As artificial intelligence (AI) matures and new applications boom amid a transition to Industry 4.0, we are beginning to accept that machines can help us make decisions more effectively and efficiently. But, at present, we don't always have a clear insight into how or why a model made those decisions – this is'blackbox AI'. In light of alleged bias in AI models in applications across recruitment, loan decisions, and healthcare applications, the ability to effectively explain the workings of decisions made by AI model has become imperative for the technology's further development and adoption. In December last year, the UK's Information Commissioner's Office (ICO) began moving to ensure businesses and other organizations are required to explain decisions made by AI by law, or face multimillion-dollar fines if unable. Explainable AI is the concept of being able to describe the procedures, services, and outcomes delivered or assisted by AI when that information is required, such as in the case of accusations of bias.

The Information Commissioner's Office (ICO) is putting forward a regulation that businesses and other organizations are required to explain decisions made by artificial intelligence (AI) or face multimillion-dollar fines if unable to. The guidance will provide advice such as how to explain the procedures, services, and outcomes delivered or assisted by AI to affected individuals. The report would detail the documentation of the decision-making process and data used to arrive at a decision. In extreme cases, organizations that fail to comply may face a fine of up to 4 percent of a company's global turnover, under the EU's data protection law. The new guidance is crucial as many firms in the UK are using some form of AI to execute critical business decisions, such as shortlisting and hiring candidates for roles. At the same time, two-thirds of UK financial services rely on AI to support customer services, drive business decisions and transactions.

A CT scan in action. Britain's National Health Service currently faces a critical shortage of cancer doctors, making it increasingly difficult to provide specialist care to seriously ill patients. According to stats from the Royal College of Radiologists, 7.5% of consultant roles at 62 major U.K.-based cancer centers are vacant. Because of this, they've become reliant on overtime. However, Swedish AI firm Peltarion worked with a radiotherapy company to develop a deep learning model that targets tumors for radiotherapy.