Generative Artificial Intelligence (GenAI) is playing an increasingly prominent role in optimizing processes, supporting decision-making, and driving innovation. From generating designs for smart energy solutions to automating complex workflows—GenAI offers unique opportunities to enhance efficiency and address societal challenges.
However, GenAI is not an independently thinking system; it operates based on statistical models and algorithmic predictions, without true understanding or judgment. This raises crucial questions for the future: how can we ensure that users apply GenAI responsibly, assess it critically, and integrate it effectively into their work? A lack of insight into how GenAI works and its limitations can lead to risks such as unreliable outputs, ethical dilemmas, or unintended biases, which may undermine the benefits of this technology.
To ensure that (Gen)AI contributes to a sustainable, inclusive, and digitally skilled future, it is essential that everyone not only learns how to use this technology, but also how to test and evaluate it critically. This requires targeted education in understanding GenAI’s reliability, ethical implications, and potential pitfalls, such as discriminatory patterns or opaque decision-making—think of cases like the childcare benefits scandal. Developing these critical testing skills is a key component of the broader agenda for digital upskilling and reskilling.
More details about the need to become critical testers can be found in the Tedx Talk of Professor Tanja Vos in the following link:
