Artificial Intelligence (AI) has become a popular buzzword, not in the least due to Hollywood movies depicting machines with superhuman capabilities. In reality, today’s AI solutions can carry out specific, well-defined tasks exceptionally well, but they aren’t ready to take over the world just yet. However, that does not mean that AI is science-fiction. On the contrary, the technology is frequently deployed in the real world and has enormous potential for future applications. The key to unlocking all this potential lies in the responsible use of AI.

Great power, great responsibility

Data science allows us to use AI to leverage enormous amounts of data to support complex and high-impact decision-making processes. However, just because we can do this does not always mean we should. For example, there are many ethical and legal considerations when using sensitive data. Even when businesses have the right to use this data, AI models are just as susceptible to bias as their human creators – hiding behind a veil of objectivity.

Dealing with bias

Trained data professionals are instrumental in enabling responsible use of AI, as they are well-equipped to identify and mitigate potential sources of bias. Bias presents a potential risk at multiple stages while creating and maintaining an AI model that supports complex and high-impact decision-making processes.

Bias represents a significant risk during the creation, selection, cleaning, and enrichment of the data for processing by an AI model. Applying the wrong AI model to biased data only adds insult to injury. For example, using machine learning algorithms in a public employment solution could end up repeating the kind of recruitment patterns that have previously led to various forms of discrimination. These biased patterns are best left in the past.

Human bias could also influence the fine-tuning and evaluation of AI models. For example, a significant challenge for data scientists is demonstrating that their models work effectively – not just in a way that reflects their personal opinions. However, using the resulting model in practice can also introduce another source of bias, for instance, by misinterpreting its outcomes or using the model outside the intended context. Yet another source of bias could be an inappropriate, incomplete, or selective feedback loop; One should be careful only to update AI models using representative feedback.

Responsible AI at WCC

We power WCC’s solutions for passenger screening and border management and Public Employment Services (PES) by applying various forms of AI. Given the sensitive nature of the applications that these solutions target, responsible use of AI is one of our main priorities.

In this light, we primarily rely on rule-based, knowledge-driven forms of AI to power our solutions. This approach allows us to apply a high degree of control to govern the data we use, how we use it, and for what purpose so we can clearly explain the results. Data-driven, self-learning capabilities also have their place in WCC’s products, and we use them when appropriate.

In our way of working, we strive for responsible use of AI through methodological rigor, focusing on transparency, clarity, and diversity. When we use machine learning, our data professionals are thorough and precise as they design, validate, and document an appropriate methodology and the outcomes, performance, applicability, and limitations of the resulting models. Furthermore, we always strive to find the optimal balance between clarity and performance. On top of that, we use state-of-the-art techniques like Shapley analyses to give more insight into the logic learned by our machine-learning algorithms. Lastly, the wide range of backgrounds shared by the professionals in our data science, product, and delivery teams enables them to look at real-world application scenarios from various perspectives. As a result, we are confident that our solutions effectively reduce bias and can equally benefit diverse populations worldwide.

Today, AI has become more accessible than ever. Anyone with at least some basic technical skills can apply an algorithm to data sets and create a model that has real-world impact. This technology provides a huge opportunity for innovation, but with great power comes great responsibility. When using AI techniques for passenger screening, employment solutions, or any other application, businesses have an obligation to use AI fairly and ethically. That is something we always keep front of mind at WCC.