The AI leviathan continues to tower over every data center, with organizations rushing to deploy AI-based solutions for immediate benefits, or to build the infrastructure and models to deliver ambitious long-term returns on research projects. Regardless of where an organization is on its AI journey, the rapid development of this technology has left regulators playing catch-up when it comes to how AI should be moderated to ensure the technology is used ethically . There is an urgent need for clarity on liability in the event of errors or unintended consequences. There is also a clear need to develop legal frameworks that provide guidance for determining responsibility when AI systems cause harm or fail to meet expected standards.
CTO International at Pure Storage.
What is ethical AI?
Ethical AI means supporting the responsible design and development of AI systems and applications that do not harm people and society as a whole. While this is a noble goal, it is not always easy to achieve and requires in-depth planning and constant vigilance. For developers and designers, key ethical considerations should include, at a minimum, protecting sensitive training data and model parameters from manipulation. They must also provide real transparency into how AI models work and are affected by new data, which is essential to ensure proper oversight. Regardless of whether ethical AI is approached by the C-level of a private company, government or regulatory agency, it can be difficult to know where to start.
Transparency as a basis
When planning AI implementation strategies, transparency should always be the starting point and foundation on which all applications are built. This means that we must provide internal and external insight into how AI systems make decisions, how they arrive at results and what data they use for this. Transparency and accountability are essential for building trust in AI technologies and limiting potential harm. Understanding how an AI model works, including the data used to train it before it is deployed, is essential. When this is put into practice, there are ethical, privacy and copyright issues that need to be addressed so that the boundaries are clear when AI is deployed, especially when it comes to applications in sectors such as healthcare. In Britain, for example, the Information Commissioner’s Office has issued useful guidelines to ensure transparency in AI. The repeatability of results remains an important area of focus to ensure that conscious or unconscious biases do not play a role when training a model, or when using a trained model for inference.
Concerns about aggregated data profiles
Balancing privacy concerns with potential societal benefits will be an ongoing discussion as AI technologies evolve and there will always be trade-offs between what individuals give up in data and what society gains. Personal data such as shopping, fitness, and healthcare data can be combined and used together, increasing privacy and insurance risks for individuals. This is because aggregated and linked data sources can reveal an unprecedented level of detail about people’s lives, behavior and vulnerabilities. As more data streams are combined, the value of the aggregated profile is much higher, allowing greater and potentially more targeted influence on individuals. The security of personal data becomes even more important given the risks of data breaches and theft when so much valuable information is collected in one place. The need for data management and transparency about sourcing and consent practices is fundamental. Ensuring that personal data is processed securely and for agreed purposes remains critical to maintaining public confidence in the applications of this powerful technology.
Regulations on the horizon
Ultimately, ethical AI practices will require external guidance and the development of agreed-upon standards. After all, organizations and commercial enterprises are part of society and are not separate from it. The development of globally agreed ethical standards for AI is of paramount importance. As technology becomes increasingly integrated internationally, finding workable solutions in this area will clearly be important. However, there are significant obstacles to implementation, given differing social and legal views. Starting with areas where there is broad consensus, such as fundamental rights and security, could help make initial progress, even if full harmonization remains elusive for now. It is encouraging that governments are taking a leadership position in this area, participating in international summits including last year’s AI Safety Summit in Britain, the AI Seoul Summit 2024 and the upcoming Cyber Summit in Paris.
Any legislation resulting from regulatory decisions on AI must address liability concerns. Legal frameworks should be developed to outline guidelines for determining responsibility when AI systems cause harm or fail to meet expected standards. Biases in AI models, often unintentionally perpetuated by distorted training data, raise concerns about the potential reinforcement and perpetuation of societal inequalities. The ethical considerations surrounding AI are not secondary concerns, but fundamentally necessary pillars that will shape the responsible development and deployment of AI technologies in the future.
International collaboration will be critical as AI technologies are inherently global. Looking to international precedents such as the Law of the Sea for universal standards is potentially a good starting point. While it is encouraging that addressing AI ethics is increasingly recognized as an urgent priority that requires coordinated global action, we must accelerate our efforts to drive tangible change within the next five years or we can move beyond point of no return racing and reaping unthinkable harvests. consequences resulting from fundamentally flawed and unethical AI.
AI regulation benefits everyone
AI is rapidly becoming ubiquitous in society and is doing so in an emerging regulatory environment. We cannot afford to wait to regulate this technology, but at the same time we must recognize that government policies and legislation take time to be formulated and adopted. Drafting and implementing international agreements will also likely take a lot of time. Any organization that uses AI unethically will face reputational damage and loss of public trust once regulations are introduced. That’s reason enough for organizations to assess their use of AI now and ensure they apply ethical and transparent processes to their AI technologies and projects.
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