An artificial intelligence tool Google provides to developers won’t add gender labels to images anymore, saying a person’s gender can’t be determined just by how they look in a photo, Business Insider reports.

The company emailed developers today about the change to its widely used Cloud Vision API tool, which uses AI to analyze images and identify faces, landmarks, explicit content, and other recognizable features. Instead of using “man” or “woman” to identify images, Google will tag such images with labels like “person,” as part of its larger effort to avoid instilling AI algorithms with human bias.

In the email to developers announcing the change, Google cited its own AI guidelines, Business Insider reports. “Given that a person’s gender cannot be inferred by appearance, we have decided to remove these labels in order to align with the Artificial Intelligence Principles at Google, specifically Principle #2: Avoid creating or reinforcing unfair bias.”

AI image recognition has been a thorny issue for Google in the past. In 2015, a software engineer noted that Google Photos’ image recognition algorithms were categorizing his black friends as “gorillas.” Google promised to fix the issue, but a follow-up report by Wiredin 2018 found Google had blocked its AI from recognizing gorillas and had not done much else to address the problem at its core.

Google released its AI principles in 2018, in response to backlash from Google employees, who protested the company’s work on a Pentagon drone project. The company pledged not to develop AI-powered weaponry, and it also outlined a number of principles, such as the one referenced above, to address issues of bias, oversight, and other potential ethical issues in its future development of the technology.

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One of the major challenges faced in treating cancer is the constantly changing nature of tumours hence proposed treatment at a particular time may not be effective because tumours become resistant to drugs or proposed treatment.

Artificial Intelligence in a new development has come in useful in predicting how cancers will progress and evolve, and this will go a long way in helping doctors propose the most effective treatment for each patient.

A team led by the Institute of Cancer Research London[ICR] and the University of Edinburgh developed a new technique known as Revolver [Repeated Evolution of Cancer]

This technique notes and selects the system in DNA mutation within cancers and uses the information to predict future genetic changes.

Cancer evolves unpredictably but if doctors can predict how the tumours evolve, they could step in and stop it before it advances or develops and increase the patient’s chances of survival.

The team also discovered a link between a certain pattern of recurrent tumour mutations and survival outcomes.
This indicates that repeating patterns of DNA mutations could be used as a means of prognosis, helping to build future treatment.

The research team developed a new machine learning technique which identifies patterns in genetic mutations that happen in tumours and applying the patterns to predict another.

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