GN-GloVe AI to Have No Gender Prejudice

New model of scientists at the University of California showed 35% fewer mistakes
10 September 2018   1004

Scientists from the University of California created a model for learning neural networks called Gender-Neutral Global Vectors (GN-GloVe). The development is intended for AI, specializing in the recognition of speech and texts. According to programmers, this training model will reduce the percentage of false gender associations. This is reported by Venture Beat.

Neural networks designed for speech recognition are trained on special data sets. However, these kits carry the imprint of a living language, filled with stereotypes. For example, the words "cook" or "secretary" are more often associated with the female sex, and "locksmith" or "welder" - with the male. Or, another examples: "doctor" is usually replaced by the pronoun "he", and "nurse" - "she".

Artificial intelligence, trained on such datasets, assimilates all the prejudices inherent in them. In particular, if a "doctor" is mentioned in the text without mentioning a particular sex, the neural network will more likely be considered a man. GN-GloVe, as claimed by its creators, removes the false associations with the sex.

This technology does not affect those areas where the sex is specified directly. To achieve this effect, the method determines gender-neutral words simultaneously with the formation of the semantic vectors of the text. Another advantage of development scientists call independence from the language being processed.

In a comparative analysis with GloVe, one of the most common teaching methods, the new model of scientists at the University of California showed 35% fewer mistakes due to false identification of a person's sex by type of activity.

Data sets for training contain many prerequisites for the formation of retraining errors. For example, smart speakers from Amazon and Google are 30% less likely to recognize English, pronounced with accent. And this problem is not just about speech: face recognition algorithms are worse at copying images of African Americans than Caucasians.

The bias of artificial intelligence bias surfaced in the work of Princeton University scientists in early 2017. While protection from such errors does not exist, however, similar GN-GloVe algorithms can in time reduce the bias error to an acceptable level.

Apple to Acquire Drive.ai

Apple's decision came just in time - management of self-driving car startup was going to lay off a lot employees on Friday, 28.06
27 June 2019   462

Apple confirmed to Axios and The Verge that it bought a startup Drive.ai. As you can guess from the name, he developed the system of unmanned vehicle control. In recent times, things have been going badly. The management was going to close the company on Friday and disband the employees.

Drive.ai tested its technology on the redesigned Nissan NV200s - a bright orange car with several LED screens. They displayed messages for passersby and other road users: that the car gives way to a pedestrian, continues to move or turns into a ramp.

According to The Verge, a year ago, Drive.ai was considered one of the most promising startups in its field. It was estimated at 200 million dollars. According to the publications, Apple paid less for a startup.