IBM to Train AI to Follow Code of Ethics

Tech giant made one more step in artificial intelligence research
19 July 2018   585

Developers from IBM have created an artificial intelligence that dynamically forms norms of ethics, expressed in a set of rules when creating content recommendation algorithms. This is reported by Venture Beat.

The IBM Neural Network is trained in two phases. Initially, the AI ​​receives a set of constrained examples that the system of recommendations should adhere to. By processing the received data, the neural network forms the required norms of ethics. The more a set of examples, the more accurate the limitations will be.

At the second stage the AI ​​works directly with the user, studying his preferences and reaction to various content. Based on their received information, the system forms a list of recommended videos for viewing. In this case, the neural network adheres to the previously obtained ethical restrictions. In the system settings, you can set the priority relationship between the user's interests and ethical standards.

The problem with this approach is the need to compile examples for the AI. For a child, an older generation has to set up the limits. However, in the overwhelming majority of cases, the system remains with the user tete-a-tete. The user can also determine some ethical norms, however, in the same way, he can change them. On this issue, a group of IBM researchers continues to work together with MIT Media Lab. While the developers offer to choose as a mentor, responsible for ethical issues, a friend or a family member.

In 2017, hundreds of researchers and IT experts, including Elon Mask and Stephen Hawking, compiled a list of 23 basic principles that should be followed when developing AI. In the same year, the Institute of Electrical and Electronics Engineers defined ethical standards for artificial intelligence. Now AI learns to form ethics for people. And on June 17, 2018, IBM announced the creation of a neural network capable of arguably arguing with live opponents.

AI to Predict Parkinson

Looks like artifical intelligece can be used for really important things
16 November 2018   50

In Oxford, an AI-framework for the diagnosis of nystagmus is created - an early symptom of neurodegenerative pathologies, such as Parkinson's disease. Nystagmus is a form of sleep disturbance, a series of involuntary rapid tremors in the eyeballs of a sleeping person. Rapid diagnosis of nystagmus will allow to treat Parkinson’s disease at an early stage.

The researchers used data from 53 patients from an open laboratory database of the Montreal Sleep Research Archive. Records of electrical activity of the brain, skeletal muscles and eye movements were processed using the algorithm of regression decision trees (random forest).

As the main symptom of nystagmus and the approaching Parkinson's disease, researchers considered muscle atony. In total, electrograms identified 156 different features that can indicate the development of pathology.

Scientists used manual and automatic markup methods for a data set. With manual marking, they managed to achieve diagnostic accuracy of 96%, with automatic results being 4% worse. The researchers plan to improve the results of automatic processing using mathematical functions that mimic the behavior of brain neurons.

A month before the publication of the work of experts at Oxford University, scientists from the Swiss Institute of IRIS reported on the results of work on their own system for diagnosing neuropathology. The fundamental difference is that the Swiss system uses data collected using a smartphone, and the development from Oxford relies on special medical tests.