Could IBM's software show us how AI gets to its decisions?Daniel Gonzalez Lack of explainability of decisions made by Artificial Intelligence (AI) programs is a major problem. This inability to understand how AI does what it does also stops it from being deployed in areas such as law, healthcare and within enterprises that handle sensitive customer data. Understanding how data is handled, and how AI has reached a certain decision, is even more important in the context of recent data protection regulation, especially GDPR, that heavily penalizes companies who cannot provide an explanation and record as to how a decision has been reached (whether by a human or computer). IBM may have made a major step towards tackling this issue, announcing today a software service to detect bias in AI models and track the decision-making process. This service should allow companies to track AI decisions as they occur, and monitor any'biased' actions to ensure that AI processes are in line with regulation and overall business objectives.

Whether the visualizations provided by the bias-detection software will be enough to understand and more importantly explain a complex deep learning AI algorithm remains to be seen, as it has so far been impossible to understand how AI systems reach decisions. This is therefore a big claim from IBM, as only last year Tommi Jaakkola, an MIT professor working on applications of Machine Learning, said: 'If you had a very small neural network, you might be able to understand it, but once it becomes very large, and it has thousands of units per layer and maybe hundreds of layers, then it becomes quite un-understandable.' The problem is not only that we can't see what deep learning algorithms are doing, but we also can't understand their workings, so will IBM's visualization software solve anything?