betterment of society.
