As AI development pushes ahead at a neck breaking speed, considering how AI can be built in a way that is ethical, in accordance with privacy laws and able to represent all people fairly is crucial. These elements not only shape the trajectory of AI development but also determine the ethical and legal boundaries within which AI systems operate.
AI governance is key to the development of ethical and ‘for good’ AI. It comprises frameworks, policies, and best practices aimed at guiding the development and utilisation of AI technologies. Overall, its role is to minimise the risk of creating biassed AI and maximise its benefits, which can serve all people. AI governance encompasses developers, policymakers, and users navigating AI implementation.
AI governance has to also consider how it can encompass existing legislation such as the General Data Protection Regulation (GDPR) in Europe. This key piece of legislation is the cornerstone of data protection in the EU. It outlines strict rules around collecting, processing and storing personal data, in order to safeguard individuals’ rights in an era driven by data.
This protection of personal data and data privacy is especially important within AI development, as legislators and tech companies debate what level of personal data can and should be used to help speed up the development of AI technology.
Importance of AI Governance
Regulating AI development and governance is paramount to ensuring these technologies are devoid of unexpected biases, particularly in areas that significantly impact people's lives, such as criminal justice, hiring automation, and HR.
One of the biggest issues that AI governance needs to address when it comes to their development is how data irregularities or biassed data can lead to long term issues. A poignant example, shared in an article published by the JSTOR, lies in the realm of predictive policing. Law enforcement has already attempted to use existing data for identifying ‘high risk’ neighbourhoods, in models which don’t yet utilise AI.
Studies reveal that black individuals are more frequently reported for crimes compared to their white counterparts, regardless of the race of the reporter. This biassed reporting leads to black neighbourhoods being unfairly labelled as "high risk," exacerbating systemic discrimination within the criminal justice system.
Increased police presence in these communities can result in a higher number of reported crimes, further reinforcing biassed perceptions. Machine learning algorithms trained on such skewed data inadvertently perpetuate false notions about which neighbourhoods are deemed "high risk." This not only underscores the importance of mitigating bias in AI development but also emphasises the critical role of governance frameworks in rectifying and preventing such harmful outcomes. (Reference: JSTOR - What Happens When Police Use AI to Predict and Prevent Crime?)
Understanding GDPR in Relation to AI Development
The European Union's General Data Protection Regulation (GDPR) is not only about empowering individuals with greater control over their data but also plays a crucial role in shaping the development and deployment of artificial intelligence (AI).
In the context of AI development, GDPR serves as a guiding framework, ensuring that personal data used to train and operate AI systems is handled responsibly and ethically. For instance, GDPR's principles prevent scenarios where individuals' data is used without explicit consent, providing safeguards against unauthorised data processing.
Furthermore, GDPR's key principles, such as data minimisation, purpose limitation, and accountability, directly impact AI development practices. AI developers must adhere to these principles to ensure that data used in training AI models is limited to what is necessary for the intended purpose, and that further processing aligns with the original purpose of data collection.
Additionally, GDPR's accountability requirement compels AI developers to implement measures that ensure the lawful and ethical processing of personal data throughout the AI lifecycle.
How GDPR and AI Governance Overlap
The intersection of GDPR and AI governance is becoming increasingly critical as AI development relies heavily on vast datasets. The reliance on data and the realisation of tech companies that much more data is needed for future AI development raises profound concerns regarding data privacy and usage, prompting governments to assess existing regulations. (https://www.wsj.com/tech/ai/ai-training-data-synthetic-openai-anthropic-9230f8d8)
With AI technology evolving so rapidly, there's a pressing need to update GDPR to address the ethical and privacy implications of AI development, as well as wider legislation worldwide. For governments striving to protect citizens' data from AI related risk, the intersection of legislation, such as GDPR and Ai governance emerges as a pivotal point for ensuring responsible and ethical AI innovation for safeguarding individuals privacy rights.
Making AI Governance and GDPR Compliance Easier
Prioritising ethics and fairness in AI development is crucial for equal benefits for all and safeguarding customer data within your organisation's AI initiatives. Creating a frameworking for ethical AI development, considering how data privacy is inline with existing legislation and collaboration with experts who can help navigate this complex issue is key to responsible AI development.
If you're unsure how to kickstart your AI initiatives or struggling to find suitable solutions for your use cases, Deazy's AI sprint is here to help. Led by our AI product specialists, the sprint is tailored to guide you from idea conception to a minimum viable product in just a few weeks.
Reach out to our team today to embark on your journey towards seamless, ethical, and privacy-respecting AI development.
