IBM has developed a service for monitoring the processes that occur during the training of neural networks. The system identifies emerging misconceptions and gives greater transparency to the reasons for the decisions made by AI.
The new tool works with popular AI-frameworks, such as Watson, Tensorflow, SparkML, AWS SageMaker and AzureML. The service is implemented on the IBM Cloud platform and will help monitor the learning process by making the necessary adjustments. According to the representatives of the company, the software is easy to adapt to any architecture of the neural network. Moreover, the system is able to automatically offer correction of input data to eliminate delusions.
The service shows the parameters of the learning process using visual diagrams, which makes the user's work easier. Among the data displayed is a combination of factors accepted for consideration, confidence in the decision made and the foundation of this confidence. In addition, changes to the parameters are stored in the log, which will allow you to study the actions of AI more closely.
The monitoring service is not free, but at the same time IBM said it plans to release an open source version of the product. The company declares this as a contribution to international cooperation in eliminating AI's misconceptions.
The reasons for the decisions made by artificial intelligence are in most cases hidden from the end user. At the same time, studies have shown that neural networks are able to assimilate inherent misconceptions and stereotypes, for example, gender or racial. This gave rise to some mistrust of AI and the fear of losing control over the technology. According to an IBM poll, 82% of entrepreneurs consider the introduction of neural networks. However, while 60% are afraid of possible problems, and 63% are not sure that they will be able to confidently manage new tools.
The so-called "black box problem", consisting in the non-transparency of AI decisions, is taken seriously by the world community. Work to increase transparency and trust is being carried out quite actively. In September 2018, MIT scientists published their development, illustrating the decision-making process by the neural network.