Attention is drawn to grand halls where the ethics of artificial intelligence are being discussed, and there seems to be a consensus on the necessity of achieving justice and transparency. However, do these discussions reflect reality? Or are they merely slogans that do not express the suffering of entire communities that are not included in the data?
Concepts such as governance and transparency are repeated at these global summits, and AI is considered a tool to enhance justice. Yet behind this idealistic image lies an important question: what about those whose data does not reflect their suffering? Artificial intelligence relies on available data, and what is not collected is not considered.
Event Details
The discussions revolve around issues such as bias and privacy, which are real concerns, but they overlook the depth of the problem. Many communities do not record their suffering, leaving them outside the scope of any analysis or decision-making. In certain environments, diseases are not measured, and shocks are not recorded, leaving an entire health reality outside any predictive model.
In this case, bias is not a result of a technical malfunction but rather a consequence of absent data. The problem does not lie in how to analyze but in what has not been analyzed. Here, the concept of justice shifts, as how can one talk about algorithmic fairness in a world that is not digitally represented?
Context and Background
Global summits speak of AI as a tool that can be ethically refined, but this perception conceals a deeper assumption: that all problems can be solved from within the system itself. In contrast, reality highlights suffering that does not wait for algorithmic governance but needs to be seen.
At the Global AI Summit in India, which raised the banner of "Responsible AI," the focus was on principles of governance and transparency. However, what these discussions reveal is a deeper gap, where the ethical discourse assumes a fully represented world within the data, while the reality is entirely different.
Implications and Effects
Studies show that there is unmeasured suffering, such as psychological stress and environmental instability, which limits AI's ability to provide effective solutions. The problem is not in the accuracy of measurements but in the assumption that everything important can be measured. Reality is more complex, as some of the most significant determinants of health are not recorded in the data.
While summits may succeed in formulating ethical principles, the real challenge lies in those areas that data does not reach. The question then becomes: can AI see what it should be ethically concerned about?
Impact on the Arab Region
In the Arab region, this challenge is particularly pronounced. Many communities suffer from health and social issues that are not recorded in the data, making them outside the scope of any technical analysis. Therefore, discussions about AI must include all voices, including those that are not heard.
In conclusion, we must remember that AI is not just a technology; it is a tool that requires a comprehensive vision encompassing all aspects of human life. Suffering needs to be seen, and data must reflect reality in all its complexities.